Using Biological Signs of Long-Term Inflammation to Guide Fair and Personalized Care

Low-cost single markers such as CRP, serum amyloid A (SAA), and select cytokines are imperfect but useful for stratification in at-risk individuals or early disease. Multiplex panels that include inflammatory tone (CRP, SAA), cytokine modules (IL-6, TNF, IL-1β, IL-17/23), major immune cell subsets (neutrophil/lymphocyte ratio, monocyte subsets, Treg/Th17), metabolic stress markers (ketone bodies, acylcarnitines), and circulating or tissue injury markers (troponins, fibrosis biomarkers) can be assembled for robust risk stratification [1,2,4]. Integration of multiple 'omics' (transcriptome, proteome, metabolome, microbiome) and machine-learning classifiers can enable derivation of actionable endotypes that can predict risk and therapeutic response [4,6,29,40].

This narrative, mechanism-informed review synthesizes available evidence to create an actionable endotype-to-care framework for chronic inflammation to inform precision prevention and treatment, spanning from mechanisms to actionable endotypes, clinical biomarkers, therapeutic modules, and monitorable outcomes. The framework is designed for use in the general adult population at-risk for chronic inflammation, as well as adults with established chronic inflammatory diseases, including cardiometabolic, autoimmune, autoinflammatory, barrier–microbiome, and inflammaging-related conditions. In addition, the framework is meant to be transdiagnostic across all levels of prevention: primary prevention (population biomarker screening and lifestyle/exposome strategies), secondary prevention (individuals with early inflammatory or metabolic abnormalities), and tertiary prevention (patients with established chronic inflammatory disease requiring targeted therapeutics and longitudinal treat-to-target monitoring) No meta-analysis was conducted.

The review protocol (sources, search terms, inclusion/exclusion criteria, data extraction and evidence grading) was established a priori, but was not registered, due to the non-systematic nature of the review. Methodological quality criteria followed those of the Society for Academic Nursing's Guidelines for Systematic and Non-Systematic Reviews (SANRA) for narrative reviews. The PRISMA statement was not applicable.

This review is narrative and non-systematic in design; the literature search was broad, flexible, and iterative, not protocolized. The search strings were wide-ranging, encompassing mechanistic, clinical, metabolic, and endotype-related concepts, and were refined over time until the point of thematic saturation was reached. Iterative cycles of literature searching were conducted in PubMed/MEDLINE, Embase, and Web of Science, and supplemental searching was performed in Google Scholar primarily for forward citation chasing and was limited to the first 150–200 results of each search query to minimize noise from relevance-ranking algorithms. Reference lists from a set of sentinel mechanistic papers, high-quality systematic reviews, and clinical guidelines were hand-searched for additional articles.

Sentinel clinical guidelines (EULAR/ACR, AGA/ACG, ACC/AHA, GINA/GOLD), clinical trial registries, and the reference lists of included articles were also searched for additional evidence. The last search date of the electronic databases was 12 November 2025.

Mechanistic, translational, and clinical studies of all types; randomized and quasi-experimental trials; high-quality observational studies; systematic reviews/meta-analyses; expert and guideline statements; and Phase I–III reports were eligible for inclusion, with human studies prioritized and animal/mechanistic studies used to address evidence gaps/interpret relevance to human biology. Untriangulated preprints, case reports, and non-English articles not synthesized in the body of the manuscript were excluded.

Key variables abstracted: endotype class, associated biomarker(s)/threshold(s), module-specific interventions, targets/outcome metrics for monitoring, safety and equity considerations. Biomarker selection was driven by 3 criteria: (1) having been endorsed in key consensus guidelines or regulatory frameworks, (2) having robust mechanistic or clinical effect-size evidence in the chronic inflammatory biology of interest, and (3) being technically feasible in diverse resource settings. Thresholds were harmonized across centers using guideline-based cut-points where available. In the absence of consensus cut-points, and where high platform/assay heterogeneity was expected (e.g., in the case of cytokines and interferon-stimulated gene signatures), we interpret these biomarkers as "direction-of-change" classifiers rather than absolute diagnostic values. Repeat testing and trend-based monitoring will be a focus to minimize misclassification. Evidence supporting endotype-based interventions was triangulated/graded in 3 tiers:

A = Guideline-supported/approved;

B = Strong clinical/mechanistic but limited regulatory approval;

C = Emerging/experimental.

