Journal article

Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality

YE Tian, V Cropley, AB Maier, NT Lautenschlager, M Breakspear, A Zalesky

Nature Medicine | Published : 2023

Abstract

Biological aging of human organ systems reflects the interplay of age, chronic disease, lifestyle and genetic risk. Using longitudinal brain imaging and physiological phenotypes from the UK Biobank, we establish normative models of biological age for three brain and seven body systems. Here we find that an organ’s biological age selectively influences the aging of other organ systems, revealing a multiorgan aging network. We report organ age profiles for 16 chronic diseases, where advanced biological aging extends from the organ of primary disease to multiple systems. Advanced body age associates with several lifestyle and environmental factors, leukocyte telomere lengths and mortality risk,..

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Grants

Awarded by Alzheimer's Disease Neuroimaging Initiative


Funding Acknowledgements

This research has been conducted using data from UK Biobank (https://www.ukbiobank.ac.uk/), a major biomedical database. We are grateful to UK Biobank for making the data available and to all study participants, who generously donated their time to make this resource possible. Some of the data used in the preparation of this article were obtained from the AIBL Flagship Study of Ageing, funded by the Commonwealth Scientific and Industrial Research Organisation, which was made available at the ADNI database (https://adni.loni.usc.edu/). The AIBL researchers contributed data but did not participate in analysis or writing of this report. AIBL researchers are listed at: https://aibl.csiro.au/. Some of the data used in preparation of this article were obtained from the ADNI database (https://adni.loni.usc.edu/). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. Some of the data collection and sharing for this project was funded by ADNI (National Institutes of Health grant U01 AG024904) and Department of Defense ADNI (award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica; Biogen; Bristol-Myers Squibb Company; CereSpir; Cogstate; Eisai; Elan Pharmaceuticals; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche and its affiliated company Genentech; Fujirebio; GE Healthcare; IXICO; Janssen Alzheimer Immunotherapy Research & Development; Johnson & Johnson Pharmaceutical Research & Development; Lumosity; Lundbeck; Merck & Co.; Meso Scale Diagnostics; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (https://www.fnih.org/). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. We thank S.M. Smith (University of Oxford) and D. Vidal-Pineiro (University of Oslo) for their feedback and discussion on data analyses. Y.E.T. was supported by the Mary Lugton Postdoctoral Fellowship. A.Z. was supported by a National Health and Medical Research Council (NHMRC) grant (APP1142801 and APP118153), V.C. was supported by an NHMRC grant (APP1177370) and M.B. was supported by an NHMRC grant (APP1152623 and APP2008612).