Aging biomarkers are crucial for quantifying molecular, physiological, or functional features that vary among individuals as they age. They may enhance the prediction of health outcomes beyond mere chronological age. In this study, published in Aging Cell, researchers investigated the relationship between multimodal ageing biomarkers and plasma proteomic signatures associated with all-cause mortality.
The study utilized data from the Lothian Birth Cohort 1936 (LBC1936), involving 861 participants, of whom 444 had died over a 16-year follow-up period. The researchers employed Cox regression to analyze the associations between various biomarkers and mortality risk. Among the biomarkers assessed were the epigenetic clock GrimAge2, telomere length, and measures of physical function such as grip strength, walk time, and respiratory function, along with neuroimaging and cognitive assessments.
Notably, the study found that accelerated ageing in specific organs, particularly the liver, immune system, and heart, was significantly associated with increased mortality risk. For instance, the hazard ratios (HR) indicated that accelerated liver ageing had an HR of 1.43, immune ageing 1.42, and heart ageing 1.38, all suggesting a higher risk of mortality. However, the study also highlighted that older epigenetic age, smaller brain volumes, reduced respiratory function, and poorer cognitive performance exhibited even stronger associations with mortality, with HRs ranging from 1.44 to 1.62.
In addition to organ clocks, the researchers conducted survival analyses on 9703 plasma protein targets, identifying 368 proteins associated with mortality risk. High-risk proteins were primarily linked to immune functions, while low-risk proteins were associated with genomic stability and cellular maintenance. Among the leading candidates identified were GDF15, WFDC2, and TIMP1, with HRs of 1.56, 1.47, and 1.45, respectively.
This study represents a systematic benchmarking of proteomic organ clocks against established ageing biomarkers, providing insights into proteins and biological functions that may be linked to mortality risk. The findings suggest that integrating proteomic data with traditional ageing biomarkers could enhance our understanding of health outcomes in aging populations.
What this study does not show
This study does not establish a causal relationship between the identified biomarkers and mortality, nor does it imply that interventions based on these findings will improve health outcomes.
Evidence scorecard
- Analytic validity: Established
- Clinical validity: Partial
- Clinical utility: Not established
The evidence is derived from primary research involving human participants.