Aging biomarkers are essential for quantifying molecular, physiological, or functional features that change with age, potentially enhancing the prediction of health outcomes beyond mere chronological age. Recent advancements in plasma proteomics have enabled the estimation of biological ages for various human organs. However, the relationship between these proteomic organ clocks and established ageing biomarkers, particularly concerning mortality risk, has not been systematically evaluated.
This study aimed to address this gap by pursuing two complementary objectives. The first was to benchmark proteomic organ clocks against multimodal ageing biomarkers in relation to 16-year all-cause mortality within the Lothian Birth Cohort 1936 (LBC1936), which included 861 participants and recorded 444 deaths. The biomarkers assessed included the epigenetic clock GrimAge2, telomere length, physical function indicators (such as grip strength, walking time, and respiratory function), neuroimaging data, and cognitive measures.
Findings revealed that accelerated ageing of the liver (hazard ratio per standard deviation [HRperSD] = 1.43), immune system (1.42), and heart (1.38) were significantly associated with increased mortality risk. However, older epigenetic age, smaller total brain and grey matter volumes, reduced respiratory function, and poorer cognitive performance exhibited even stronger associations with mortality (HRperSD = 1.44-1.62).
The second objective involved survival analyses of 9703 plasma protein targets, which identified 368 proteins associated with mortality. Notably, high-risk proteins were predominantly linked to immune functions, while low-risk proteins were associated with genomic stability and cellular maintenance. Among these, GDF15 (HRperSD = 1.56), WFDC2 (1.47), and TIMP1 (1.45) emerged as leading candidates correlated with mortality risk.
This study provides a systematic cross-modal benchmarking of proteomic organ clocks against established ageing biomarkers, highlighting specific proteins and biological functions that are associated with mortality risk.
What this study does not show
This study does not establish a causal relationship between the identified biomarkers and mortality, nor does it provide evidence for interventions based on these findings.
Evidence scorecard
- Analytic validity: Established
- Clinical validity: Partial
- Clinical utility: Not established