{"@context":"https://w3id.org/ro/crate/1.1/context","@type":"Dataset","id":"85440cfa-aa74-4ac3-983b-efad9e093f27","name":"Adjacent Evidence Brief: Plant based diet biological age — full paper","doi":"10.17605/OSF.IO/VZ23E","doi_status":"minted","osf_url":"https://osf.io/vz23e/","dw_chain_url":"https://provenance.researka.org/artifacts/claim_76823fa9014b44d1/chain","content_hash":"sha256:2526a89f9affe0fb84d5cbc9d897cef94e1d70f663925c33fa2196a7d0ae1ec6","provenance_passport":{"publication_id":"85440cfa-aa74-4ac3-983b-efad9e093f27","submission_id":"a5089c76-8f6d-47f2-a47c-f07af49a364c","artifact_type":"research_paper","decision":"accept","content_hash":"sha256:2526a89f9affe0fb84d5cbc9d897cef94e1d70f663925c33fa2196a7d0ae1ec6","persistent_identifiers":{"doi":"10.17605/OSF.IO/VZ23E","osf_url":"https://osf.io/vz23e/","orcid":null,"ror_id":null,"raid_id":null},"persistent_identifier_status":{"doi":"supplied","osf_url":"supplied","orcid":"not_supplied","ror_id":"not_supplied","raid_id":"not_supplied"},"institution":{"name":null,"ror_id":null,"status":"not_supplied"},"integrity":{"recommendation":"unavailable","available":false,"matched_publication_id":null,"duplication_score":null,"similarity_score":null,"plagiarism_flag":false,"matched_sources":[],"breakdown":{},"feedback_for_agent":null,"status":"unavailable"},"provenance":{"dw_artifact_id":"claim_76823fa9014b44d1","dw_chain_url":"https://provenance.researka.org/artifacts/claim_76823fa9014b44d1/chain"},"timeline":["submission_intake","autonomous_review","autonomous_editorial_decision","autonomous_publish"]},"publication":{"id":"85440cfa-aa74-4ac3-983b-efad9e093f27","object_type":"publication","parent_object_id":"a5089c76-8f6d-47f2-a47c-f07af49a364c","title":"Adjacent Evidence Brief: Plant based diet biological age — full paper","body_markdown":"# Adjacent Evidence Brief: Plant based diet biological age — full paper\n## Abstract\n\nThis synthesis tests the thesis that evidence for Plant based diet biological age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation.\n\nEvidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims.\n\nThis paper synthesizes evidence on Plant based diet biological age across 13 included source papers and 369 high-confidence extracted claims.\n\nThe evidence profile contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, with 9 cross-study disagreements across the evidence base.\n\nNo single positive outcome class dominates the retained corpus; null signals cluster in the contextual adjacent evidence, longevity, safety and comorbidity outcome classes, and negative signals cluster in the longevity outcome class. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect.\n\nThe conclusion is that Plant based diet biological age should be treated as a bounded geroscience hypothesis: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim.\n\n## Methods\n\n### Review type and protocol\nThis manuscript is reported as a Evidence brief. A deterministic protocol governed source retrieval, screening, extraction, and synthesis; the protocol was frozen before manuscript rendering. The full audit trail is in the supplementary `methods_pack.json` and the timestamped submission directory `synthesis-plant_based_diet_biological_age-v06-DAILY-2026-06-25T14-56-22Z`.\n\n### Information sources\nSources were retrieved across PubMed, Europe PMC, OpenAlex, Semantic Scholar, Crossref, DOAJ, OpenAIRE, PMC OAI, bioRxiv, medRxiv, arXiv, and ClinicalTrials.gov. Retrieval window: 2026-06-25.\n\n### Search strategy\nThe following topic-anchored queries were executed against the information sources listed above:\n\n- `plant based diet biological age AND aging AND human`\n- `plant based diet biological age AND older adults`\n- `plant based diet biological age AND randomized controlled trial`\n- `plant-based diet AND aging AND human`\n- `plant-based diet AND older adults`\n- `plant-based diet AND randomized controlled trial`\n- `vegan diet AND aging AND human`\n- `vegan diet AND older adults`\n- `vegan diet AND randomized controlled trial`\n- `biological age AND aging AND human`\n\n### Eligibility criteria\n- Sources whose primary content addresses plant based diet biological age.\n- Sources with extractable quantitative or qualitative findings.\n- Peer-reviewed primary research, systematic reviews, or meta-analyses; preprints accepted only when source-traceable.\n- Sources with verifiable bibliographic identifiers (DOI / PMID / canonical handle).\n\n### Selection of sources of evidence\nThe synthesis did not begin from an unfiltered database export. It began from a pre-curated receipt-candidate set generated by the retrieval and claim-binding pipeline. Of 164 records in the receipt-candidate union, 44 were classified as source candidates and 13 were admitted as traceable synthesis sources. Mixed partial-or-none and partial-only rows are separate claim-binding audit buckets, not additive exclusion totals. No additional records were excluded after final source admission.\n\n### source admission funnel\n\n| Admission bucket | n |\n|---|---:|\n| Receipt candidate union | 164 |\n| Classified source candidates | 44 |\n| No extractable claims | 11 |\n| None-only claim binding | 4 |\n| Mixed partial-or-none claim-binding candidates | 17 |\n| Partial-only claim-binding candidates | 1 |\n| Strict high-confidence sources | 3 |\n| Admitted final sources | 13 |\n\n### Exclusion reasons\n- No records were excluded at the gates instrumented for this run: the eligibility criteria above were applied during retrieval and claim-binding but produced no post-screening exclusions with recorded counts for this corpus.\n\n### Data items\nThe following fields were extracted from each included source: study design, population / cohort, intervention or exposure, comparator, outcome class, effect direction, effect size, confidence interval or credible interval, p-value, sample size, follow-up duration, risk-of-bias rating. Under the calibration rule, source verification in the public bundle is limited to reference-level metadata; exact statistics and effect directions are drawn from these structured extraction artifacts (the synthesis manifest, risk-of-bias sidecar when populated, and claim registry) rather than from re-parsed full text.\n\n### Risk-of-bias appraisal\nRisk-of-bias framework assignment follows study design (RoB-2 for RCTs, ROBINS-I for non-randomised studies, AMSTAR-2 for systematic reviews / meta-analyses). Public appraisal claims are limited to populated `risk_of_bias.json` rows; when no populated ratings are present, interpretation remains bounded by source tier and directness rather than formal RoB certification.\n\n### Synthesis approach\nEvidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, longevity, mortality and survival, safety and comorbidity); within-class agreement, disagreement, and directness gaps surfaced explicitly. Quantitative pooling applied only where ≥3 sources reported a comparable endpoint with extractable effect estimates.\n\n### AI-use disclosure\nSource retrieval, claim extraction, evidence routing, and prose drafting were assisted by large language models under a deterministic audit-trail protocol. Every manuscript claim is traceable to a source record in the supplementary `manifest.json`. Final eligibility and interpretation decisions are author-verified.\n\n### Accountability\nAccountability is established through reproducible artifacts: a deterministic protocol (`methods_pack.json`), a complete claim and citation registry, extracted numeric trace, deterministic gates (`full_paper.journal_surface.json`, `pre_submit_gate.json`, `artifact_consistency.json`), and a versioned correction path documented in the run's submission record. Certification under the `researka_agent_certified` model verifies that the manuscript is machine-verifiable, internally consistent, provenance-traced, and format-checked against these artifacts; it does not adjudicate domain correctness, corpus fit, or novelty, which remain subject to expert and reader review.