Research Synthesis: Curcumin Inflammaging

Abstract

Inflammaging, the chronic low-grade inflammation that accompanies aging, is a key driver of age-related disease, and curcumin is a pleiotropic polyphenoid proposed to modulate this process (Xu 2025).

This synthesis employed a structured, AI-assisted evidence review of 61 accepted reference papers to evaluate the clinical and mechanistic evidence for curcumin in the context of inflammaging, adhering to a transparent audit trail.

However, the evidence base is heterogeneous; some trials report null effects on immune markers (Saleh 2025) or on neuropathic outcomes in diabetic patients (Mansour 2025), highlighting the importance of context and condition.

Furthermore, a critical review found curcumin's efficacy is often limited by poor bioavailability, creating a tension between mechanistic promise and clinical realization (Xu 2025).

The synthesis of cross-study disagreements across outcome classes, such as the severe disagreement on dosing pharmacokinetics (Wang 2025; Lamichhane 2025), underscores that the current evidence does not uniformly support a broad anti-aging claim.

The evidence profile indicates that while curcumin demonstrates anti-inflammatory and cardiometabolic effects in specific clinical contexts, its role in combating systemic inflammaging remains incomplete and conditional on factors like bioavailability and population.

Introduction

Global population aging has accelerated interest in interventions that might compress the period of morbidity at the end of life rather than merely extending chronological years. The distinction between lifespan and healthspan is central to this conversation: a therapy that adds years without preserving functional independence may simply shift the burden of disability to later dates. Chronic low-grade inflammation, often termed inflammaging, has been proposed as a unifying mechanism linking age-related declines in muscle strength, cardiometabolic health, and cognitive function. If inflammaging is indeed a tractable driver of multimorbidity, then pharmacological or nutraceutical agents that modulate inflammatory signaling could theoretically delay or attenuate multiple age-related phenotypes simultaneously. Curcumin inflammaging—the use of curcumin or turmeric-derived preparations to target inflammatory processes in the context of aging—has emerged as one such candidate, generating both scientific enthusiasm and considerable skepticism. The question of whether Curcumin inflammaging can meaningfully improve healthspan in older adults remains unresolved, and the urgency of answering it grows as the global population aged 60 and over is projected to reach approximately one-third of total demographics by mid-century. This introduction frames the clinical stakes, the mechanistic rationale, the current human evidence landscape, and the specific contributions of the present synthesis.

The human randomized controlled trial landscape for Curcumin inflammaging spans a remarkably broad range of clinical contexts, from type 2 diabetes and non-alcoholic fatty liver disease to rheumatoid arthritis, osteoarthritis, postmenopausal symptoms, and cognitive aging. Multiple systematic reviews and meta-analyses have been published in recent years, including umbrella reviews evaluating the totality of curcumin evidence across health outcomes (Xu 2025) and focused meta-analyses of lipid profiles (Unhapipatpong 2025), anthropometric indices in diabetes (Baniasadi 2025), rheumatoid arthritis disease activity (Fan 2026), and cognitive function (Wang 2025). Within the present corpus, positive effect directions have been reported for cardiometabolic endpoints including improvements in triglycerides, total cholesterol, and blood pressure in diabetic populations (Baniasadi 2025; Bahari 2025), and for functional endpoints such as reduced gastrointestinal symptoms in women with severe obesity (Kattah 2025). Immune and inflammatory endpoints show a particularly mixed profile, with some trials reporting significant reductions in pro-inflammatory cytokines (Yaikwawong 2026) and others finding no effect on inflammatory biomarkers (Lazou-Ahren 2024; Saleh 2025). The evidence base as a whole appears to support the conclusion that Curcumin inflammaging has a context-dependent profile, with the strongest signals in cardiometabolic and anti-inflammatory domains but persistent uncertainty regarding effect magnitude, durability, and clinical meaningfulness.

Several unresolved questions complicate the translational trajectory of Curcumin inflammaging from bench to bedside. First, the mechanism-to-function translation gap remains wide: preclinical models consistently demonstrate NF-κB inhibition and downstream anti-inflammatory effects, yet human trials frequently report null or inconsistent findings on the same biomarkers, raising the question of whether Curcumin inflammaging achieves sufficient target engagement in vivo or whether the mechanistic story is incomplete. Second, dose-response relationships are poorly characterized; the present corpus includes trials administering doses ranging from 80 mg/day of nano-curcumin (Gerami 2025) to 1500 mg of hydrolyzed curcumin (Helder 2025), with no systematic evidence identifying an optimal therapeutic window. Third, the duration of most trials—typically 8 to 16 weeks—is short relative to the chronicity of inflammaging as a biological process, raising the possibility that longer interventions might be required to observe clinically meaningful effects on healthspan-relevant endpoints. Tradeoffs also merit consideration: curcumin's safety profile is generally favorable, but the absence of long-term safety data in older adult populations, combined with the potential for drug-supplement interactions in polypharmacy regimens, warrants cautious interpretation. The tension between curcumin's accessibility and the rigor of evidence supporting its use in aging populations appears to be a defining feature of the field as currently constituted.

The present synthesis contributes to this landscape by applying a structured evidence-weighting framework that explicitly separates clinical outcome evidence from mechanistic and preclinical data, a distinction that has been insufficiently maintained in prior reviews of Curcumin inflammaging. Across 61 curated reference papers, the evidence base reveals a pattern of cross-outcome tensions: positive signals in cardiometabolic and dosing-pharmacokinetic domains coexist with negative or null findings in immune and inflammatory endpoints, creating cross-study disagreements across outcome classes that are tabulated in the accompanying Cross-Domain Synthesis. This structured approach enables readers to evaluate whether apparent inconsistencies reflect true biological heterogeneity, methodological limitations, or publication bias, rather than accepting surface-level aggregations of effect sizes at face value. We also address the gap between clinical and mechanistic evidence by mapping trial-level findings against proposed molecular mechanisms, identifying domains where mechanistic plausibility is strong but clinical translation has been disappointing, and vice versa. The synthesis further highlights areas of population specificity, where Curcumin inflammaging may perform differently in older adults with prediabetes versus younger adults with rheumatoid arthritis, and identifies dose and formulation as critical moderating variables that future trials should systematically investigate. Ultimately, the Curcumin inflammaging case for anti-aging benefit remains incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions—dose, duration, formulation, population, and target outcome—remain to be rigorously established. This synthesis is intended to provide the structured evidence base necessary for rational clinical trial design and regulatory evaluation in this rapidly evolving field.

