Review: proteomic biomarkers of biological aging across physiological systems
This review describes circulating-protein biomarkers linked to biological rather than chronological aging across immune, metabolic/endocrine, cardiovascular, musculoskeletal and nervous systems, and reports that proteomic aging clocks in large cohorts predict frailty, multimorbidity, organ-specific biological age and mortality. [1]
Automatic summary · not editorially reviewed
The key findings
The review synthesizes evidence on proteomic biomarkers across immune, metabolic/endocrine, cardiovascular, musculoskeletal and nervous systems. [1]
Named biomarkers include IL-6, CRP, CXCL9/10, GDF15, IGF-1, VCAM-1, NT-proBNP, NfL and GFAP. [1]
Large population cohorts show proteomic aging clocks can predict frailty, multimorbidity, organ-specific biological age and mortality with high accuracy. [1]
The source at a glance
- Study type / format
- Review (abstract only)
- Population / context
- Circulating proteins in large population cohorts, as described in a review
- Summary based on
- Study abstract
- Original publication
- August 14, 2026
Review scope across five physiological systems
The source is a review that synthesizes current evidence on proteomic biomarkers across major physiological systems: immune, metabolic/endocrine, cardiovascular, musculoskeletal and nervous. It states that high-throughput proteomics has enabled mapping of age-related changes in circulating proteins, with dynamic and non-linear trajectories reflecting biological rather than chronological aging. It also highlights shared molecular signatures said to underpin multisystem decline.
Supporting source [1]
Named biomarkers and cohort-based aging clocks
The review names IL-6, CRP, CXCL9/10, GDF15, IGF-1, VCAM-1, NT-proBNP, NfL and GFAP as robust biomarkers that consistently track inflammatory activation, mitochondrial and metabolic stress, extracellular matrix remodeling and neuro-glial injury. It reports that large population cohorts show proteomic aging clocks, using dozens to hundreds of circulating proteins, can predict frailty, multimorbidity, organ-specific biological age and mortality with high accuracy. Emerging evidence suggests a limited set of cross-system protein aging modules may act as integrative readouts and potential regulators.
Supporting source [1]
Translational framing and abstract-only limits
The review discusses methodological advances, system-specific mechanisms and translational applications of proteomic aging models, positioning proteomics as a tool for quantifying biological age, identifying early disease risk and guiding precision interventions. These are described as predictive associations and potential applications, not proven causal effects or established clinical benefits. Only the abstract was reviewed; the full text was not reviewed, so study designs, cohort sizes, follow-up and effect estimates behind these statements could not be checked.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. Study designs, cohort sizes, follow-up and effect estimates are not reported in the abstract. The described predictions are associations, and the proposed modules and interventions are not established clinical tools.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Luo Y, Xiao YL, Chen JH, Wang H, Luo S, Dong H, Huang RP. · europepmc.org · August 14, 2026