The Australian Genetics of Depression Study: New Risk Loci and Dissecting Heterogeneity Between Subtypes

重性抑郁障碍 全基因组关联研究 萧条(经济学) 遗传异质性 遗传建筑学 遗传关联 双相情感障碍 队列 精神科 遗传学 生物 医学 心理学 单核苷酸多态性 基因 心情 数量性状位点 基因型 表型 内科学 经济 宏观经济学
作者
Brittany L. Mitchell,Adrián I. Campos,David C. Whiteman,Catherine M. Olsen,Scott D. Gordon,Adam J. Walker,Olivia Dean,Michael Berk,Ian B. Hickie,Sarah E. Medland,Naomi R. Wray,Nicholas G. Martin,Enda M. Byrne
出处
期刊:Biological Psychiatry [Elsevier]
卷期号:92 (3): 227-235 被引量:19
标识
DOI:10.1016/j.biopsych.2021.10.021
摘要

Major depressive disorder (MDD) is a common and highly heterogeneous psychiatric disorder, but little is known about the genetic characterization of this heterogeneity. Understanding the genetic etiology of MDD can be challenging because large sample sizes are needed for gene discovery-often achieved with a trade-off in the depth of phenotyping.The Australian Genetics of Depression Study is the largest stand-alone depression cohort with both genetic data and in-depth phenotyping and comprises a total of 15,792 participants of European ancestry, 92% of whom met diagnostic criteria for MDD. We leveraged the unique nature of this cohort to conduct a meta-analysis with the largest publicly available depression genome-wide association study to date and subsequently used polygenic scores to investigate genetic heterogeneity across various clinical subtypes of MDD.We increased the number of known genome-wide significant variants associated with depression from 103 to 126 and found evidence of association of novel genes implicated in neuronal development. We found that a polygenic score for depression explained 5.7% of variance in MDD liability in our sample. Finally, we found strong support for genetic heterogeneity in depression with differential associations of multiple psychiatric and comorbid traits with age of onset, longitudinal course, and various subtypes of MDD.Until now, this degree of detailed phenotyping in such a large sample of MDD cases has not been possible. Along with the discovery of novel loci, we provide support for differential pathways to illness models that recognize the overlap with other common psychiatric disorders as well as pathophysiological differences.
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