Genome-wide Association Study of Antidepressant Treatment Resistance in a Population-based Cohort Using Health Service Prescription Data and Meta-analysis with GENDEP

Overview

Journal Pharmacogenomics J

Specialties Genetics
Molecular Biology
Pharmacology

Date 2019 Feb 1

PMID 30700811

Citations 27

Authors

Eleanor M Wigmore

Jonathan D Hafferty

Lynsey S Hall

David M Howard

Toni-Kim Clarke

Chiara Fabbri

Cathryn M Lewis

Rudolf Uher

Lauren B Navrady

Mark J Adams

Yanni Zeng

Archie Campbell

Jude Gibson

Pippa A Thomson

Caroline Hayward

Blair H Smith

Lynne J Hocking

Sandosh Padmanabhan

Ian J Deary

David J Porteous

Ole Mors

Manuel Mattheisen

Kristin K Nicodemus

Andrew M McIntosh

Affiliations

Soon will be listed here.

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.

Citing Articles

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Genome-wide meta-analyses of non-response to antidepressants identify novel loci and potential drugs.

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References

Iniesta R, Malki K, Maier W, Rietschel M, Mors O, Hauser J . Combining clinical variables to optimize prediction of antidepressant treatment outcomes. J Psychiatr Res. 2016; 78:94-102. DOI: 10.1016/j.jpsychires.2016.03.016. View

Wang W, Grimmer J, van de Water T, Lufkin T . Hmx2 and Hmx3 homeobox genes direct development of the murine inner ear and hypothalamus and can be functionally replaced by Drosophila Hmx. Dev Cell. 2004; 7(3):439-53. DOI: 10.1016/j.devcel.2004.06.016. View

Nagy R, Boutin T, Marten J, Huffman J, Kerr S, Campbell A . Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants. Genome Med. 2017; 9(1):23. PMC: 5339960. DOI: 10.1186/s13073-017-0414-4. View

Ustun T, Ayuso-Mateos J, Chatterji S, Mathers C, Murray C . Global burden of depressive disorders in the year 2000. Br J Psychiatry. 2004; 184:386-92. DOI: 10.1192/bjp.184.5.386. View

Ruhe H, van Rooijen G, Spijker J, Peeters F, Schene A . Staging methods for treatment resistant depression. A systematic review. J Affect Disord. 2011; 137(1-3):35-45. DOI: 10.1016/j.jad.2011.02.020. View

Menke A, Binder E . Epigenetic alterations in depression and antidepressant treatment. Dialogues Clin Neurosci. 2014; 16(3):395-404. PMC: 4214180. View

Li Q, Tian C, Seabrook G, Drevets W, Narayan V . Analysis of 23andMe antidepressant efficacy survey data: implication of circadian rhythm and neuroplasticity in bupropion response. Transl Psychiatry. 2016; 6(9):e889. PMC: 5048209. DOI: 10.1038/tp.2016.171. View

Willer C, Li Y, Abecasis G . METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010; 26(17):2190-1. PMC: 2922887. DOI: 10.1093/bioinformatics/btq340. View

Zeng Y, Navarro P, Xia C, Amador C, Fernandez-Pujals A, Thomson P . Shared Genetics and Couple-Associated Environment Are Major Contributors to the Risk of Both Clinical and Self-Declared Depression. EBioMedicine. 2016; 14:161-167. PMC: 5161419. DOI: 10.1016/j.ebiom.2016.11.003. View

10.

McGirr A, Van Den Eynde F, Chachamovich E, Fleck M, Berlim M . Personality dimensions and deep repetitive transcranial magnetic stimulation (DTMS) for treatment-resistant depression: a pilot trial on five-factor prediction of antidepressant response. Neurosci Lett. 2014; 563:144-8. DOI: 10.1016/j.neulet.2014.01.037. View

11.

Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S . Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLoS Genet. 2013; 9(5):e1003520. PMC: 3667752. DOI: 10.1371/journal.pgen.1003520. View

12.

Myung W, Kim J, Lim S, Shim S, Won H, Kim S . A genome-wide association study of antidepressant response in Koreans. Transl Psychiatry. 2015; 5:e672. PMC: 5115712. DOI: 10.1038/tp.2015.173. View

13.

Takahashi M, Shirayama Y, Muneoka K, Suzuki M, Sato K, Hashimoto K . Low openness on the revised NEO personality inventory as a risk factor for treatment-resistant depression. PLoS One. 2013; 8(9):e71964. PMC: 3760870. DOI: 10.1371/journal.pone.0071964. View

14.

. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015; 386(9995):743-800. PMC: 4561509. DOI: 10.1016/S0140-6736(15)60692-4. View

15.

Tansey K, Guipponi M, Perroud N, Bondolfi G, Domenici E, Evans D . Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis. PLoS Med. 2012; 9(10):e1001326. PMC: 3472989. DOI: 10.1371/journal.pmed.1001326. View

16.

Peters E, Reus V, Hamilton S . The ABCB1 transporter gene and antidepressant response. F1000 Biol Rep. 2010; 1:23. PMC: 2920683. DOI: 10.3410/B1-23. View

17.

de Leeuw C, Mooij J, Heskes T, Posthuma D . MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015; 11(4):e1004219. PMC: 4401657. DOI: 10.1371/journal.pcbi.1004219. View

18.

Kerr S, Campbell A, Murphy L, Hayward C, Jackson C, Wain L . Pedigree and genotyping quality analyses of over 10,000 DNA samples from the Generation Scotland: Scottish Family Health Study. BMC Med Genet. 2013; 14:38. PMC: 3614907. DOI: 10.1186/1471-2350-14-38. View

19.

Hicks J, Sangkuhl K, Swen J, Ellingrod V, Muller D, Shimoda K . Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clin Pharmacol Ther. 2016; 102(1):37-44. PMC: 5478479. DOI: 10.1002/cpt.597. View

20.

McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood A, Teumer A . A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016; 48(10):1279-83. PMC: 5388176. DOI: 10.1038/ng.3643. View