Nature Communications (Oct 2022)

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

  • Margaret Sunitha Selvaraj,
  • Xihao Li,
  • Zilin Li,
  • Akhil Pampana,
  • David Y. Zhang,
  • Joseph Park,
  • Stella Aslibekyan,
  • Joshua C. Bis,
  • Jennifer A. Brody,
  • Brian E. Cade,
  • Lee-Ming Chuang,
  • Ren-Hua Chung,
  • Joanne E. Curran,
  • Lisa de las Fuentes,
  • Paul S. de Vries,
  • Ravindranath Duggirala,
  • Barry I. Freedman,
  • Mariaelisa Graff,
  • Xiuqing Guo,
  • Nancy Heard-Costa,
  • Bertha Hidalgo,
  • Chii-Min Hwu,
  • Marguerite R. Irvin,
  • Tanika N. Kelly,
  • Brian G. Kral,
  • Leslie Lange,
  • Xiaohui Li,
  • Martin Lisa,
  • Steven A. Lubitz,
  • Ani W. Manichaikul,
  • Preuss Michael,
  • May E. Montasser,
  • Alanna C. Morrison,
  • Take Naseri,
  • Jeffrey R. O’Connell,
  • Nicholette D. Palmer,
  • Patricia A. Peyser,
  • Muagututia S. Reupena,
  • Jennifer A. Smith,
  • Xiao Sun,
  • Kent D. Taylor,
  • Russell P. Tracy,
  • Michael Y. Tsai,
  • Zhe Wang,
  • Yuxuan Wang,
  • Wei Bao,
  • John T. Wilkins,
  • Lisa R. Yanek,
  • Wei Zhao,
  • Donna K. Arnett,
  • John Blangero,
  • Eric Boerwinkle,
  • Donald W. Bowden,
  • Yii-Der Ida Chen,
  • Adolfo Correa,
  • L. Adrienne Cupples,
  • Susan K. Dutcher,
  • Patrick T. Ellinor,
  • Myriam Fornage,
  • Stacey Gabriel,
  • Soren Germer,
  • Richard Gibbs,
  • Jiang He,
  • Robert C. Kaplan,
  • Sharon L. R. Kardia,
  • Ryan Kim,
  • Charles Kooperberg,
  • Ruth J. F. Loos,
  • Karine A Viaud-Martinez,
  • Rasika A. Mathias,
  • Stephen T. McGarvey,
  • Braxton D. Mitchell,
  • Deborah Nickerson,
  • Kari E. North,
  • Bruce M. Psaty,
  • Susan Redline,
  • Alexander P. Reiner,
  • Ramachandran S. Vasan,
  • Stephen S. Rich,
  • Cristen Willer,
  • Jerome I. Rotter,
  • Daniel J. Rader,
  • Xihong Lin,
  • NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium,
  • Gina M. Peloso,
  • Pradeep Natarajan

DOI
https://doi.org/10.1038/s41467-022-33510-7
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 18

Abstract

Read online

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.