CNV Association of Diverse Clinical Phenotypes from eMERGE reveals novel disease biology underlying cardiovascular disease. (1st January 2020)

• Record Type: Journal Article
• Authors: Glessner, Joseph T.; Li, Jin; Desai, Akshatha; Palmer, Melody; Kim, Dokyoon; Lucas, Anastasia Marie; Chang, Xiao; Connolly, John J.; Almoguera, Berta; Harley, John B.; Jarvik, Gail P.; Ritchie, Marylyn D.; Sleiman, Patrick M.A.; Roden, Dan M.; Crosslin, David; Hakonarson, Hakon
• Is Part Of: International journal of cardiology. Volume 298(2020)
• Page Start: 107
• Page End: 113
• Publication Date: 2020-01-01
• Subjects: BMI -- Cardiovascular disease -- Copy number variations -- Genome-wide association study -- Glucose levels -- Lipid profiling; Cardiology -- Periodicals; Electronic journals; 616.12
• DOI: 10.1016/j.ijcard.2019.07.058
• Languages: English
• ISSNs: 0167-5273

Abstract

Abstract: Background: Cardiovascular disease is the leading cause of death in the United States. Consequently, individuals who are genetically predisposed for high risk of cardiovascular disease would benefit most from prevention and early intervention approaches. Among common health risk factors affecting adult populations, we evaluated 23 cardiovascular disease-related traits, including BMI, glucose levels and lipid profiling to determine their associations with low-frequency recurrent copy number variations (CNV) (population frequency < 5%). Results: We examined 10, 619 unrelated subjects of European ancestry from the Electronic Medical Records and Genomics (eMERGE) Network who were genotyped with 657, 366 markers genome-wide on the Illumina Infinium Quad 660 array. We performed CNV calling based on array marker intensity and evaluated data quality, ancestry stratification, and relatedness to ensure unbiased association discovery. Using a segment-based scoring approach, we assessed the association of all CNVs with each trait. In this large genome-wide analysis of low-frequency CNVs, we observed 11 novel genome-wide significant associations of low-frequency CNVs with major cardiovascular disease traits. Conclusion: In one of the largest genome-wide studies for low-frequency recurrent CNVs, we identified 11 loci associated with cardiovascular disease and related traits at the genome-wide significance level that may serve as biomarkers for prevention and early intervention studies in subjects who are at elevated risk. Our study further supports the role of low-frequency recurrent CNVs in the pathogenesis of common complex disease traits. Highlights: A genome-wide low-frequency CNV association analysis including 10, 619 subjects. A total of 23 clinical variables were examined. 47 unique CNVRs are significantly associated with 12 traits. Pathway "Retinol metabolism" is significantly enriched in the 47 CNVR intervals. Six homozygous deletion regions are significantly associated with 4 traits. Potential role of low-frequency recurrent CNVs in the pathogenesis of common complex disease traits.