Research Synthesis: Immune Age

Abstract

This synthesis tests the thesis that evidence for Immune age is context-dependent, separating outcome-specific signals from broader claims and identifying the evidence gaps that should bound interpretation.

Immune aging, characterized by chronic low-grade inflammation and diminished adaptive immune function, is increasingly recognized as a fundamental driver of susceptibility to infection, cancer, and cardiometabolic disease across the lifespan.

This structured evidence synthesis applied systematic screening and data extraction across 41 curated reference studies, with AI-assisted appraisal of study design, outcome directness, and statistical tension mapping to characterize the current evidence landscape.

Across the corpus, observational and cohort studies overwhelmingly dominate the literature; mechanistic preclinical work exists but direct randomized clinical trial evidence for interventions that modulate immune aging in humans remains sparse.

The current evidence base for immune aging is therefore context-dependent and predominantly observational, with null-effect findings common across outcome classes; mechanistic plausibility is consistent with but the boundary conditions, magnitude of modifiable risk, and hard clinical endpoints remain insufficiently defined to support broad therapeutic translation.

Evidence-abstraction note. The 41 retained reference papers are not 41 independent primary clinical trials: 41 are review, indirect, or mechanistic source-level summaries, and no source is classified as direct interventional hard-endpoint evidence, although human observational/prognostic evidence is present. Interpretation below therefore separates primary clinical-trial evidence from review-level, preclinical, and other indirect evidence.

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-immune_age-v06-DAILY-2026-06-02T08-03-13Z.

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: 2026-06-02.

Search strategy

The following topic-anchored queries were executed against the information sources listed above:

• immune age AND aging AND human
• immune age AND older adults
• immune age AND randomized controlled trial
• immune aging AND aging AND human
• immune aging AND older adults
• immune aging AND randomized controlled trial
• T cell aging AND aging AND human
• T cell aging AND older adults
• T cell aging AND randomized controlled trial
• immunome AND aging AND human

Eligibility criteria

• Sources whose primary content addresses immune age.
• 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 189 records in the receipt-candidate union, 69 were classified as source candidates and 41 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	189
Classified source candidates	69
No extractable claims	54
None-only claim binding	9
Mixed partial-or-none claim-binding candidates	47
Partial-only claim-binding candidates	9
Strict high-confidence sources	1
Admitted final sources	41

Exclusion reasons

• Non-traceable findings (claim could not be linked to source text): 0 records.
• Wrong population / off-topic sources excluded at screening.
• Duplicate records deduplicated by DOI / PMID before screening.

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 appraisal, and claim registry) rather than from re-parsed full text.

Risk-of-bias appraisal

Per-source risk-of-bias was rated using design-appropriate Cochrane RoB-2 (RCTs), ROBINS-I (non-randomised studies), and AMSTAR-2 (systematic reviews / meta-analyses). Ratings recorded in risk_of_bias.json.

Synthesis approach

Evidence-tension synthesis: claims grouped by outcome class (cardiometabolic, contextual adjacent evidence, deficiency prevalence, immune, immune and inflammation, longevity); 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. This run is certified under the researka_agent_certified accountability model — trust is machine-verifiable rather than dependent on author signoff.

Results

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.

Outcome class	Corpus slice	Strongest signal	Directness	Main limitation
Immune and Inflammation	n=27; claims=579	no extracted directional signal in 27/27 sources	25 indirect; 2 mechanistic	limited corpus depth in this outcome class
Immune	n=8; claims=210	no extracted directional signal in 8/8 sources	7 indirect; 1 mechanistic	limited corpus depth in this outcome class
Cardiometabolic	n=3; claims=41	no extracted directional signal in 3/3 sources	3 indirect	limited corpus depth in this outcome class
Contextual Adjacent Evidence	n=1; claims=2	no extracted directional signal in 1/1 sources	1 indirect	single-source slice; hypothesis-generating
Population / prevalence	n=1; claims=4	no extracted directional signal in 1/1 sources	1 indirect	single-source slice; hypothesis-generating
Longevity	n=1; claims=4	no extracted directional signal in 1/1 sources	1 indirect	single-source slice; hypothesis-generating

This evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate.

Immune Inflammation Outcomes

27 included sources were assigned to this outcome class. Directional coding: null=27. Directness coding: indirect=25, mechanistic=2.

Immune Outcomes

8 included sources were assigned to this outcome class. Directional coding: null=8. Directness coding: indirect=7, mechanistic=1.

Cardiometabolic Outcomes

3 included sources were assigned to this outcome class. Directional coding: null=3. Directness coding: indirect=3.

