Aeron M Small1, Christopher J O'Donnell2,3,4, Scott M Damrauer5,6,7. 1. Department of Medicine, Yale New Haven Hospital, Yale University School of Medicine, New Haven, CT, USA. 2. Cardiology Section, Department of Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA. 3. Cardiovascular Medicine Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 4. Million Veteran Program, Department of Veteran's Affairs, Washington, DC, USA. 5. Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA. Scott.Damrauer@uphs.upenn.edu. 6. Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Scott.Damrauer@uphs.upenn.edu. 7. Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein, Philadelphia, PA, 19104-5158, USA. Scott.Damrauer@uphs.upenn.edu.
Abstract
PURPOSE OF REVIEW: Cardiovascular disease is a leading cause of morbidity and mortality worldwide and is the focus of extensive biomedical research. Large genetic consortia combining data from many traditional prospective cohort and ascertained case-control study designs have facilitated the discovery of genetic associations for a variety of cardiovascular diseases including diabetes, coronary artery disease, and hypertension. Biobank-based genetic studies offer an alternative whereby large populations are genotyped and linked to electronic health records. RECENT FINDINGS: Biobank sample sizes worldwide have surpassed even the largest genetic consortia and have yielded key insights into the genetic determinants of both common and rare cardiovascular phenotypes. Herein, we provide an overview of the largest genomic biobanks and discuss the relevant advantages and challenges inherent to the biobank model of cohort generation and genomic study design.
PURPOSE OF REVIEW: Cardiovascular disease is a leading cause of morbidity and mortality worldwide and is the focus of extensive biomedical research. Large genetic consortia combining data from many traditional prospective cohort and ascertained case-control study designs have facilitated the discovery of genetic associations for a variety of cardiovascular diseases including diabetes, coronary artery disease, and hypertension. Biobank-based genetic studies offer an alternative whereby large populations are genotyped and linked to electronic health records. RECENT FINDINGS: Biobank sample sizes worldwide have surpassed even the largest genetic consortia and have yielded key insights into the genetic determinants of both common and rare cardiovascular phenotypes. Herein, we provide an overview of the largest genomic biobanks and discuss the relevant advantages and challenges inherent to the biobank model of cohort generation and genomic study design.
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