What this means
Researchers built new scores that estimate biological age and link it to disease and death risk. The scores were tested in people, but this does not show they improve health or guide care.
Plain-English summary written by an AI model from the abstract. The original is below.
- Who it was tested in
- About 31,000 people in discovery and validation groups, including 3,451 in the main group
- Kind of research
- A study
The science
- Original title
- OMICmAge quantifies biological age by integrating multi-omics with electronic medical records.
- Authors
- Chen Q, Dwaraka VB, Carreras-Gallo N et al.
- Journal
- Nature aging
- Published
- Feb 25, 2026
- Study type
- Study · in humans
- PMID
- 41741793 ↗
Abstract
Biological aging reflects complex cellular and biochemical processes that can be measured across multiple omic layers. Using routine clinical laboratory data from ~31,000 participants in the Mass General Brigham Biobank, we developed EMRAge, a biomarker of mortality risk that can be broadly recapitulated across electronic medical records. Here we show that EMRAge can be modeled using elastic net regression with DNA methylation and multi-omics to generate DNAmEMRAge and OMICmAge, respectively. Both biomarkers are strongly associated with incident and prevalent chronic diseases and mortality, performing comparably or better than current biomarkers across discovery (Massachusetts General Brigham Aging Biobank Cohort, n = 3,451) and validation cohorts (TruDiagnostic, n = 14,213; Generation Scotland, n = 18,672). Importantly, OMICmAge leverages epigenetic biomarker proxies to integrate proteomic, metabolomic and clinical domains while remaining quantifiable from DNA methylation alone. This framework establishes an accessible, scalable measure of biological aging with potential to reveal molecular interconnections that shape healthspan and disease risk.
Chen Q, Dwaraka VB, Carreras-Gallo N et al. OMICmAge quantifies biological age by integrating multi-omics with electronic medical records. Nature aging. 2026. doi:10.1038/s43587-026-01073-7. PMID: 41741793. https://pubmed.ncbi.nlm.nih.gov/41741793/