\n\n## Results\n\n**Outcome-class note:** Contextual Adjacent Evidence denotes background, boundary-condition, or adjacent-outcome sources. It is not pooled with direct outcome evidence; these sources bound scope, safety, methods, and translation rather than serving as equal-weight support for the main efficacy claim.\n\n| Evidence domain | Corpus slice | Strongest signal | Directness | Main limitation |\n|---|---|---|---|---|\n| Longevity | n=6; claims=167 | negative signal in 3/6 sources | 5 indirect; 1 review | limited corpus depth in this outcome class |\n| Contextual Adjacent Evidence | n=4; claims=92 | no extracted directional signal in 4/4 sources | 3 indirect; 1 protocol | limited corpus depth in this outcome class |\n| Cardiometabolic | n=1; claims=8 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating |\n| Mortality and Survival | n=1; claims=64 | unclear signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating |\n| Safety and Comorbidity | n=1; claims=38 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating |\n\nThis evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate.\n\n### Longevity Outcomes\n\n6 included sources were assigned to this outcome class. Directional coding: negative=3, null=2, unclear=1. Directness coding: indirect=5, review=1.\n\n### Contextual Adjacent Evidence Outcomes\n\n4 included sources were assigned to this outcome class. Directional coding: null=4. Directness coding: indirect=3, protocol=1.\n\n### Cardiometabolic Outcomes\n\n1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.\n\n### Mortality Survival Outcomes\n\n1 included source were assigned to this outcome class. Directional coding: unclear=1. Directness coding: indirect=1.\n\n### Safety Comorbidity Outcomes\n\n1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.\n\n## Limitations\n\n**Verification note:** Reference-only or no-abstract records are treated as verification-limited context, not as equal-weight support for the main claim.\n\nThe principal limitation is evidence-role imbalance. The retained corpus contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, which means causal interpretation depends on how much weight is assigned to each evidence tier.\n\nA second limitation is endpoint heterogeneity. Study-level signals span the contextual adjacent evidence, longevity, and safety and comorbidity outcome classes; these domains cannot be pooled narratively without losing clinically relevant differences in measurement, population, and study design.\n\nA third limitation is that unsafe source-level numerics are excluded from public prose unless they can be tied to the correct source role and citation context. This protects the manuscript from over-specific drift but can make some sections more conservative than a free-form narrative review.\n\nThis framing also preserves comparability across topics. The same rules can classify a biomedical intervention, a management field experiment, or an economics policy corpus by asking what evidence is direct, what evidence is indirect, and what mechanism connects the two.\n\nThe final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence.\n\nReaders can weigh each section against the provenance trail published with the run. Every quantitative statement links back to an extraction source, and every source names its source document, so disagreement between summary and source is detectable rather than silent.\n\nInterpretation is deliberately scoped to the retained corpus. Sources screened out at admission do not influence direction or emphasis, and no narrative weight is given to literature the pipeline could not verify end to end.\n\n## Conclusion\n\nFor Plant based diet biological age, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. The current corpus is non-supportive for clinical efficacy or general health-intervention claims; it supports only hypothesis generation and structured follow-up within the limits of indirect evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging.\n\n## What This Synthesis Adds\n\nThis synthesis maps 13 included sources on Plant Based Diet Biological Age across 5 outcome classes and 9 cross-study disagreements. It separates endpoint-specific evidence from broad geroprotection claims so that favorable biomarker signals are not treated as proof of durable healthspan benefit.\n\nAcross 13 curated reference papers, the evidence base for plant-based diets shows a context-dependent profile. Negative signals appear in: longevity. Null findings dominate: contextual other, longevity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The plant-based diet anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established.\n\nThe strongest unresolved contrast is the null vs negative between Wei 2025 and Longo 2025 on longevity (severity 4/5), which defines the boundary condition future studies must test rather than smooth over.\n\nPrior reviews in the corpus (Morawitz 2026) emphasize convergent signals on Plant Based Diet Biological Age. This synthesis adds a design-level evidence-weighting layer and an explicit cross-study disagreement map, keeping boundary conditions visible instead of averaging them away in narrative summary.\n\n### Boundary-Condition Matrix\n\n| Evidence domain | Direct sources | Indirect / mechanism sources | Direction profile | Interpretation boundary |\n|---|---:|---:|---|---|\n| longevity | 0 | 6 | negative, null, unclear | conflict-resolution gap |\n| cardiometabolic | 0 | 1 | null | direct interventional hard-endpoint gap |\n| contextual adjacent evidence | 0 | 4 | null | direct interventional hard-endpoint gap |\n| mortality and survival | 0 | 1 | unclear | direct interventional hard-endpoint gap |\n| safety and comorbidity | 0 | 1 | null | direct interventional hard-endpoint gap |\n\n### Evidence-Gap Priority\n\n| Priority | Gap | Rationale |\n|---|---|---|\n| P1 | longevity: conflict-resolution gap | 0 direct and 6 indirect sources; direction profile: negative, null, unclear |\n| P2 | cardiometabolic: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null |\n| P3 | contextual adjacent evidence: direct interventional hard-endpoint gap | 0 direct and 4 indirect sources; direction profile: null |\n| P4 | mortality and survival: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: unclear |\n| P5 | safety and comorbidity: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null |\n\n### Next-Study Design Recommendation\n\nThe next high-yield study for Plant Based Diet Biological Age should target the **longevity** evidence gap, pre-register the primary endpoint, separate clinical from mechanistic endpoints, preserve safety and adherence capture, and include an analysis plan that can falsify the current boundary-condition claim rather than only confirming a favorable direction. Minimum useful design: at least 200 participants per arm, a priority population of adults or older adults with baseline risk in the target outcome domain, and follow-up lasting at least 24 weeks; shorter or smaller studies should be treated as hypothesis-generating.\n\n## Evidence Snapshot\n\nThe manuscript foregrounds the load-bearing evidence; the full evidence tables remain in the supplement.\n\n### Load-Bearing Included Studies\n\n- Morawitz 2026; tier=B1; directness=review; endpoint=longevity; direction=unclear.\n- Zhang 2026; tier=B2; directness=indirect; endpoint=longevity; direction=negative; representative statistic=P < 0.001.\n- Ecker 2026; tier=B2; directness=indirect; endpoint=mortality survival; direction=unclear.\n- Rieth 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null; representative statistic=P ≤ .05.\n- Yang 2026; tier=B2; directness=indirect; endpoint=longevity; direction=null.\n- Zhu 2026; tier=B2; directness=indirect; endpoint=safety comorbidity; direction=null.\n- Wei 2025; tier=B2; directness=indirect; endpoint=longevity; direction=negative; representative statistic=P < 0.0001.\n- Zuo 2026; tier=B2; directness=indirect; endpoint=longevity; direction=negative; representative statistic=P < 0.001.\n- Yin 2026; tier=B2; directness=indirect; endpoint=cardiometabolic; direction=null; representative statistic=p ≤ 0.004.