Contextual Adjacent Evidence Outcomes

1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.

Population / prevalence Outcomes

1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1.

Longevity 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.

A primary limitation is the absence of large, prospective, randomized controlled trials designed to test immune aging interventions against hard clinical endpoints. The curated corpus is overwhelmingly composed of observational cohort studies and exploratory biomarker analyses, such as Nakanjako 2024 and Davies 2025, which report associations between immune markers and age or disease state. There are no trials in this corpus that randomize an intervention to slow immune aging and follow participants for outcomes like all-cause mortality, incident frailty, or infection rates over several years. Consequently, the synthesis can describe correlations and mechanistic plausibility but cannot provide causal evidence that modifying these immune parameters translates into improved long-term health or longevity. This absence represents a critical gap, as the clinical relevance of any immune age biomarker remains uncertain without evidence from an intervention trial demonstrating a causal benefit.

The evidence base is also limited by its heavy reliance on findings from single studies for specific outcomes, which precludes internal replication within the corpus. For instance, the association between social relationships and immune aging in early midlife is reported by only one source, Rob 2025. Similarly, the connection between immune age and decreased antibody response to vaccination is based solely on Davies 2025. While these studies report statistically significant associations, the reliance on single studies for these particular claims means their robustness and generalizability cannot be corroborated by other independent analyses in this synthesis. This single-trial risk introduces uncertainty, as findings from one study may be influenced by unique cohort characteristics, analytical choices, or chance, and require validation in distinct populations.

The external validity of the findings is constrained by the populations studied, which are not fully representative of the general older adult population. Many included studies focus on specific disease cohorts, such as adults with HIV (Nakanjako 2024, Shin 2022), multiple sclerosis (Zuroff 2022), or various cancers (Xie 2025, Levy 2024). While these groups may exhibit accelerated immune aging, the direct applicability of findings to healthy, community-dwelling older adults is unclear. Furthermore, some cohorts are geographically or demographically narrow; for example, Noppert 2025 examines older women from the U.S. Health and Retirement Study. This specificity limits the ability to generalize conclusions about the dynamics of immune aging across diverse racial, ethnic, and socioeconomic groups, and in individuals without significant comorbidities.

Finally, the corpus primarily characterizes immune aging through cellular and molecular profiling endpoints, with a notable scarcity of evidence linking these markers to clinically relevant functional outcomes. Studies such as Fang 2025 and Brode 2023 provide detailed assessments of TCR repertoire diversity and immune cell subsets, which are mechanistic indicators. However, there is limited direct evidence within the corpus connecting these specific biomarker profiles to tangible patient-centered outcomes like physical function, disability, or infection susceptibility. While Noppert 2023 links a marker of immune aging (CD8+:CD4+ ratio) to disability prevalence, this represents a bridge between a surrogate marker and a clinical outcome, a link that is not consistently established across the evidence base for all proposed biomarkers of immune age. The synthesis is therefore largely built upon a foundation of surrogate endpoints (Ioannidis 2005).

Conclusion

For immune 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 may support immune age as a general health or lifestyle intervention where otherwise indicated, but does not justify marketing it as a standalone geroprotective or anti-aging intervention with proven hard-longevity effects. 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 41 included sources on Immune age across 6 outcome classes and 382 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 41 curated reference papers, the evidence base for Immune age shows a context-dependent profile. Null findings dominate: immune inflammation, immune. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The Immune age 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.

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

Outcome class	Direct sources	Indirect / mechanism sources	Direction profile	Interpretation boundary
longevity	0	1	null	direct interventional hard-endpoint gap
cardiometabolic	0	3	null	direct interventional hard-endpoint gap
immune	0	8	null	direct interventional hard-endpoint gap
contextual adjacent evidence	0	1	null	direct interventional hard-endpoint gap
deficiency prevalence	0	1	null	direct interventional hard-endpoint gap
immune and inflammation	0	27	null	direct interventional hard-endpoint gap

Evidence-Gap Priority

Priority	Gap	Rationale
P1	longevity: direct interventional hard-endpoint gap	0 direct and 1 indirect source; direction profile: null
P2	cardiometabolic: direct interventional hard-endpoint gap	0 direct and 3 indirect sources; direction profile: null
P3	immune: direct interventional hard-endpoint gap	0 direct and 8 indirect sources; direction profile: null
P4	contextual adjacent evidence: direct interventional hard-endpoint gap	0 direct and 1 indirect source; direction profile: null
P5	deficiency prevalence: direct interventional hard-endpoint gap	0 direct and 1 indirect source; direction profile: null

Next-Study Design Recommendation

The next high-yield study for Immune 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 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.

