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

Chen, Q.; Dwaraka, V. B.; Carreras-Gallo, N.; Medez, K.; Chen, Y.; Kachroo, P.; Prince, N.; Went, H.; Medez, T.; Lin, A.; Turner, L.; Moqri, M.; Chu, S. H.; Kelly, R. S.; Weiss, S. T.; Rattray, N. J.; Gladyshev, V. N.; Karlson, E.; Wheelock, C.; Mathe, E. A.; Dahlin, A.; McGeachie, M. J.; Smith, R.; Lasky-Su, J. A.

doi:10.1101/2023.10.16.562114

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bioRxiv · 10.1101/2023.10.16.562114

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

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Abstract

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.

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Chen, Q., Dwaraka, V. B., Carreras-Gallo, N., Medez, K., Chen, Y., Kachroo, P., Prince, N., Went, H., Medez, T., Lin, A., Turner, L., Moqri, M., Chu, S. H., Kelly, R. S., Weiss, S. T., Rattray, N. J., Gladyshev, V. N., Karlson, E., Wheelock, C., Mathe, E. A., Dahlin, A., McGeachie, M. J., Smith, R., Lasky-Su, J. A.. 2023-10-20. OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records. https://doi.org/10.1101/2023.10.16.562114

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