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Updated: Jun 26, 2025

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits
JooEun Kang1, Victor M Castro1, Michael Ripperger1
1Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute (Kang, Morley, Han, Ruderfer), Department of Psychiatry (Castro, Kim, Ge, McCoy, Perlis) and Center for Quantitative Health (Castro, Kim, McCoy, Perlis), Massachusetts General Hospital, Boston; Research Information Science and Computing, Mass General Brigham, Somerville, Mass. (Castro); Department of Psychiatry, Center for Disease Neurogenomics, Friedman Brain Institute, Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, and Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York (Venkatesh, Burstein, Voloudakis, Roussos); Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, N.Y. (Venkatesh, Burstein, Voloudakis, Roussos); Autism and Developmental Medicine Institute, Geisinger, Lewisburg, Pa. (Linnér, Chabris); Department of Economics, Leiden University, Leiden, the Netherlands (Linnér); Phenomic Analytics and Clinical Data Core (Rocha) and Population Health Sciences (Hu), Geisinger, Danville, Pa.; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei (Feng).
Objective:
Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, 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. The objective of this study was to perform a well-powered genetic study of TRD.
Methods:
Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks.
Results:
Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications.
Conclusions:
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.
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