OMICmAge quantifies biological age by integrating multi-omics with electronic medical records

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Chen, Qingwen and Dwaraka, Varun B and Carreras-Gallo, Natàlia and Armstrong, Jenel F and Sehgal, Raghav and Argentieri, M Austin and Richmond, Anne and Aparicio, Andrea and Mendez, Kevin and Chen, Yulu and Begum, Sofina and Kachroo, Priyadarshini and Prince, Nicole and Guo, Tao and Went, Hannah and Mendez, Tavis and Lin, Aaron and Turner, Logan and Moqri, Mahdi and Chu, Su H and Kelly, Rachel S and Weiss, Scott T and Rattray, Nicholas J W and Gladyshev, Vadim N and Karlson, Elizabeth and Wheelock, Craig E and Mathé, Ewy A and Dahlin, Amber and McGeachie, Michael J and Marioni, Riccardo E and Higgins-Chen, Albert T and Smith, Ryan and Lasky-Su, Jessica (2026) OMICmAge quantifies biological age by integrating multi-omics with electronic medical records. Nature Aging, 6 (3). pp. 722-737. ISSN 2662-8465 (https://doi.org/10.1038/s43587-026-01073-7)

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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. [Abstract copyright: © 2026. The Author(s).]

ORCID iDs

Chen, Qingwen, Dwaraka, Varun B, Carreras-Gallo, Natàlia, Armstrong, Jenel F, Sehgal, Raghav, Argentieri, M Austin, Richmond, Anne, Aparicio, Andrea, Mendez, Kevin, Chen, Yulu, Begum, Sofina, Kachroo, Priyadarshini, Prince, Nicole, Guo, Tao, Went, Hannah, Mendez, Tavis, Lin, Aaron, Turner, Logan, Moqri, Mahdi, Chu, Su H, Kelly, Rachel S, Weiss, Scott T, Rattray, Nicholas J W ORCID logoORCID: https://orcid.org/0000-0002-3528-6905, Gladyshev, Vadim N, Karlson, Elizabeth, Wheelock, Craig E, Mathé, Ewy A, Dahlin, Amber, McGeachie, Michael J, Marioni, Riccardo E, Higgins-Chen, Albert T, Smith, Ryan and Lasky-Su, Jessica;
CORE (COnnecting REpositories)