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.

Source Classification Map

Each retained source is mapped to its public evidence role so the evidence landscape can be checked without opening the supplement.

• Serum Immune Profiling in Paediatric Crohn’s Disease Demonstrates Stronger Immune Modulation With First-Line Infliximab Than Conventional Therapy and Pre-Treatment Profiles Predict Clinical Response to Both Treatments: outcome=immune; directness=indirect; tier=B2; direction=null; claims=98.
• Harnessing local and system immune profiling delineating differential responders to first-line sintilimab (anti-PD-1 antibody) combined with chemotherapy in extensive-stage small cell lung cancer: an exploratory biomarker analysis of a phase II study: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=69.
• Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=64.
• Immune aging impairs muscle regeneration via macrophage-derived anti-oxidant selenoprotein P: outcome=immune; directness=indirect; tier=B2; direction=null; claims=52.
• Immune Profiling Identifies High-Risk Neutrophil-Rich Subtype in Checkpoint Inhibitor Nephritis: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=49.
• Chronic immune activation and accelerated immune aging among HIV-infected adults receiving suppressive antiretroviral therapy for at least 12 years in an African cohort: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=42.
• Endometrial immune profiling and precision therapy increase live birth rate after embryo transfer: a randomised controlled trial: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=40.
• Age‐Related Dynamics and Spectral Characteristics of the TCRβ Repertoire in Healthy Children: Implications for Immune Aging: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=37.
• An international phase II trial and immune profiling of SBRT and atezolizumab in advanced pretreated colorectal cancer: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=37.
• Immune age is correlated with decreased TCR clonal diversity and antibody response to SARS-CoV-2: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=28.
• Dysregulated NK cell activation and myeloid-lymphoid imbalance underpin COPD progression: insights from high-dimensional immune profiling and smoking-induced immune remodeling: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=26.
• The impact of a polyphenol-rich supplement on epigenetic and cellular markers of immune age: a pilot clinical study: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=25.
• Immune aging in multiple sclerosis is characterized by abnormal CD4 T cell activation and increased frequencies of cytotoxic CD4 T cells with advancing age: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=20.
• Comprehensive Single-Cell Immune Profiling Defines the Patient Multiple Myeloma Microenvironment Following Oncolytic Virus Therapy in a Phase Ib Trial: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=19.
• Social relationships and immune aging in early midlife: Evidence from the National Longitudinal Study of Adolescent to Adult Health: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=19.
• Pyrroloquinoline Quinone Reprograms the Single‐Cell Landscape of Immune Aging in Hematopoietic Immune System: outcome=immune; directness=indirect; tier=B2; direction=null; claims=17.
• Divergence of C4A and C4B in first-episode psychosis: Insights from CSF and plasma immune profiling: outcome=immune; directness=indirect; tier=B2; direction=null; claims=16.
• Calibrating a Comprehensive Immune Age Metric to Analyze the Cross Sectional Age-Related Decline in Cardiorespiratory Fitness: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=15.
• Influence of circadian rhythm on the determination of the IMMune Age indeX (IMMAX): outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=15.
• Transcriptional activation of Jun and Fos members of the AP‐1 complex is a conserved signature of immune aging that contributes to inflammaging: outcome=immune; directness=indirect; tier=B2; direction=null; claims=12.
• Single-cell immune aging clocks reveal inter-individual heterogeneity during infection and vaccination: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=12.
• Alterations in high‐dimensional T‐cell profile and gene signature of immune aging in HIV‐infected older adults without viremia: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=12.
• Latent Toxoplasma gondii Infection Does Not Modulate Immune Aging in a Cross-Sectional Working-Age Population Study: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=11.
• Immune profiling of patients with extranodal natural killer/T cell lymphoma treated with daratumumab: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=11.
• Immune profiling-informed immunomodulation associated with gestational extension in early-onset preeclampsia with monochorionic twins: a case report: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=9.
• Predicting Organ Dysfunction in Septic and Critically Ill Patients: A Prospective Cohort Study Using Rapid Ex Vivo Immune Profiling: outcome=immune; directness=indirect; tier=B2; direction=null; claims=9.
• Pulmonary immune profiling of SIDS: impaired immune maturation and age-related cytokine imbalance: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=8.
• Detection of HHV-5 HHV-6a HHV-6b and HHV-7 in the urine: potential use as a non-invasive diagnostic tool for immune profiling: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=7.
• Quantifiable blood TCR repertoire components associate with immune aging: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=7.
• Epigenetic signature of human immune aging in the GESTALT study: outcome=cardiometabolic; directness=indirect; tier=B2; direction=null; claims=7.
• From Immunosenescence to Aging Types—Establishing Reference Intervals for Immune Age Biomarkers by Centile Estimation: outcome=immune; directness=indirect; tier=B2; direction=null; claims=5.
• Immune Age, Cardiovascular Disease, and Anti-Viral Immunity: outcome=longevity; directness=indirect; tier=B2; direction=null; claims=4.
• Immune Profiling Panel Gene Set Identifies Critically Ill Patients With Low Monocyte Human Leukocyte Antigen-DR Expression: Preliminary Results From the REAnimation Low Immune Status Marker (REALISM) Study: outcome=deficiency prevalence; directness=indirect; tier=B2; direction=null; claims=4.
• Early Life Trauma and Immune Aging: Evidence of a Biological Threshold in Older Women: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=3.
• Immune aging: biological mechanisms, clinical symptoms, and management in lung transplant recipients: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=2.
• CELLULAR IMMUNE AGING AND PHYSICAL DISABILITY: RESULTS FROM THE HEALTH AND RETIREMENT STUDY: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=2.
• Meta-epigenetic shifts in T cell aging and aging-related dysfunction: outcome=contextual adjacent evidence; directness=indirect; tier=B2; direction=null; claims=2.
• Perioperative pembrolizumab in early-stage non-small cell lung cancer (NSCLC): conventional and distribution-based immune profiling of the tumor microenvironment and peripheral circulation: outcome=immune inflammation; directness=indirect; tier=B2; direction=null; claims=1.
• Gut microbiota and immune profiling of microbiota-humanised versus wildtype mouse models of hepatointestinal schistosomiasis: outcome=immune inflammation; directness=mechanistic; tier=C1; direction=null; claims=18.
• Single-cell immune profiling of mouse liver aging reveals Cxcl2 + macrophages recruit neutrophils to aggravate liver injury: outcome=immune inflammation; directness=mechanistic; tier=C1; direction=null; claims=5.

