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# Hypothesis-Generating Brief: Plasma proteomic age clocks — full paper ## Abstract Evidence-honesty note: 58/60 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. 59/60 retained sources are indirect, review-level, adjacent, or mechanistic and are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims. This paper synthesizes evidence on Plasma proteomic age clocks across 60 accepted source papers and 1589 high-confidence extracted claims. The evidence profile contains 1 direct clinical source, 57 adjacent clinical sources, and 2 mechanistic or model-system sources, with 59 cross-study disagreements across the evidence base. No single positive outcome class dominates the retained corpus; null signals cluster in the contextual adjacent evidence, immune and inflammation, cardiometabolic outcome classes, and negative signals cluster in no dominant outcome class. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect. The conclusion is that Plasma proteomic age clocks remains a bounded geroscience case: the retained clinical and mechanistic evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim. ## Methods ### Review type and protocol 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-plasma_proteomic_age_clocks-v06-DAILY-2026-06-23T20-54-00Z-R2`. ### Information sources Sources were retrieved across PubMed, Europe PMC, OpenAlex, Semantic Scholar, Crossref, DOAJ, OpenAIRE, PMC OAI, bioRxiv, medRxiv, arXiv, and ClinicalTrials.gov. Retrieval window: 2026-06-23. ### Search strategy The following topic-anchored queries were executed against the information sources listed above: - `plasma proteomic age clocks AND aging AND human` - `plasma proteomic age clocks AND older adults` - `plasma proteomic age clocks AND randomized controlled trial` - `plasma proteomics AND aging AND human` - `plasma proteomics AND older adults` - `plasma proteomics AND randomized controlled trial` - `proteomic aging clock AND aging AND human` - `proteomic aging clock AND older adults` - `proteomic aging clock AND randomized controlled trial` - `blood protein age AND aging AND human` ### Eligibility criteria - Sources whose primary content addresses plasma proteomic age clocks. - Sources with extractable quantitative or qualitative findings. - Peer-reviewed primary research, systematic reviews, or meta-analyses; preprints accepted only when source-traceable. - Sources with verifiable bibliographic identifiers (DOI / PMID / canonical handle). ### Selection of sources of evidence The 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 190 records in the receipt-candidate union, 70 were classified as source candidates and 60 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. ### source admission funnel | Admission bucket | n | |---|---:| | Receipt candidate union | 190 | | Classified source candidates | 70 | | No extractable claims | 18 | | None-only claim binding | 17 | | Mixed partial-or-none claim-binding candidates | 75 | | Partial-only claim-binding candidates | 10 | | Strict high-confidence sources | 0 | | Admitted final sources | 60 | ### Exclusion reasons - 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. ### Data items 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. ### Risk-of-bias appraisal 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. ### Synthesis approach Evidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, deficiency prevalence, immune and inflammation, longevity, mechanism, muscle function, safety, 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. ### AI-use disclosure 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. ### Accountability Accountability 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. ## Results | Evidence domain | Corpus slice | Strongest signal | Directness | Main limitation | |---|---|---|---|---| | Contextual Adjacent Evidence | n=28; claims=675 | no extracted directional signal in 27/28 sources | 28 indirect | limited corpus depth in this outcome class | | Immune and Inflammation | n=12; claims=287 | no extracted directional signal in 11/12 sources | 1 direct; 11 indirect | limited corpus depth in this outcome class | | Cardiometabolic | n=8; claims=359 | no extracted directional signal in 8/8 sources | 8 indirect | limited corpus depth in this outcome class | | Longevity | n=4; claims=116 | no extracted directional signal in 4/4 sources | 4 indirect | limited corpus depth in this outcome class | | Safety and Comorbidity | n=4; claims=92 | no extracted directional signal in 4/4 sources | 3 indirect; 1 mechanistic | limited corpus depth in this outcome class | | Deficiency Prevalence | n=1; claims=8 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Mechanism | n=1; claims=2 | no extracted directional signal in 1/1 sources | 1 mechanistic | single-source slice; hypothesis-generating | | Muscle Function | n=1; claims=44 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Safety | n=1; claims=6 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | **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. This evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate. ### Contextual Adjacent Evidence Outcomes 28 included sources were assigned to this outcome class. Directional coding: null=27, unclear=1. Directness coding: indirect=28. ### Cardiometabolic Outcomes 8 included sources were assigned to this outcome class. Directional coding: null=8. Directness coding: indirect=8. ### Immune Outcomes 7 included sources were assigned to this outcome class. Directional coding: null=7. Directness coding: direct=1, indirect=6. 