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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, E...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614756/ https://www.ncbi.nlm.nih.gov/pubmed/37904959 http://dx.doi.org/10.1101/2023.10.16.562114 |
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author | Chen, Qingwen Dwaraka, Varun B. Carreras-Gallo, Natàlia Mendez, Kevin Chen, Yulu Begum, Sofina Kachroo, Priyadarshini Prince, Nicole Went, Hannah Mendez, Tavis Lin, Aaron Turner, Logan Moqri, Mahdi Chu, Su H. Kelly, Rachel S. Weiss, Scott T. Rattray, Nicholas J.W Gladyshev, Vadim N. Karlson, Elizabeth Wheelock, Craig Mathé, Ewy A. Dahlin, Amber McGeachie, Michae J. Smith, Ryan Lasky-Su, Jessica A. |
author_facet | Chen, Qingwen Dwaraka, Varun B. Carreras-Gallo, Natàlia Mendez, Kevin Chen, Yulu Begum, Sofina Kachroo, Priyadarshini Prince, Nicole Went, Hannah Mendez, Tavis Lin, Aaron Turner, Logan Moqri, Mahdi Chu, Su H. Kelly, Rachel S. Weiss, Scott T. Rattray, Nicholas J.W Gladyshev, Vadim N. Karlson, Elizabeth Wheelock, Craig Mathé, Ewy A. Dahlin, Amber McGeachie, Michae J. Smith, Ryan Lasky-Su, Jessica A. |
author_sort | Chen, Qingwen |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10614756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-106147562023-10-31 OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records Chen, Qingwen Dwaraka, Varun B. Carreras-Gallo, Natàlia Mendez, Kevin Chen, Yulu Begum, Sofina Kachroo, Priyadarshini Prince, Nicole Went, Hannah Mendez, Tavis Lin, Aaron Turner, Logan Moqri, Mahdi Chu, Su H. Kelly, Rachel S. Weiss, Scott T. Rattray, Nicholas J.W Gladyshev, Vadim N. Karlson, Elizabeth Wheelock, Craig Mathé, Ewy A. Dahlin, Amber McGeachie, Michae J. Smith, Ryan Lasky-Su, Jessica A. bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-10-24 /pmc/articles/PMC10614756/ /pubmed/37904959 http://dx.doi.org/10.1101/2023.10.16.562114 Text en https://creativecommons.org/licenses/by-nd/4.0/This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Chen, Qingwen Dwaraka, Varun B. Carreras-Gallo, Natàlia Mendez, Kevin Chen, Yulu Begum, Sofina Kachroo, Priyadarshini Prince, Nicole Went, Hannah Mendez, Tavis Lin, Aaron Turner, Logan Moqri, Mahdi Chu, Su H. Kelly, Rachel S. Weiss, Scott T. Rattray, Nicholas J.W Gladyshev, Vadim N. Karlson, Elizabeth Wheelock, Craig Mathé, Ewy A. Dahlin, Amber McGeachie, Michae J. Smith, Ryan Lasky-Su, Jessica A. OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title | OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title_full | OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title_fullStr | OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title_full_unstemmed | OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title_short | OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records |
title_sort | omicmage: an integrative multi-omics approach to quantify biological age with electronic medical records |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614756/ https://www.ncbi.nlm.nih.gov/pubmed/37904959 http://dx.doi.org/10.1101/2023.10.16.562114 |
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