Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase approximately 50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

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Publication Details

Journal
BMC Medical Genomics
Published
2024-10-24
DOI
https://doi.org/10.1186/s12920-024-02024-0
Citations
8
Primary Topic
Cardiomyopathy and Myosin Studies
Type
article
Field-Weighted Citation Impact
3.22

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article

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

Luis F. Paulin, Sairam Behera, James Han, Michael A. Eberle et al.
8 citations
BMC Medical Genomics
Cardiomyopathy and Myosin Studies
3.22
article

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

Luis F. Paulin, Sairam Behera, James Han, Michael A. Eberle, Parag H. Joshi, Emma Newman, Ginger Metcalf, Fritz J. Sedlazeck, Donna M. Muzny, Medhat Mahmoud, Christy L. Avery, Eric Boerwinkle, Christie Mitchell Ballantyne, Carlos J. Rodríguez, Robert C. Kaplan, Vitor Onuchic, Richard A. Gibbs, Bing Yu, Xiao Chen, Santica M. Marcovina, Vipin K. Menon, Qibin Qi, Massimiliano Rossi, Jonathan R. Belyeu, Ngoc Quynh Nguyen, Eric Roller
article en
8 citations

Abstract

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase approximately 50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

BMC Medical GenomicsVol. 17(1)
University of North Carolina at Chapel Hill (US), Medpace (United States) (US), Albert Einstein College of Medicine (US), Illumina (United States) (US), Baylor College of Medicine (US), Fred Hutch Cancer Center (US), Pacific Biosciences (United States) (US), Rice University (US), The University of Texas Southwestern Medical Center (US), The University of Texas Health Science Center at Houston (US)
U.S. Department of Health and Human Services, Office of Dietary Supplements, University of Miami, Northwestern University, San Diego State University, National Institutes of Health, University of Illinois at Urbana-Champaign, National Heart, Lung, and Blood Institute, National Institute on Deafness and Other Communication Disorders, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute on Minority Health and Health Disparities
Good health and well-being
Openalex Percentile: Top 7%
Cardiomyopathy and Myosin Studies
3.22
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