TY - JOUR
T1 - Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP
AU - Wigmore, Eleanor M
AU - Hafferty, Jonathan D
AU - Hall, Lynsey S
AU - Howard, David M
AU - Clarke, Toni-Kim
AU - Fabbri, Chiara
AU - Lewis, Cathryn M
AU - Uher, Rudolf
AU - Navrady, Lauren B
AU - Adams, Mark J
AU - Zeng, Yanni
AU - Campbell, Archie
AU - Gibson, Jude
AU - Thomson, Pippa A
AU - Hayward, Caroline
AU - Smith, Blair H
AU - Hocking, Lynne J
AU - Padmanabhan, Sandosh
AU - Deary, Ian J
AU - Porteous, David J
AU - Mors, Ole
AU - Mattheisen, Manuel
AU - Nicodemus, Kristin K
AU - McIntosh, Andrew M
PY - 2019/1/31
Y1 - 2019/1/31
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85060909626&partnerID=8YFLogxK
U2 - 10.1038/s41397-019-0067-3
DO - 10.1038/s41397-019-0067-3
M3 - Article
C2 - 30700811
SN - 1470-269X
JO - The pharmacogenomics journal
JF - The pharmacogenomics journal
ER -