American Journal of PsychiatryGenetic & Genomic MedicinePeer-reviewed journal article
Genome-wide association study of treatment resistant depression highlights shared biology with metabolic traits
Jooeun KangiD, Victor Manuel CastroiD, Michael A. RippergeriD, Sanan VenkateshiD, David BursteiniD, Richard Karlsson LinnériD, Daniel RochaiD, Yirui HuiD, Drew WilimitisiD, Theodore J. MorleyiD, Lide HaniD, Rachel Youngjung KimiD, Yen‐Chen Anne FengiD, Tian GeiD, Stephan HeckersiD, Georgios VoloudakisiD, Christopher F. ChabrisiD, Panos RoussosiD, Thomas H. McCoyiD, Colin G. WalshiD, Roy H. PerlisiD, Douglas M. RuderferiD
Abstract
Treatment resistant depression (TRD), often defined by absence of symptomatic remission following at least two adequate treatment trials, occurs in roughly a third of all individuals with major depressive disorder (MDD). Prior work has suggested a significant common variant genetic component of liability to TRD, with heritability estimates of 8% when comparing to non-treatment resistant MDD. Despite this evidence of heritability, no replicated genetic loci have been identified and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. Using electroconvulsive therapy (ECT) as a surrogate for TRD, we applied standard machine learning methods to electronic health record (EHR) data to derive predicted probabilities of receiving ECT. We applied these probabilities as a quantitative trait in a genome-wide association study (GWAS) over 154,433 genotyped patients across four large biobanks. With this approach, we demonstrate heritability ranging from 2% to 4.2% and significant genetic overlap with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits and body mass index. We identify two genome-wide significant loci, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.
- organism: human
- assay: electronic health records
- research focus: GWAS / association mapping
- approach: machine learning (classical)
- approach: statistical model
- Citations
- 25
- FWCI
- 6.08
- Field percentile
- top 3%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping
Chiara Fabbri, Siegfried Kasper, … Alessandro Serretti·Translational PsychiatryPeer-reviewed·Feb 3, 2020
- Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
eQTLGen, Naomi R. Wray, … Niamh Mullins·Nature GeneticsPeer-reviewed·Apr 26, 2018
- Genome-Wide Meta-Analyses Of Stratified Depression In Generation Scotland And UK Biobank
Lynsey S. Hall, Mark J. Adams, … Andrew Mark McIntosh·Translational PsychiatryPeer-reviewed·Jan 9, 2018
- Identification of 64 new risk loci for major depression, refinement of the genetic architecture and risk prediction of recurrence and comorbidities
Thomas D. Als, Mitja Kurki, … Anders Dupont Børglum·Nature MedicinePeer-reviewed·Jul 1, 2023
- Genome-wide association study of depression phenotypes in UK Biobank (n = 322,580) identifies the enrichment of variants in excitatory synaptic pathways
David M. Howard, Mark J. Adams, … Andrew Mark McIntosh·Nature CommunicationsPeer-reviewed·Apr 11, 2018
- Trans-ancestry genome-wide association meta-analysis of antidepressant response to selective serotonin reuptake inhibitors in clinical studies of depression
Ke Hu, Chris Wai Hang Lo, … Cathryn M. Lewis·medRxiv·Jun 4, 2026