Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305, USA.
Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
Neuropsychopharmacology. 2023 Apr;48(5):764-772. doi: 10.1038/s41386-022-01524-w. Epub 2023 Jan 24.
A new era of human postmortem tissue research has emerged thanks to the development of 'omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10, 17.2%) and in donors with African ancestry (p = 1.6 × 10, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.
得益于“组学”技术的发展，人类死后组织研究已经进入了一个新时代，这些技术可以以前所未有的细节水平测量基因、蛋白质和空间参数。同样新出现的是构建多基因评分的能力，这是一种基于全基因组关联研究（GWAS）的个体遗传风险的度量（也称为多基因风险评分/PRS）。在这里，我们报告了在人类大脑采集核心（HBCC）中具有不同祖先的样本中多基因评分的临床、教育和大脑基因表达相关性。对 1418 名供体的基因型进行了质量控制过滤、推断，并用于构建多基因评分。多基因评分预测了欧洲血统供体的精神分裂症状态（p=4.7×10，17.2%的表型方差解释）和非洲血统供体的精神分裂症状态（p=1.6×10，10.4%的表型方差解释）。在欧洲血统样本中观察到更高的方差解释模式也存在于其他精神障碍（抑郁、双相情感障碍、物质使用障碍、焦虑障碍）和身高、体重指数和受教育年限。对于 223 个样本的子集，通过共同思维协会（CommonMind Consortium）可获得来自背外侧前额叶皮层（DLPFC）的基因表达数据。在这个亚组中，精神分裂症多基因评分也预测了精神分裂症的总基因表达评分（欧洲血统：p=0.0032，非洲血统：p=0.15）。总体而言，多基因评分在具有不同祖先的样本中表现符合预期，考虑到历史上偏向使用欧洲血统样本和多基因评分在表型上的可变预测能力。这里报告的转录组结果表明，遗传性精神分裂症遗传风险会影响基因表达，即使在成年期也是如此。对于未来的研究，这些和其他的多基因评分正在被用于分析，并通过人类大脑采集核心的死后组织来选择样本。
