4.8 Article

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

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-33510-7

Keywords

-

Funding

  1. National Heart, Lung and Blood Institute (NHLBI)
  2. Fondation Leducq [TNE-18CVD04]
  3. Massachusetts General Hospital (Paul and Phyllis Fireman Endowed Chair in Vascular Medicine)
  4. NIH [R01HL139731, R01HL157635, R01HL142711, R01HL127564]
  5. National Heart, Lung, and Blood Institute [R01HL142711, R01HL148050, R01HL151283, R01HL148565, R01HL135242, R01HL151152]
  6. American Heart Association [18SFRN34250007]
  7. Leducq [TNE-18CVD04]
  8. [R35-CA197449]
  9. [U19-CA203654]
  10. [R01-HL113338]
  11. [U01HG009088]
  12. [R01 HL121007]
  13. [U01 HL072515]
  14. [R01 AG18728]
  15. [X01HL134588]
  16. [HL 046389]
  17. [HL113338]
  18. [1R35HL135818]
  19. [K01 HL135405]
  20. [R03 HL154284]
  21. [U01HL072507]
  22. [R01HL087263]
  23. [R01HL090682]
  24. [P01HL045522]
  25. [R01MH078143]
  26. [R01MH078111]
  27. [R01MH083824]
  28. [U01DK085524]
  29. [R01HL113323]
  30. [R01HL093093]
  31. [R01HL140570]
  32. [HL105756]

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This study used whole genome sequencing to expand the range of genetic variations associated with blood lipids and identified multiple genes related to blood lipids, including both common and rare coding and non-coding variants. The study also found a correlation between rare LDLR intronic variants and increased LDL-C.
Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; -400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

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