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.

中文翻译：

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难治性抑郁症的全基因组关联研究：与代谢特征共享的生物学特性

客观的：

大约三分之一的重度抑郁症 (MDD) 患者出现难治性抑郁症 (TRD)。尽管研究表明，与非治疗耐药性MDD相比，TRD的遗传性估计为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研究队列，这很大程度上是因为前瞻性研究这种表型的挑战。本研究的目的是对 TRD 进行强有力的遗传学研究。

方法：

作者将接受电休克治疗 (ECT) 作为 TRD 的替代，将标准机器学习方法应用于电子健康记录数据，以得出接受 ECT 的预测概率。然后将这些概率作为定量特征应用于对四个大型生物库的 154,433 名基因分型患者进行的全基因组关联研究中。

结果：

遗传力估计范围为 2% 至 4.2%，并且在认知、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方面观察到显着的遗传重叠。确定了两个全基因组的重要位点，这两个位点之前都与代谢特征有关，这表明它们具有共同的生物学和潜在的药理学意义。

结论：

这项工作为基因组研究中疾病概率估计的实用性提供了支持，并提供了对 TRD 遗传结构和生物学的见解。