5 included sources were assigned to this outcome class. Directional coding: mixed=1, null=4. Directness coding: indirect=5. Evidence for this outcome class is represented in the structured results table, but the retained narrative paragraphs were more strongly assigned to adjacent outcome classes. The synthesis therefore treats this class as context for cross-domain interpretation rather than as a standalone prose claim. ### Longevity Outcomes 4 included sources were assigned to this outcome class. Directional coding: null=4. Directness coding: indirect=4. ### Safety Comorbidity Outcomes 4 included sources were assigned to this outcome class. Directional coding: null=4. Directness coding: indirect=3, mechanistic=1. ### Deficiency Prevalence Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ### Mechanism Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: mechanistic=1. ### Muscle Function Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ### Safety Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ## Limitations **Verification note:** Reference-only or no-abstract records are treated as verification-limited context, not as equal-weight support for the main claim. The principal limitation is evidence-role imbalance. The retained corpus contains 1 direct clinical source, 57 adjacent clinical sources, and 2 mechanistic or model-system sources, which means causal interpretation depends on how much weight is assigned to each evidence tier. A second limitation is endpoint heterogeneity. Study-level signals span no dominant outcome class, the contextual adjacent evidence, immune and inflammation, cardiometabolic outcome classes, no dominant outcome class, and the immune and inflammation outcome class; these domains cannot be pooled narratively without losing clinically relevant differences in measurement, population, and study design. A 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. 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. 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. Readers 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. Interpretation 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. ## Conclusion For Plasma proteomic age clocks, the final interpretation is deliberately tiered: the retained clinical and mechanistic 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. ## What This Synthesis Adds This synthesis maps 60 included sources on Plasma Proteomic Age Clocks across 10 outcome classes and 59 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. Across 60 curated reference papers, the evidence base for Plasma proteomic age clocks shows a context-dependent profile. Null findings dominate: contextual other, cardiometabolic. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The Plasma 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. The strongest unresolved contrast is the mechanism vs clinical between Shah 2024 and Navarro 2015 on cardiometabolic (severity 3/5), which defines the boundary condition future studies must test rather than smooth over. 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. ### Boundary-Condition Matrix | Evidence domain | Direct sources | Indirect / mechanism sources | Direction profile | Interpretation boundary | |---|---:|---:|---|---| | longevity | 0 | 4 | null | direct interventional hard-endpoint gap | | cardiometabolic | 0 | 8 | null | direct interventional hard-endpoint gap | | muscle function | 0 | 1 | null | direct interventional hard-endpoint gap | | safety | 0 | 1 | null | direct interventional hard-endpoint gap | | mechanism | 0 | 1 | null | direct interventional hard-endpoint gap | | contextual adjacent evidence | 0 | 28 | null, unclear | direct interventional hard-endpoint gap | | deficiency prevalence | 0 | 1 | null | direct interventional hard-endpoint gap | | immune | 1 | 6 | null | replication gap | | immune and inflammation | 0 | 5 | mixed, null | direct interventional hard-endpoint gap | | safety and comorbidity | 0 | 4 | null | direct interventional hard-endpoint gap | ### Evidence-Gap Priority | Priority | Gap | Rationale | |---|---|---| | P1 | longevity: direct interventional hard-endpoint gap | 0 direct and 4 indirect sources; direction profile: null | | P2 | cardiometabolic: direct interventional hard-endpoint gap | 0 direct and 8 indirect sources; direction profile: null | | P3 | muscle function: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null | | P4 | safety: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null | | P5 | mechanism: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null | ### Next-Study Design Recommendation The next high-yield study for Plasma Proteomic Age Clocks 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 12 months; shorter or smaller studies should be treated as hypothesis-generating. ## Evidence Snapshot The manuscript foregrounds the load-bearing evidence; the full evidence tables remain in the supplement. ### Load-Bearing Included Studies - Additional corpus sources included animal/preclinical evidence; Navarro 2015; tier=A1; directness=direct; endpoint=immune; direction=null. - Argentieri 2024; tier=B2; directness=indirect; endpoint=cardiometabolic; direction=null. - Li 2025; tier=B2; directness=indirect; endpoint=cardiometabolic; direction=null. - Vadaq 2022; tier=B2; directness=indirect; endpoint=immune; direction=null. - Manousopoulou 2020; tier=B2; directness=indirect; endpoint=cardiometabolic; direction=null; representative statistic=P = 0.20. - Huang 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null. - Wang 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null; representative statistic=P = 0.052. - Pooja 2021; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null. - Gonzales 