OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process. ### Competing Interest Statement This work was funded in part by TruDiagnostic. JLS is a scientific advisor to Precision Inc and Ahara Inc. MM and VNG have filed patents on measuring cellular aging. STW receives royalties from UpToDate and is on the Board of Histolix, a digital pathology company. Role of the Funder/Sponsor: TruDiagnostic generated the DNA methylation and proteomic data. Investigators from TruDiagnostic co-analyzed and co-wrote the manuscript as described in the contributions above.