The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
12 01 2021
12 01 2021
Historique:
received:
24
06
2020
accepted:
11
12
2020
entrez:
13
1
2021
pubmed:
14
1
2021
medline:
11
8
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33436761
doi: 10.1038/s41598-020-79964-x
pii: 10.1038/s41598-020-79964-x
pmc: PMC7804422
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
632Subventions
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S003061/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_17217
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Références
Genome Biol Evol. 2019 Apr 1;11(4):1066-1076
pubmed: 30895295
Nat Genet. 2018 May;50(5):668-681
pubmed: 29700475
Nature. 2014 Jul 24;511(7510):421-7
pubmed: 25056061
J Am Coll Cardiol. 2012 Oct 16;60(16):1489-99
pubmed: 22999719
Nat Genet. 2011 Nov 06;43(12):1193-201
pubmed: 22057235
Psychol Med. 2019 Jun;49(8):1286-1298
pubmed: 30045777
PLoS Genet. 2012;8(8):e1002793
pubmed: 22876189
Am J Hum Genet. 2007 Sep;81(3):559-75
pubmed: 17701901
PLoS Med. 2015 Mar 31;12(3):e1001779
pubmed: 25826379
JAMA Psychiatry. 2017 Dec 1;74(12):1214-1225
pubmed: 29049554
Mol Psychiatry. 2020 Jul;25(7):1469-1476
pubmed: 31427754
Transl Psychiatry. 2017 Jan 24;7(1):e1007
pubmed: 28117839
Cell. 2019 Oct 17;179(3):589-603
pubmed: 31607513
Biol Psychiatry. 2017 May 1;81(9):807-814
pubmed: 26742925
World Psychiatry. 2011 Feb;10(1):52-77
pubmed: 21379357
Diabetologia. 2020 Jul;63(7):1305-1311
pubmed: 32270255
Eur Heart J. 2010 Mar;31(5):614-22
pubmed: 19952003
Nature. 2018 Oct;562(7726):203-209
pubmed: 30305743
Am J Epidemiol. 2017 Nov 1;186(9):1026-1034
pubmed: 28641372
Nat Genet. 2019 May;51(5):793-803
pubmed: 31043756
Nat Commun. 2019 Jan 21;10(1):358
pubmed: 30664655
Brain. 2015 Dec;138(Pt 12):3463-5
pubmed: 26598488