Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging
The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but ass...
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description | The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but associations with frailty are poorly described. Further, it is uncertain whether newer generations of epigenetic clocks, trained on variables other than chronological age, would be more strongly associated with frailty than earlier developed clocks. Using data from the Canadian Longitudinal Study on Aging (CLSA), we tested the hypothesis that clocks trained on phenotypic markers of health or mortality (i.e., Dunedin PoAm, GrimAge, PhenoAge and Zhang in Nat Commun 8:14617, 2017) would best predict changes in a 76-item frailty index (FI) over a 3-year interval, as compared to clocks trained on chronological age (i.e., Hannum in Mol Cell 49:359-367, 2013, Horvath in Genome Biol 14:R115, 2013, Lin in Aging 8:394-401, 2016, and Yang Genome Biol 17:205, 2016).
We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.
Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging. |
doi_str_mv | 10.1186/s13148-021-01150-1 |
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We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.
Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging.</description><identifier>ISSN: 1868-7075</identifier><identifier>ISSN: 1868-7083</identifier><identifier>EISSN: 1868-7083</identifier><identifier>EISSN: 1868-7075</identifier><identifier>DOI: 10.1186/s13148-021-01150-1</identifier><identifier>PMID: 34425884</identifier><language>eng</language><publisher>Germany: BioMed Central Ltd</publisher><subject>Age ; Age Factors ; Aged ; Aged, 80 and over ; Aging ; Aging - genetics ; Canada ; Cause of Death ; DNA methylation ; DNA Methylation - genetics ; Epigenesis, Genetic ; Epigenetic inheritance ; Epigenetics ; Estimates ; Female ; Frailty ; Frailty - genetics ; Frailty - mortality ; Genetic Variation ; Genomes ; Genomics ; Gerontology ; Health aspects ; Humans ; Life span ; Longitudinal Studies ; Male ; Methylation ; Middle Aged ; Mortality ; Older people ; Phenotypes ; Physiology ; Public health ; Risk factors ; Sociodemographic Factors ; Sociodemographics ; Time Factors ; Womens health</subject><ispartof>Clinical epigenetics, 2021-08, Vol.13 (1), p.163, Article 163</ispartof><rights>2021. The Author(s).</rights><rights>COPYRIGHT 2021 BioMed Central Ltd.</rights><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c458t-dcb15d628eaf230912bc4f6518747e4df6ed6667b74a6266b2e0f87353cab6ed3</citedby><cites>FETCH-LOGICAL-c458t-dcb15d628eaf230912bc4f6518747e4df6ed6667b74a6266b2e0f87353cab6ed3</cites><orcidid>0000-0001-6190-2655</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381580/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381580/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34425884$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Verschoor, Chris P</creatorcontrib><creatorcontrib>Lin, David T S</creatorcontrib><creatorcontrib>Kobor, Michael S</creatorcontrib><creatorcontrib>Mian, Oxana</creatorcontrib><creatorcontrib>Ma, Jinhui</creatorcontrib><creatorcontrib>Pare, Guillaume</creatorcontrib><creatorcontrib>Ybazeta, Gustavo</creatorcontrib><title>Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging</title><title>Clinical epigenetics</title><addtitle>Clin Epigenetics</addtitle><description>The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but associations with frailty are poorly described. Further, it is uncertain whether newer generations of epigenetic clocks, trained on variables other than chronological age, would be more strongly associated with frailty than earlier developed clocks. Using data from the Canadian Longitudinal Study on Aging (CLSA), we tested the hypothesis that clocks trained on phenotypic markers of health or mortality (i.e., Dunedin PoAm, GrimAge, PhenoAge and Zhang in Nat Commun 8:14617, 2017) would best predict changes in a 76-item frailty index (FI) over a 3-year interval, as compared to clocks trained on chronological age (i.e., Hannum in Mol Cell 49:359-367, 2013, Horvath in Genome Biol 14:R115, 2013, Lin in Aging 8:394-401, 2016, and Yang Genome Biol 17:205, 2016).
We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.
Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging.</description><subject>Age</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Aging - genetics</subject><subject>Canada</subject><subject>Cause of Death</subject><subject>DNA methylation</subject><subject>DNA Methylation - genetics</subject><subject>Epigenesis, Genetic</subject><subject>Epigenetic inheritance</subject><subject>Epigenetics</subject><subject>Estimates</subject><subject>Female</subject><subject>Frailty</subject><subject>Frailty - genetics</subject><subject>Frailty - mortality</subject><subject>Genetic Variation</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Gerontology</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Life span</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Methylation</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Older people</subject><subject>Phenotypes</subject><subject>Physiology</subject><subject>Public health</subject><subject>Risk factors</subject><subject>Sociodemographic Factors</subject><subject>Sociodemographics</subject><subject>Time Factors</subject><subject>Womens health</subject><issn>1868-7075</issn><issn>1868-7083</issn><issn>1868-7083</issn><issn>1868-7075</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpdkUuP0zAUhS0EYkbD_AEWyBIbNgG_YjsbpKoaHlIlFsDaunFuUo9Su8QJqP8ehw7l4Y2PdL577KtDyHPOXnNu9ZvMJVe2YoJXjPOaVfwRuS6GrQyz8vFFm_qK3OZ8z8qRTdNw9pRcSaVEba26JvnuGAaMOAdPYUAaMoWckw8wY0d_hHlPW8g4hogUYkdldUKYqN9DXOlI-wnCOJ9WOe-RbiFCFyDSXYpDmJcuRBjp5yJONEW6GUIcnpEnPYwZbx_uG_L13d2X7Ydq9-n9x-1mV3lV27nqfMvrTguL0AvJGi5ar3pdc2uUQdX1GjuttWmNAi20bgWy3hpZSw9t8eQNeXvOPS7tATuPcZ5gdMcpHGA6uQTB_evEsHdD-u6stLy2rAS8egiY0rcF8-wOIXscR4iYluxErRWXijW2oC__Q-_TMpXdV8oopWTD1B9qgBFdiH0q7_o11G20kUwILtYscab8lHKesL98mTO3lu_O5btSvvtVvuNl6MXfy15GflctfwIcZqm6</recordid><startdate>20210823</startdate><enddate>20210823</enddate><creator>Verschoor, Chris P</creator><creator>Lin, David T S</creator><creator>Kobor, Michael S</creator><creator>Mian, Oxana</creator><creator>Ma, Jinhui</creator><creator>Pare, Guillaume</creator><creator>Ybazeta, Gustavo</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6190-2655</orcidid></search><sort><creationdate>20210823</creationdate><title>Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging</title><author>Verschoor, Chris P ; Lin, David T S ; Kobor, Michael S ; Mian, Oxana ; Ma, Jinhui ; Pare, Guillaume ; Ybazeta, Gustavo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c458t-dcb15d628eaf230912bc4f6518747e4df6ed6667b74a6266b2e0f87353cab6ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging</topic><topic>Aging - genetics</topic><topic>Canada</topic><topic>Cause of Death</topic><topic>DNA methylation</topic><topic>DNA Methylation - genetics</topic><topic>Epigenesis, Genetic</topic><topic>Epigenetic inheritance</topic><topic>Epigenetics</topic><topic>Estimates</topic><topic>Female</topic><topic>Frailty</topic><topic>Frailty - genetics</topic><topic>Frailty - mortality</topic><topic>Genetic Variation</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Gerontology</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Life span</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Methylation</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Older people</topic><topic>Phenotypes</topic><topic>Physiology</topic><topic>Public health</topic><topic>Risk factors</topic><topic>Sociodemographic Factors</topic><topic>Sociodemographics</topic><topic>Time Factors</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Verschoor, Chris P</creatorcontrib><creatorcontrib>Lin, David T S</creatorcontrib><creatorcontrib>Kobor, Michael S</creatorcontrib><creatorcontrib>Mian, Oxana</creatorcontrib><creatorcontrib>Ma, Jinhui</creatorcontrib><creatorcontrib>Pare, Guillaume</creatorcontrib><creatorcontrib>Ybazeta, Gustavo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Clinical epigenetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Verschoor, Chris P</au><au>Lin, David T S</au><au>Kobor, Michael S</au><au>Mian, Oxana</au><au>Ma, Jinhui</au><au>Pare, Guillaume</au><au>Ybazeta, Gustavo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging</atitle><jtitle>Clinical epigenetics</jtitle><addtitle>Clin Epigenetics</addtitle><date>2021-08-23</date><risdate>2021</risdate><volume>13</volume><issue>1</issue><spage>163</spage><pages>163-</pages><artnum>163</artnum><issn>1868-7075</issn><issn>1868-7083</issn><eissn>1868-7083</eissn><eissn>1868-7075</eissn><abstract>The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but associations with frailty are poorly described. Further, it is uncertain whether newer generations of epigenetic clocks, trained on variables other than chronological age, would be more strongly associated with frailty than earlier developed clocks. Using data from the Canadian Longitudinal Study on Aging (CLSA), we tested the hypothesis that clocks trained on phenotypic markers of health or mortality (i.e., Dunedin PoAm, GrimAge, PhenoAge and Zhang in Nat Commun 8:14617, 2017) would best predict changes in a 76-item frailty index (FI) over a 3-year interval, as compared to clocks trained on chronological age (i.e., Hannum in Mol Cell 49:359-367, 2013, Horvath in Genome Biol 14:R115, 2013, Lin in Aging 8:394-401, 2016, and Yang Genome Biol 17:205, 2016).
We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.
Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging.</abstract><cop>Germany</cop><pub>BioMed Central Ltd</pub><pmid>34425884</pmid><doi>10.1186/s13148-021-01150-1</doi><orcidid>https://orcid.org/0000-0001-6190-2655</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Age Age Factors Aged Aged, 80 and over Aging Aging - genetics Canada Cause of Death DNA methylation DNA Methylation - genetics Epigenesis, Genetic Epigenetic inheritance Epigenetics Estimates Female Frailty Frailty - genetics Frailty - mortality Genetic Variation Genomes Genomics Gerontology Health aspects Humans Life span Longitudinal Studies Male Methylation Middle Aged Mortality Older people Phenotypes Physiology Public health Risk factors Sociodemographic Factors Sociodemographics Time Factors Womens health |
title | Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging |
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