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Couser NL, Masood MM, Strande NT, Foreman AK, Crooks K, Weck KE, Lu M, Wilhelmsen KC, Roche M, Evans JP, Berg JS, Powell CM. The phenotype of multiple congenital anomalies-hypotonia-seizures syndrome 1: report and review. Am J Med Genet A. 2015 Sep;167A(9):2176-81. PubMed PMID: 25920937
Lee K, Berg JS, Milko L, Crooks K, Lu M, Bizon C, Owen P, Wilhelmsen KC, Weck KE, Evans JP, Garg S. High Diagnostic Yield of Whole Exome Sequencing in Participants With Retinal Dystrophies in a Clinical Ophthalmology Setting. Am J Ophthalmol. 2015 Aug;160(2):354-363.e9. PubMed PMID: 25910913
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Popejoy AB, Crooks KR, Fullerton SM, Hindorff LA, Hooker GW, Koenig BA, Pino N, Ramos EM, Ritter DI, Wand H, Wright MW, Yudell M, Zou JY, Plon SE, Bustamante CD, Ormond KE. Clinical Genetics Lacks Standard Definitions and Protocols for the Collection and Use of Diversity Measures. Am J Hum Genet. 2020 Jul 2;107(1):72-82. PubMed PMID: 32504544
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Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease,
Cell Genomics,
Volume 2, Issue 10,
2022,
100192,
ISSN 2666-979X,
https://doi.org/10.1016/j.xgen.2022.100192.
(https://www.sciencedirect.com/science/article/pii/S2666979X22001410)
Abstract: Summary
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.
Keywords: biobank; meta-analysis; genetic association studies; GWAS; phenotype harmonization; ancestry diversity
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