Circulating Metabolome and White Matter Hyperintensities in Women and Men

White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. We studi...

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Published in:Circulation (New York, N.Y.) N.Y.), 2022-04, Vol.145 (14), p.1040-1052
Main Authors: Sliz, Eeva, Shin, Jean, Ahmad, Shahzad, Williams, Dylan M., Frenzel, Stefan, Gauß, Friederike, Harris, Sarah E., Henning, Ann-Kristin, Hernandez, Maria Valdes, Hu, Yi-Han, Jiménez, Beatriz, Sargurupremraj, Muralidharan, Sudre, Carole, Wang, Ruiqi, Wittfeld, Katharina, Yang, Qiong, Wardlaw, Joanna M., Völzke, Henry, Vernooij, Meike W., Schott, Jonathan M., Richards, Marcus, Proitsi, Petroula, Nauck, Matthias, Lewis, Matthew R., Launer, Lenore, Hosten, Norbert, Grabe, Hans J., Ghanbari, Mohsen, Deary, Ian J., Cox, Simon R., Chaturvedi, Nishi, Barnes, Josephine, Rotter, Jerome I., Debette, Stephanie, Ikram, M. Arfan, Fornage, Myriam, Paus, Tomas, Seshadri, Sudha, Pausova, Zdenka
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Language:English
Subjects:
Aged
Brain - pathology
Diabetes Mellitus, Type 2 - pathology
Female
Humans
Magnetic Resonance Imaging - methods
Male
Metabolome
Middle Aged
White Matter - diagnostic imaging
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cited_by cdi_FETCH-LOGICAL-c4682-5fe57b36947259d0bd9062f303dcb0a3be3c5b2ae5251e487cb7157ff7ee27a03
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container_issue 14
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container_title Circulation (New York, N.Y.)
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creator Sliz, Eeva
Shin, Jean
Ahmad, Shahzad
Williams, Dylan M.
Frenzel, Stefan
Gauß, Friederike
Harris, Sarah E.
Henning, Ann-Kristin
Hernandez, Maria Valdes
Hu, Yi-Han
Jiménez, Beatriz
Sargurupremraj, Muralidharan
Sudre, Carole
Wang, Ruiqi
Wittfeld, Katharina
Yang, Qiong
Wardlaw, Joanna M.
Völzke, Henry
Vernooij, Meike W.
Schott, Jonathan M.
Richards, Marcus
Proitsi, Petroula
Nauck, Matthias
Lewis, Matthew R.
Launer, Lenore
Hosten, Norbert
Grabe, Hans J.
Ghanbari, Mohsen
Deary, Ian J.
Cox, Simon R.
Chaturvedi, Nishi
Barnes, Josephine
Rotter, Jerome I.
Debette, Stephanie
Ikram, M. Arfan
Fornage, Myriam
Paus, Tomas
Seshadri, Sudha
Pausova, Zdenka
description White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted values ( )
doi_str_mv 10.1161/CIRCULATIONAHA.121.056892
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Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted values ( )&lt;0.05 were considered significant. In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH ( &lt;0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men ( =1.40×10 ) and in both the pooled sample ( =1.66×10 ) and statin-untreated ( =1.65×10 ) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate ( =0.047). Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. 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WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted values ( )&lt;0.05 were considered significant. 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Arfan ; Fornage, Myriam ; Paus, Tomas ; Seshadri, Sudha ; Pausova, Zdenka</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4682-5fe57b36947259d0bd9062f303dcb0a3be3c5b2ae5251e487cb7157ff7ee27a03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aged</topic><topic>Brain - pathology</topic><topic>Diabetes Mellitus, Type 2 - pathology</topic><topic>Female</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Metabolome</topic><topic>Middle Aged</topic><topic>White Matter - diagnostic imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sliz, Eeva</creatorcontrib><creatorcontrib>Shin, Jean</creatorcontrib><creatorcontrib>Ahmad, Shahzad</creatorcontrib><creatorcontrib>Williams, Dylan M.</creatorcontrib><creatorcontrib>Frenzel, Stefan</creatorcontrib><creatorcontrib>Gauß, Friederike</creatorcontrib><creatorcontrib>Harris, Sarah E.</creatorcontrib><creatorcontrib>Henning, Ann-Kristin</creatorcontrib><creatorcontrib>Hernandez, Maria Valdes</creatorcontrib><creatorcontrib>Hu, Yi-Han</creatorcontrib><creatorcontrib>Jiménez, Beatriz</creatorcontrib><creatorcontrib>Sargurupremraj, Muralidharan</creatorcontrib><creatorcontrib>Sudre, Carole</creatorcontrib><creatorcontrib>Wang, Ruiqi</creatorcontrib><creatorcontrib>Wittfeld, Katharina</creatorcontrib><creatorcontrib>Yang, Qiong</creatorcontrib><creatorcontrib>Wardlaw, Joanna M.</creatorcontrib><creatorcontrib>Völzke, Henry</creatorcontrib><creatorcontrib>Vernooij, Meike W.</creatorcontrib><creatorcontrib>Schott, Jonathan M.</creatorcontrib><creatorcontrib>Richards, Marcus</creatorcontrib><creatorcontrib>Proitsi, Petroula</creatorcontrib><creatorcontrib>Nauck, Matthias</creatorcontrib><creatorcontrib>Lewis, Matthew R.