\n- Whyton 2026; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null.\n\n### Source Classification Map\n\nEach retained source is mapped to its public evidence role so the evidence landscape can be checked without opening the supplement.\n\n- Morawitz 2026: outcome=longevity; directness=review; tier=B1; direction=unclear; claims=1.\n- Zhang 2026: outcome=longevity; directness=indirect; tier=B2; direction=negative; claims=68.\n- Ecker 2026: outcome=mortality survival; directness=indirect; tier=B2; direction=unclear; claims=64.\n- Rieth 2025: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=52.\n- Yang 2026: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=45.\n- Zhu 2026: outcome=safety comorbidity; directness=indirect; tier=B2; direction=null; claims=38.\n- Wei 2025: outcome=longevity; directness=indirect; tier=B2; direction=negative; claims=34.\n- Zuo 2026: outcome=longevity; directness=indirect; tier=B2; direction=negative; claims=17.\n- Yin 2026: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=8.\n- Whyton 2026: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=5.\n- Iktilat 2025: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=4.\n- Longo 2025: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=2.\n- Sandalova 2023: outcome=contextual adjacent evidence; directness=protocol; tier=D1; direction=null; claims=31.\n\n### Classification Criteria\n\n- **Outcome class** is assigned from the source's bound endpoint, population, and claim text; adjacent/background sources are separated from clinical outcome slices.\n- **Directness** is coded as direct only when a source tests the topic against a clinically proximate outcome in the relevant population; a qualifying direct source would be a human interventional or hard-endpoint study of the topic itself. Indirect human, review-level, and mechanistic sources are weighted separately.\n- **Directional signal** is counted within the assigned outcome class only. A `no extracted directional signal` cell means the retained sources in that outcome slice did not yield a coded positive, negative, or mixed direction for that slice; it is not a claim that the source reports no associations anywhere else.\n- **Evidence tier** follows the deterministic tier/directness taxonomy used in the source builder; the prose writer cannot move a source between classes after sources are frozen.\n\n### Load-Bearing Tensions\n\n- Severity 4 null vs negative: Wei 2025 vs Longo 2025; Wei 2025 (negative on longevity) vs Longo 2025 (null on longevity) — partial conflict\n- Severity 4 null vs negative: Wei 2025 vs Yang 2026; Wei 2025 (negative on longevity) vs Yang 2026 (null on longevity) — partial conflict\n- Severity 4 null vs negative: Longo 2025 vs Zhang 2026; Zhang 2026 (negative on longevity) vs Longo 2025 (null on longevity) — partial conflict\n- Severity 4 null vs negative: Longo 2025 vs Zuo 2026; Zuo 2026 (negative on longevity) vs Longo 2025 (null on longevity) — partial conflict\n- Severity 4 null vs negative: Zhang 2026 vs Yang 2026; Zhang 2026 (negative on longevity) vs Yang 2026 (null on longevity) — partial conflict\n- Severity 4 null vs negative: Zuo 2026 vs Yang 2026; Zuo 2026 (negative on longevity) vs Yang 2026 (null on longevity) — partial conflict\n- Severity 2 agreement: Wei 2025 vs Zhang 2026; Wei 2025 and Zhang 2026 both report negative effect on longevity\n- Severity 2 agreement: Wei 2025 vs Zuo 2026; Wei 2025 and Zuo 2026 both report negative effect on longevity\n\n## References\n\n- **Zhang 2026.** _The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality._ Clinical and Experimental Dental Research, 2026. DOI: 10.1002/cre2.70305. PMID: 41664565.\n- **Ecker 2026.** _Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes._ NPJ Aging, 2026. DOI: 10.1038/s41514-026-00377-7. PMID: 41932933.\n- **Rieth 2025.** _Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers._ The Oncologist, 2025. DOI: 10.1093/oncolo/oyaf294. PMID: 40973844.\n- **Yang 2026.** _Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study._ Frontiers in Public Health, 2026. DOI: 10.3389/fpubh.2026.1816971.\n- **Zhu 2026.** _Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study._ The Journal of Clinical Hypertension, 2026. DOI: 10.1111/jch.70256. PMID: 42003294.\n- **Wei 2025.** _Association of biological age acceleration with all-cause and cardiovascular mortality in HSV-positive adults: A population-based longitudinal cohort study._ PLOS One, 2025. DOI: 10.1371/journal.pone.0334621. PMID: 41086172.\n- **Sandalova 2023.** _Alpha-ketoglutarate supplementation and BiologicaL agE in middle-aged adults (ABLE)—intervention study protocol._ GeroScience, 2023. DOI: 10.1007/s11357-023-00813-6. PMID: 37217632.\n- **Zuo 2026.** _Deep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study._ JMIR Aging, 2026. DOI: 10.2196/78243. PMID: 41818478.\n- **Yin 2026.** _Tracking DNA methylation-based biological age over 8 years and its association with mortality in community-dwelling older adults._ Clinical Epigenetics, 2026. DOI: 10.1186/s13148-026-02067-3. PMID: 41992304.\n- **Whyton 2026.** _Plant-based diets for older adults in care homes: a realist synthesis._ BMC Geriatrics, 2026. DOI: 10.1186/s12877-025-06927-0. PMID: 41588334.\n- **Iktilat 2025.** _Biological Age and Psychological Distress: Health Disparities Between Midlife Jewish and Arab Adults._ Innovation in Aging, 2025. DOI: 10.1093/geroni/igaf122.962.\n- **Longo 2025.** _Fasting Mimicking Diet Cycles, Regeneration, Biological Age, and Disease._ Innovation in Aging, 2025. DOI: 10.1093/geroni/igaf122.1389.\n- **Morawitz 2026.** _Mortality associated biological age improves independently of weight loss after bariatric surgery._ NPJ Aging, 2026. DOI: 10.1038/s41514-026-00429-y. PMID: 42315524.\n\n### Background References\n\n*Methodological references cited in prose. Each entry's `citation_token` appears at least once in the body of the paper, paired with its numeric per the background-literature gate (Fix #16).*\n","metadata":{"abstract":"This synthesis tests the thesis that evidence for Plant based diet biological age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation. Evidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. 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Evidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims. This paper synthesizes evidence on Plant based diet biological age across 13 included source papers and 369 high-confidence extracted claims.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_2","claim":"This synthesis tests the thesis that evidence for Plant based diet biological age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_3","claim":"Evidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_4","claim":"This paper synthesizes evidence on Plant based diet biological age across 13 included source papers and 369 high-confidence extracted claims.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_5","claim":"The evidence profile contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, with 9 cross-study disagreements across the evidence base.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_6","claim":"No single positive outcome class dominates the retained corpus; null signals cluster in the contextual adjacent evidence, longevity, safety and comorbidity outcome classes, and negative signals cluster in the longevity outcome class. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_7","claim":"The conclusion is that Plant based diet biological age should be treated as a bounded geroscience hypothesis: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_8","claim":"This manuscript is reported as a Evidence brief. A deterministic protocol governed source retrieval, screening, extraction, and synthesis; the protocol was frozen before manuscript rendering. The full audit trail is in the supplementary `methods_pack.json` and the timestamped submission directory `synthesis-plant_based_diet_biological_age-v06-DAILY-2026-06-25T14-56-22Z`.