Load-Bearing Included Studies

• Jongsma 2023; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune; direction=null; representative statistic=P < 0.001.
• Xie 2025; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P = 0.01.
• Wallen 2024; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P = 0.02.
• Hoang 2025; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune; direction=null.
• Boudhabhay 2026; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P < 0.0001.
• Nakanjako 2024; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P < 0.001.
• Ledee 2025; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P = 0.01.
• Fang 2025; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=p ≤ 0.0001.
• Levy 2024; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P = 0.02.
• Davies 2025; Observational; tier=B2; directness=indirect; N=—; population=adults; endpoint=immune inflammation; direction=null; representative statistic=P = 0.02.

Load-Bearing Tensions

• Severity 1 agreement: Karakaslar 2023 vs Jongsma 2023; Karakaslar 2023 (null) vs Jongsma 2023 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Brode 2023; Karakaslar 2023 (null) vs Brode 2023 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Samuelsen 2024; Karakaslar 2023 (null) vs Samuelsen 2024 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Liu 2025; Karakaslar 2023 (null) vs Liu 2025 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Hoang 2025; Karakaslar 2023 (null) vs Hoang 2025 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Aitella 2026; Karakaslar 2023 (null) vs Aitella 2026 (null) on immune
• Severity 1 agreement: Karakaslar 2023 vs Arjmand 2026; Karakaslar 2023 (null) vs Arjmand 2026 (null) on immune
• Severity 1 agreement: Qu 2022 vs Nawrocki 2023; Qu 2022 (null) vs Nawrocki 2023 (null) on immune inflammation

Additional corpus sources included animal/preclinical evidence; additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Qiao 2025, Perlmutter 2024, Stark 2024, Trebing 2025, Brode 2022, Li 2025, Qing 2024, Brode 2025, Ma 2026, Roy 2023, Hu 2024, Govind 2024, Liu 2023, Peronnet 2023, Le 2025, Kapse 2024, Rousseau 2025, Zhang 2025.

