Association Between Behavioral, Biological, and Genetic Markers of Cardiovascular Health and MRI Markers of Brain Aging: A Cohort Study
The life's simple 7 approach was proposed to define cardiovascular health (CVH) metrics. We sought to investigate the associations between behavioral, biological, and genetic markers for CVH and vascular brain aging in older adults. This population-based cohort study included participants who h...
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description | The life's simple 7 approach was proposed to define cardiovascular health (CVH) metrics. We sought to investigate the associations between behavioral, biological, and genetic markers for CVH and vascular brain aging in older adults.
This population-based cohort study included participants who had repeated brain MRI measures from 2001 to 2003 to 2007-2010 (i.e., count of perivascular spaces, volumes of white matter hyperintensity [WMH] and gray matter, and lacunes). At baseline, global, behavioral, and biological CVH metrics were defined and scored following the life's simple 7 approach and categorized into unfavorable, intermediate, and favorable profiles according to tertiles. The metabolic genetic risk score was calculated by counting 15 risk alleles associated with hypertension, diabetes, or dyslipidemia. Data were analyzed using linear mixed-effects and Cox proportional hazards models, adjusting for age, sex, and education.
The study sample consisted of 317 participants (age 60 years or older; 61.8% women). Favorable and intermediate (vs unfavorable) global CVH profiles were related to slower WMH progression, with β-coefficients (95% CI) being -0.019(-0.035-0.002) and -0.018(-0.034-0.001), respectively. Favorable and intermediate (vs unfavorable) biological CVH profiles were significantly related to slower WMH increase only in people aged 60-72 years. CVH profiles were not related to progression of other brain measures. Furthermore, a higher metabolic genetic risk score (range: 6-21) was associated with faster WMH increase (β-coefficient = 0.005; 95% CI: 0.003-0.008). There were statistical interactions of metabolic genetic risk score with global and behavioral CVH profiles on WMH accumulation. A higher metabolic genetic risk score was related to faster WMH accumulation, with β-coefficients being 0.015(0.007-0.023), 0.005(0.001-0.009), and 0.003(-0.001 to 0.006) among people with unfavorable, intermediate, and favorable global CVH profiles, respectively; the corresponding β-coefficients were 0.013(0.006-0.020), 0.006(0.003-0.009), and 0.002(-0.002 to 0.006) among people with unfavorable, intermediate, and favorable behavioral CVH profiles.
Intermediate to favorable global CVH profiles in older adults are associated with slower vascular brain aging. The association of metabolic genetic risk load with accelerated vascular brain aging was evident among people with unfavorable to intermediate, but not favorable, CVH profiles. These findings highlight the i |
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This population-based cohort study included participants who had repeated brain MRI measures from 2001 to 2003 to 2007-2010 (i.e., count of perivascular spaces, volumes of white matter hyperintensity [WMH] and gray matter, and lacunes). At baseline, global, behavioral, and biological CVH metrics were defined and scored following the life's simple 7 approach and categorized into unfavorable, intermediate, and favorable profiles according to tertiles. The metabolic genetic risk score was calculated by counting 15 risk alleles associated with hypertension, diabetes, or dyslipidemia. Data were analyzed using linear mixed-effects and Cox proportional hazards models, adjusting for age, sex, and education.
The study sample consisted of 317 participants (age 60 years or older; 61.8% women). Favorable and intermediate (vs unfavorable) global CVH profiles were related to slower WMH progression, with β-coefficients (95% CI) being -0.019(-0.035-0.002) and -0.018(-0.034-0.001), respectively. Favorable and intermediate (vs unfavorable) biological CVH profiles were significantly related to slower WMH increase only in people aged 60-72 years. CVH profiles were not related to progression of other brain measures. Furthermore, a higher metabolic genetic risk score (range: 6-21) was associated with faster WMH increase (β-coefficient = 0.005; 95% CI: 0.003-0.008). There were statistical interactions of metabolic genetic risk score with global and behavioral CVH profiles on WMH accumulation. A higher metabolic genetic risk score was related to faster WMH accumulation, with β-coefficients being 0.015(0.007-0.023), 0.005(0.001-0.009), and 0.003(-0.001 to 0.006) among people with unfavorable, intermediate, and favorable global CVH profiles, respectively; the corresponding β-coefficients were 0.013(0.006-0.020), 0.006(0.003-0.009), and 0.002(-0.002 to 0.006) among people with unfavorable, intermediate, and favorable behavioral CVH profiles.