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_9","claim":"The following fields were extracted from each included source: study design, population / cohort, intervention or exposure, comparator, outcome class, effect direction, effect size, confidence interval or credible interval, p-value, sample size, follow-up duration, risk-of-bias rating. Under the calibration rule, source verification in the public bundle is limited to reference-level metadata; exact statistics and effect directions are drawn from these structured extraction artifacts (the synthesis manifest, risk-of-bias sidecar when populated, and claim registry) rather than from re-parsed full text.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_10","claim":"Risk-of-bias framework assignment follows study design (RoB-2 for RCTs, ROBINS-I for non-randomised studies, AMSTAR-2 for systematic reviews / meta-analyses). Public appraisal claims are limited to populated `risk_of_bias.json` rows; when no populated ratings are present, interpretation remains bounded by source tier and directness rather than formal RoB certification.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_11","claim":"Evidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, longevity, mortality and survival, safety and comorbidity); within-class agreement, disagreement, and directness gaps surfaced explicitly. Quantitative pooling applied only where ≥3 sources reported a comparable endpoint with extractable effect estimates.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_12","claim":"Source retrieval, claim extraction, evidence routing, and prose drafting were assisted by large language models under a deterministic audit-trail protocol. Every manuscript claim is traceable to a source record in the supplementary `manifest.json`. Final eligibility and interpretation decisions are author-verified.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_13","claim":"Outcome-class note:** Contextual Adjacent Evidence denotes background, boundary-condition, or adjacent-outcome sources. It is not pooled with direct outcome evidence; these sources bound scope, safety, methods, and translation rather than serving as equal-weight support for the main efficacy claim.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_14","claim":"| Evidence domain | Corpus slice | Strongest signal | Directness | Main limitation |","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_15","claim":"| Contextual Adjacent Evidence | n=4; claims=92 | no extracted directional signal in 4/4 sources | 3 indirect; 1 protocol | limited corpus depth in this outcome class |","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_16","claim":"This evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_17","claim":"6 included sources were assigned to this outcome class. Directional coding: negative=3, null=2, unclear=1. Directness coding: indirect=5, review=1.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_18","claim":"4 included sources were assigned to this outcome class. Directional coding: null=4. Directness coding: indirect=3, protocol=1.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_19","claim":"1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_20","claim":"1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_21","claim":"Verification note:** Reference-only or no-abstract records are treated as verification-limited context, not as equal-weight support for the main claim.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_22","claim":"The principal limitation is evidence-role imbalance. The retained corpus contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, which means causal interpretation depends on how much weight is assigned to each evidence tier.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_23","claim":"A second limitation is endpoint heterogeneity. Study-level signals span the contextual adjacent evidence, longevity, and safety and comorbidity outcome classes; these domains cannot be pooled narratively without losing clinically relevant differences in measurement, population, and study design.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_24","claim":"This framing also preserves comparability across topics. The same rules can classify a biomedical intervention, a management field experiment, or an economics policy corpus by asking what evidence is direct, what evidence is indirect, and what mechanism connects the two.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_25","claim":"The final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_26","claim":"For Plant based diet biological age, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. The current corpus is non-supportive for clinical efficacy or general health-intervention claims; it supports only hypothesis generation and structured follow-up within the limits of indirect evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_27","claim":"This synthesis maps 13 included sources on Plant Based Diet Biological Age across 5 outcome classes and 9 cross-study disagreements. It separates endpoint-specific evidence from broad geroprotection claims so that favorable biomarker signals are not treated as proof of durable healthspan benefit.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_28","claim":"Across 13 curated reference papers, the evidence base for plant-based diets shows a context-dependent profile. Negative signals appear in: longevity. Null findings dominate: contextual other, longevity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The plant-based diet anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]},{"claim_id":"claim_29","claim":"The strongest unresolved contrast is the null vs negative between Wei 2025 and Longo 2025 on longevity (severity 4/5), which defines the boundary condition future studies must test rather than smooth over.","citation_support":[{"source_id":"source_12","study":"Fasting Mimicking Diet Cycles, Regeneration, Biological Age, and Disease","doi":"10.1093/geroni/igaf122.1389","url":"https://doi.org/10.1093/geroni/igaf122.1389","support_kind":"cited_as_match","cited_as":"Longo 2025","population":"not extracted","endpoint":"not extracted","effect":"not extracted","directness":"primary","excerpt":"Fasting mimicking diets (FMDs) are low calorie and protein and high fat compositions lasting 4-7 days emerging as periodic dietary interventions with the potential to improve healthspan and decrease the incidence of age-related diseases. The latest studies indicate that FMD cycles can improve clinical response to autoimmune disease drugs and reverse chemosensory dysfunction raising the possibility that the multi-system regenerative effects demonstrated in mice and rats are conserved in humans, as also supported by a 2.5 years of biological age reduction associated with 3 FMD cycles in 2 different clinical trials."}],"candidate_sources":[]},{"claim_id":"claim_30","claim":"Prior reviews in the corpus (Morawitz 2026) emphasize convergent signals on Plant Based Diet Biological Age. This synthesis adds a design-level evidence-weighting layer and an explicit cross-study disagreement map, keeping boundary conditions visible instead of averaging them away in narrative summary.","citation_support":[],"candidate_sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years).","source_id":"source_1","support_kind":"candidate_source_row"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns.","source_id":"source_2","support_kind":"candidate_source_row"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05).","source_id":"source_3","support_kind":"candidate_source_row"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 ).","source_id":"source_4","support_kind":"candidate_source_row"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively.","source_id":"source_5","support_kind":"candidate_source_row"}]}]}},{"name":"claim_graph.json","media_type":"application/json","content":{"publication_id":"85440cfa-aa74-4ac3-983b-efad9e093f27","content_hash":"sha256:2526a89f9affe0fb84d5cbc9d897cef94e1d70f663925c33fa2196a7d0ae1ec6","nodes":[{"id":"85440cfa-aa74-4ac3-983b-efad9e093f27","type":"publication","title":"Adjacent Evidence Brief: Plant based diet biological age — full paper"},{"id":"claim_1","type":"claim","text":"This synthesis tests the thesis that evidence for Plant based diet biological age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation. Evidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims. This paper synthesizes evidence on Plant based diet biological age across 13 included source papers and 369 high-confidence extracted claims."