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Development of a novel transcriptomic measure of aging: Transcriptomic Mortality-risk Age (TraMA)

  • Eric T. Klopack
  • , Gokul Seshadri
  • , Thalida Em Arpawong
  • , Steve Cole
  • , Bharat Thyagarajan
  • , Eileen M. Crimmins

Research output: Contribution to journalArticlepeer-review

Abstract

Increasingly, research suggests that aging is a coordinated multi-system decline in functioning that occurs at multiple biological levels. We developed and validated a transcriptomic (RNA-based) aging measure we call Transcriptomic Mortality-risk Age (TraMA) using RNA-seq data from the 2016 Health and Retirement Study using elastic net Cox regression analyses to predict 4-year mortality hazard. In a holdout test sample, TraMA was associated with earlier mortality, more chronic conditions, poorer cognitive functioning, and more limitations in activities of daily living. TraMA was also externally validated in the Long Life Family Study and several publicly available datasets. Results suggest that TraMA is a robust, portable RNAseq-based aging measure that is comparable, but independent from past biological aging measures (e.g., GrimAge). TraMA is likely to be of particular value to researchers interested in understanding the biological processes underlying health and aging, and for social, psychological, epidemiological, and demographic studies of health and aging.

Original languageEnglish (US)
Pages (from-to)1521-1543
Number of pages23
JournalAging
Volume17
Issue number6
DOIs
StatePublished - Jun 30 2025

Bibliographical note

Publisher Copyright:
© 2025 Klopack et al.

Keywords

  • accelerated aging
  • biological aging
  • machine learning
  • mortality
  • transcriptomics

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural

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