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Polygenic Risk Scores Derived From Varying Definitions of Depression and Risk of Depression.
Mitchell, Brittany L; Thorp, Jackson G; Wu, Yeda; Campos, Adrian I; Nyholt, Dale R; Gordon, Scott D; Whiteman, David C; Olsen, Catherine M; Hickie, Ian B; Martin, Nicholas G; Medland, Sarah E; Wray, Naomi R; Byrne, Enda M.
Afiliación
  • Mitchell BL; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Thorp JG; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia.
  • Wu Y; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Campos AI; Faculty of Medicine, The University of Queensland, Brisbane, Australia.
  • Nyholt DR; Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
  • Gordon SD; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Whiteman DC; Faculty of Medicine, The University of Queensland, Brisbane, Australia.
  • Olsen CM; School of Biomedical Sciences, The University of Queensland, Brisbane, Australia.
  • Hickie IB; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia.
  • Martin NG; Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Australia.
  • Medland SE; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Wray NR; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Byrne EM; QIMR Berghofer Medical Research Institute, Brisbane, Australia.
JAMA Psychiatry ; 78(10): 1152-1160, 2021 10 01.
Article en En | MEDLINE | ID: mdl-34379077
ABSTRACT
Importance Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies.

Objective:

To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). Design, Setting, and

Participants:

In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. Main Outcome and

Measures:

Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health.

Results:

Participants included 12 106 (71% female; mean age, 42.3 years; range, 18-88 years) patients meeting criteria for MDD and 12 621 (55% female; mean age, 60.9 years; range, 43-87 years) control participants with no history of psychiatric disorders. The effect size of the PRS was proportional to the discovery sample size, with the largest study having the largest effect size with the odds ratio for MDD (1.75; 95% CI, 1.73-1.77) per SD of PRS and the PRS derived from ICD-10 codes documented in hospitalization records in a population health cohort having the lowest odds ratio (1.14; 95% CI, 1.12-1.16). When accounting for differences in sample size, the PRS from a genome-wide association study of patients meeting diagnostic criteria for MDD and control participants was the best estimator of MDD, but not in those with self-reported depression, and associations with higher odds ratios with childhood adverse experiences and measures of somatic distress. Conclusions and Relevance These findings suggest that increasing sample sizes, regardless of the depth of phenotyping, may be most informative for estimating risk of depression. The next generation of genome-wide association studies should, like the Australian Genetics of Depression Study, have both large sample sizes and extensive phenotyping to capture genetic risk factors for MDD not identified by other definitions of depression.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Herencia Multifactorial / Trastorno Depresivo Mayor / Estudio de Asociación del Genoma Completo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Psychiatry Año: 2021 Tipo del documento: Article País de afiliación: Australia Pais de publicación: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Herencia Multifactorial / Trastorno Depresivo Mayor / Estudio de Asociación del Genoma Completo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Psychiatry Año: 2021 Tipo del documento: Article País de afiliación: Australia Pais de publicación: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA