Campbell, Archie

Hayward, Caroline

Marioni, Riccardo E

Porteous, David John

Richmond , Anne

English

Biobanks are being established across the world to understand the genetic and environmental basis of human diseases with the goal of better prevention and treatments. Genome-wide association studies (GWAS) have been very successful at mapping genomic loci for a wide range of human diseases and traits, but in general lack appropriate representation of diverse ancestries - with most biobanks and preceding GWAS studies composed of individuals of European ancestry. Here, 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 GWAS generated using harmonized genotypes and phenotypes from member biobanks. GBMI brings together results from GWAS analyses across 6 main ancestry groups: approximately 42,000 of African ancestries from admixed-ancestry diaspora (AFR), 18,000 admixed American (AMR), 31,000 Central and South Asian (CSA), 415,000 East Asian (EAS), 1.4 million European (EUR), and 12,000 Middle Eastern (MID) individuals. In this flagship project, we generated GWASs from across 14 exemplar diseases and endpoints, including both common and less prevalent diseases that were previously understudied. Using the genetic association results, we validate that GWASs conducted in biobanks worldwide can be successfully integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics between biobanks. We demonstrate the value of this collaborative effort to improve GWAS power for diseases, increase representation, benefit understudied diseases, and improve 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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Global Biobank Meta-analysis Initiative: powering genetic discovery across human disease

https://www.research.ed.ac.uk/files/299065111/Supplementary_Note_achknowledgement_SFigures_GBMI.pdf

Global Biobank Meta-analysis Initiative: powering genetic discovery across human disease

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