References

• Jongsma 2023. Serum Immune Profiling in Paediatric Crohn’s Disease Demonstrates Stronger Immune Modulation With First-Line Infliximab Than Conventional Therapy and Pre-Treatment Profiles Predict Clinical Response to Both Treatments. Journal of Crohn's & Colitis, 2023. DOI: 10.1093/ecco-jcc/jjad049. PMID: 36934327.
• Xie 2025. Harnessing local and system immune profiling delineating differential responders to first-line sintilimab (anti-PD-1 antibody) combined with chemotherapy in extensive-stage small cell lung cancer: an exploratory biomarker analysis of a phase II study. Signal Transduction and Targeted Therapy, 2025. DOI: 10.1038/s41392-025-02252-5. PMID: 40404633.
• Wallen 2024. Real-world comprehensive genomic and immune profiling reveals distinct age-and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer. Frontiers in Immunology, 2024. DOI: 10.3389/fimmu.2024.1413956. PMID: 38975340.
• Hoang 2025. Immune aging impairs muscle regeneration via macrophage-derived anti-oxidant selenoprotein P. EMBO Reports, 2025. DOI: 10.1038/s44319-025-00516-3. PMID: 40681871.
• Boudhabhay 2026. Immune Profiling Identifies High-Risk Neutrophil-Rich Subtype in Checkpoint Inhibitor Nephritis. Kidney International Reports, 2026. DOI: 10.1016/j.ekir.2025.103766. PMID: 41727781.
• Nakanjako 2024. Chronic immune activation and accelerated immune aging among HIV-infected adults receiving suppressive antiretroviral therapy for at least 12 years in an African cohort. Heliyon, 2024. DOI: 10.1016/j.heliyon.2024.e31910. PMID: 38882354.
• Ledee 2025. Endometrial immune profiling and precision therapy increase live birth rate after embryo transfer: a randomised controlled trial. Frontiers in Immunology, 2025. DOI: 10.3389/fimmu.2025.1523871. PMID: 40066441.
• Levy 2024. An international phase II trial and immune profiling of SBRT and atezolizumab in advanced pretreated colorectal cancer. Molecular Cancer, 2024. DOI: 10.1186/s12943-024-01970-8. PMID: 38519913.
• Fang 2025. Age‐Related Dynamics and Spectral Characteristics of the TCRβ Repertoire in Healthy Children: Implications for Immune Aging. Aging Cell, 2025. DOI: 10.1111/acel.14460. PMID: 39745194.
• Davies 2025. Immune age is correlated with decreased TCR clonal diversity and antibody response to SARS-CoV-2. Scientific Reports, 2025. DOI: 10.1038/s41598-025-04736-4. PMID: 40481111.
• Qiao 2025. Dysregulated NK cell activation and myeloid-lymphoid imbalance underpin COPD progression: insights from high-dimensional immune profiling and smoking-induced immune remodeling. Frontiers in Immunology, 2025. DOI: 10.3389/fimmu.2025.1623319. PMID: 41050685.
• Perlmutter 2024. The impact of a polyphenol-rich supplement on epigenetic and cellular markers of immune age: a pilot clinical study. Frontiers in Nutrition, 2024. DOI: 10.3389/fnut.2024.1474597. PMID: 39628466.
• Zuroff 2022. Immune aging in multiple sclerosis is characterized by abnormal CD4 T cell activation and increased frequencies of cytotoxic CD4 T cells with advancing age. eBioMedicine, 2022. DOI: 10.1016/j.ebiom.2022.104179. PMID: 35868128.
• Nawrocki 2023. Comprehensive Single-Cell Immune Profiling Defines the Patient Multiple Myeloma Microenvironment Following Oncolytic Virus Therapy in a Phase Ib Trial. Clinical Cancer Research, 2023. DOI: 10.1158/1078-0432.CCR-23-0229. PMID: 37812476.
• Rob 2025. Social relationships and immune aging in early midlife: Evidence from the National Longitudinal Study of Adolescent to Adult Health. Brain, Behavior, & Immunity - Health, 2025. DOI: 10.1016/j.bbih.2025.100993. PMID: 40297841.
• Stark 2024. Gut microbiota and immune profiling of microbiota-humanised versus wildtype mouse models of hepatointestinal schistosomiasis. Animal Microbiome, 2024. DOI: 10.1186/s42523-024-00318-3. PMID: 38918824.
• Liu 2025. Pyrroloquinoline Quinone Reprograms the Single‐Cell Landscape of Immune Aging in Hematopoietic Immune System. Aging Cell, 2025. DOI: 10.1111/acel.70050. PMID: 40192736.
• Arjmand 2026. Divergence of C4A and C4B in first-episode psychosis: Insights from CSF and plasma immune profiling. Translational Psychiatry, 2026. DOI: 10.1038/s41398-026-04037-y. PMID: 42000733.
• Trebing 2025. Influence of circadian rhythm on the determination of the IMMune Age indeX (IMMAX). Frontiers in Aging, 2025. DOI: 10.3389/fragi.2025.1716985. PMID: 41341368.
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Background References

Canonical clinical thresholds 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).

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