Background

The human evidence base for Curcumin inflammaging spans multiple clinical populations, outcome domains, and study designs, yielding a heterogeneous and sometimes contradictory body of findings. Lamichhane 2025, in a pilot trial of curcumin in prediabetic older adults, similarly found null effects on most immune and metabolic markers, with only select glucose homeostasis parameters reaching significance (P = 0.044). The contradiction between positive RCTs in diabetes-associated inflammation (Yaikwawong 2025, Yaikwawong 2025b) and null or negative trials in other inflammatory contexts (Mansour 2025, Saleh 2025) suggests that Curcumin inflammaging effects may be disease-context-dependent rather than uniformly anti-inflammatory across human populations.

Several methodological challenges complicate the interpretation of Curcumin inflammaging evidence and define the boundary conditions for future research. First, the heterogeneity of curcumin formulations across trials—including turmeric powder, standardized extracts, nano-curcumin, phospholipid complexes, and hydrolyzed preparations at doses ranging from 80 mg/day (Gerami 2025) to 1500 mg/day (Helder 2025)—renders cross-trial comparison difficult and may explain discordant findings within the same disease population. Second, intervention durations across the evidence base span from as short as 4 weeks to 12 months (Zeng 2022), and the optimal treatment period for modulating inflammaging biomarkers—particularly in older adults, who are underrepresented in most trials—remains undefined. Third, many curcumin trials combine supplementation with concurrent lifestyle interventions such as resistance training (Flensted-Jensen 2025, Flensted-Jensen 2025b) or dietary modifications (Bourbour 2025, Sukatta 2025), making it impossible to isolate the independent anti-inflammatory contribution of curcumin itself. Finally, the cross-study disagreement map of the present evidence synthesis reveals cross-study disagreements across outcome classes, with particularly pronounced disagreements in the immune and dosing-pharmacokinetics domains—underscoring that the Curcumin inflammaging hypothesis, while biologically plausible, has not yet achieved the evidentiary consistency required to support clinical recommendations for aging populations.

Evidence Context

The evidence context combines established clinical use, adjacent human evidence, animal or cellular mechanisms, and open translational questions. Separating those evidence types prevents later sections from collapsing unlike forms of support into a single verdict. The central research problem remains whether mechanistic plausibility and source-traced findings converge strongly enough to justify further clinical testing while keeping patient-facing claims conservative.

Methods

Review type and protocol

This manuscript is reported as a PRISMA-ScR structured scoping synthesis. 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-curcumin_inflammaging-v06-DAILY-2026-05-31T18-52-16Z.

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: 2026-05-31.

Search strategy

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

• curcumin inflammaging AND aging AND human
• curcumin inflammaging AND older adults
• curcumin inflammaging AND randomized controlled trial
• curcumin AND aging AND human
• curcumin AND older adults
• curcumin AND randomized controlled trial
• turmeric AND aging AND human
• turmeric AND older adults
• turmeric AND randomized controlled trial
• inflammaging AND aging AND human

Eligibility criteria

• Sources whose primary content addresses curcumin inflammaging.
• 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 178 records in the receipt-candidate union, 58 were classified as source candidates and 61 were admitted as traceable synthesis sources. No additional records were excluded after final source admission.

source admission funnel

Admission bucket	n
Receipt candidate union	178
Classified source candidates	58
No extractable claims	25
None-only claim binding	8
Partial/none-only claim binding	25
Partial-only candidates	18
Strict high-confidence sources	44
Admitted final sources	61

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. Source verification in the public bundle is limited to reference-level metadata; reported 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, dosing and pharmacokinetics, immune, immune and inflammation, longevity, muscle function, 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. 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.

Outcome class	Corpus slice	Strongest signal	Directness	Main limitation
Contextual Adjacent Evidence	n=20; claims=1290	null signal in 12/20 sources	1 direct; 5 indirect; 14 review	limited corpus depth in this outcome class
Immune	n=11; claims=514	null signal in 4/11 sources	5 direct; 2 indirect; 4 review	limited corpus depth in this outcome class
Cardiometabolic	n=10; claims=581	positive signal in 3/10 sources	3 direct; 1 indirect; 1 mechanistic; 5 review	limited corpus depth in this outcome class
Dosing and Pharmacokinetics	n=10; claims=1039	unclear signal in 4/10 sources	3 direct; 2 indirect; 5 review	limited corpus depth in this outcome class
Safety and Comorbidity	n=4; claims=198	null signal in 3/4 sources	1 indirect; 3 review	limited corpus depth in this outcome class
Longevity	n=3; claims=24	null signal in 2/3 sources	1 indirect; 2 review	limited corpus depth in this outcome class
Immune and Inflammation	n=2; claims=161	positive signal in 1/2 sources	2 indirect	limited corpus depth in this outcome class
Muscle Function	n=1; claims=2	positive signal in 1/1 sources	1 review	single-source slice; hypothesis-generating

Results Summary

• Contextual Adjacent Evidence: n=20; claims=1290; null signal in 12/20 sources | directness: 1 direct; 5 indirect; main limitation: directionally heterogeneous.
• Immune: n=11; claims=514; null signal in 4/11 sources | directness: 5 direct; 2 indirect; main limitation: directionally heterogeneous.
• Cardiometabolic: n=10; claims=581; benefit signal in 3/10 sources | directness: 3 direct; 1 indirect; 1 mechanistic; main limitation: directionally heterogeneous.
• Dosing and Pharmacokinetics: n=10; claims=1039; mixed signal in 4/10 sources | directness: 3 direct; 2 indirect; main limitation: directionally heterogeneous.
• Safety and Comorbidity: n=4; claims=198; null signal in 3/4 sources | directness: 1 indirect; main limitation: no direct clinical anchor.
• Longevity: n=3; claims=24; null signal in 2/3 sources | directness: 1 indirect; main limitation: no direct clinical anchor.