Intermediate to favorable global CVH profiles in older adults are associated with slower vascular brain aging. The association of metabolic genetic risk load with accelerated vascular brain aging was evident among people with unfavorable to intermediate, but not favorable, CVH profiles. These findings highlight the importance of adhering to favorable CVH profiles, especially healthy behaviors, in vascular brain health.</description><identifier>ISSN: 0028-3878</identifier><identifier>ISSN: 1526-632X</identifier><identifier>EISSN: 1526-632X</identifier><identifier>DOI: 10.1212/WNL.0000000000201346</identifier><identifier>PMID: 36319110</identifier><language>eng</language><publisher>United States: Lippincott Williams & Wilkins</publisher><subject>Aged ; Aging - genetics ; Brain - diagnostic imaging ; Cardiovascular Diseases - diagnostic imaging ; Cardiovascular Diseases - genetics ; Cohort Studies ; Female ; Genetic Markers ; Health Status ; Humans ; Magnetic Resonance Imaging ; Male ; Medicin och hälsovetenskap ; Risk Factors</subject><ispartof>Neurology, 2023-01, Vol.100 (1), p.e38-e48</ispartof><rights>Lippincott Williams & Wilkins</rights><rights>Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.</rights><rights>Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. 2022 American Academy of Neurology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c4818-4fc7b504720176c79a298fee0870beb08f1fe1eb69a6b0e967de9e42d1740e593</cites><orcidid>0000-0002-1525-5538</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,552,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36319110$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-214378$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:151575058$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Yuanjing</creatorcontrib><creatorcontrib>Laukka, Erika J.</creatorcontrib><creatorcontrib>Dekhtyar, Serhiy</creatorcontrib><creatorcontrib>Papenberg, Goran</creatorcontrib><creatorcontrib>Speh, Andreja</creatorcontrib><creatorcontrib>Fratiglioni, Laura</creatorcontrib><creatorcontrib>Kalpouzos, Grégoria</creatorcontrib><creatorcontrib>Qiu, Chengxuan</creatorcontrib><title>Association Between Behavioral, Biological, and Genetic Markers of Cardiovascular Health and MRI Markers of Brain Aging: A Cohort Study</title><title>Neurology</title><addtitle>Neurology</addtitle><description>The life's simple 7 approach was proposed to define cardiovascular health (CVH) metrics. We sought to investigate the associations between behavioral, biological, and genetic markers for CVH and vascular brain aging in older adults.
This population-based cohort study included participants who had repeated brain MRI measures from 2001 to 2003 to 2007-2010 (i.e., count of perivascular spaces, volumes of white matter hyperintensity [WMH] and gray matter, and lacunes). At baseline, global, behavioral, and biological CVH metrics were defined and scored following the life's simple 7 approach and categorized into unfavorable, intermediate, and favorable profiles according to tertiles. The metabolic genetic risk score was calculated by counting 15 risk alleles associated with hypertension, diabetes, or dyslipidemia. Data were analyzed using linear mixed-effects and Cox proportional hazards models, adjusting for age, sex, and education.
The study sample consisted of 317 participants (age 60 years or older; 61.8% women). Favorable and intermediate (vs unfavorable) global CVH profiles were related to slower WMH progression, with β-coefficients (95% CI) being -0.019(-0.035-0.002) and -0.018(-0.034-0.001), respectively. Favorable and intermediate (vs unfavorable) biological CVH profiles were significantly related to slower WMH increase only in people aged 60-72 years. CVH profiles were not related to progression of other brain measures. Furthermore, a higher metabolic genetic risk score (range: 6-21) was associated with faster WMH increase (β-coefficient = 0.005; 95% CI: 0.003-0.008). There were statistical interactions of metabolic genetic risk score with global and behavioral CVH profiles on WMH accumulation. A higher metabolic genetic risk score was related to faster WMH accumulation, with β-coefficients being 0.015(0.007-0.023), 0.005(0.001-0.009), and 0.003(-0.001 to 0.006) among people with unfavorable, intermediate, and favorable global CVH profiles, respectively; the corresponding β-coefficients were 0.013(0.006-0.020), 0.006(0.003-0.009), and 0.002(-0.002 to 0.006) among people with unfavorable, intermediate, and favorable behavioral CVH profiles.
