作者: Suzette J. Bielinski , High Seng Chai , Jyotishman Pathak , Jayant A. Talwalkar , Paul J. Limburg
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摘要: OBJECTIVE To create a cohort for cost-effective genetic research, the Mayo Genome Consortia (MayoGC) has been assembled with participants from research studies across Clinic high-throughput data and electronic medical record (EMR) phenotype extraction. PARTICIPANTS AND METHODS Eligible include those who gave general consent in contributing to share genotyping other investigators. Herein, we describe design of MayoGC, including current participating cohorts, expansion efforts, processing, study management organization. A genome-wide association identify variants associated total bilirubin levels was conducted test capability MayoGC. RESULTS Genome-wide significant results were observed on 2q37 (top single nucleotide polymorphism, rs4148325; P =5.0 × 10 −62 ) 12p12 rs4363657; =5.1 −8 corresponding gene cluster uridine 5′-diphospho-glucuronosyltransferases (the UGT1A solute carrier organic anion transporter family, member 1B1 ( SLCO1B1 ), respectively. CONCLUSION have identified numerous phenotypes but historically limited by inadequate sample size due costly phenotyping. Large consortia harmonized genotype attain sufficient statistical power, phenotyping remains rate-limiting factor discovery efforts. The EMR consists an abundance that can be extracted relatively quick systematic manner. MayoGC provides model unique collaborative effort environment common investigation determinants diseases.