全球生物样本库荟萃分析中的全蛋白质组孟德尔随机化揭示了常见疾病的多祖先药物靶点。
Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases.
作者信息
Zhao Huiling, Rasheed Humaria, Nøst Therese Haugdahl, Cho Yoonsu, Liu Yi, Bhatta Laxmi, Bhattacharya Arjun, Hemani Gibran, Davey Smith George, Brumpton Ben Michael, Zhou Wei, Neale Benjamin M, Gaunt Tom R, Zheng Jie
机构信息
MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
出版信息
Cell Genom. 2022 Nov 9;2(11):None. doi: 10.1016/j.xgen.2022.100195.
Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development.
全蛋白质组孟德尔随机化(MR)在确定欧洲人群药物靶点方面显示出价值,但在其他血统人群中的证据有限。在此,我们基于全球生物银行荟萃分析倡议(GBMI)的跨人群数据进行了多血统全蛋白质组MR分析。我们估计了1545种蛋白质对非洲(32658人)和欧洲(1219993人)血统中8种疾病的假定因果效应,分别在两个血统中确定了45对和7对具有MR和基因共定位证据的蛋白质-疾病对。多血统MR比较确定了两个在两个血统中均有MR证据的蛋白质-疾病对,以及七个在两个血统中分别具有特定效应的对。将这些MR信号与临床试验证据相结合,我们确定了16对在未来药物试验中进行研究的优先对象。我们的结果突出了全蛋白质组MR在了解跨血统疾病预防药物靶点可推广性方面的价值,并说明了生物银行荟萃分析在药物开发中的价值。