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Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9

Published online by Cambridge University Press:  18 September 2019

Jackson G. Thorp Open the ORCID record for Jackson G. Thorp [Opens in a new window] ,
Andries T. Marees ,
Jue-Sheng Ong ,
Jiyuan An ,
Stuart MacGregor  and
Eske M. Derks
Jackson G. Thorp*
Affiliation:
Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Andries T. Marees
Affiliation:
Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
Jue-Sheng Ong
Affiliation:
Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Jiyuan An
Affiliation:
Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Stuart MacGregor
Affiliation:
Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Eske M. Derks
Affiliation:
Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
*
Author for correspondence: Jackson G. Thorp, E-mail: [email protected] and Eske M. Derks, E-mail: [email protected]
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Abstract

Background

Depression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case–control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity.

Methods

We analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms.

Results

We identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10−3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing ‘psychological’ and ‘somatic’ symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms.

Conclusions

Patterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.

Keywords

Depressiondepressive symptomsgenetic heterogeneityGWASPHQ-9
Type
Original Articles
Information
Psychological Medicine , Volume 50 , Issue 14 , October 2020 , pp. 2385 - 2396
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Copyright
Copyright © Cambridge University Press 2019

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