Cardiometabolic Outcomes

The cardiometabolic evidence base comprises ten studies spanning observational cohorts, randomized controlled trials, systematic reviews, and preclinical models, with the majority focusing on adults with type 2 diabetes mellitus. Baniasadi 2025 and Bahari 2025 each conducted GRADE-assessed systematic reviews and dose-response meta-analyses of randomized controlled trials in prediabetic and diabetic populations, providing pooled estimates across multiple intervention studies.

Quantitative findings across these trials revealed statistically significant improvements in multiple cardiometabolic parameters. Yaikwawong 2025b found curcumin attenuated liver steatosis via antioxidant and anti-inflammatory pathways with all primary outcomes reaching P < 0.001. Amgain 2025 pooled analysis revealed curcumin significantly reduced fasting blood glucose (mean difference = -6.30 mg/dL; 95% CI reported), though this review did not report individual p-values for the pooled estimate.

Mechanistically, the anti-inflammatory and antioxidant pathways implicated in curcumin's cardiometabolic effects align with broader inflammaging biology. Yaikwawong 2025b specifically identified attenuation of liver steatosis through antioxidant and anti-inflammatory pathways in obese patients with T2DM, providing a direct mechanistic link between curcumin supplementation and hepatic lipid metabolism. The convergence of these mechanistic human studies and preclinical data supports biological plausibility for curcumin's cardiometabolic effects, though the specific contribution of curcumin versus other polyphenols requires further delineation.

Within-corpus tensions are apparent when comparing effect directions and endpoint sensitivity across studies. By contrast, Mansour 2025 found that nanocurcumin supplementation over 16 weeks did not improve pain, neuropathic outcomes, or metabolic cardiovascular markers, with the primary neuropathy endpoint yielding P = 0.787 and other outcomes reported as P > 0.05, though one secondary endpoint reached P = 0.010. Cares 2026, a systematic review examining diet and exercise interventions in pediatric cancer survivors, reported null findings for cardiometabolic disease risk and inflammaging biomarkers, contrasting with the positive clinical RCT evidence from Kattah 2025 and Yaikwawong 2025b. These disagreements suggest that curcumin's cardiometabolic benefits may be context-dependent, varying by population, dose, formulation, and specific endpoint measured.

Contextual Adjacent Evidence Outcomes

The curated evidence base encompasses a broad array of clinical contexts in which curcumin's anti-inflammatory and antioxidant properties have been evaluated. Multiple systematic reviews and meta-analyses synthesize findings across rheumatoid arthritis, oral lichen planus, postmenopausal symptoms, metabolic syndrome, osteoarthritis, ulcerative colitis, and Parkinson's disease models (Fan 2026, AlMaweri 2025, Akyakar 2025, Fang 2025, Wang 2025b, Pang 2026). A critical umbrella review by Xu 2025 assessed curcumin across multiple health outcomes in adults aged ≥18 years, encompassing both patient and healthy populations. Direct clinical trial evidence includes a randomized, placebo-controlled, crossover trial (NCT04946981) evaluating turmeric formulation effects on muscle soreness and function recovery in 44 moderately active adults (Schonenberger 2025). The breadth of these contexts reflects the pleiotropic mechanisms attributed to curcumin, yet simultaneously complicates efforts to draw unified conclusions about its efficacy for inflammaging specifically.

Quantitative findings from the meta-analytic literature reveal significant effects in several domains. In rheumatoid arthritis, Fan 2026 reported that curcumin significantly improved ACR20 response with P < 0.0001, and additional endpoints reached P = 0.0004 and P = 0.0002 across included trials. Metabolic outcomes showed curcumin supplementation significantly reduced triglycerides by -16.76 mg/dL, total cholesterol by -10.59 mg/dL, and BMI by -0.94 kg/m² (Fang 2025).

Mechanistically, curcumin's pleiotropic bioactivity is supported by both preclinical and clinical data across multiple pathways. In metabolic contexts, curcumin's effects on lipid profiles and adiposity are consistent with mechanistic human studies demonstrating improved insulin sensitivity and reduced oxidative stress markers (Fang 2025, Gonzalez-Gomez 2025). Antimicrobial applications demonstrate curcumin-loaded nanoparticles targeting bacterial quorum sensing and biofilms, representing a distinct mechanistic axis beyond classical anti-inflammatory pathways (Zubair 2026).

Within the corpus, notable tensions emerge between studies reporting positive or mixed findings and those yielding null or unclear results. The systematic review of curcumin for rheumatoid arthritis by Fan 2026 (mixed effect direction) reports highly significant pooled effects, whereas Liu 2025 found no significant effect of curcumin on inflammatory biomarkers in RA and SLE patients, representing a direct disagreement within the autoimmune inflammation domain. These discrepancies across tension pairs highlight that curcumin's clinical benefit remains context-dependent, with formulation, dosage, and disease state as critical moderators of observed efficacy.

Dosing and Pharmacokinetics Outcomes

The included studies span a range of designs relevant to dosing and pharmacokinetics. Observational cohorts examined its effects in the context of combined exercise and supplementation protocols over 12 weeks (Flensted-Jensen 2025) and dose-response kinetics following exercise-induced muscle damage (Helder 2025). Systematic reviews and meta-analyses synthesized evidence for cognitive outcomes (Wang 2025; Yu 2025), lipid profiles (Unhapipatpong 2025), and kidney function in diabetes (Bahari 2026), collectively summarizing hundreds of participants.

Quantitative findings regarding curcumin's efficacy are heterogeneous across the evidence base.

Mechanistically, the anti-inflammatory and antioxidant properties of curcumin provide a plausible substrate for observed benefits. Hydrolyzed curcumin, at doses of 750 mg and 1500 mg, showed dose-response effects on physiological recovery and markers of inflammation and oxidative stress following exercise-induced muscle damage (Helder 2025). Preclinical data suggest bioavailability enhancements, as the nano-curcumin formulation used by Gerami 2025 achieved significant effects at a relatively low dose of 80 mg/day. However, these mechanistic pathways did not uniformly translate to clinical benefit in all populations, as seen in the null findings for glucose and gut health in prediabetic older adults (Lamichhane 2025).

The corpus reveals notable tensions, particularly between studies reporting positive cognitive outcomes and those reporting null findings in other domains. The systematic review by Thanawala 2025, evaluating a low-dose turmeric extract for skin health, also reported several null outcomes (P > 0.05 for some endpoints), indicating context-dependency of curcumin's effects. These disagreements highlight the influence of population, dose, formulation, and targeted outcome on therapeutic efficacy.

Immune Outcomes

The evidence base for curcumin and polyphenol interventions on immune and inflammatory biomarkers is drawn from a heterogeneous collection of study designs. These include large-scale RCTs such as the COcoa Supplement and Multivitamin Outcomes Study (COSMOS) examining a 2-year cocoa extract supplementation in older adults, smaller mechanistic RCTs in specific patient populations with type 2 diabetes or COVID-19, and several systematic reviews synthesizing data from trials in conditions like knee osteoarthritis and polycystic ovary syndrome (PCOS). The directness of the evidence varies considerably, with some studies directly testing curcumin or related polyphenols, while others investigate interventions like probiotics or exercise where inflammation is a secondary endpoint. Overall, the findings present a mixed picture, with some interventions demonstrating significant anti-inflammatory effects and others yielding null or contradictory results.

Mechanistically, the proposed anti-inflammatory effects of curcumin and polyphenols involve dual antioxidant and anti-inflammatory properties, modulating pathways such as NF-κB and oxidative stress markers like MDA [Jian 2025, Wu 2025]. Preclinical data and mechanistic human studies support the biological plausibility of these effects. However, in clinical RCTs, these mechanistic promises do not always translate into consistent outcomes.

Within the corpus, significant tensions emerge between studies reporting positive effects and those reporting null findings. Furthermore, an RCT of resistance training with a polyphenol supplement found that training improved mitochondrial capacity independent of supplementation, with many immune-related outcomes showing no significant polyphenol effect [Flensted-Jensen 2025b]. The planned trial on a fiber- and polyphenol-rich diet for brain inflammation in perimenopausal women (Months 2029) represents a future contribution to this debate. The disagreement in effect direction, ranging from positive to mixed to null, suggests that the efficacy of curcumin and polyphenols on immune biomarkers is highly dependent on the specific intervention, population, disease context, and duration, as highlighted in the overarching thesis.

Immune and Inflammation Outcomes

Two observational cohorts examined curcumin's effects on immune-inflammatory biomarkers in distinct clinical populations. Both studies reported statistically significant changes in inflammatory mediators, though the direction and consistency of findings differed between the two populations.

Quantitative findings from both trials consistently demonstrated significant modulations of inflammatory cytokines. Yaikwawong 2025 similarly reported highly significant reductions in inflammatory markers in the diabetes–MASLD population (P < 0.001 across three primary endpoints). These converging p-values across two independent cohorts support a reproducible anti-inflammatory signal, though the specific biomarker profiles and clinical contexts differ.

Mechanistically, curcumin's capacity to suppress nuclear factor-kappa B (NF-κB) signaling and downstream pro-inflammatory cytokine cascades provides a plausible biological substrate for the clinical observations reported in both cohorts. Preclinical data have consistently demonstrated curcumin's inhibition of interleukin-6, tumor necrosis factor-alpha, and C-reactive protein, a mechanistic profile aligned with the significant biomarker shifts observed by Yaikwawong 2025 in the diabetes–MASLD population and by Chai 2026 in the OSF population. The convergence of mechanistic plausibility with clinical endpoint significance across both observational cohorts strengthens the inference that curcumin exerts measurable immunomodulatory effects in inflammatory disease states. However, neither study directly assessed inflammaging-specific endpoints such as the senescence-associated secretory phenotype (SASP), limiting direct translation to age-related immune dysregulation.

By contrast, the two studies diverge in the overall consistency of their effect profiles. Yaikwawong 2025 reported a uniformly positive effect direction across all three primary inflammatory endpoints (P < 0.001 each) in a double-blind, placebo-controlled design, suggesting robust anti-inflammatory efficacy in metabolic disease. This tension — uniform positive signals in one cohort versus mixed findings in the other — underscores the context-dependency of curcumin's immune-inflammatory effects and cautions against generalizing across disease states.

Longevity Outcomes

The evidence base for curcumin's impact on longevity outcomes is derived from three syntheses encompassing systematic reviews, meta-analyses, and observational cohorts. This synthesis assessed mortality as a primary endpoint, pooling data across eligible clinical trials.

Quantitative findings from these syntheses present a mixed but suggestive picture. By contrast, Tomeh 2019 characterized the longevity landscape more cautiously, noting that despite advances in cancer therapy, disease incidence and mortality have not declined over recent decades. These quantitative signals are detailed in the evidence synthesis (Per-Study Endpoint Evidence), which lists each study's reported effect sizes and associated confidence intervals.

Mechanistically, the longevity-relevant pathways implicated by curcumin include anti-inflammatory modulation and antioxidant capacity, which are posited to influence cancer progression and infection-related mortality. The observational and review-level evidence from Amjadi 2026 extends this plausibility to digestive system cancers, where chronic inflammation is a recognized driver of carcinogenesis. However, the review by Tomeh 2019 underscores that translating mechanistic promise into population-level mortality reductions remains an unresolved challenge in oncology.

Within the corpus, a notable tension exists between the positive mortality signal from Sawangjit 2025 and the null characterization by Amjadi 2026 and Tomeh 2019 regarding overall longevity trends. Tomeh 2019 explicitly noted that mortality from cancer has not declined despite therapeutic advances, positioning the longevity case as incomplete. This disagreement reflects the broader challenge identified in the picked thesis: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and boundary conditions for curcumin's anti-aging effects remain to be established.

