The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

Abstract Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic d...

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Autores principales:	Rona J. Strawbridge, Keira J. A. Johnston, Mark E. S. Bailey, Damiano Baldassarre, Breda Cullen, Per Eriksson, Ulf deFaire, Amy Ferguson, Bruna Gigante, Philippe Giral, Nicholas Graham, Anders Hamsten, Steve E. Humphries, Sudhir Kurl, Donald M. Lyall, Laura M. Lyall, Jill P. Pell, Matteo Pirro, Kai Savonen, Andries J. Smit, Elena Tremoli, Tomi-Pekka Tomainen, Fabrizio Veglia, Joey Ward, Bengt Sennblad, Daniel J. Smith
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7e59d46ec2fd4250ae99b8ac5242f619
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spelling	oai:doaj.org-article:7e59d46ec2fd4250ae99b8ac5242f6192021-12-02T14:12:43ZThe overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals10.1038/s41598-020-79964-x2045-2322https://doaj.org/article/7e59d46ec2fd4250ae99b8ac5242f6192021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79964-xhttps://doaj.org/toc/2045-2322Abstract Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.Rona J. StrawbridgeKeira J. A. JohnstonMark E. S. BaileyDamiano BaldassarreBreda CullenPer ErikssonUlf deFaireAmy FergusonBruna GigantePhilippe GiralNicholas GrahamAnders HamstenSteve E. HumphriesSudhir KurlDonald M. LyallLaura M. LyallJill P. PellMatteo PirroKai SavonenAndries J. SmitElena TremoliTomi-Pekka TomainenFabrizio VegliaJoey WardBengt SennbladDaniel J. SmithNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rona J. Strawbridge Keira J. A. Johnston Mark E. S. Bailey Damiano Baldassarre Breda Cullen Per Eriksson Ulf deFaire Amy Ferguson Bruna Gigante Philippe Giral Nicholas Graham Anders Hamsten Steve E. Humphries Sudhir Kurl Donald M. Lyall Laura M. Lyall Jill P. Pell Matteo Pirro Kai Savonen Andries J. Smit Elena Tremoli Tomi-Pekka Tomainen Fabrizio Veglia Joey Ward Bengt Sennblad Daniel J. Smith The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
description	Abstract Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.
format	article
author	Rona J. Strawbridge Keira J. A. Johnston Mark E. S. Bailey Damiano Baldassarre Breda Cullen Per Eriksson Ulf deFaire Amy Ferguson Bruna Gigante Philippe Giral Nicholas Graham Anders Hamsten Steve E. Humphries Sudhir Kurl Donald M. Lyall Laura M. Lyall Jill P. Pell Matteo Pirro Kai Savonen Andries J. Smit Elena Tremoli Tomi-Pekka Tomainen Fabrizio Veglia Joey Ward Bengt Sennblad Daniel J. Smith
author_facet	Rona J. Strawbridge Keira J. A. Johnston Mark E. S. Bailey Damiano Baldassarre Breda Cullen Per Eriksson Ulf deFaire Amy Ferguson Bruna Gigante Philippe Giral Nicholas Graham Anders Hamsten Steve E. Humphries Sudhir Kurl Donald M. Lyall Laura M. Lyall Jill P. Pell Matteo Pirro Kai Savonen Andries J. Smit Elena Tremoli Tomi-Pekka Tomainen Fabrizio Veglia Joey Ward Bengt Sennblad Daniel J. Smith
author_sort	Rona J. Strawbridge
title	The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title_short	The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title_full	The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title_fullStr	The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title_full_unstemmed	The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title_sort	overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7e59d46ec2fd4250ae99b8ac5242f619
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The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

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