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Metabolic Profiling of Cognitive Aging in Midlife
Alzheimer's dementia (AD) begins many years before its clinical symptoms. Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic pr...
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Published in: | Frontiers in aging neuroscience 2020-11, Vol.12, p.555850-555850 |
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description | Alzheimer's dementia (AD) begins many years before its clinical symptoms. Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife. |
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Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife.</description><identifier>ISSN: 1663-4365</identifier><identifier>EISSN: 1663-4365</identifier><identifier>DOI: 10.3389/fnagi.2020.555850</identifier><identifier>PMID: 33250761</identifier><language>eng</language><publisher>Switzerland: Frontiers Research Foundation</publisher><subject>Aging ; Alzheimer's disease ; Brain research ; Cognitive ability ; cognitive change ; Dementia ; Dementia disorders ; Enrollments ; Executive function ; Memory ; Metabolism ; Metabolites ; Metabolomics ; Middle age ; Neurodegenerative diseases ; Neuroscience ; Older people ; Risk factors ; Sphingomyelin ; Twin studies ; Twins ; untargeted metabolomics ; White people</subject><ispartof>Frontiers in aging neuroscience, 2020-11, Vol.12, p.555850-555850</ispartof><rights>Copyright © 2020 Huo, Rana, Elman, Dong, Engelman, Johnson, Lyons, Franz, Kremen and Zhao.</rights><rights>2020. 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>Copyright © 2020 Huo, Rana, Elman, Dong, Engelman, Johnson, Lyons, Franz, Kremen and Zhao. 2020 Huo, Rana, Elman, Dong, Engelman, Johnson, Lyons, Franz, Kremen and Zhao</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c493t-45cee02068bf06c3ee7c5bf0f8b6d3ea10eeee11b240d997ac77a73305a8795b3</citedby><cites>FETCH-LOGICAL-c493t-45cee02068bf06c3ee7c5bf0f8b6d3ea10eeee11b240d997ac77a73305a8795b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2457798795/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2457798795?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,25734,27905,27906,36993,36994,44571,53772,53774,74875</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33250761$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Huo, Zhiguang</creatorcontrib><creatorcontrib>Rana, Brinda K</creatorcontrib><creatorcontrib>Elman, Jeremy A</creatorcontrib><creatorcontrib>Dong, Ruocheng</creatorcontrib><creatorcontrib>Engelman, Corinne D</creatorcontrib><creatorcontrib>Johnson, Sterling C</creatorcontrib><creatorcontrib>Lyons, Michael J</creatorcontrib><creatorcontrib>Franz, Carol E</creatorcontrib><creatorcontrib>Kremen, William S</creatorcontrib><creatorcontrib>Zhao, Jinying</creatorcontrib><title>Metabolic Profiling of Cognitive Aging in Midlife</title><title>Frontiers in aging neuroscience</title><addtitle>Front Aging Neurosci</addtitle><description>Alzheimer's dementia (AD) begins many years before its clinical symptoms. Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife.</description><subject>Aging</subject><subject>Alzheimer's disease</subject><subject>Brain research</subject><subject>Cognitive ability</subject><subject>cognitive change</subject><subject>Dementia</subject><subject>Dementia disorders</subject><subject>Enrollments</subject><subject>Executive function</subject><subject>Memory</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Middle age</subject><subject>Neurodegenerative diseases</subject><subject>Neuroscience</subject><subject>Older people</subject><subject>Risk factors</subject><subject>Sphingomyelin</subject><subject>Twin studies</subject><subject>Twins</subject><subject>untargeted metabolomics</subject><subject>White people</subject><issn>1663-4365</issn><issn>1663-4365</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkU1LAzEQhoMoKtUf4EUWvHhpTTafexGk-AUWPeg5JNnJmrLd1Oy24L83tSrqXDJM3nmYmRehE4InlKrqwnemCZMSl3jCOVcc76BDIgQdMyr47q_8AB33_RznoBRjrvbRAaUlx1KQQ0RmMBgb2-CKpxR9aEPXFNEX09h0YQhrKK6aTSl0xSzUbfBwhPa8aXs4_npH6OXm-nl6N354vL2fXj2MHavoMGbcAeThhLIeC0cBpOM59cqKmoIhGHIQYkuG66qSxklpZJ6QGyUrbukI3W-5dTRzvUxhYdK7jiboz0JMjTZpCK4FXVeeWwGq9MIy4oURGWqVJCXzNbcusy63rOXKLqB20A3JtH-gf3-68KqbuNZSSEaEyoDzL0CKbyvoB70IvYO2NR3EVa9LJrjkgqkyS8_-Sedxlbp8qqziUlab9bKKbFUuxb5P4H-GIVhv_NWf_uqNv3rrb-45_b3FT8e3m_QDNW6guA</recordid><startdate>20201105</startdate><enddate>20201105</enddate><creator>Huo, Zhiguang</creator><creator>Rana, Brinda K</creator><creator>Elman, Jeremy A</creator><creator>Dong, Ruocheng</creator><creator>Engelman, Corinne D</creator><creator>Johnson, Sterling C</creator><creator>Lyons, Michael J</creator><creator>Franz, Carol E</creator><creator>Kremen, William S</creator><creator>Zhao, Jinying</creator><general>Frontiers Research Foundation</general><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88I</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>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20201105</creationdate><title>Metabolic Profiling of Cognitive Aging in Midlife</title><author>Huo, Zhiguang ; 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Metabolic dysfunction represents a core feature of AD and cognitive impairment, but few metabolomic studies have focused on cognitive aging in midlife. Using an untargeted metabolomics approach, we identified metabolic predictors of cognitive aging in midlife using fasting plasma sample from 30 middle-aged (mean age 57.2), male-male twin pairs enrolled in the Vietnam Era Twin Study of Aging (VETSA). For all twin pairs, one twin developed incident MCI, whereas his co-twin brother remained to be cognitively normal during an average 5.5-year follow-up. Linear mixed model was used to identify metabolites predictive of MCI conversion or cognitive change over time, adjusting for traditional risk factors. Results from twins were replicated in an independent cohort of middle-aged adults (mean age 59.1) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Results in twins showed that higher baseline levels of four plasma metabolites, including sphingomyelin (d18:1/20:1 and d18:2/20:0), sphingomyelin (d18:1/22:1, d18:2/22:0, and d16:1/24:1), DAG (18:2/20:4), and hydroxy-CMPF, were significantly associated with a slower decrease in one or more domains of cognitive function. The association of sphingomyelin (d18:1/20:1 and d18:2/20:0) was replicated in WRAP. Our results support that metabolic perturbation occurs many years before cognitive impairment and plasma metabolites may serve as early biomarkers for prediction or monitoring of cognitive aging and AD in midlife.</abstract><cop>Switzerland</cop><pub>Frontiers Research Foundation</pub><pmid>33250761</pmid><doi>10.3389/fnagi.2020.555850</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aging Alzheimer's disease Brain research Cognitive ability cognitive change Dementia Dementia disorders Enrollments Executive function Memory Metabolism Metabolites Metabolomics Middle age Neurodegenerative diseases Neuroscience Older people Risk factors Sphingomyelin Twin studies Twins untargeted metabolomics White people |
title | Metabolic Profiling of Cognitive Aging in Midlife |
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