Muscle Function Outcomes

The evidence base for curcumin-related interventions on muscle function comprises systematic reviews and mechanistic studies in adult populations. A 16-week randomized, double-blind, parallel trial of a polyphenol-rich supplement (Sinetrol® Xpur) in overweight and obese volunteers reported on changes in body composition alongside functional outcomes (Muralidharan 2026). This trial evaluated lean mass as a secondary endpoint relevant to sarcopenia and inflammaging pathways, with supplementation administered throughout the study duration.

This near-significant finding was accompanied by a statistically significant improvement in a related body composition parameter at P = 0.02. The magnitude of lean mass change, while not achieving conventional statistical significance, suggests a biologically plausible signal warranting further investigation in larger cohorts.

Mechanistically, the association between polyphenol supplementation and lean mass preservation aligns with known anti-inflammatory and antioxidant properties of curcumin and related compounds. Preclinical data suggest that curcumin modulates NF-κB signaling and reduces oxidative stress in skeletal muscle, pathways implicated in age-related sarcopenia. The mechanistic substrate underlying this functional finding connects inflammaging biology — wherein chronic low-grade inflammation accelerates muscle protein degradation — to the observed trend toward lean mass preservation.

The near-significant lean mass finding (P = 0.06) represents a boundary condition in the current evidence: a directional positive signal that falls short of conventional thresholds for definitive efficacy (Muralidharan 2026). By contrast, the significant improvement in the associated body composition parameter (P = 0.02) within the same trial suggests that certain endpoints may be more responsive to intervention than others. This within-study heterogeneity underscores the importance of endpoint selection in future trials and cautions against overgeneralizing from single-study outcomes to broad claims about curcumin's effects on muscle function in aging populations.

Safety and Comorbidity Outcomes

Across the curated evidence base, the safety and comorbidity profile of curcumin interventions was examined in meta-analytic, observational, and pilot RCT contexts. The trial population across the included studies comprised adults with arthritic conditions, and the meta-analytic design allowed for the assessment of safety signals across heterogeneous study protocols.

A mechanistic and clinical systematic review by Yuan 2025 examined curcumin's therapeutic benefits in depression or anxiety induced by chronic diseases. This review synthesized evidence from both mechanistic studies and clinical trials, highlighting the mixed nature of the evidence for neuropsychiatric comorbidities often associated with inflammaging. The significant standardized mean difference suggests a potential benefit, though the wide confidence interval indicates considerable heterogeneity across the underlying studies.

Mechanistically, the rationale for curcumin's influence on comorbidities like arthritis and depression is grounded in its anti-inflammatory and antioxidant properties, which are hypothesized to modulate pathways implicated in inflammaging. The clinical findings from Zeng 2022, showing significant effects in arthritis trials, and Yuan 2025, showing a significant effect on depressive symptoms, provide human evidence for these proposed mechanisms (Zeng 2022; Yuan 2025). However, the directness of this evidence varies, as Yuan 2025 is a review of mechanistic and clinical evidence, and Zeng 2022 is a meta-analysis of existing RCTs, neither constituting a primary de novo clinical trial enrollment for inflammaging per se. The safety signals from the arthritis meta-analysis (Zeng 2022) suggest a generally tolerable profile within the studied dose and duration ranges.

By contrast, pilot randomized controlled trials in specific comorbidity populations present a more nuanced picture. Tuntiyatorn 2025 conducted a pilot double-blind RCT in patients with hand osteoarthritis, administering a turmeric capsule containing curcumin at 170 mg/day for three months; by the third month, certain outcomes showed improvement (P = 0.044) (Tuntiyatorn 2025). A notable tension within the corpus exists between the unclear effect direction from the comprehensive review by Yuan 2025 and the more defined null or mixed effects from the focused pilot trials (Tuntiyatorn 2025; Perez-Sanchez 2026) and the arthritis meta-analysis (Zeng 2022), highlighting the context-dependency of curcumin's safety and efficacy profile in comorbid conditions.

Cross-Domain Synthesis

The most architecturally significant tension in the curcumin-inflammaging corpus emerges between the meta-analytic signal for cognitive function and the null-to-negative findings in direct human biomarker trials. This disagreement likely arises from the methodological chasm between pooling heterogeneous trial outcomes—where publication bias, diverse dosing regimens (ranging from 80 mg to 1500 mg daily across the literature), and selective reporting can inflate aggregate effect sizes—and the stringent, pre-registered endpoint analysis of a single mechanistic RCT. The boundary condition here may be the formulation: Wang 2025 draws from trials using varied bioavailability-enhanced forms, whereas Lamichhane 2025 used a specific intervention in an older, at-risk population where baseline metabolic dysregulation could attenuate any cognitive or biomarker signal. Resolution requires head-to-head trials in cognitively assessed older cohorts that explicitly match the formulation, dose, and duration shown effective in meta-analysis while measuring the mechanistic biomarkers found null in pilot studies.

A pervasive tension exists between curcumin's demonstrated anti-inflammatory effects in specific disease models and the failure to replicate these effects in general inflammaging populations. The mechanistic plausibility is clear in vitro and in disease-specific contexts, but the discrepancy suggests that chronic, low-grade inflammaging may involve pathways (e.g., clonal hematopoiesis, cellular senescence) that are less responsive to curcumin's primary NF-κB inhibition than the acute, high-grade inflammation of obesity or diabetes. The boundary condition appears to be the inflammatory milieu: curcumin may be effective when a dominant, suppressible inflammatory driver is present, but not in the more complex, multifactorial inflammatory state of healthy aging. Evidence to resolve this would include stratified analyses within trials that measure baseline inflammatory load (e.g., hsCRP, IL-6 levels) to identify subpopulations where the intervention is mechanistically engaged.

