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

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 ar...

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Autores principales: Strawbridge, Rona J., Johnston, Keira J. A., Bailey, Mark E. S., Baldassarre, Damiano, Cullen, Breda, Eriksson, Per, deFaire, Ulf, Ferguson, Amy, Gigante, Bruna, Giral, Philippe, Graham, Nicholas, Hamsten, Anders, Humphries, Steve E., Kurl, Sudhir, Lyall, Donald M., Lyall, Laura M., Pell, Jill P., Pirro, Matteo, Savonen, Kai, Smit, Andries J., Tremoli, Elena, Tomainen, Tomi-Pekka, Veglia, Fabrizio, Ward, Joey, Sennblad, Bengt, Smith, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804422/
https://www.ncbi.nlm.nih.gov/pubmed/33436761
http://dx.doi.org/10.1038/s41598-020-79964-x
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author Strawbridge, Rona J.
Johnston, Keira J. A.
Bailey, Mark E. S.
Baldassarre, Damiano
Cullen, Breda
Eriksson, Per
deFaire, Ulf
Ferguson, Amy
Gigante, Bruna
Giral, Philippe
Graham, Nicholas
Hamsten, Anders
Humphries, Steve E.
Kurl, Sudhir
Lyall, Donald M.
Lyall, Laura M.
Pell, Jill P.
Pirro, Matteo
Savonen, Kai
Smit, Andries J.
Tremoli, Elena
Tomainen, Tomi-Pekka
Veglia, Fabrizio
Ward, Joey
Sennblad, Bengt
Smith, Daniel J.
author_facet Strawbridge, Rona J.
Johnston, Keira J. A.
Bailey, Mark E. S.
Baldassarre, Damiano
Cullen, Breda
Eriksson, Per
deFaire, Ulf
Ferguson, Amy
Gigante, Bruna
Giral, Philippe
Graham, Nicholas
Hamsten, Anders
Humphries, Steve E.
Kurl, Sudhir
Lyall, Donald M.
Lyall, Laura M.
Pell, Jill P.
Pirro, Matteo
Savonen, Kai
Smit, Andries J.
Tremoli, Elena
Tomainen, Tomi-Pekka
Veglia, Fabrizio
Ward, Joey
Sennblad, Bengt
Smith, Daniel J.
author_sort Strawbridge, Rona J.
collection PubMed
description 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.
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spelling pubmed-78044222021-01-13 The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals Strawbridge, Rona J. Johnston, Keira J. A. Bailey, Mark E. S. Baldassarre, Damiano Cullen, Breda Eriksson, Per deFaire, Ulf Ferguson, Amy Gigante, Bruna Giral, Philippe Graham, Nicholas Hamsten, Anders Humphries, Steve E. Kurl, Sudhir Lyall, Donald M. Lyall, Laura M. Pell, Jill P. Pirro, Matteo Savonen, Kai Smit, Andries J. Tremoli, Elena Tomainen, Tomi-Pekka Veglia, Fabrizio Ward, Joey Sennblad, Bengt Smith, Daniel J. Sci Rep Article 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. Nature Publishing Group UK 2021-01-12 /pmc/articles/PMC7804422/ /pubmed/33436761 http://dx.doi.org/10.1038/s41598-020-79964-x Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Strawbridge, Rona J.
Johnston, Keira J. A.
Bailey, Mark E. S.
Baldassarre, Damiano
Cullen, Breda
Eriksson, Per
deFaire, Ulf
Ferguson, Amy
Gigante, Bruna
Giral, Philippe
Graham, Nicholas
Hamsten, Anders
Humphries, Steve E.
Kurl, Sudhir
Lyall, Donald M.
Lyall, Laura M.
Pell, Jill P.
Pirro, Matteo
Savonen, Kai
Smit, Andries J.
Tremoli, Elena
Tomainen, Tomi-Pekka
Veglia, Fabrizio
Ward, Joey
Sennblad, Bengt
Smith, Daniel J.
The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
title 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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804422/
https://www.ncbi.nlm.nih.gov/pubmed/33436761
http://dx.doi.org/10.1038/s41598-020-79964-x
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