Abstract

The diathesis–stress theory for depression states that the effects of stress on the depression risk are dependent on the diathesis or vulnerability, implying multiplicative interactive effects on the liability scale. We used polygenic risk scores for major depressive disorder (MDD) calculated from the results of the most recent analysis from the Psychiatric Genomics Consortium as a direct measure of the vulnerability for depression in a sample of 5221 individuals from 3083 families. In the same we also had measures of stressful life events and social support and a depression symptom score, as well as DSM-IV MDD diagnoses for most individuals. In order to estimate the variance in depression explained by the genetic vulnerability, the stressors and their interactions, we fitted linear mixed models controlling for relatedness for the whole sample as well as stratified by sex. We show a significant interaction of the polygenic risk scores with personal life events (0.12% of variance explained, P-value=0.0076) contributing positively to the risk of depression. Additionally, our results suggest possible differences in the aetiology of depression between women and men. In conclusion, our findings point to an extra risk for individuals with combined vulnerability and high number of reported personal life events beyond what would be expected from the additive contributions of these factors to the liability for depression, supporting the multiplicative diathesis–stress model for this disease.

Details

Title
A direct test of the diathesis–stress model for depression
Author
Colodro-Conde, L 1 ; Couvy-Duchesne, B 2 ; Zhu, G 3 ; Coventry, W L 4 ; Byrne, E M 5 ; Gordon, S 3 ; Wright, M J 6 ; Montgomery, G W 5 ; Madden, P A F 7 ; Ripke, S 8 ; Eaves, L J 9 ; Heath, A C 7 ; Wray, N R 10 ; Medland, S E 3 ; Martin, N G 3 

 Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain 
 Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia 
 Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia 
 School of Behavioural and Social Sciences, University of New England, Armidale, NSW, Australia 
 Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia 
 Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia 
 Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA 
 Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany; Department of Medical and Population Genetics, Broad Institute, Cambridge, MA, USA 
 Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA 
10  Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia 
Pages
1590-1596
Publication year
2018
Publication date
Jul 2018
Publisher
Nature Publishing Group
ISSN
13594184
e-ISSN
14765578
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2091210852
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.