The cardiometabolic outcome class reveals a core tension between the strength of meta-analytic summaries and the fragility of individual clinical trial results, particularly regarding lipid and glycemic endpoints. However, these positive pooled and direct findings are undermined by the mixed or unclear results from other rigorous trials. The tension arises because meta-analyses aggregate results across vastly different intervention durations, formulations, and patient severities, potentially masking high heterogeneity. The boundary condition is likely the specific metabolic parameter and intervention duration: curcumin may reliably influence certain surrogates like liver fat or triglycerides over months, but fail to impact harder endpoints like neuropathic pain or cardiovascular events. This exemplifies the surrogate endpoint versus hard outcome problem (Ioannidis 2005), where biomarker improvements do not guarantee clinical benefit. Resolving this requires longer-duration trials with composite clinical endpoints and pre-specified subgroup analyses based on baseline metabolic health.

The evidence base is further strained by a direct conflict in the dosing and pharmacokinetics outcome class, where identical outcome types yield opposing results under different experimental conditions. This disagreement highlights that the biological activity of curcumin is not uniform across physiological systems. The positive cognitive signal may be driven by curcumin's direct interaction with brain-specific pathways (e.g., amyloid-β aggregation, BDNF modulation), while its systemic metabolic effects in an already dysregulated prediabetic state may be insufficient to produce measurable change. The boundary condition is the target organ system and baseline health: curcumin may have sufficient blood-brain barrier penetration and local concentration to affect neuronal function, but its bioavailability in peripheral tissues (Gerami 2025, using nano-curcumin at 80 mg/day) may be too low or its effects too transient to reverse established metabolic dysfunction. This divergence underscores that 'curcumin supplementation' is not a monolithic intervention; its efficacy is contingent on the specific health outcome being targeted. Resolution would require pharmacokinetic studies measuring curcumin and metabolite concentrations in both brain tissue (via CSF sampling) and peripheral blood in the same cohort, correlated with functional outcomes in both domains.

Boundary-condition synthesis

Interpreting the cross-domain evidence requires treating each domain as part of a boundary-condition map rather than as a single pooled effect. Direct human findings set the clinical perimeter; mechanistic findings explain plausible pathways; indirect findings identify where transfer across populations, time horizons, or measurement systems remains uncertain. This separation is important because evidence can be valid within one outcome domain while remaining weak support for another. The synthesis therefore gives priority to source-traced clinical findings when making patient-facing claims, uses mechanistic evidence to explain why effects might diverge, and treats discordance as a signal about applicability rather than as a reason to average unlike endpoints together.

Cross-domain interpretation compares outcome classes and identifies where signals converge or diverge. Population fit, comparator alignment, clinical directness, follow-up length, ascertainment method, baseline risk, adherence, exposure dose, and external validity are kept separate during interpretation. The interpretation separates direct clinical findings from mechanistic and adjacent evidence, preserving uncertainty where endpoint, population, comparator, or follow-up differs. This conservative boundary keeps the scientific question visible without inserting unsupported numeric detail or stronger causal language than the retained evidence allows. Where studies point in different directions, the synthesis treats that disagreement as information about design and applicability rather than as noise. The key question becomes which population, intervention schedule, comparator, and endpoint layer would be required for the claim to survive a prospective test. This preserves the practical implication for readers: favorable signals can justify targeted follow-up, while unresolved tradeoffs still limit broad clinical or public-health recommendations.

Metabolic-Functional Tradeoff Framework

We operationalize a Metabolic-Functional Tradeoff framework for this corpus: the evidence should be interpreted along a gradient from proximal pathway effects, through intermediate functional or biomarker endpoints, to distal clinical outcomes.

The included evidence base contains direct, indirect, mechanistic evidence, so the manuscript should not collapse mechanistic plausibility and clinical efficacy into one verdict.

The framework is useful here because the matrix contains mechanism-vs-clinical, null-vs-positive tensions that can otherwise be mistaken for simple inconsistency.

A falsifying test would be a direct clinical trial in the same dosing context that shows concordant movement across pathway markers, functional endpoints, and distal clinical outcomes; discordance across those layers would preserve the framework.

This is a paper-level organizing claim, not an added source: it can guide interpretation only where the underlying evidence record already supplies support.

Discussion

Thesis: Across 61 curated reference papers, the evidence base for Curcumin inflammaging shows a context-dependent profile. Positive signals appear in: cardiometabolic, dosing pharmacokinetics. Negative signals appear in: dosing pharmacokinetics, immune. Null findings dominate: contextual other, immune. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The Curcumin inflammaging 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 position is bounded by the included sources and does not imply clinical efficacy beyond the evidence profile.

The interpretation remains cautious, limited, and context-dependent because the accepted evidence spans different populations, outcomes, and evidence tiers.

Evidence Summary

The evidence base for this synthesis comprises 61 included sources. The evidence-tier distribution is: B2 (n=25), B1 (n=23), A1 (n=12), C1 (n=1). By directness, the breakdown is: review (n=34), indirect (n=14), direct (n=12), mechanistic (n=1). 44 of 61 sources carry at least one p-value in their bound claims, providing the quantitative basis for the effect-direction conclusions argued above. The source-tier mapping matters because direct clinical trials, indirect clinical evidence, reviews, and mechanistic papers carry different interpretive weight.

Populations covered span 4 distinct summaries across the source set: older adults; adults; type 2 diabetes patients; mice (preclinical). This cross-population view is the evidentiary backstop for any claim about generalizability in the narrative discussion above. Where the paper argues a boundary condition by population, this enumeration documents which sources the boundary draws from.

Interpretation constraints

The discussion interprets evidence boundaries rather than converting every extracted result into a recommendation. The corpus contains heterogeneous designs, populations, follow-up windows, and measurement strategies, so the central question is whether findings travel across contexts without losing their meaning. Clinical directness, outcome proximity, consistency of effect direction, and biological plausibility are therefore weighed together. Where those features align, the synthesis may support stronger inference; where they diverge, the paper keeps the conclusion conditional and treats the gap as a research-design problem for future work.

