Million Veteran Program: A mega-biobank to study genetic influences on health and disease.
By J. Gaziano, J. Concato, M. Brophy, L. Fiore, S. Pyarajan, Jim L. Breeling, S. Whitbourne, Jennifer E. Deen, Colleen Shannon, Donald E. Humphries and 11 more. Journal of Clinical Epidemiology, 2016
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OBJECTIVE To describe the design and ongoing conduct of the Million Veteran Program (MVP), as an observational cohort study and mega-biobank in the Department of Veterans Affairs (VA) health care system. STUDY DESIGN AND SETTING Data are being collected from participants using questionnaires, the VA electronic health record, and a blood sample for genomic and other testing. Several ongoing projects are linked to MVP, both as peer-reviewed research studies and as activities to help develop an infrastructure for future, broad-based research uses. RESULTS Formal planning for MVP commenced in 2009; the protocol was approved in 2010, and enrollment began in 2011. As of August 3, 2015, and with a steady state of ≈50 recruiting sites nationwide, N = 397,104 veterans have been enrolled. Among N = 199,348 with currently available genotyping data, most participants (as expected) are male (92.0%) between the ages of 50 and 69 years (55.0%). On the basis of self-reported race, white (77.2%) and African American (13.5%) populations are well represented. CONCLUSIONS By helping to promote the future integration of genetic testing in health care delivery, including clinical decision making, the MVP is designed to contribute to the development of precision medicine.
Subfields: Genetics
View Paper: https://www.semanticscholar.org/paper/d3f214b51ddd06547d796de85c7dd368125c9681
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Citations in the corpus
- Multimodal biomedical AI (2022, background): “In the USA, the Department of Veteran Affairs launched the Million Veteran Program 88 in 2011, aiming to enroll 1 million veterans to contribute to scientific discovery.”
- Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ethnic meta-analysis (2020, neutral): “…Grant D. Huang80, Rachel B. Ramoni16, Saiju Pyarajan16,25,26, Yan V. Sun34,35, Kelly Cho16,25, Peter W. Wilson34,40, Christopher J. O’Donnell16,25,26, Philip S. Tsao13,14, Kyong-Mi Chang1,2, J. Michael Gaziano16,25 and Sumitra Muralidhar80 51Iowa City VA Health Care System, Iowa City, IA, USA.”
- Axes of a revolution: challenges and promises of big data in healthcare (2020, background): “Although the concept of mega biobanks 49 is not well defined in the literature, it can be viewed qualitatively as biobanks that integrate many of the data axes mentioned above at a broad scale and includes data measured on large sample sizes (axis N) together with deep phenotyping of each subject…”