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

Eleanor Wigmore (Lead Author), Jonathan Hafferty, Lynsey Hall, David M. Howard, Toni-Kim Clarke, Chiara Fabbri, Cathryn M. Lewis, Rudolf Uher, Lauren Navrady, Mark James Adams, Yanni Zeng, Archibald Campbell, Jude Gibson, Philippa Thomson, Caroline Hayward, Blair H Smith, Lynne J. Hocking, Sandosh Padmanabhan, Ian Deary, David PorteousOle Mors, Manuel Mattheisen, Kristin Nicodemus, Andrew McIntosh

Research output: Contribution to journalArticlepeer-review

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=4,213, cases=358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n=3,452). 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.
Original languageEnglish
JournalPharmacogenomics Journal
DOIs
Publication statusPublished - 31 Jan 2019

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