RT Journal Article
SR Electronic
T1 An accurate aging clock developed from the largest dataset of microbial and human gene expression reveals molecular mechanisms of aging
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.09.17.301887
DO 10.1101/2020.09.17.301887
A1 Vishakh Gopu
A1 Ying Cai
A1 Subha Krishnan
A1 Sathyapriya Rajagopal
A1 Francine R. Camacho
A1 Ryan Toma
A1 Pedro J. Torres
A1 Momchilo Vuyisich
A1 Ally Perlina
A1 Guruduth Banavar
A1 Hal Tily
YR 2020
UL http://biorxiv.org/content/early/2020/09/19/2020.09.17.301887.abstract
AB Accurate measurement of the biological markers of the aging process could provide an “aging clock” measuring predicted longevity and allow for the quantification of the effects of specific lifestyle choices on healthy aging. Using modern machine learning techniques, we demonstrate that chronological age can be predicted accurately from (a) the expression level of human genes in capillary blood, and (b) the expression level of microbial genes in stool samples. The latter uses the largest existing metatranscriptomic dataset, stool samples from 90,303 individuals, and is the highest-performing gut microbiome-based aging model reported to date. Our analysis suggests associations between biological age and lifestyle/health factors, e.g., people on a paleo diet or with IBS tend to be biologically older, and people on a vegetarian diet tend to be biologically younger. We delineate the key pathways of systems-level biological decline based on the age-specific features of our model; targeting these mechanisms can aid in development of new anti-aging therapeutic strategies.Competing Interest StatementAll authors are employees of Viome Inc, a for-profit company