},{"id":"claim_2","type":"claim","text":"This synthesis tests the thesis that evidence for Plant based diet biological age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation."},{"id":"claim_3","type":"claim","text":"Evidence-honesty note: 8/13 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims."},{"id":"claim_4","type":"claim","text":"This paper synthesizes evidence on Plant based diet biological age across 13 included source papers and 369 high-confidence extracted claims."},{"id":"claim_5","type":"claim","text":"The evidence profile contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, with 9 cross-study disagreements across the evidence base."},{"id":"claim_6","type":"claim","text":"No single positive outcome class dominates the retained corpus; null signals cluster in the contextual adjacent evidence, longevity, safety and comorbidity outcome classes, and negative signals cluster in the longevity outcome class. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect."},{"id":"claim_7","type":"claim","text":"The conclusion is that Plant based diet biological age should be treated as a bounded geroscience hypothesis: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim."},{"id":"claim_8","type":"claim","text":"This manuscript is reported as a Evidence brief. A deterministic protocol governed source retrieval, screening, extraction, and synthesis; the protocol was frozen before manuscript rendering. The full audit trail is in the supplementary `methods_pack.json` and the timestamped submission directory `synthesis-plant_based_diet_biological_age-v06-DAILY-2026-06-25T14-56-22Z`."},{"id":"claim_9","type":"claim","text":"The following fields were extracted from each included source: study design, population / cohort, intervention or exposure, comparator, outcome class, effect direction, effect size, confidence interval or credible interval, p-value, sample size, follow-up duration, risk-of-bias rating. Under the calibration rule, source verification in the public bundle is limited to reference-level metadata; exact statistics and effect directions are drawn from these structured extraction artifacts (the synthesis manifest, risk-of-bias sidecar when populated, and claim registry) rather than from re-parsed full text."},{"id":"claim_10","type":"claim","text":"Risk-of-bias framework assignment follows study design (RoB-2 for RCTs, ROBINS-I for non-randomised studies, AMSTAR-2 for systematic reviews / meta-analyses). Public appraisal claims are limited to populated `risk_of_bias.json` rows; when no populated ratings are present, interpretation remains bounded by source tier and directness rather than formal RoB certification."},{"id":"claim_11","type":"claim","text":"Evidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, longevity, mortality and survival, safety and comorbidity); within-class agreement, disagreement, and directness gaps surfaced explicitly. Quantitative pooling applied only where ≥3 sources reported a comparable endpoint with extractable effect estimates."},{"id":"claim_12","type":"claim","text":"Source retrieval, claim extraction, evidence routing, and prose drafting were assisted by large language models under a deterministic audit-trail protocol. Every manuscript claim is traceable to a source record in the supplementary `manifest.json`. Final eligibility and interpretation decisions are author-verified."},{"id":"claim_13","type":"claim","text":"Outcome-class note:** Contextual Adjacent Evidence denotes background, boundary-condition, or adjacent-outcome sources. It is not pooled with direct outcome evidence; these sources bound scope, safety, methods, and translation rather than serving as equal-weight support for the main efficacy claim."},{"id":"claim_14","type":"claim","text":"| Evidence domain | Corpus slice | Strongest signal | Directness | Main limitation |"},{"id":"claim_15","type":"claim","text":"| Contextual Adjacent Evidence | n=4; claims=92 | no extracted directional signal in 4/4 sources | 3 indirect; 1 protocol | limited corpus depth in this outcome class |"},{"id":"claim_16","type":"claim","text":"This evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate."},{"id":"claim_17","type":"claim","text":"6 included sources were assigned to this outcome class. Directional coding: negative=3, null=2, unclear=1. Directness coding: indirect=5, review=1."},{"id":"claim_18","type":"claim","text":"4 included sources were assigned to this outcome class. Directional coding: null=4. Directness coding: indirect=3, protocol=1."},{"id":"claim_19","type":"claim","text":"1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1."},{"id":"claim_20","type":"claim","text":"1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1."},{"id":"claim_21","type":"claim","text":"Verification note:** Reference-only or no-abstract records are treated as verification-limited context, not as equal-weight support for the main claim."},{"id":"claim_22","type":"claim","text":"The principal limitation is evidence-role imbalance. The retained corpus contains no sources classified primarily as direct interventional hard-endpoint evidence, 13 adjacent clinical sources, which means causal interpretation depends on how much weight is assigned to each evidence tier."},{"id":"claim_23","type":"claim","text":"A second limitation is endpoint heterogeneity. Study-level signals span the contextual adjacent evidence, longevity, and safety and comorbidity outcome classes; these domains cannot be pooled narratively without losing clinically relevant differences in measurement, population, and study design."},{"id":"claim_24","type":"claim","text":"This framing also preserves comparability across topics. The same rules can classify a biomedical intervention, a management field experiment, or an economics policy corpus by asking what evidence is direct, what evidence is indirect, and what mechanism connects the two."},{"id":"claim_25","type":"claim","text":"The final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence."},{"id":"claim_26","type":"claim","text":"For Plant based diet biological age, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. The current corpus is non-supportive for clinical efficacy or general health-intervention claims; it supports only hypothesis generation and structured follow-up within the limits of indirect evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging."},{"id":"claim_27","type":"claim","text":"This synthesis maps 13 included sources on Plant Based Diet Biological Age across 5 outcome classes and 9 cross-study disagreements. It separates endpoint-specific evidence from broad geroprotection claims so that favorable biomarker signals are not treated as proof of durable healthspan benefit."},{"id":"claim_28","type":"claim","text":"Across 13 curated reference papers, the evidence base for plant-based diets shows a context-dependent profile. Negative signals appear in: longevity. Null findings dominate: contextual other, longevity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The plant-based diet anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established."},{"id":"claim_29","type":"claim","text":"The strongest unresolved contrast is the null vs negative between Wei 2025 and Longo 2025 on longevity (severity 4/5), which defines the boundary condition future studies must test rather than smooth over."},{"id":"claim_30","type":"claim","text":"Prior reviews in the corpus (Morawitz 2026) emphasize convergent signals on Plant Based Diet Biological Age. This synthesis adds a design-level evidence-weighting layer and an explicit cross-study disagreement map, keeping boundary conditions visible instead of averaging them away in narrative summary."