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Differences Between Men and Women in Human Aging Revealed by Metabolites, Proteins, and Genes

Updated

Abstract

A sex-specific metabolic aging clock was developed using data from 390,941 individuals in the UK Biobank.

  • Dysregulation of cholesterol metabolism, immune response, blood clotting, and cell growth is linked to accelerated metabolic aging in both sexes.
  • Oxidative stress detoxification, cellular resilience, and tissue integrity are associated with decelerated metabolic aging in both males and females.
  • In females, additional dysregulation of carbohydrate metabolism, circadian rhythms, and hormone metabolism is observed that accelerates aging.
  • Energy metabolism and cancer-related pathways are specifically disrupted in males, accelerating their metabolic aging.
  • Reproductive factors such as late puberty and higher parity may help decelerate metabolic aging in both sexes.
  • Accelerated metabolic age predicts higher morbidity and mortality rates, particularly in males, with obesity explaining most disease associations in females.

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Full Text

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Funding

Competing interests

The computational aspects of this research were supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z and the Oxford NIHR BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. S.X and S.B.H and B.H are funded by CAIPM, King Abdulaziz University, Jeddah, Saudi Arabia. P.K is funded by the US National Institute on Aging (NIH). R.K.D is an inventor on a series of patents on use of metabolomics for the diagnosis and treatment of CNS diseases and holds equity in Metabolon Inc., Chymia LLC and Metabosensor. This project was enabled in part by the Alzheimer’s Gut Microbiome Project (AGMP), supported by the National Institute on Aging grants: 1U19AG063744 and 3U19AG063744-04S1, awarded to R.K.D at Duke University in partnership with multiple academic institutions. As such, the investigators within the AGMP not listed in this publication’s authors’ list, provided analysis-ready data, but did not participate in designing the study, conducting the analyses or writing of this manuscript. A listing of AGMP investigators can be found at https://alzheimergut.org/meet-the-team/. A complete listing of the AD Metabolomics Consortium (ADMC) investigators can be found at: https://sites.duke.edu/adnimetab/team/. In addition, this work was supported by the Alzheimer Disease Metabolomics Consortium which is a part of NIA’s national initiatives AMP-AD (3U01AG061359, 3U01 AG024904-09S4). Najaf Amin is funded by NIH and Oxford-GSK Institute of Molecular and Computational Medicine (IMCM). Cornelia M van Duijn is supported by the NIH, NovoNordisk, the IMCM, CAIPM of the University of Oxford and King Abdul Aziz University, Alzheimer Research UK (ARUK), UK National Institute for Health and Care Research (NIHR) Oxford Research Center (BRC), ZonMW (Delta Dementie) and Alzheimer Nederland. Cornelia M van Duijn is currently the Research Director Brain Health of the Health Data Research UK (HDR UK) and the UK Dementia Research Institute (UK DRI), working in partnership with Dementias Platform UK (DPUK). M Austin Argentieri was funded by NIH grant number 5U01AG061359-05.
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