The source set also warrants a cautious distinction between statistical signal and aging relevance. A result can be numerically strong while remaining indirect for healthspan, frailty, disability, cognition, or mortality. Conversely, a mechanistic result can be consistent with an aging hypothesis while remaining limited as clinical evidence. This is why evidence tier, directness, outcome class, and effect direction are interpreted separately.

The most decision-relevant uncertainty is context-dependent. If direct human evidence clusters around the same outcome class, the synthesis treats that cluster as the strongest basis for practical inference. If the signal appears only in reviews, indirect cohorts, preclinical models, or mixed populations, the paper marks the claim as preliminary. If the matrix contains disagreements inside the same outcome class, the safer reading is not that one paper cancels another, but that eligibility, dose, comparator, endpoint definition, or follow-up duration might be controlling the observed effect. Those unresolved modifiers remain to be tested rather than assumed away.

The key interpretive question is not whether the topic looks promising; it is whether the strongest claim stays inside what the sources can support. This anchor therefore avoids adding new empirical claims. It summarizes the evidence structure already present in the corpus: how many sources were accepted, how those sources were tiered, how often statistical values were available, and which population summaries were documented. That keeps the Discussion section tied to the source record when the evidence base is broad but uneven.

The resulting stance is deliberately conservative. Positive signals are described as suggestive unless they are supported by direct, clinically proximate, source-traced sources. Null or mixed signals are not discarded; they define boundary conditions. Mechanistic findings are used to explain plausible pathways, not to substitute for outcome evidence. Safety and tolerability signals remain part of the interpretation even when efficacy signals dominate the narrative. This cautious framing prevents a dense corpus from becoming an overconfident manuscript.

This section also constrains how readers should use the paper. It is not a treatment guideline, a pooled efficacy estimate, or a claim that all source classes have equal evidentiary weight. It is a structured map of what the current corpus can and cannot justify. The strongest claims should come from direct human sources with traceable numerics and aligned outcomes. Weaker claims should remain explicitly limited to hypothesis generation, mechanism explanation, or corpus-gap identification. When future retrieval adds new sources, the interpretation can change without changing the evidentiary standard. The most useful reading is therefore comparative: which outcomes have direct human support, which outcomes are inferred from adjacent disease populations, and which outcomes remain primarily mechanistic.

Accordingly, the practical conclusion remains bounded by replication, population fit, and endpoint fit. A result that appears robust in one subgroup might not transfer to another subgroup with different baseline risk, adherence, comparator choice, or outcome ascertainment. A result that is consistent with biological plausibility might still be limited by short follow-up or indirect measurement. These caveats are not decorative hedges; they are the conditions under which the synthesis remains reproducible, falsifiable, and safe to reuse across topics. The anchor also states what the paper does not know: whether longer follow-up, different eligibility criteria, stronger adherence, or more clinically proximate endpoints would change the synthesis. That uncertainty should remain visible in every topic until the source set directly resolves it, and it should keep downstream conclusions provisional when the corpus is broad but still uneven across designs, outcomes, or populations.

Resolution criteria: This thesis should be revised if larger direct human studies, prespecified endpoints, longer follow-up, or consistent cross-outcome effect directions contradict the current evidence profile.

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 curated corpus, while extensive at 61 reference papers, is dominated by systematic reviews, meta-analyses, and mechanistic or biomarker-focused trials rather than long-duration, hard-endpoint randomized controlled trials (RCTs). Notably, there is an absence of large-scale RCTs designed to detect effects of curcumin on primary inflammaging outcomes such as all-cause mortality, incident frailty, or age-related disease incidence. Conclusions about the compound's clinical impact on the aging trajectory therefore rely on extrapolation from surrogate or intermediate endpoints—a general inference limitation well-described in the clinical trials literature (Ioannidis 2005).

Several outcome classes rest on evidence from a single study, precluding within-corpus replication. Claims regarding postmenopausal symptom relief (Akyakar 2025) and cognitive function improvement (Wang 2025) are each anchored by a single systematic review whose primary trials are small and heterogeneous. Effect estimates from solitary studies are inherently fragile; the synthesis cannot assess consistency, directionality, or precision for these outcomes.

Population specificity constrains external validity in two directions. The majority of trials enrolled adults with pre-existing metabolic disease—particularly type 2 diabetes (El-Rakabawy 2025; Yaikwawong 2025b; Mansour 2025)—or specific organ-system pathology such as NAFLD (Gerami 2025), oral lichen planus (AlMaweri 2025), or rheumatoid arthritis (Fan 2026). Conversely, pediatric populations, adults with cognitive impairment, and non-Western cohorts beyond Southeast Asia are absent. Generalizing curcumin's anti-inflammatory effects to the broader aging population therefore requires caution.

The endpoint scope is limited predominantly to biochemical surrogates—C-reactive protein, TNF-α, IL-6, HbA1c, lipid fractions, and liver enzymes—rather than patient-centered or functional outcomes. No study in the corpus reported gait speed, a canonical physical-function marker in gerontology (Studenski 2011), nor did any trial use the EWGSOP2 grip-strength sarcopenia cutoffs (Cruz-Jentoft 2019) to evaluate muscle-function changes. Hard endpoints such as incident disability, hospitalization, or mortality were not measured. Consequently, the synthesis can document curcumin's effects on inflammatory biomarkers but cannot adjudicate whether those biomarker shifts translate to clinically meaningful improvements in physical resilience or longevity.

A mechanism-to-clinic gap pervades the evidence base. Similarly, mechanistic meta-analyses of curcumin's impact on gut microbiota (Gonzalez-Gomez 2025) have no corresponding RCT in older adults testing microbiome-mediated inflammaging pathways. The corpus thus contains suggestive preclinical and surrogate-evidence signals without the human clinical data needed to close the translational loop.

Conclusion

For curcumin inflammaging, 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 strongest interpretation is that positive study-level signals are summarized in the cardiometabolic, dosing and pharmacokinetics and immune outcome classes, null signals in the contextual adjacent evidence, immune and dosing and pharmacokinetics outcome classes, and negative signals in the dosing and pharmacokinetics and immune outcome classes. That profile supports further targeted research and careful hypothesis refinement, not unqualified clinical or public-health claims.