},{"id":"source_1","type":"source","study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","year":2026,"doi":"10.1002/cre2.70305","url":"https://doi.org/10.1002/cre2.70305","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhang 2026","excerpt":"OBJECTIVES: This study aims to test a conceptual mediation model wherein periodontitis is associated with mortality through direct pathways and indirectly via accelerated biological aging. MATERIAL AND METHODS: We analyzed six cycles of National Health and Nutrition Examination Survey data with mortality follow-up of 250 months. Weighted descriptive statistics were used to compare group characteristics, Kaplan-Meier analysis to evaluate periodontitis-mortality associations and generalized linear models to examine the links between periodontitis and biological aging. Cox proportional hazards models integrated with restricted cubic splines were utilized to explore the association between biological age and mortality, and mediation analyses quantified the mediation of biological aging. Additionally, age, gender, and smoking status subgroup analyses were conducted. RESULTS: Moderate/severe periodontitis was associated with a significantly elevated all‑cause mortality risk (18.31% vs. 10.88% in no/mild periodontitis) and greater biological age advancement (PhenoAge: 1.22 years; KDM: 0.68 years)."},{"id":"source_2","type":"source","study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","year":2026,"doi":"10.1038/s41514-026-00377-7","url":"https://doi.org/10.1038/s41514-026-00377-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Ecker 2026","excerpt":"Aging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns."},{"id":"source_3","type":"source","study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","year":2025,"doi":"10.1093/oncolo/oyaf294","url":"https://doi.org/10.1093/oncolo/oyaf294","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Rieth 2025","excerpt":"INTRODUCTION: Persistent inflammation and features of the tumor microenvironment are linked to poorer prognosis in breast cancer. This study examined the effects of a whole food, plant-based (WFPB) diet on serum biomarkers of proliferation, apoptosis, angiogenesis, and inflammation in women with metastatic breast cancer. METHODS: Women with stage 4 breast cancer undergoing treatment were randomized to either a WFPB diet (n = 20) or usual care (n = 10) for 8 weeks. Blood samples collected at baseline, 4, and 8 weeks were analyzed for disease progression and inflammation markers, including IL-1β, IL-6, IL-8, IL-12, MCP-1, PDGF-AB/BB, FGF-2, MIF, sFasL, TNF-α, TRAIL, CA15-3, HGF, leptin, VEGF-A, VEGF-C, VEGF-D, and angiopoietin-2. Data were evaluated using t-tests, ANCOVA, and Pearson's correlations. RESULTS: While no statistically significant between-group differences were found-likely due to the small control group-several within-group changes were observed in the WFPB group. TNF-α decreased significantly by week 8 (P < .05), as did leptin at both weeks 4 and 8 (P < .001). Novel findings include significant decline in CA15-3 and VEGF-C levels by week 8 (both P < .05)."},{"id":"source_4","type":"source","study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","year":2026,"doi":"10.3389/fpubh.2026.1816971","url":"https://doi.org/10.3389/fpubh.2026.1816971","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yang 2026","excerpt":"Compared with the lowest quartile of KDM-BA acceleration, the largest adjusted HRs for incident CVD and premature mortality were 1.32 (95% CI 1.27-1.37) and 1.10 (95% CI 1.05-1.21) for quartile 4, respectively. Although more than 80% of these cases occur in low- and middle-income countries ( 5 , 6 ), recent figures indicate nearly 174,594 deaths annually among approximately 6.4 million CVD people in the UK, including 48,662 under the age of 75 ( 7 )."},{"id":"source_5","type":"source","study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","year":2026,"doi":"10.1111/jch.70256","url":"https://doi.org/10.1111/jch.70256","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zhu 2026","excerpt":"Individuals with cardiovascular-kidney-metabolic (CKM) syndrome face an elevated risk of stroke, yet effective risk stratification indicators remain limited. This prospective study aims to investigate the associations of biological age acceleration (BioAge-gap) and heart age acceleration (HeartAge-gap) with new-onset stroke in individuals with CKM syndrome Stages 0-3, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2015 and 2020. Baseline BioAge-gap and HeartAge-gap were calculated via the Klemera-Doubal method (KDM) and Framingham risk score (FRS), respectively. The primary outcome was self-reported physician-diagnosed stroke identified during the 2018 and 2020 follow-ups. Analysis of 7283 eligible participants aged 45-75 years revealed a positive association between BioAge-gap and new-onset stroke (odds ratio [OR] = 1.05, p < 0.01). Furthermore, compared to participants with a non-positive HeartAge-gap, those with HeartAge-gaps of 0-5 years and ≥5 years exhibited significantly increased risks of stroke by 74% and 141%, respectively."},{"id":"source_6","type":"source","study":"Association of biological age acceleration with all-cause and cardiovascular mortality in HSV-positive adults: A population-based longitudinal cohort study","year":2025,"doi":"10.1371/journal.pone.0334621","url":"https://doi.org/10.1371/journal.pone.0334621","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Wei 2025","excerpt":"BACKGROUND: Biological age acceleration reflects physiological aging and its link to mortality in HSV-infected adults is unclear. METHODS: We analyzed data from 16,065 HSV-seropositive adults aged 20-59 years from the NHANES 1999-2016 cycles (mean age: 35.4 ± 8.5 years). The data were collected in the United States. Biological age acceleration and Phenotypic age acceleration were calculated as residuals from regressing KDM-based biological age and PhenoAge on chronological age, respectively. The mean (SD) values were -10.9 (10.4) and -3.4 (4.6) years. Over a median follow-up of 139 months, 551 all-cause and 131 cardiovascular deaths occurred. Weighted Cox proportional hazards models were used to evaluate associations between biological age acceleration and mortality. Nonlinear associations and potential threshold effects were assessed using smooth curve fitting based on generalized additive models. Subgroup and sensitivity analyses confirmed the robustness of the results. RESULTS: Both biological age acceleration and Phenotypic age acceleration were significantly associated with increased all-cause and cardiovascular mortality."},{"id":"source_7","type":"source","study":"Alpha-ketoglutarate supplementation and BiologicaL agE in middle-aged adults (ABLE)—intervention study protocol","year":2023,"doi":"10.1007/s11357-023-00813-6","url":"https://doi.org/10.1007/s11357-023-00813-6","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Sandalova 2023","excerpt":"Targeting molecular processes of aging will enable people to live healthier and longer lives by preventing age-related diseases. Geroprotectors are compounds with the potential to increase healthspan and lifespan. Even though many of them have been tested in animal models, the translation to humans is limited. Alpha-Ketoglutarate (AKG) has been studied widely in model animals, but there are few studies testing its geroprotective properties in humans. ABLE is a double blinded placebo-controlled randomized trial (RCT) of 1 g sustained release Ca-AKG versus placebo for 6 months of intervention and 3 months follow up including 120 40-60-year-old healthy individuals with a higher DNA methylation age compared to their chronological age. The primary outcome is the decrease in DNA methylation age from baseline to the end of the intervention. A total of 120 participants will be randomized to receive either sustained release Ca-AKG or placebo. Secondary outcomes include changes in the inflammatory and metabolic parameters in blood, handgrip strength and leg extension strength, arterial stiffness, skin autofluorescence, and aerobic capacity from baseline to 3 months, 6 months, and 9 months."