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Nat Commun. 2018 Aug 23;9(1):3391. doi: 10.1038/s41467-018-05747-8.

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Collaborators (303)

Abe N, Albert C, Allred NNP, Almasy L, Alonso A, Ament S, Anderson P, Anugu P, Applebaum-Bowden D, Arking D, Arnett DK, Ashley-Koch A, Aslibekyan S, Assimes T, Auer P, Avramopoulos D, Barnard J, Barnes K, Barr RG, Barron-Casella E, Beaty T, Becker D, Becker L, Beer R, Begum F, Beitelshees A, Benjamin E, Bezerra M, Bielak L, Bis J, Blackwell T, Blangero J, Boerwinkle E, Borecki I, Bowler R, Brody J, Broeckel U, Broome J, Bunting K, Burchard E, Cardwell J, Carty C, Casaburi R, Casella J, Chang C, Chasman D, Chavan S, Chen BJ, Chen WM, Chen YI, Cho M, Choi SH, Chuang LM, Chung M, Cornell E, Crandall C, Crapo J, Curran J, Curtis J, Custer B, Damcott C, Darbar D, Das S, David S, Davis C, Daya M, de Andrade M, DeBaun M, Deka R, DeMeo D, Devine S, Do R, Duan Q, Duggirala R, Durda P, Dutcher S, Eaton C, Ekunwe L, Ellinor P, Emery L, Farber C, Farnam L, Fingerlin T, Flickinger M, Fornage M, Franceschini N, Fu M, Fullerton M, Fulton L, Gabriel S, Gan W, Gao Y, Gass M, Gelb B, Geng XP, Germer S, Gignoux C, Gladwin M, Glahn D, Gogarten S, Gong DW, Goring H, Gu CC, Guan Y, Guo X, Haessler J, Hall M, Harris D, Hawley N, He J, Heavner B, Heckbert S, Hernandez R, Herrington D, Hersh C, Hidalgo B, Hixson J, Hokanson J, Hong E, Hoth K, Hsiung CA, Huston H, Hwu CM, Irvin MR, Jackson R, Jain D, Jaquish C, Jhun MA, Johnsen J, Johnson A, Johnston R, Jones K, Kang HM, Kaplan R, Kardia S, Kaufman L, Kelly S, Kenny E, Kessler M, Khan A, Kinney G, Konkle B, Kooperberg C, Kramer H, Krauter S, Lange C, Lange E, Lange L, Laurie C, Laurie C, LeBoff M, Lee SS, Lee WJ, LeFaive J, Levine D, Levy D, Lewis J, Li Y, Lin H, Lin KH, Liu S, Liu Y, Loos R, Lubitz S, Lunetta K, Luo J, Mahaney M, Make B, Manson J, Margolin L, Martin L, Mathai S, Mathias R, McArdle P, McDonald ML, McFarland S, McGarvey S, Mei H, Meyers DA, Mikulla J, Min N, Minear M, Minster RL, Musani S, Mwasongwe S, Mychaleckyj JC, Nadkarni G, Naik R, Nekhai S, Nickerson D, North K, O'Connor T, Ochs-Balcom H, Pankow J, Papanicolaou G, Parker M, Parsa A, Penchev S, Peralta JM, Perez M, Peters U, Peyser P, Phillips L, Phillips S, Pollin T, Post W, Becker JP, Boorgula MP, Preuss M, Prokopenko D, Psaty B, Qasba P, Qiao D, Qin Z, Rafaels N, Raffield L, Rao DC, Rasmussen-Torvik L, Ratan A, Redline S, Reed R, Regan E, Reiner A, Rice K, Roden D, Roselli C, Ruczinski I, Russell P, Ruuska S, Ryan K, Sakornsakolpat P, Salimi S, Salzberg S, Sandow K, Sankaran V, Schmidt E, Schwander K, Schwartz D, Sciurba F, Seidman C, Sheehan V, Shetty A, Shetty A, Sheu WH, Shoemaker MB, Silver B, Silverman E, Smith J, Smith J, Smith N, Smith T, Smoller S, Snively B, Sofer T, Sotoodehnia N, Stilp A, Streeten E, Sung YJ, Sylvia J, Szpiro A, Sztalryd C, Taliun D, Tang H, Taub M, Taylor K, Taylor S, Telen M, Thornton TA, Tinker L, Tirschwell D, Tiwari H, Tracy R, Tsai M, Vaidya D, VandeHaar P, Vrieze S, Walker T, Wallace R, Walts A, Wan E, Wang FF, Watson K, Weeks DE, Weir B, Weiss S, Weng LC, Willer C, Williams K, Williams LK, Wilson C, Wong Q, Xu H, Yanek L, Yang I, Yang R, Zaghloul N, Zhang Y, Zhao SX, Zheng X, Zhi D, Zhou X, Zody M, Zoellner S.

Author information

1
Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA.
2
Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA.
3
Broad Institute of Harvard & MIT, Cambridge, MA, 02142, USA.
4
Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.
5
Yale School of Medicine, New Haven, CT, 06510, USA.
6
Department of Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA.
7
School of Medicine, University of Maryland, Baltimore, MD, 21201, USA.
8
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA.
9
Department of Computational Medicine and Bioinformatics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
10
Society of Fellows, Harvard University, Cambridge, MA, 02138, USA.
11
Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
12
Institute for Molecular Medicine Finland, Helsinki, 00290, Finland.
13
Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia.
14
Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
15
Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA.
16
Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216, USA.
17
Sections of Preventive Medicine and Epidemiology and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.
18
Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA.
19
Framingham Heart Study, Framingham, MA, 01702, USA.
20
Computer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
21
Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
22
Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 39216, USA.
23
Institute for Translational Genomics and Population Sciences, LABioMed and Departments of Pediatrics and Medicine, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
24
Departments of Human Genetics, Internal Medicine, and Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.
25
Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA. skathiresan1@mgh.harvard.edu.
26
Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA. skathiresan1@mgh.harvard.edu.
27
Broad Institute of Harvard & MIT, Cambridge, MA, 02142, USA. skathiresan1@mgh.harvard.edu.

Abstract

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia.

PMID:
30140000
PMCID:
PMC6107638
DOI:
10.1038/s41467-018-05747-8
[Indexed for MEDLINE]
Free PMC Article

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