生命银行
全基因组关联研究
遗传关联
疾病
荟萃分析
数据科学
生物
计算生物学
遗传学
计算机科学
医学
基因
基因型
单核苷酸多态性
内科学
病理
作者
Wei Zhou,Masahiro Kanai,Kuan-Han Wu,Humaira Rasheed,Kristin Tsuo,Jibril Hirbo,Ying Wang,Arjun Bhattacharya,Huiling Zhao,Shinichi Namba,Ida Surakka,Brooke N. Wolford,Valeria Lo Faro,Esteban A. Lopera-Maya,Kristi Läll,Marie-Julie Favé,Juulia Partanen,Sinéad B. Chapman,Juha Karjalainen,Mitja Kurki
出处
期刊:Cell genomics
[Elsevier BV]
日期:2022-10-01
卷期号:2 (10): 100192-100192
被引量:381
标识
DOI:10.1016/j.xgen.2022.100192
摘要
Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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