Abstract：
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
摘要：
■难治性抑郁症（TRD）发生在大约三分之一的重度抑郁症（MDD）患者中。尽管研究表明了对TRD的责任的重要常见变异遗传成分，与非治疗抗性MDD相比，遗传力估计为8%，没有发现复制的遗传基因座，TRD的遗传结构仍不清楚。这项工作的一个关键障碍是缺乏足够的力量进行调查的队列，主要是因为前瞻性研究这种表型的挑战。这项研究的目的是对TRD进行有力的遗传研究。
■使用接受电惊厥治疗（ECT）作为TRD的替代品，作者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名基因分型患者的全基因组关联研究中。
■遗传力估计范围从2%到4.2%，并且在认知中观察到显著的遗传重叠，注意缺陷多动障碍,精神分裂症,酒精和吸烟特征，和体重指数。确定了两个全基因组重要基因座，两者以前都与代谢特征有关，提示共同的生物学和潜在的药理意义。
■这项工作为基因组研究的疾病概率估计的实用性提供了支持，并提供了对TRD的遗传结构和生物学的见解。
■使用接受电惊厥治疗（ECT）作为TRD的替代品，作者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名基因分型患者的全基因组关联研究中。
■遗传力估计范围从2%到4.2%，并且在认知中观察到显著的遗传重叠，注意缺陷多动障碍,精神分裂症,酒精和吸烟特征，和体重指数。确定了两个全基因组重要基因座，两者以前都与代谢特征有关，提示共同的生物学和潜在的药理意义。
■这项工作为基因组研究的疾病概率估计的实用性提供了支持，并提供了对TRD的遗传结构和生物学的见解。
