Characterization of aging heterogeneity using molecular biomarkers

Aging is a universal yet heterogeneous process, characterized by diverse trajectories in health outcomes and functional capacities. Although chronological age is a major risk factor for diseases such as type 2 diabetes, cardiovascular disease, and cancer, it often fails to capture individual vulnerability and therapeutic resilience. This discrepancy highlights the need for validated biomarkers—quantitative measures of biological aging that can inform disease onset, predict mortality risk, and assess the efficacy of longevity interventions. This work is organized in three parts. First, we propose a two-step methodology for identifying physiological measures that were previously less recognized as relevant to healthy aging. In the first step, we detect health-related phenotypes by examining variance heterogeneity between the least and most healthy groups. In the second step, we determine sex-specific optimal values, or sweet spots, by analyzing non-linear effects on health. Additionally, we explore lifestyle and socioeconomic factors associated with deviations from these sweet spots. Next, we investigate the molecular basis of heterogeneity in aging by leveraging untargeted metabolomic profiling data from participants in the Canadian Longitudinal Study on Aging. We introduce the Sweet Spot Clock, a metabolomic predictor of biological age that incorporates key metabolites associated with health and their deviations from sweet spots. We further examine genetic and environmental contributions to deviations from predicted metabolomic age. Finally, we explore the epigenetic signatures of aging heterogeneity by identifying regions that are differentially methylated and differentially variable in relation to health. We present an epigenetic biomarker that outperforms models based solely on differential methylation, showing significant associations with mortality and the onset of chronic obstructive pulmonary disease.