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Title: | Symptom-level modelling unravels the shared genetic architecture of anxiety and depression | Authors: | Derks, Eske M. An, Jiyuan Ong, Jue-Sheng Wang, Wei Shringarpure, Suyash Byrne, Enda M. MacGregor, Stuart Martin, Nicholas G. Medland, Sarah E. Middeldorp, Christel M. Thorp, Jackson G. Campos, Adrian I. Grotzinger, Andrew D. Gerring, Zachary F. |
Issue Date: | 2021 | Source: | 5, (10), 2021, p. 1432-1442 | Pages: | 1432-1442 | Journal: | Nature human behaviour | Abstract: | Depression and anxiety are highly prevalent and comorbid psychiatric traits that cause considerable burden worldwide. Here we use factor analysis and genomic structural equation modelling to investigate the genetic factor structure underlying 28 items assessing depression, anxiety and neuroticism, a closely related personality trait. Symptoms of depression and anxiety loaded on two distinct, although highly genetically correlated factors, and neuroticism items were partitioned between them. We used this factor structure to conduct genome-wide association analyses on latent factors of depressive symptoms (89 independent variants, 61 genomic loci) and anxiety symptoms (102 variants, 73 loci) in the UK Biobank. Of these associated variants, 72% and 78%, respectively, replicated in an independent cohort of approximately 1.9 million individuals with self-reported diagnosis of depression and anxiety. We use these results to characterize shared and trait-specific genetic associations. Our findings provide insight into the genetic architecture of depression and anxiety and comorbidity between them. (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)Depression and Other Common Mental Disorders: Global Health Estimates (World Health Organization, 2017).; Lamers, F. et al. Comorbidity patterns of anxiety and depressive disorders in a large cohort study: the Netherlands study of depression and anxiety (NESDA). J. Clin. Psychiatry 72, 341–348 (2011). (PMID: 21294994); Hettema, J. M., Neale, M. C. & Kendler, K. S. A review and meta-analysis of the genetic epidemiology of anxiety disorders. Am. J. Psychiatry 158, 1568–1578 (2001). (PMID: 11578982); Sullivan, P. F., Neale, M. 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Subset: MEDLINE; Grant Information: MC_PC_17228 United Kingdom MRC_ Medical Research Council; MC_QA137853 United Kingdom MRC_ Medical Research Council Date of Electronic Publication: 2021 Apr 15. ; Original Imprints: Publication: [London] : Springer Nature Publishing, [2017]- | DOI: | 10.1038/s41562-021-01094-9 | Resources: | https://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,athens&db=mdc&AN=33859377&site=ehost-live | Keywords: | Depression*/epidemiology;Depression*/genetics;Neuroticism/*physiology;Comorbidity;Factor Analysis, Statistical;Genetic Predisposition to Disease;Genome-Wide Association Study;Anxiety*/genetics;Latent Class Analysis;Symptom Assessment/methods;Symptom Assessment/statistics & numerical data;Anxiety*/diagnosisAnxiety*/epidemiology;Humans;Behavioral Symptoms*/diagnosis;Behavioral Symptoms*/psychology;Depression*/diagnosis | Type: | Article |
Appears in Sites: | Children's Health Queensland Publications |
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