Mortality Associations With DNA Methylation-Based Biological Aging and Physical Functioning Measures Across a 20-Year Follow-up Period

Abstract Background Measures of biological aging range from DNA methylation (DNAm)-based estimates to measures of physical abilities. The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. Methods We studied 63- to 76-year-...

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Veröffentlicht in:The journals of gerontology. Series A, Biological sciences and medical sciences Biological sciences and medical sciences, 2023-08, Vol.78 (8), p.1489-1496
Hauptverfasser: Föhr, Tiina, Waller, Katja, Viljanen, Anne, Rantanen, Taina, Kaprio, Jaakko, Ollikainen, Miina, Sillanpää, Elina
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container_end_page 1496
container_issue 8
container_start_page 1489
container_title The journals of gerontology. Series A, Biological sciences and medical sciences
container_volume 78
creator Föhr, Tiina
Waller, Katja
Viljanen, Anne
Rantanen, Taina
Kaprio, Jaakko
Ollikainen, Miina
Sillanpää, Elina
description Abstract Background Measures of biological aging range from DNA methylation (DNAm)-based estimates to measures of physical abilities. The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. Methods We studied 63- to 76-year-old women (N = 395) from the Finnish Twin Study on Aging (FITSA). Participants’ biological age (epigenetic clocks DNAm GrimAge and DunedinPACE) was estimated using blood DNAm data. Tests of physical functioning conducted under standardized laboratory conditions included the Timed Up and Go (TUG) test and 10-m walk test. Mortality hazard ratios were calculated per every 1 standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. Results During the follow-up period (mean 17.0 years, range 0.2–20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. Conclusions The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each others and genetic influences. DNAm-based measures and functional tests capture different aspects of the aging process and thus complement each other as measures of biological aging in predicting mortality.
doi_str_mv 10.1093/gerona/glad026
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The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. Methods We studied 63- to 76-year-old women (N = 395) from the Finnish Twin Study on Aging (FITSA). Participants’ biological age (epigenetic clocks DNAm GrimAge and DunedinPACE) was estimated using blood DNAm data. Tests of physical functioning conducted under standardized laboratory conditions included the Timed Up and Go (TUG) test and 10-m walk test. Mortality hazard ratios were calculated per every 1 standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. Results During the follow-up period (mean 17.0 years, range 0.2–20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. Conclusions The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each others and genetic influences. DNAm-based measures and functional tests capture different aspects of the aging process and thus complement each other as measures of biological aging in predicting mortality.</description><identifier>ISSN: 1079-5006</identifier><identifier>EISSN: 1758-535X</identifier><identifier>DOI: 10.1093/gerona/glad026</identifier><identifier>PMID: 36682031</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Aging ; Biomarkers ; Body mass index ; Chronic illnesses ; DNA methylation ; Epigenetics ; Mortality ; Physical activity ; Regression analysis ; THE JOURNAL OF GERONTOLOGY: Medical Sciences</subject><ispartof>The journals of gerontology. Series A, Biological sciences and medical sciences, 2023-08, Vol.78 (8), p.1489-1496</ispartof><rights>The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. 2023</rights><rights>The Author(s) 2023. 