Design and Implementation of a Cardiovascular Gene-Centric SNP Array
Author Information
Author(s): Brendan J. Keating, Sam Tischfield, Sarah S. Murray, Tushar Bhangale, Thomas S. Price, Joseph T. Glessner, Luana Galver, Jeffrey C. Barrett, Struan F. A. Grant, Deborah N. Farlow, Hareesh R. Chandrupatla, Mark Hansen, Saad Ajmal, George J. Papanicolaou, Yiran Guo, Mingyao Li, Stephanie DerOhannessian, Paul I. W. de Bakker, Swneke D. Bailey, Alexandre Montpetit, Andrew C. Edmondson, Kent Taylor, Xiaowu Gai, Susanna S. Wang, Myriam Fornage, Tamim Shaikh, Leif Groop, Michael Boehnke, Alistair S. Hall, Andrew T. Hattersley, Edward Frackelton, Nick Patterson, Charleston W. K. Chiang, Cecelia E. Kim, Richard R. Fabsitz, Willem Ouwehand, Alkes L. Price, Patricia Munroe, Mark Caulfield, Thomas Drake, Eric Boerwinkle, David Reich, A. Stephen Whitehead, Thomas P. Cappola, Nilesh J. Samani, A. Jake Lusis, Eric Schadt, James G. Wilson, Wolfgang Koenig, Mark I. McCarthy, Sekar Kathiresan, Stacey B. Gabriel, Hakon Hakonarson, Sonia S. Anand, Muredach Reilly, James C. Engert, Deborah A. Nickerson, Daniel J. Rader, Joel N. Hirschhorn, Garret A. FitzGerald
Primary Institution: Institute for Translational Medicine and Therapeutics, School of Medicine, University of Pennsylvania
Hypothesis
The study aims to create a gene-centric 50 K SNP array to assess genetic loci related to cardiovascular, metabolic, and inflammatory syndromes.
Conclusion
The IBC array provides enhanced coverage of high-priority cardiovascular disease-related loci and facilitates more robust genetic analyses.
Supporting Evidence
- The IBC array captures genetic diversity across ∼2,000 loci.
- Over 200,000 individuals will be genotyped using this array.
- The array complements existing GWAS tools by increasing coverage in high-priority loci.
- Custom SNP selection allows for better representation of genetic variants.
- Data generated will facilitate in silico replication attempts and analyses of rare variants.
- The array is designed to improve the detection of subtle genetic effects.
- Collaboration among international partners enhances the study's robustness.
- Findings will support secondary analyses like gene-environment interactions.
Takeaway
Researchers made a special tool to look at genes that might cause heart problems, using information from a lot of people to help find these genes better.
Methodology
The study involved designing a custom SNP array and analyzing data from over 200,000 individuals to assess genetic variants related to cardiovascular diseases.
Potential Biases
The reliance on existing databases may introduce bias in the representation of genetic variants.
Limitations
The study acknowledges potential biases in SNP selection and the need for diverse population representation for comprehensive coverage.
Participant Demographics
Participants included individuals from diverse populations, particularly focusing on those with cardiovascular traits.
Digital Object Identifier (DOI)
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