Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals
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Author(s):
Margaret Sunitha Selvaraj, Xihao Li, Zilin Li, Eric Van Buren, Sara Haidermota, Darina Postupaka, Whitney Hornsby, Joshua C. Bis, Jennifer A. Brody, Brian E. Cade, Ren-Hua Chung, Joanne E. Curran, Scott M. Damrauer, Lisa de las Fuentes, Paul S. de Vries, Ravindranath Duggirala, Barry I. Freedman, MariaElisa Graff, Xiuqing Guo, Bertha A. Hidalgo, Lifang Hou, Ryan Irvin, Renae Judy, Rita R. Kalyani, Tanika N. Kelly, Iain R. Konigsberg, Brian G. Kral, Lydia Coulter Kwee, Daniel Levy, Changwei Li, Ani W. Manichaikul, Lisa Warsinger Martin, May E. Montasser, Alanna C. Morrison, Take Naseri, Kari E. North, Jeffrey R. O'Connell, Nicholette D. Palmer, Patricia A. Peyser, Alex P. Reiner, Svati H. Shah, Roelof A. J. Smit, Jennifer A. Smith, Kent D. Taylor, Hemant Tiwari, Michael Y. Tsai, Satupa'itea Viali, Zhe Wang, Yuxuan Wang, Wei Zhao, Donna K. Arnett, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jenna C. Carlson, Yii-Der Ida Chen, Patrick T. Ellinor, Myriam Fornage, Jiang He, Nancy Heard-Costa, Robert C. Kaplan, Sharon L. R. Kardia, Charles Kooperberg, William E. Kraus, Leslie A. Lange, Ruth J. F. Loos, Braxton D. Mitchell, Bruce M. Psaty, Daniel J. Rader, Susan Redline, Stephen S. Rich, Lisa R. Yanek, Richard Gibbs, Stacey Gabriel, Karine A. Viaud-Martinez, Susan K. Dutcher, Soren Germer, Ryan Kim, Jerome I. Rotter, Xihong Lin, Gina M. Peloso, Pradeep Natarajan
BackgroundRare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.ResultsHere, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate.ConclusionsThis study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.
Coronary artery disease (CAD) is the leading cause of death in the UK. When CAD occurs prematurely, the role for inheritance is greater. DNA sequencing…