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Series A, Biological sciences and medical sciences</title><addtitle>J Gerontol A Biol Sci Med Sci</addtitle><description>Abstract Background Measures of biological aging range from DNA methylation (DNAm)-based estimates to measures of physical abilities. The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. Methods We studied 63- to 76-year-old women (N = 395) from the Finnish Twin Study on Aging (FITSA). Participants’ biological age (epigenetic clocks DNAm GrimAge and DunedinPACE) was estimated using blood DNAm data. Tests of physical functioning conducted under standardized laboratory conditions included the Timed Up and Go (TUG) test and 10-m walk test. Mortality hazard ratios were calculated per every 1 standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. Results During the follow-up period (mean 17.0 years, range 0.2–20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. Conclusions The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each others and genetic influences. DNAm-based measures and functional tests capture different aspects of the aging process and thus complement each other as measures of biological aging in predicting mortality.</description><subject>Aging</subject><subject>Biomarkers</subject><subject>Body mass index</subject><subject>Chronic illnesses</subject><subject>DNA methylation</subject><subject>Epigenetics</subject><subject>Mortality</subject><subject>Physical activity</subject><subject>Regression analysis</subject><subject>THE JOURNAL OF GERONTOLOGY: Medical Sciences</subject><issn>1079-5006</issn><issn>1758-535X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqFkU1v1DAQhi1ERUvhyhFZ4gKHtP6Ik-wJpYVtkbrQAwg4WbO2k3Xltbd20mr_AL-73g8q4IIvY80889ozL0KvKDmhZMJPexODh9PegSaseoKOaC2aQnDx42m-k3pSCEKqQ_Q8pRuyOYI9Q4e8qhpGOD1Cv2YhDuDssMZtSkFZGGzwCX-3wwJ_-NzimRkWa7fNFmeQjMZnNrjQWwUOt731PQav8fVinbap6ejVBt4UZgbSGE3CrYohJQyYkeKngYinwblwX4wrfG2iDfoFOujAJfNyH4_Rt-nHr-eXxdWXi0_n7VWhSsGHggEo05SGUMKZ0apTHBqtKa_noinnjJtSawKUUQDDNOHzWpdcC65qIjre8WP0fqe7GufLLGD8EMHJVbRLiGsZwMq_K94uZB_uZH5wIoSYZIW3e4UYbkeTBrm0SRnnwJswJsnqvFpOSUUz-uYf9CaM0ef5JGvKmtQVFyJTJztqu6NousffUCI3Hsudx3LvcW54_ecMj_hvUzPwbgeEcfU_sQcVPbUv</recordid><startdate>20230802</startdate><enddate>20230802</enddate><creator>Föhr, Tiina</creator><creator>Waller, Katja</creator><creator>Viljanen, Anne</creator><creator>Rantanen, Taina</creator><creator>Kaprio, Jaakko</creator><creator>Ollikainen, Miina</creator><creator>Sillanpää, Elina</creator><general>Oxford University Press</general><scope>TOX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1654-1333</orcidid><orcidid>https://orcid.org/0000-0002-0121-249X</orcidid><orcidid>https://orcid.org/0000-0001-6375-959X</orcidid><orcidid>https://orcid.org/0000-0002-1604-1945</orcidid></search><sort><creationdate>20230802</creationdate><title>Mortality Associations With DNA Methylation-Based Biological Aging and Physical Functioning Measures Across a 20-Year Follow-up Period</title><author>Föhr, Tiina ; Waller, Katja ; Viljanen, Anne ; Rantanen, Taina ; Kaprio, Jaakko ; Ollikainen, Miina ; Sillanpää, Elina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c453t-2aace84e01032edcfc3a8dd137b584b23e4dd0a121aae2d03b7d43d53c705f3f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aging</topic><topic>Biomarkers</topic><topic>Body mass index</topic><topic>Chronic illnesses</topic><topic>DNA methylation</topic><topic>Epigenetics</topic><topic>Mortality</topic><topic>Physical activity</topic><topic>Regression analysis</topic><topic>THE JOURNAL OF GERONTOLOGY: Medical Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Föhr, Tiina</creatorcontrib><creatorcontrib>Waller, Katja</creatorcontrib><creatorcontrib>Viljanen, Anne</creatorcontrib><creatorcontrib>Rantanen, Taina</creatorcontrib><creatorcontrib>Kaprio, Jaakko</creatorcontrib><creatorcontrib>Ollikainen, Miina</creatorcontrib><creatorcontrib>Sillanpää, Elina</creatorcontrib><collection>Access via Oxford University Press (Open Access Collection)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The journals of gerontology. 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Mortality hazard ratios were calculated per every 1 standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. Results During the follow-up period (mean 17.0 years, range 0.2–20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. Conclusions The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each others and genetic influences. 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source Oxford University Press Journals All Titles (1996-Current); Alma/SFX Local Collection
subjects Aging
Biomarkers
Body mass index
Chronic illnesses
DNA methylation
Epigenetics
Mortality
Physical activity
Regression analysis
THE JOURNAL OF GERONTOLOGY: Medical Sciences
title Mortality Associations With DNA Methylation-Based Biological Aging and Physical Functioning Measures Across a 20-Year Follow-up Period
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