A molecular index for biological age identified from the metabolome and senescence‐associated secretome in humans
Year: 2024
Type: article
Study design: Observational Study
Abstract: Unlike chronological age, biological age is a strong indicator of health of an individual. However, the molecular fingerprint associated with biological age is ill-defined. To define a high-resolution signature of biological age, we analyzed metabolome, circulating senescence-associated secretome (SASP)/inflammation markers and the interaction between them, from a cohort of healthy and rapid agers. The balance between two fatty acid oxidation mechanisms, β-oxidation and ω-oxidation, associated with the extent of functional aging. Furthermore, a panel of 25 metabolites, Healthy Aging Metabolic (HAM) index, predicted healthy agers regardless of gender and race. HAM index was also validated in an independent cohort. Causal inference with machine learning implied three metabolites, β-cryptoxanthin, prolylhydroxyproline, and eicosenoylcarnitine as putative drivers of biological aging. Multiple SASP markers were also elevated in rapid agers. Together, our findings reveal that a network of metabolic pathways underlie biological aging, and the HAM index could serve as a predictor of phenotypic aging in humans.
Source: Aging Cell
DOI: 10.1111/acel.14104
Language: English
Subfield: Aging
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,350
Awards: G1886952231, G4202057321, G5136424781, Genomic and Metabolomic Data Integration in a Longitudinal Cohort at Risk for Alzheimer's Disease, G640327682, G741073515, Pittsburgh Older Americans Independence Center, Genomic and Metabolomic Data Integration in a Longitudinal Cohort at Risk for Alzheimer's Disease, Mapping the cell specific DNA damage-induced molecular and bioelectrical responses in the 3D cardiac unit
OpenAlex ID: W4392593224