2020; tier=B2; directness=indirect; endpoint=longevity; direction=null; representative statistic=P = 0.05. - He 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null. ### Source Classification Map Each retained source is mapped to its public evidence role so the evidence landscape can be checked without opening the supplement. - Randomized Trial of Glucosamine and Chondroitin Supplementation on Inflammation and Oxidative Stress Biomarkers and Plasma Proteomics Profiles in Healthy Humans: outcome=immune; directness=direct; tier=A1; direction=null; claims=38. - Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=102. - Modifiable risk factors and plasma proteomics in relation to complications of type 2 diabetes: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=85. - Targeted plasma proteomics reveals upregulation of distinct inflammatory pathways in people living with HIV: outcome=immune; directness=indirect; tier=B2; direction=null; claims=82. - Increased plasma CD14 levels 1 year postpartum in women with pre-eclampsia during pregnancy: a case–control plasma proteomics study: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=72. - Seminal plasma proteomics of asymptomatic COVID-19 patients reveals disruption of male reproductive function: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=69. - Organ-specific proteomic aging clocks predict disease and longevity across diverse populations: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=69. - TMT-Based Plasma Proteomics Reveals Dyslipidemia Among Lowlanders During Prolonged Stay at High Altitudes: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=67. - Plasma proteomics reveals markers of metabolic stress in HIV infected children with severe acute malnutrition: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=66. - Plasma proteomics identifies S100A8/A9 as a novel biomarker and therapeutic target for fulminant myocarditis: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=54. - Large scale plasma proteomics identifies novel proteins and protein networks associated with heart failure development: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=47. - Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=45. - General intelligence is associated with subclinical inflammation in Nepalese children: A population-based plasma proteomics study: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=44. - Plasma proteomics improves risk prediction in heart failure and reveals unique biology in chronic chagas cardiomyopathy: outcome=muscle function; directness=indirect; tier=B2; direction=null; claims=44. - Plasma proteomics links brain and immune system aging with healthspan and longevity: outcome=immune inflammation; directness=indirect; tier=B2; direction=mixed; claims=43. - Insulin Sensitivity and Associated Plasma Proteomics During Sex Hormone Therapy: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=39. - Harnessing New Tools for Old Challenges: Optimising Neat Plasma Proteomics with Automation and Gas-Phase Fractionation: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=35. - Neutrophil-associated plasma proteomics identifies HDAC1 as a baseline biomarker of immune tolerance during immunosuppressant withdrawal after pediatric liver transplantation: a single-center cohort study: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=32. - Plasma proteomics identify novel biomarkers and dynamic patterns of biological aging: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=30. - Quantitative plasma proteomics identifies metallothioneins as a marker of acute-on-chronic liver failure associated acute kidney injury: outcome=safety comorbidity; directness=indirect; tier=B2; direction=null; claims=29. - In-depth plasma proteomics reveals increase in circulating PD-1 during anti-PD-1 immunotherapy in patients with metastatic cutaneous melanoma: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=27. - Current landscape of plasma proteomics from technical innovations to biological insights and biomarker discovery: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=27. - Plasma proteomics stratification identifies phospholamban R14del carriers at risk for disease progression: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=24. - Exploratory study linking plasma proteomics to cardiotoxicity in Hodgkin lymphoma: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=24. - Plasma proteomics and incident coronary heart disease: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=23. - Relation Between Plasma Proteomics Analysis and Major Adverse Cardiovascular Events in Patients With Stable Coronary Artery Disease: outcome=safety comorbidity; directness=indirect; tier=B2; direction=null; claims=22. - A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=20. - Analysis of Peripheral T Cell Profiling and Plasma Proteomics in Advanced NSCLC Patients Treated With Atezolizumab: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=20. - Longitudinal plasma proteomics: relation to incident Alzheimer's disease dementia and biomarkers: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=19. - Plasma proteomics profile-based comparison of torso versus brain injury: A prospective cohort study: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=18. - Plasma Proteomics Identifies Thousand‐and‐One–Amino Acid Kinase 3 as a Potential Biomarker of Rheumatoid Arthritis Activity and a Novel Therapeutic Target: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=18. - Assessment of Plasma Proteomics Biomarker’s Ability to Distinguish Benign From Malignant Lung Nodules: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=16. - Plasma Proteomics