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Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

机译:精神疾病的异质性和多基因性:全基因组视角

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摘要

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.
机译:已针对许多精神疾病进行了全基因组关联研究(GWAS),并揭示了连接精神和身体健康表型的复杂多基因体系结构。精神病学诊断通常是异质性的,特质异质性的多个层次可能有助于检测每种疾病或多种疾病的遗传风险。在这篇综述中,我们讨论了这些异质性及其对使用大规模遗传数据发现风险基因座的后果。我们主要强调性别和诊断复杂性如何影响精神分裂症,双相情感障碍,注意力缺陷多动障碍,自闭症谱系障碍,创伤后应激障碍,重度抑郁症,强迫症,图雷特氏综合症和慢性抽动症的危险基因,焦虑症,自杀,进食和进食障碍以及物质使用障碍。遗传数据也促进了临床相关亚表型的发现,在此也进行了描述。总的来说,精神疾病的GWAS揭示了对异质性,多基因性和多效性的理解对于将遗传发现转化为治疗策略至关重要。

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