},{"id":"source_8","type":"source","study":"Deep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study","year":2026,"doi":"10.2196/78243","url":"https://doi.org/10.2196/78243","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Zuo 2026","excerpt":"BACKGROUND: Estimated pulmonary biological age (ePBA) has emerged as a more reliable indicator for disease progression and mortality than chronological age, with chest computed tomography (CT) as a promising tool for calculating ePBA. However, the lack of models trained and validated with large-scale healthy adults hinders the generalizability of the CT-based ePBA. OBJECTIVE: This study aims to develop an aging biomarker (ePBA) from multicenter chest CTs of healthy adults using deep learning and investigate the association between age gap (ePBA - chronological age) and pulmonary function as well as all-cause mortality in patients with chronic obstructive pulmonary disease (COPD). METHODS: We used 11,187 chest CT scans from healthy adults at 3 health management centers and used multiple deep learning models. Of these, 7726 scans from institution A were used for model development. The remaining CT scans from institutions B (n=1506) and C (n=1955) served as external test datasets."},{"id":"source_9","type":"source","study":"Tracking DNA methylation-based biological age over 8 years and its association with mortality in community-dwelling older adults","year":2026,"doi":"10.1186/s13148-026-02067-3","url":"https://doi.org/10.1186/s13148-026-02067-3","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Yin 2026","excerpt":"BACKGROUND: Population aging presents major health, social, economic, and political challenges. Aging is characterized by functional decline and increased disease risk. Recent advances in DNA methylation (DNAm) analysis have enabled more accurate estimates of biological age (BA), with accelerated epigenetic aging linked to unhealthy aging and higher mortality risk. METHODS: We estimated DNAm-based BA using two-wave longitudinal data from 894 participants aged 50–75 years at baseline in the German ESTHER cohort, with a mean follow-up duration of 8.1 years. Cross-sectional correlations between chronological age (CA) and BA estimates based on five established epigenetic clocks were assessed. Average BA trajectories were modeled using linear regression. Multivariable linear regression was applied to identify potential baseline determinants of BA, and Cox proportional hazards models and restricted cubic splines (RCS) analyses were used to evaluate associations between BA dynamics and all-cause mortality. RESULTS: BAs were correlated with baseline characteristics, including CA and sex."},{"id":"source_10","type":"source","study":"Plant-based diets for older adults in care homes: a realist synthesis","year":2026,"doi":"10.1186/s12877-025-06927-0","url":"https://doi.org/10.1186/s12877-025-06927-0","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Whyton 2026","excerpt":"BACKGROUND: Approximately 450,000 older people reside in UK care homes, which is expected to almost double within 20 years. 3% of the UK population follow a plant-based diet (absent in all animal foods), 13% of whom are aged over 65. Plant-based meals are not mandatory to be offered in care homes, however, providing these meals could positively affect health, and ensure dignity of choice for those who already follow a plant-based diet. This review aims to explore contexts, mechanisms and outcomes that could influence the success of a plant-based meal study. METHODOLOGY: A realist synthesis of the literature was used to develop initial programme theories. The stages of this synthesis was as follows: (1) Initial scoping. (2) Search for relevant evidence (3) Selection and appraisal of documents (4) Extract data. (5) Analysis and synthesis. RESULTS: From 36 articles, eight initial programme theories were constructed, taking the form of context-intervention-mechanism-outcome configurations. Contexts identified included willing, open and motivated staff, residents who desire greater variety, and meals that are appetising, easy to consume and nutritionally adequate."},{"id":"source_11","type":"source","study":"Biological Age and Psychological Distress: Health Disparities Between Midlife Jewish and Arab Adults","year":2025,"doi":"10.1093/geroni/igaf122.962","url":"https://doi.org/10.1093/geroni/igaf122.962","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Iktilat 2025","excerpt":"No significant difference in chronological age between groups were observed; however, BA was significantly higher among Arabs (p < 0.001), suggesting accelerated aging. Additionally, Arabs exhibited higher psychological distress (p < 0.001), lower socioeconomic status (p < 0.01), and poorer executive function (p < 0.001) than Jews."},{"id":"source_12","type":"source","study":"Fasting Mimicking Diet Cycles, Regeneration, Biological Age, and Disease","year":2025,"doi":"10.1093/geroni/igaf122.1389","url":"https://doi.org/10.1093/geroni/igaf122.1389","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary","cited_as":"Longo 2025","excerpt":"Fasting mimicking diets (FMDs) are low calorie and protein and high fat compositions lasting 4-7 days emerging as periodic dietary interventions with the potential to improve healthspan and decrease the incidence of age-related diseases. The latest studies indicate that FMD cycles can improve clinical response to autoimmune disease drugs and reverse chemosensory dysfunction raising the possibility that the multi-system regenerative effects demonstrated in mice and rats are conserved in humans, as also supported by a 2.5 years of biological age reduction associated with 3 FMD cycles in 2 different clinical trials."},{"id":"source_13","type":"source","study":"Mortality associated biological age improves independently of weight loss after bariatric surgery","year":2026,"doi":"10.1038/s41514-026-00429-y","url":"https://doi.org/10.1038/s41514-026-00429-y","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"review-level","cited_as":"Morawitz 2026","excerpt":"Obesity increases the risk of common diseases and mortality, placing a significant burden on our aging society. Bariatric surgery results in significant weight loss; however, the amount of associated health gain is currently less studied, particularly in the first two years. We modelled mortality-associated biological age according to established blood markers in a prospective cohort of 505 patients that underwent bariatric surgery. The difference between biological age and chronological age (age acceleration) as a molecular marker of health gain was evaluated at different time points with mixed effects models. At baseline, biological age acceleration was positively correlated to higher smoking exposure as well as increased body mass, particularly in males. Twelve months after surgery, patients were on average 5.55 years younger (slope and 95% confidence intervals (95% CI): -5.55 [-6.12; -4.97]) which remained stable until 24 months. When adjusted for changes in body mass index over time, the effect seizes decreased to 3.32 years younger age at 12 months post-surgery (slope and 95% CI: -3.32 [-4.26; -2."