What markers track PhenoAge?
PhenoAge is a biological age clock derived from nine clinical biomarkers. This page summarises the markers it tracks and the research studies that have used it.
PhenoAge is a biological age clock — formally, a composite score derived from chronological age and nine routine clinical biomarkers, developed to estimate physiological age rather than time since birth. It belongs to the class of epigenetic and clinical biomarker-based aging clocks, and is sometimes referred to as a phenotypic age or a clinical biomarker age. The nine markers it tracks are albumin, creatinine, glucose, C-reactive protein (CRP), lymphocyte percentage, mean cell volume (MCV), red cell distribution width (RDW), alkaline phosphatase, and white blood cell count. The clock outputs an estimated biological age in years; the difference between that estimate and chronological age is termed age acceleration [1].
The work around PhenoAge centres on the biology of aging and the pathways that link systemic inflammation, metabolic function, and haematological parameters to functional decline — a network that includes inflammatory signalling and metabolic regulation rather than a single receptor family [1].
Research Studies
PhenoAge and seasonal variation in adults
A registered clinical study is evaluating how seasonal changes influence biological age in adults. The study aims to provide insights into how seasonal variation affects biological age clocks and to inform the design and analysis of long-term lifestyle interventions that target biological clocks. Biological age clocks, including those measured from blood or saliva, are being assessed as tools for estimating the pace of aging and calculating age acceleration — the difference between chronological and biological age [1].
PhenoAge and calcium alpha-ketoglutarate in middle-aged and older adults
A randomised, double-blind, placebo-controlled trial is evaluating the effects of calcium alpha-ketoglutarate (CaAKG) supplementation on biological aging and age-related health indicators in middle-aged and older adults. Alpha-ketoglutarate is a key intermediate in the Krebs cycle and has been investigated for its potential role in modulating aging-related metabolic and cellular pathways. Because free AKG has poor oral bioavailability, the stabilised calcium salt (CaAKG) is used to enhance absorption and also provides calcium. The trial notes a lack of systematic population-level assessment of these effects [2].
PhenoAge and genetic susceptibility to epigenetic age acceleration in Asian populations
A genome-wide association study examined epigenetic age acceleration using multiple epigenetic clocks in a Korean population, with the aim of exploring ethnic differences and individual variability in Asian populations. The study reports Asian-specific genetic susceptibility for epigenetic age acceleration [3].
PhenoAge and the comparison of biological age clocks
Research on biological age clocks distinguishes between clocks derived from clinical biomarkers, such as PhenoAge, and those derived from epigenetic marks. The evidence describes biological age clocks as emerging tools for assessing the pace of aging and calculating age acceleration, with samples obtainable from blood or saliva [1].
PhenoAge and age-related health indicators
The CaAKG trial includes age-related health indicators as outcomes alongside biological aging measures, reflecting the use of PhenoAge-type clocks to track physiological change in middle-aged and older adults [2].
PhenoAge and intervention design
Seasonality research explicitly aims to enhance the design and analysis of long-term lifestyle interventions targeting biological clocks, indicating that PhenoAge and similar clocks are being positioned as endpoints in intervention studies [1].
PhenoAge and population-level assessment
The CaAKG trial notes that at the population level there is currently a lack of systematic assessment studies on the effects of CaAKG on biological aging, highlighting a gap that PhenoAge-based endpoints could help address [2].
PhenoAge and ethnic variability
The GWAS of epigenetic age acceleration in a Korean population reports ethnic differences and individual variability, underscoring that genetic contributions to age acceleration may differ across populations [3].
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