Intermediate to favorable global CVH profiles in older adults are associated with slower vascular brain aging. The association of metabolic genetic risk load with accelerated vascular brain aging was evident among people with unfavorable to intermediate, but not favorable, CVH profiles. These findings highlight the importance of adhering to favorable CVH profiles, especially healthy behaviors, in vascular brain health.</description><subject>Aged</subject><subject>Aging - genetics</subject><subject>Brain - diagnostic imaging</subject><subject>Cardiovascular Diseases - diagnostic imaging</subject><subject>Cardiovascular Diseases - genetics</subject><subject>Cohort Studies</subject><subject>Female</subject><subject>Genetic Markers</subject><subject>Health Status</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Medicin och hälsovetenskap</subject><subject>Risk Factors</subject><issn>0028-3878</issn><issn>1526-632X</issn><issn>1526-632X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>D8T</sourceid><recordid>eNp1kl1v0zAUhiMEYmXjHyDkSy6W4a_ENhdIbYFtUsckvu8sJzlpTdO42Emr_QL-Nu7Hug1pvjnW8fO-x5bfJHlF8BmhhL79-Xlyhg-LYsJ4_iQZkIzmac7or6fJILZlyqSQR8mLEH5jHA-Fep4csZwRRQgeJH-HIbjSms66Fo2gWwNs6sysrPOmOUUj6xo3teVmb9oKnUMLnS3RlfFz8AG5Go2Nr6xbmVD2jfHoAkzTzbbw1ZfL--DIG9ui4dS203doiMZu5nyHvnZ9dXOSPKtNE-Dlvh4n3z99_Da-SCfX55fj4SQtuSQy5XUpigxzEd8r8lIoQ5WsAbAUuIACy5rUQKDIlckLDCoXFSjgtCKCY8gUO07SnW9Yw7Iv9NLbhfE32hmr96153IHmXEkhIq8e5ZfeVXeiWyHJSCYynMmoPX1U-8H-GGrnpzr0mhLOxAZ_v8Mju4CqhLaLP_Bw4oOT1s701K20klQQhqPBm72Bd396CJ1e2FBC05gWXB80FYxwmnOeRZTv0NK7EDzUhzEE6028dIyX_j9eUfb6_hUPots83fmuXdPFX583_Rq8nm0jsfXLCeEpxZThiOM0dohk_wA3-905</recordid><startdate>20230103</startdate><enddate>20230103</enddate><creator>Li, Yuanjing</creator><creator>Laukka, Erika J.</creator><creator>Dekhtyar, Serhiy</creator><creator>Papenberg, Goran</creator><creator>Speh, Andreja</creator><creator>Fratiglioni, Laura</creator><creator>Kalpouzos, Grégoria</creator><creator>Qiu, Chengxuan</creator><general>Lippincott Williams & Wilkins</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>7X8</scope><scope>5PM</scope><scope>ABAVF</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>DG7</scope><scope>ZZAVC</scope><orcidid>https://orcid.org/0000-0002-1525-5538</orcidid></search><sort><creationdate>20230103</creationdate><title>Association Between Behavioral, Biological, and Genetic Markers of Cardiovascular Health and MRI Markers of Brain Aging: A Cohort Study</title><author>Li, Yuanjing ; Laukka, Erika J. ; Dekhtyar, Serhiy ; Papenberg, Goran ; Speh, Andreja ; Fratiglioni, Laura ; Kalpouzos, Grégoria ; Qiu, Chengxuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4818-4fc7b504720176c79a298fee0870beb08f1fe1eb69a6b0e967de9e42d1740e593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aged</topic><topic>Aging - genetics</topic><topic>Brain - diagnostic imaging</topic><topic>Cardiovascular Diseases - diagnostic imaging</topic><topic>Cardiovascular Diseases - genetics</topic><topic>Cohort Studies</topic><topic>Female</topic><topic>Genetic Markers</topic><topic>Health Status</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Medicin och hälsovetenskap</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Yuanjing</creatorcontrib><creatorcontrib>Laukka, Erika J.</creatorcontrib><creatorcontrib>Dekhtyar, Serhiy</creatorcontrib><creatorcontrib>Papenberg, Goran</creatorcontrib><creatorcontrib>Speh, Andreja</creatorcontrib><creatorcontrib>Fratiglioni, Laura</creatorcontrib><creatorcontrib>Kalpouzos, Grégoria</creatorcontrib><creatorcontrib>Qiu, Chengxuan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Stockholms universitet full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Stockholms universitet</collection><collection>SwePub Articles full text</collection><jtitle>Neurology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Yuanjing</au><au>Laukka, Erika J.