Reveals Biomarkers and Undulating Changes in Metabolic Aging: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=unclear; claims=16. - Immune status assessment based on plasma proteomics with meta graph convolutional networks: outcome=immune; directness=indirect; tier=B2; direction=null; claims=15. - Deep plasma proteomics identifies and validates an eight-protein biomarker panel that separate benign from malignant tumors in ovarian cancer: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=14. - Prioritizing Candidates of Post–Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=13. - Identification of early prediction biomarkers of severity in patients with severe fever with thrombocytopenia syndrome based on plasma proteomics: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=13. - Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=11. - Proteomic aging clock ( PAC ) predicts age‐related outcomes in middle‐aged and older adults: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=10. - Plasma proteomics profiles predict the risk of future aortic aneurysm and aortic dissection: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=10. ### Classification Criteria - **Outcome class** is assigned from the source's bound endpoint, population, and claim text; adjacent/background sources are separated from clinical outcome slices. - **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. - **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. - **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. ### Load-Bearing Tensions - Severity 3 indirectness gap: Zhang 2025b vs Navarro 2015; Navarro 2015 (direct, A1) vs Zhang 2025b (indirect) on immune — direct vs indirect must be kept separate - Severity 3 indirectness gap: Chu 2025 vs Navarro 2015; Navarro 2015 (direct, A1) vs Chu 2025 (indirect) on immune — direct vs indirect must be kept separate - Severity 3 indirectness gap: Zeng 2026 vs Navarro 2015; Navarro 2015 (direct, A1) vs Zeng 2026 (indirect) on immune — direct vs indirect must be kept separate - Severity 3 indirectness gap: Ravassa 2026 vs Navarro 2015; Navarro 2015 (direct, A1) vs Ravassa 2026 (indirect) on immune — direct vs indirect must be kept separate - Severity 3 indirectness gap: Zhang 2026 vs Navarro 2015; Navarro 2015 (direct, A1) vs Zhang 2026 (indirect) on immune — direct vs indirect must be kept separate - Severity 3 indirectness gap: Navarro 2015 vs Vadaq 2022; Navarro 2015 (direct, A1) vs Vadaq 2022 (indirect) on immune — direct vs indirect must be kept separate - Severity 3 mechanism vs clinical: Shah 2024 vs Navarro 2015; Navarro 2015 (direct, immune) vs Shah 2024 (indirect, cardiometabolic) — cross-domain: clinical evidence on one outcome must not be fused with mechanistic / preclinical evidence on a different outcome - Severity 3 mechanism vs clinical: Fraering 2024 vs Navarro 2015; Navarro 2015 (direct, immune) vs Fraering 2024 (indirect, contextual other) — cross-domain: clinical evidence on one outcome must not be fused with mechanistic / preclinical evidence on a different outcome Additional corpus sources included animal/preclinical evidence; additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Sun 2024, Patane 2026, Lee 2016, Oh 2025, Eeghen 2025, Maxwell 2026, Wang 2026, Ma 2025, Acharya 2023, Kirsher 2025, Babacic 2020, Ulfstedt 2025, Deiman 2026, Huber 2026, Dregoesc 2022, Mouri 2026, Lee 2017, Lee 2025, Tachino 2024, Xin 2026, Zhang 2025, Silvestri 2018, Moskov 2025, Zhang 2025c, Chan 2020, Miller 2021, Kuo 2024, Li 2025b, Rojas-Sanchez 2026, Xu 2025, Zhao 2025, Steelman 2012, Najib 2026, Nunez 2022, Cousin 2024, Fakfum 2024, Fukuda 2026, Hong 2026, Venkatesh 2026, Fan 2025, Lin 2025. Additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Liu 2025, Sari-Ak 2026. ## References - **Argentieri 2024.** _Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations._ Nature Medicine, 2024. DOI: 10.1038/s41591-024-03164-7. PMID: 39117878. - **Li 2025.** _Modifiable risk factors and plasma proteomics in relation to complications of type 2 diabetes._ Nature Communications, 2025. DOI: 10.1038/s41467-025-57830-6. PMID: 40140682. - **Vadaq 2022.** _Targeted plasma proteomics reveals upregulation of distinct inflammatory pathways in people living with HIV._ iScience, 2022. DOI: 10.1016/j.isci.2022.105089. PMID: 36157576. - **Manousopoulou 2020.** _Increased plasma CD14 levels 1 year postpartum in women with pre-eclampsia during pregnancy: a case–control plasma proteomics study._ Nutrition & Diabetes, 2020. DOI: 10.1038/s41387-019-0105-x. PMID: 32066653. - **Huang 2025.** _Seminal plasma proteomics of asymptomatic COVID-19 patients reveals disruption of male reproductive function._ BMC Genomics, 2025. DOI: 10.1186/s12864-025-11473-5. PMID: 40119256. - **Wang 2025.** _Organ-specific proteomic aging clocks predict disease and longevity across diverse populations._ Nature Aging, 2025. DOI: 10.1038/s43587-025-01016-8. PMID: 41299092. - **Pooja 2021.** _TMT-Based Plasma Proteomics Reveals Dyslipidemia Among Lowlanders During Prolonged Stay at High Altitudes._ Frontiers in Physiology, 2021. DOI: 10.3389/fphys.2021.730601. PMID: 34721061. - **Gonzales 2020.** _Plasma proteomics reveals markers of metabolic stress in HIV infected children with severe acute malnutrition._ Scientific Reports, 2020. DOI: 10.1038/s41598-020-68143-7. PMID: 32641735. - **He 2025.** _Plasma proteomics identifies S100A8/A9 as a novel biomarker and therapeutic target for fulminant myocarditis._ Journal of Advanced Research, 2025. 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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).*
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