绘制精神障碍及相关特征遗传重叠的图谱：超越遗传关联。
Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation.
机构信息
NORMENT Center, Institute of Clinical Medicine, University of Oslo, and Division of Mental Health and Addiction, Oslo University Hospital, Oslo (Hindley, Frei, Shadrin, Cheng, O'Connell, Icick, Parker, Bahrami, Karadag, Roelfs, Holen, Lin, Smeland, Andreassen); Psychosis Studies, Institute of Psychiatry, Psychology, and Neurosciences, King's College London (Hindley); Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo (Frei); INSERM UMR-S1144, Université Paris Cité, Paris (Icick); Department of Cognitive Science (Fan), Multimodal Imaging Laboratory (Fan, Dale), and Departments of Psychiatry, Neurosciences, and Radiology (Dale), University of California, San Diego, La Jolla; Department of Medical Genetics, Oslo University Hospital, Oslo (Djurovic); NORMENT Center, Department of Clinical Science, University of Bergen, Bergen, Norway (Djurovic); KG Jebsen Center for Neurodevelopmental disorders, University of Oslo, Oslo (Shadrin, Djurovic, Andreassen).
出版信息
Am J Psychiatry. 2022 Nov 1;179(11):833-843. doi: 10.1176/appi.ajp.21101051. Epub 2022 Sep 7.
OBJECTIVE
Mental disorders are heritable and polygenic, and genome-wide genetic correlations (r) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, r may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions.
METHODS
The authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of "causal" variants for a given trait ("polygenicity"), the number of variants shared between traits, and the genetic correlation of shared variants (r). Local r was investigated using LAVA.
RESULTS
Among mental disorders, ADHD was the least polygenic (5.6K "causal" variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in r and r. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local r (r=0.88, p<0.001).
CONCLUSIONS
There is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction.
目的
精神障碍具有遗传性和多基因性，全基因组遗传相关性 (r) 表明多种障碍和相关特征之间存在广泛的共同遗传风险，反映了它们重叠的临床特征。然而，r 可能低估了精神障碍和相关特征的共同遗传基础，因为它不能区分一致和不一致遗传效应的混合物与遗传重叠的缺失。使用新的统计遗传学工具，作者旨在评估在考虑混合效应方向时，精神障碍和相关特征之间的遗传重叠。
方法
作者应用双变量因果混合模型 (MiXeR) 对来自全基因组关联研究的四种精神障碍、四种相关精神特征和身高的汇总统计数据进行了分析 (Ns 范围从 53293 到 766345)。MiXeR 估计了给定特征的“因果”变体数量（“多效性”）、特征之间共享的变体数量以及共享变体的遗传相关性 (r)。使用 LAVA 研究了局部 r。
结果
在精神障碍中，ADHD 的多效性最低（5600 个“因果”变体），其次是双相情感障碍（8600 个）、精神分裂症（9600 个）和抑郁症（14500 个）。大多数变体在精神障碍之间（4400-9300 个）和精神障碍与相关特征之间（5200-12800 个）共享，但 r 和 r 存在障碍特异性变化。与身高的重叠很小（700-1100 个）。MiXeR 估计与 LAVA 局部 r 相关（r=0.88，p<0.001）。
结论
精神障碍和相关特征之间存在广泛的遗传重叠，具有混合效应方向和很少的障碍特异性变体。这表明，精神障碍的遗传风险主要是由多效性遗传变体的发散效应分布而不是障碍特异性变体来区分的。这代表了我们对精神障碍共享遗传结构景观的理解的概念性进展，这可能为遗传发现、生物学特征描述、分类学和遗传预测提供信息。
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