</au><au>Dekhtyar, Serhiy</au><au>Papenberg, Goran</au><au>Speh, Andreja</au><au>Fratiglioni, Laura</au><au>Kalpouzos, Grégoria</au><au>Qiu, Chengxuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Association Between Behavioral, Biological, and Genetic Markers of Cardiovascular Health and MRI Markers of Brain Aging: A Cohort Study</atitle><jtitle>Neurology</jtitle><addtitle>Neurology</addtitle><date>2023-01-03</date><risdate>2023</risdate><volume>100</volume><issue>1</issue><spage>e38</spage><epage>e48</epage><pages>e38-e48</pages><issn>0028-3878</issn><issn>1526-632X</issn><eissn>1526-632X</eissn><abstract>The life's simple 7 approach was proposed to define cardiovascular health (CVH) metrics. We sought to investigate the associations between behavioral, biological, and genetic markers for CVH and vascular brain aging in older adults.
This population-based cohort study included participants who had repeated brain MRI measures from 2001 to 2003 to 2007-2010 (i.e., count of perivascular spaces, volumes of white matter hyperintensity [WMH] and gray matter, and lacunes). At baseline, global, behavioral, and biological CVH metrics were defined and scored following the life's simple 7 approach and categorized into unfavorable, intermediate, and favorable profiles according to tertiles. The metabolic genetic risk score was calculated by counting 15 risk alleles associated with hypertension, diabetes, or dyslipidemia. Data were analyzed using linear mixed-effects and Cox proportional hazards models, adjusting for age, sex, and education.
The study sample consisted of 317 participants (age 60 years or older; 61.8% women). Favorable and intermediate (vs unfavorable) global CVH profiles were related to slower WMH progression, with β-coefficients (95% CI) being -0.019(-0.035-0.002) and -0.018(-0.034-0.001), respectively. Favorable and intermediate (vs unfavorable) biological CVH profiles were significantly related to slower WMH increase only in people aged 60-72 years. CVH profiles were not related to progression of other brain measures. Furthermore, a higher metabolic genetic risk score (range: 6-21) was associated with faster WMH increase (β-coefficient = 0.005; 95% CI: 0.003-0.008). There were statistical interactions of metabolic genetic risk score with global and behavioral CVH profiles on WMH accumulation. A higher metabolic genetic risk score was related to faster WMH accumulation, with β-coefficients being 0.015(0.007-0.023), 0.005(0.001-0.009), and 0.003(-0.001 to 0.006) among people with unfavorable, intermediate, and favorable global CVH profiles, respectively; the corresponding β-coefficients were 0.013(0.006-0.020), 0.006(0.003-0.009), and 0.002(-0.002 to 0.006) among people with unfavorable, intermediate, and favorable behavioral CVH profiles.
Intermediate to favorable global CVH profiles in older adults are associated with slower vascular brain aging. The association of metabolic genetic risk load with accelerated vascular brain aging was evident among people with unfavorable to intermediate, but not favorable, CVH profiles. These findings highlight the importance of adhering to favorable CVH profiles, especially healthy behaviors, in vascular brain health.</abstract><cop>United States</cop><pub>Lippincott Williams & Wilkins</pub><pmid>36319110</pmid><doi>10.1212/WNL.0000000000201346</doi><orcidid>https://orcid.org/0000-0002-1525-5538</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Aging - genetics Brain - diagnostic imaging Cardiovascular Diseases - diagnostic imaging Cardiovascular Diseases - genetics Cohort Studies Female Genetic Markers Health Status Humans Magnetic Resonance Imaging Male Medicin och hälsovetenskap Risk Factors |
title | Association Between Behavioral, Biological, and Genetic Markers of Cardiovascular Health and MRI Markers of Brain Aging: A Cohort Study |
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