Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology

Estimators of biological age (BA) – defined as the hypothetical underlying age of an organism – have attracted more and more attention in the last years, especially after the advent of new algorithms based on machine learning and genetic markers. While different aging clocks reportedly predict mortality in the general population, very little is known on their overlap. Here we review the evidence reported so far to support the existence of a partial overlap among different BA acceleration estimators, both from an epidemiological and a genetic perspective. On the epidemiological side, we review evidence supporting shared and independent influence on mortality risk of different aging clocks - including telomere length, brain, blood and epigenetic aging – and provide an overview of how an important exposure like diet may affect the different aging systems. On the genetic side, we apply linkage disequilibrium score regression analyses to support the existence of partly shared genomic overlap among these aging clocks. Through multivariate analysis of published genetic associations with these clocks, we also identified the most associated variants, genes, and pathways, which may affect common mechanisms underlying biological aging of different systems within the body. Based on our analyses, the most implicated pathways were involved in inflammation, lipid and carbohydrate metabolism, suggesting them as potential molecular targets for future anti-aging interventions. Overall, this review is meant as a contribution to the knowledge on the overlap of aging clocks, trying to clarify their shared biological basis and epidemiological implications. •Reviewed evidence supports the existence of a partial overlap among different biological aging acceleration estimators.•Epidemiological studies reveal partly independent influence of different aging clocks on mortality risk.•Healthy dietary patterns like Mediterranean diet are linked to biological aging deceleration in different domains.•Genetic correlations suggest a partial genomic overlap among different aging clocks.•Genetic associations suggest an implication of inflammation, lipid and carbohydrate homeostasis in different aging domains.