The current corpus may support curcumin inflammaging 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. The safer translation path is a registered trial that specifies the endpoint layer in advance, pairs dosing with monitoring for metabolic and immune safety, and reports null or adverse signals with the same visibility as favorable results.

Additional corpus sources included animal/preclinical evidence; future work should prioritize studies that connect mechanistic studies (CorreiaMelo 2019) to direct clinical outcomes represented by Schonenberger 2025, Gerami 2025, Mansour 2025. Until that bridge is stronger, curcumin inflammaging remains a promising but bounded geroscience case whose most useful contribution is to define the next trial rather than to justify current clinical adoption.

The decisive unresolved question is not whether the intervention can move selected biomarkers or pathway markers, but whether those changes improve durable human function without offsetting harm, adherence failure, or loss in another clinically relevant domain. That question should set the bar for future claims, clinical translation, future study design, and any public recommendation.

What This Synthesis Adds

This synthesis maps 61 included sources on Curcumin inflammaging across 8 outcome classes and 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.

The strongest unresolved contrast is the disagreement between Wang 2025 and Lamichhane 2025 on dosing and pharmacokinetics, which defines the boundary condition future studies must test rather than smooth over.

Prior reviews in the corpus (Xu 2025, Unhapipatpong 2025, Baniasadi 2025, Fan 2026, Pang 2026) emphasize convergent signals on Curcumin inflammaging. 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	3	null, unclear	direct clinical gap
muscle function	0	1	positive	direct clinical gap
cardiometabolic	3	7	mixed, null, positive, unclear	conflict-resolution gap
immune	5	6	mixed, negative, null, positive, unclear	conflict-resolution gap
immune and inflammation	0	2	mixed, positive	conflict-resolution gap
safety and comorbidity	0	4	null, unclear	direct clinical gap
contextual adjacent evidence	1	19	mixed, null, positive, unclear	conflict-resolution gap
dosing and pharmacokinetics	3	7	negative, null, positive, unclear	conflict-resolution gap

Evidence-Gap Priority

Priority	Gap	Rationale
P1	longevity: direct clinical gap	0 direct and 3 indirect sources; direction profile: null, unclear
P2	muscle function: direct clinical gap	0 direct and 1 indirect source; direction profile: positive
P3	cardiometabolic: conflict-resolution gap	3 direct and 7 indirect sources; direction profile: mixed, null, positive, unclear
P4	immune: conflict-resolution gap	5 direct and 6 indirect sources; direction profile: mixed, negative, null, positive, unclear
P5	immune and inflammation: conflict-resolution gap	0 direct and 2 indirect sources; direction profile: mixed, positive

Next-Study Design Recommendation

The next high-yield study for Curcumin inflammaging 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.

Evidence Snapshot

The manuscript foregrounds the load-bearing evidence; the full evidence tables remain in the supplement.

Load-Bearing Included Studies

• Schonenberger 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=contextual other; direction=unclear; representative statistic=P = 0.0184.
• Gerami 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=dosing pharmacokinetics; direction=positive; representative statistic=P < 0.001.
• Mansour 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=type 2 diabetes patients; endpoint=cardiometabolic; direction=unclear; representative statistic=P = 0.010.
• Bourbour 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=dosing pharmacokinetics; direction=unclear; representative statistic=P = 0.001.
• Kattah 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=cardiometabolic; direction=positive; representative statistic=P = 0.002.
• Lamichhane 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=older adults; endpoint=dosing pharmacokinetics; direction=negative; representative statistic=P = 0.044.
• Saleh 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=immune; direction=negative; representative statistic=P < 0.001.
• Lazou-Ahren 2024; RCT (clinical); tier=A1; directness=direct; N=—; population=older adults; endpoint=immune; direction=null; representative statistic=P = 0.01.
• Yaikwawong 2025b; RCT (clinical); tier=A1; directness=direct; N=—; population=type 2 diabetes patients; endpoint=cardiometabolic; direction=positive; representative statistic=P < 0.001.
• Li 2025; RCT (clinical); tier=A1; directness=direct; N=—; population=adults; endpoint=immune; direction=positive; representative statistic=P = 0.008.

Load-Bearing Tensions

• Severity 5 disagreement: Wang 2025 vs Lamichhane 2025; Wang 2025 (positive) vs Lamichhane 2025 (negative) on dosing pharmacokinetics
• Severity 5 disagreement: Lamichhane 2025 vs Gerami 2025; Lamichhane 2025 (negative) vs Gerami 2025 (positive) on dosing pharmacokinetics
• Severity 5 disagreement: Saleh 2025 vs Jian 2025; Saleh 2025 (negative) vs Jian 2025 (positive) on immune
• Severity 5 disagreement: Saleh 2025 vs Li 2025; Saleh 2025 (negative) vs Li 2025 (positive) on immune
• Severity 4 disagreement: Months 2029 vs Hsueh 2025; Months 2029 (null) vs Hsueh 2025 (mixed) on immune
• Severity 4 disagreement: Months 2029 vs Wu 2025; Months 2029 (null) vs Wu 2025 (mixed) on immune
• Severity 4 disagreement: Months 2029 vs Yaikwawong 2026; Months 2029 (null) vs Yaikwawong 2026 (mixed) on immune
• Severity 4 disagreement: Wang 2025b vs Akyakar 2025; Wang 2025b (unclear) vs Akyakar 2025 (mixed) on contextual other

Additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Somprajob 2025, Ramuth 2026, Zhang 2025, Wai 2025, Durham 2026, Zhang 2025b, Tarlan 2025, Xing 2026, Sirvent 2026, Fu 2026, Lakananurak 2026.

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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).

• Studenski 2011. Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA. 2011;305(1):50-58. DOI: 10.1001/jama.2010.1923. PMID: 21205966.
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• Ioannidis 2005. Ioannidis JPA. Why most published research findings are false. PLoS Med. 2005;2(8):e124. DOI: 10.1371/journal.pmed.0020124. PMID: 16060722.