Schizophrenia (SZ), Bipolar Disorder (BD) and Depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUGEI case-control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD). Participants (573 cases, 1005 controls) of european ancestry from 17 sites as part of the EUGEI study were successfully genotyped following standard quality control procedures. Using standardised PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons. In case-control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case-case comparison, both PRS-SZ (OR=0.7, 95 %CI 0.53-0.92) and PRS-D (OR=1.29, 95%CI 1.05-1.6) differentiated global AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR=2.38, 95%CI 1.32-4.29). Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards potential usefulness of PRSs for diagnostic prediction in specific populations such as high-risk or early psychosis phases.

中文翻译：

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使用多个多基因风险评分来区分精神分裂症谱系障碍和情感性精神病类别；EUGEI研究

精神分裂症（SZ），双相情感障碍（BD）和抑郁症（D）在家庭中生活。这种敏感性部分归因于成百上千种常见的遗传变异，每种变异都有一定的风险。相关变体的累积效应可以概括为多基因风险评分（PRS）。利用EUGEI病例对照研究的数据，我们旨在测试三种主要精神疾病（SZ，BD，D）和智能商（IQ）作为神经发育代用品的PRSs是否可以将情感性精神病（AP）与精神分裂症区别开来。频谱障碍（SSD）。作为EUGEI研究的一部分，来自欧洲17个站点的欧洲血统的参与者（573例，1005例对照）已成功按照标准的质量控制程序进行了基因分型。使用根据最新的可用摘要统计信息构建的SZ，BD，D和IQ的标准化PRS，我们针对不同的临床比较，针对10个主要成分进行了简单或多项式Lo​​gistic回归模型调整。在病例对照比较中，PRS-SZ，PRS-BD和PRS-D在精神病亚类之间的分布不同。在个案比较中，PRS-SZ（OR = 0.7，95％CI 0.53-0.92）和PRS-D（OR = 1.29，95％CI 1.05-1.6）都将全局AP与SSD区别开来。在AP类别中，只有PRS-SZ可以将BD与精神抑郁症区分开（OR = 2.38，95％CI 1.32-4.29）。在精神病性表型的预测模型中将PRS用于严重的精神疾病，可以提高判别能力并改善我们对这些表型的理解。我们的结果表明，PRS在特定人群（例如高危或早期精神病阶段）中进行诊断预测的潜在有用性。