Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP

Wigmore, E. M. et al. (2020) Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP. Pharmacogenomics Journal, 20, pp. 329-341. (doi: 10.1038/s41397-019-0067-3) (PMID:30700811) (PMCID:PMC7096334)

Abstract

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power.

• Item Type: Articles
• Additional Information: This investigation was supported by the Wellcome Trust 104036/Z/14/Z (STRADL, Stratifying Resilience and Depression Longitudinally). Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6 and the Scottish Funding Council HR03006. We are grateful to the Sackler Foundation for the generous support of this work. IJD is supported by MRC and BBSRC funding to the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (MR/K026992/1).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Padmanabhan, Professor Sandosh
• Authors: Wigmore, E. M., Hafferty, J. D., Hall, L. S., Howard, D. M., Clarke, T.-K., Fabbri, C., Lewis, C. M., Uher, R., Navrady, L. B., Adams, M. J., Zeng, Y., Campbell, A., Gibson, J., Thomson, P. A., Hayward, C., Smith, B. H., Hocking, L. J., Padmanabhan, S., Deary, I. J., Porteous, D. J., Mors, O., Mattheisen, M., Nicodemus, K. K., and McIntosh, A. M.
• College/School: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
• Journal Name: Pharmacogenomics Journal
• Publisher: Nature Publishing Group
• ISSN: 1470-269X
• ISSN (Online): 1473-1150
• Published Online: 31 January 2019
• Copyright Holders: Copyright © 2019 The Authors
• First Published: First published in Pharmacogenomics Journal 20:329-341
• Publisher Policy: Reproduced under a Creative Commons License