Review algorithmically translates screening steps (e.g., hs-CRP, NLR, fibrinogen) into endotype identification, module-targeted therapy selection, and treat-to-target outcome benchmarks (e.g., hs-CRP lowered ≥40% at 8–12 weeks, disease activity measures, urate-to-target).

To avoid overinterpreting the available evidence, biomarkers and thresholds were cross-referenced to levels of evidence (A–C). Level A biomarkers are those supported by guidelines or that have regulatory approval (e.g., hs-CRP, IL-6, TNF), level B are those with strong clinical or mechanistic evidence but with limited or no approvals, and level C are those that are experimental or emerging (e.g., multi-omic classifiers, senescence signatures). Thresholds lacking harmonized clinical validation were to be interpreted as directional trends and not absolute diagnostic cut-points.

Clinical pathways and algorithmic steps were adapted for resource-rich and -limited environments, from minimum/essential markers and lifestyle-first approaches at the population level to expanded biomarker panels and omics profiling in more comprehensive clinical/research settings. Elements of decentralized, task-shifted care delivery (e.g., dried blood spot collection, digital adherence reminders/monitoring, remote treatment targets/outcome checks) were also integrated for purposes of equity and feasibility.

The endotype-to-care framework was derived by integrating evidence maps across mechanistic axes (cytokine profiles, metabolic pathways, ISG signatures), biomarker feasibility across resource settings, and principles of treat-to-target design borrowed from rheumatology, cardiometabolic medicine, and implementation science. The final framework reflects the convergence of three factors: (1) mechanistic coherence, (2) feasibility of measurement and intervention, and (3) alignment with modifiable pathways of disease progression.

The study selection was based on the highest level of evidence from available mechanistic, translational, and clinical research. As an exercise in methodological transparency, biomarker heterogeneity was accounted for with explicit language: guideline-derived cut-points were used if validated; otherwise, relative change and trends over time were emphasized over single absolute values to reduce the impact of inter-assay variability. When different cytokine or multi-omic platforms were used, results were considered based on the directionality and reproducibility of findings rather than numeric equivalency. Conflicts between studies were noted where relevant, and evidence gaps, uncertainties, and assay variability were acknowledged. All reporting was per best-practice guidance for narrative reviews.

The operational thresholds and multi-omic approaches discussed in this review are meant to be conceptual frameworks that should be further tested in future investigations. Their integration into this review was included as an indication of an evolving area of study and is not a current standard of care.

We offer a pragmatic, iterative framework to translate mechanistic understanding into actionable concepts that inform clinical and population practice aligned with the primary, secondary, and tertiary prevention applications defined in Section 2.1; however, several components, particularly multi-omic classifiers and certain cytokine-based endotyping panels, should be viewed as emerging proposals rather than validated clinical standards (Figure 1).

Step 1: Screening Using Inexpensive Biomarkers. Population-based screening and risk stratification can employ validated inexpensive markers such as high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA), fibrinogen, or complete blood count–derived indices (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR]), among others. High levels of CRP (>3 mg/L) and NLR (>3) have been consistently associated with cardiometabolic, oncologic, and frailty outcomes [1,46,47,48]. If out of range proceed to step 2.

Step 2: Mechanistic Endotyping (Table 1). People with elevated inflammatory tone may be further defined by targeted cytokine panels and, when possible, actionable multi-omic classifiers integrated across metabolic, epigenomic, and microbiome data. Because evidence strength varies across these tools, cytokine panels and multi-omic classifiers should be interpreted according to their evidence tier (A–C), with several elements still considered exploratory rather than validated clinical standards.

Panel selection should be guided by the predominant clinical and metabolic context. Individuals with metabolic features such as central adiposity or insulin resistance may be evaluated using IL-6/TNF panel testing, whereas those with autoimmune features, such as photosensitivity, anti-dsDNA positivity, or low complement, may be tested using an ISG/Type I interferon panel. Neutrophilic skin or joint disease favors assessment with IL-17/23 panels, while crystal arthropathies or recurrent inflammatory flares warrant IL-1β, urate, and NLRP3 inflammasome profiling. In cases characterized by gastrointestinal symptoms or evidence of metabolic endotoxemia, evaluation of intestinal permeability markers and stool microbiome profiles is recommended. Where assay variability or platform heterogeneity is substantial (e.g., cytokine assays), biomarkers should be used primarily as direction-of-change indicators rather than strict diagnostic thresholds.

These targeted assays help refine age-associated and metabolic inflammatory endotypes [2,49], and multi-omics integration has shown particular utility for distinguishing disease subtypes [4,12,18,50]. However, multi-omic classifiers remain an emerging adjunct and should be applied cautiously until additional validation studies are available.

