Division 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).
Am J Psychiatry. 2024 Jul 1;181(7):608-619. doi: 10.1176/appi.ajp.20230247. Epub 2024 May 15.
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.
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.
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.
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.
约有三分之一的重度抑郁症（MDD）患者会出现治疗抵抗性抑郁症（TRD）。尽管研究表明，TRD 存在明显的常见变异遗传易感性，与非治疗抵抗性 MDD 相比，遗传率估计为 8%，但尚未发现复制的遗传位点，TRD 的遗传结构仍不清楚。这项工作的一个主要障碍是缺乏足够强大的队列进行调查，这主要是因为前瞻性研究这种表型具有挑战性。本研究旨在对 TRD 进行一项具有充分效力的遗传研究。
作者使用接受电休克治疗（ECT）作为 TRD 的替代指标，应用标准机器学习方法对电子健康记录数据进行分析，得出接受 ECT 的预测概率。然后，将这些概率作为一个数量性状，应用于四个大型生物库中 154433 名基因分型患者的全基因组关联研究中。
遗传率估计值在 2%到 4.2%之间，与认知、注意力缺陷多动障碍、精神分裂症、酒精和吸烟特征以及体重指数存在显著的遗传重叠。确定了两个具有全基因组意义的显著位点，这两个位点之前都与代谢特征有关，这表明存在共同的生物学和潜在的药物学意义。
这项工作为使用疾病概率估计进行基因组研究提供了支持，并为 TRD 的遗传结构和生物学提供了新的见解。