</creatorcontrib><creatorcontrib>Launer, Lenore</creatorcontrib><creatorcontrib>Hosten, Norbert</creatorcontrib><creatorcontrib>Grabe, Hans J.</creatorcontrib><creatorcontrib>Ghanbari, Mohsen</creatorcontrib><creatorcontrib>Deary, Ian J.</creatorcontrib><creatorcontrib>Cox, Simon R.</creatorcontrib><creatorcontrib>Chaturvedi, Nishi</creatorcontrib><creatorcontrib>Barnes, Josephine</creatorcontrib><creatorcontrib>Rotter, Jerome I.</creatorcontrib><creatorcontrib>Debette, Stephanie</creatorcontrib><creatorcontrib>Ikram, M. Arfan</creatorcontrib><creatorcontrib>Fornage, Myriam</creatorcontrib><creatorcontrib>Paus, Tomas</creatorcontrib><creatorcontrib>Seshadri, Sudha</creatorcontrib><creatorcontrib>Pausova, Zdenka</creatorcontrib><creatorcontrib>NeuroCHARGE Working Group</creatorcontrib><creatorcontrib>for the NeuroCHARGE Working Group</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><jtitle>Circulation (New York, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sliz, Eeva</au><au>Shin, Jean</au><au>Ahmad, Shahzad</au><au>Williams, Dylan M.</au><au>Frenzel, Stefan</au><au>Gauß, Friederike</au><au>Harris, Sarah E.</au><au>Henning, Ann-Kristin</au><au>Hernandez, Maria Valdes</au><au>Hu, Yi-Han</au><au>Jiménez, Beatriz</au><au>Sargurupremraj, Muralidharan</au><au>Sudre, Carole</au><au>Wang, Ruiqi</au><au>Wittfeld, Katharina</au><au>Yang, Qiong</au><au>Wardlaw, Joanna M.</au><au>Völzke, Henry</au><au>Vernooij, Meike W.</au><au>Schott, Jonathan M.</au><au>Richards, Marcus</au><au>Proitsi, Petroula</au><au>Nauck, Matthias</au><au>Lewis, Matthew R.</au><au>Launer, Lenore</au><au>Hosten, Norbert</au><au>Grabe, Hans J.</au><au>Ghanbari, Mohsen</au><au>Deary, Ian J.</au><au>Cox, Simon R.</au><au>Chaturvedi, Nishi</au><au>Barnes, Josephine</au><au>Rotter, Jerome I.</au><au>Debette, Stephanie</au><au>Ikram, M. Arfan</au><au>Fornage, Myriam</au><au>Paus, Tomas</au><au>Seshadri, Sudha</au><au>Pausova, Zdenka</au><aucorp>NeuroCHARGE Working Group</aucorp><aucorp>for the NeuroCHARGE Working Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Circulating Metabolome and White Matter Hyperintensities in Women and Men</atitle><jtitle>Circulation (New York, N.Y.)</jtitle><addtitle>Circulation</addtitle><date>2022-04-05</date><risdate>2022</risdate><volume>145</volume><issue>14</issue><spage>1040</spage><epage>1052</epage><pages>1040-1052</pages><issn>0009-7322</issn><eissn>1524-4539</eissn><abstract>White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted values ( )&lt;0.05 were considered significant. In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH ( &lt;0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men ( =1.40×10 ) and in both the pooled sample ( =1.66×10 ) and statin-untreated ( =1.65×10 ) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate ( =0.047). Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.</abstract><cop>United States</cop><pub>Lippincott Williams &amp; Wilkins</pub><pmid>35050683</pmid><doi>10.1161/CIRCULATIONAHA.121.056892</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-4658-2176</orcidid><orcidid>https://orcid.org/0000-0002-9812-6642</orcidid><orcidid>https://orcid.org/0000-0002-7784-1380</orcidid><orcidid>https://orcid.org/0000-0003-1684-3750</orcidid><orcidid>https://orcid.org/0000-0001-5087-5970</orcidid><orcidid>https://orcid.org/0000-0003-0677-8158</orcidid><orcidid>https://orcid.org/0000-0003-4593-6075</orcidid><orcidid>https://orcid.org/0000-0001-7191-1723</orcidid><orcidid>https://orcid.org/0000-0002-2587-8587</orcidid><orcidid>https://orcid.org/0000-0002-6894-1320</orcidid><orcidid>https://orcid.org/0000-0002-6211-2775</orcidid><orcidid>https://orcid.org/0000-0002-9476-7143</orcidid><orcidid>https://orcid.org/0000-0003-0372-8585</orcidid><orcidid>https://orcid.org/0000-0002-8658-3790</orcidid><orcidid>https://orcid.org/0000-0003-4383-5043</orcidid><orcidid>https://orcid.org/0000-0002-3238-7612</orcidid><orcidid>https://orcid.org/0000-0002-3658-1375</orcidid><orcidid>https://orcid.org/0000-0002-4941-5106</orcidid><orcidid>https://orcid.org/0000-0001-7353-5178</orcidid><orcidid>https://orcid.org/0000-0001-8675-7968</orcidid><orcidid>https://orcid.org/0000-0003-2771-6546</orcidid><orcidid>https://orcid.org/0000-0001-5753-428X</orcidid><orcidid>https://orcid.org/0000-0003-0882-6563</orcidid><orcidid>https://orcid.org/0000-0002-4149-5666</orcidid><orcidid>https://orcid.org/0000-0002-2316-058X</orcidid><oa>free_for_read</oa></addata></record>
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subjects Aged
Brain - pathology
Diabetes Mellitus, Type 2 - pathology
Female
Humans
Magnetic Resonance Imaging - methods
Male
Metabolome
Middle Aged
White Matter - diagnostic imaging
title Circulating Metabolome and White Matter Hyperintensities in Women and Men
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