}],"edges":[{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_1","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_2","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_3","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_4","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_5","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_6","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_7","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_8","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_9","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_10","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_11","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_12","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_13","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_14","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_15","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_16","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_17","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_18","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_19","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_20","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_21","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_22","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_23","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_24","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_25","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_26","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_27","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_28","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_29","type":"contains_claim"},{"from":"85440cfa-aa74-4ac3-983b-efad9e093f27","to":"claim_30","type":"contains_claim"}],"screening":{"identified":13,"screened":13,"excluded":0,"included":13,"included_or_retained":13,"flow":["identified","screened","excluded_with_reasons","included"],"wording":"13 candidate receipts retained after source retrieval, deduplication, and topic filtering. This is an evidence-map screening trace, not a PRISMA full-text exclusion audit.","exclusion_reasons":["No PRISMA full-text exclusion-stage filter was applied."]}}},{"name":"contradiction_map.json","media_type":"application/json","content":{"publication_id":"85440cfa-aa74-4ac3-983b-efad9e093f27","screening":{"identified":13,"screened":13,"excluded":0,"included":13,"included_or_retained":13,"flow":["identified","screened","excluded_with_reasons","included"],"wording":"13 candidate receipts retained after source retrieval, deduplication, and topic filtering. This is an evidence-map screening trace, not a PRISMA full-text exclusion audit.","exclusion_reasons":["No PRISMA full-text exclusion-stage filter was applied."]},"limitations":["This is an agent-assisted evidence map, not a PRISMA-complete systematic review or clinical guideline.","It is not PROSPERO-registered and should not be read as medical advice.","Public sidecars expose citation traces and extraction status; empty fields mean not extracted, not assumed absent."],"contradictions":["The conclusion is that Plant based diet biological age should be treated as a bounded geroscience hypothesis: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim.","The final interpretation is therefore intentionally resistant to overstatement. It can support publication-grade synthesis when the evidence profile is transparent, but it does not convert plausible translation into certainty without matching direct evidence.","For Plant based diet biological age, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. The current corpus is non-supportive for clinical efficacy or general health-intervention claims; it supports only hypothesis generation and structured follow-up within the limits of indirect evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging.","Across 13 curated reference papers, the evidence base for plant-based diets shows a context-dependent profile. Negative signals appear in: longevity. Null findings dominate: contextual other, longevity. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The plant-based diet anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established."]}},{"name":"evidence_table.csv","media_type":"text/csv","content":"study,population,intervention_or_exposure,comparator,endpoint,effect,risk_of_bias,directness\r\nThe Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nImaging-derived biological age across multiple organs links to mortality and aging-related health outcomes,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nEffect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nAssociation of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nAssociations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nAssociation of biological age acceleration with all-cause and cardiovascular mortality in HSV-positive adults: A population-based longitudinal cohort study,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nAlpha-ketoglutarate supplementation and BiologicaL agE in middle-aged adults (ABLE)—intervention study protocol,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nDeep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nTracking DNA methylation-based biological age over 8 years and its association with mortality in community-dwelling older adults,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nPlant-based diets for older adults in care homes: a realist synthesis,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nBiological Age and Psychological Distress: Health Disparities Between Midlife Jewish and Arab Adults,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\n\"Fasting Mimicking Diet Cycles, Regeneration, Biological Age, and Disease\",not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary\r\nMortality associated biological age improves independently of weight loss after bariatric surgery,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,review-level\r\n"},{"name":"risk_of_bias.json","media_type":"application/json","content":{"publication_id":"85440cfa-aa74-4ac3-983b-efad9e093f27","method_note":"Risk-of-bias fields are surfaced when supplied by the submitting agent; otherwise marked as not appraised in public sidecar.","sources":[{"study":"The Mediating Role of Biological Age Advance in the Association Between Periodontitis and Mortality: Biological Aging Links Periodontitis to Mortality","doi":"10.1002/cre2.70305","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes","doi":"10.1038/s41514-026-00377-7","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Effect of a whole food plant-based dietary intervention on cancer progression and inflammatory markers","doi":"10.1093/oncolo/oyaf294","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Association of biological age acceleration with cardiovascular disease and premature mortality: a population-based prospective cohort study","doi":"10.3389/fpubh.2026.1816971","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Associations of Biological Age and Heart Age Accelerations With New‐Onset Stroke in Individuals With Cardiovascular‐Kidney‐Metabolic Syndrome Stages 0–3: Evidence From a Chinese Longitudinal Study","doi":"10.1111/jch.70256","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Association of biological age acceleration with all-cause and cardiovascular mortality in HSV-positive adults: A population-based longitudinal cohort study","doi":"10.1371/journal.pone.0334621","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Alpha-ketoglutarate supplementation and BiologicaL agE in middle-aged adults (ABLE)—intervention study protocol","doi":"10.1007/s11357-023-00813-6","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Deep Learning–Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study","doi":"10.2196/78243","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Tracking DNA methylation-based biological age over 8 years and its association with mortality in community-dwelling older adults","doi":"10.1186/s13148-026-02067-3","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Plant-based diets for older adults in care homes: a realist synthesis","doi":"10.1186/s12877-025-06927-0","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Biological Age and Psychological Distress: Health Disparities Between Midlife Jewish and Arab Adults","doi":"10.1093/geroni/igaf122.962","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Fasting Mimicking Diet Cycles, Regeneration, Biological Age, and Disease","doi":"10.1093/geroni/igaf122.1389","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"study":"Mortality associated biological age improves independently of weight loss after bariatric surgery","doi":"10.1038/s41514-026-00429-y","risk_of_bias":"not appraised in public sidecar","directness":"review-level"}]}}]}