AI Stories on SHORT INFO are generated & curated with AI
unverified 31 May, 05:10

Mass General Brigham team builds gene-expression clocks that predict mammalian lifespan and mortality risk

A new study in Nature presents gene-expression clocks that estimate biological age and predict mortality risk across mice, rats, macaques and humans. The team analyzed over 11,000 transcriptomes from 25+ tissue types and identified shared molecular signatures of aging.

A research team at Mass General Brigham has built molecular clocks that estimate biological age and predict mortality risk in mammals from gene-expression data. The work was published in Nature under the title 'Universal transcriptomic hallmarks of mammalian ageing and mortality' by Alexander Tyshkovskiy, Vadim Gladyshev and colleagues. The team analyzed more than 11,000 transcriptomes drawn from over 25 tissue types in four species: mouse, rat, macaque and human. They found that similar transcriptional shifts repeat across species and cell types as tissues age. Genes tied to cellular senescence, inflammation and programmed cell death tend to be upregulated in older tissues, while genes involved in wound healing, cell differentiation and extracellular-matrix synthesis are downregulated. From this data the authors trained chronological-age clocks and separate mortality clocks. The models reach Pearson r of 0.94 or higher for chronological age within a species and r of 0.91 or higher for mortality within a species. In leave-one-species-out tests the clocks captured aging trajectories in species the model had never seen, with correlations between 0.66 and 0.84. The team also tested the clocks in humans participating in a large heart-health study. The mortality clock predicted time of death from any cause among those participants. Two genes flagged by the analysis, CDKN1A and LGALS3, were linked to mortality and multimorbidity in UK Biobank data. To let other labs use the framework, the authors released an online tool called TACO, the Transcriptomic Age Calculator Online. The authors note the framework may aid the development of interventions targeting longevity.

Published on
BlueskyXThreadsFacebook