Step 3: Stepwise Treatment Approach. Treatment should first emphasize lifestyle and environmental interventions that reduce the inflammatory baseline and lower the set point, including nutrition, physical activity, stress reduction, sleep, and avoidance of pollution and other inflammatory stimuli. Nutritional and metabolic factors are key modulators of cardiometabolic and immune risk and remain major drivers of inflammation [51,52]. Neuroimmune signaling and vagal anti-inflammatory pathways also contribute to inflammatory tone and are targets for behavioral interventions [32].

Step 4: Precision, Evidence-Based, Mechanistically Targeted Therapeutics. In persons whose endotyping or clinical phenotyping points to specific inflammatory pathways, targeted therapeutics can be applied to that inflammatory "module." These include, for example, IL-6 receptor or TNF-blocking agents, JAK inhibitors, inflammasome antagonists, and senolytics, among others, each with mechanistic and clinical rationales in chronic inflammatory disease [4,12,18,50]. Before initiating biologics or JAK inhibitors, standard infection, malignancy, and cardiovascular risk screening should be performed in accordance with clinical guidelines, and antimicrobial and steroid stewardship must be documented as part of safety oversight.

Step 5: Iterative Monitoring and Treatment Optimization (8–12 weeks). Follow-up and treat-to-target can be accomplished with repeat screening using the inexpensive markers above (hs-CRP, NLR, fibrinogen), among others, and supported by cytokine or metabolite panels when indicated in complex or mixed phenotypes. Emerging digital health measures and real-time biometric analytics can also be leveraged for dynamic therapy titration [53].

Monitoring rule: Review at 8–12 weeks; if the target is not achieved and adherence is adequate, escalate within the same module before switching modules; de-escalate after two consecutive target achievements.

This five-tiered strategy maps onto three foundational principles of precision, equity, and stewardship (Figure 1). It aims to ensure that at a minimum, inflammatory burden is assessed at the population level in low-resource settings while also providing a framework to try to provide evidence-based, mechanism-based treatments for high-risk individuals.

Implementation of the endotype-to-care pathway can be adapted to diverse resource environments through a tiered approach that preserves clinical validity while maximizing feasibility.

Tier 1 (Essential Tier): Population and primary-care settings may rely on low-cost markers such as hs-CRP, NLR, and fibrinogen to stratify inflammatory risk, paired with lifestyle optimization and metformin where appropriate. Follow-up should use a 12-week treat-to-target loop based on repeat hs-CRP or NLR.

Tier 2 (Expanded Tier): Centers with moderate laboratory capacity can add a single cytokine panel (for example, IL-6/TNF or IL-1β) to refine mechanistic attribution and, where available, incorporate metabolic co-targets such as fasting insulin or HOMA-IR. GLP-1 receptor agonists may be considered as metabolic–anti-inflammatory adjuncts.

Tier 3 (Comprehensive Tier): Specialized or research facilities can deploy multiplex cytokine panels and selected multi-omic assays (transcriptomic, metabolomic, or microbiome profiling) to enable individualized endotyping and therapeutic precision, including access to biologics, targeted small-molecule inhibitors, or clinical trials.

Task-Shifting and Remote Monitoring

To support equitable delivery, elements of screening and follow-up can be decentralized through task-shifting and digital health integration. Community health workers can facilitate collection of dried blood spots for hs-CRP or related biomarkers, enabling remote or population-level surveillance without venipuncture infrastructure. SMS-based adherence prompts, and symptom check-ins can reinforce behavioral and pharmacologic adherence between visits. Group consultations every three months may optimize clinician efficiency, peer support, and monitoring continuity in resource-constrained settings. These decentralized strategies lower access barriers while maintaining fidelity to the 8–12-week treat-to-target framework.

This vignette is an illustrative, entirely synthetic example created solely to demonstrate how the endotype-to-care framework operates in practice. It does not represent real patient data and does not constitute human-subject research.

A middle-aged person with obesity/T2D; hs-CRP 6.2 mg/L, NLR 3.4, triglycerides high. Endotype panel: IL-6 high, TNF modest; ISG negative; IL-23/17 negative.

Plan: lifestyle bundle + GLP-1RA; consider IL-6R/TNF inhibition only if guideline-supported and comorbid inflammatory disease present.

12-week monitoring: hs-CRP ↓ 52%, weight −7%, HOMA-IR improved → continue bundle; reassess quarterly.