Whole genome sequence analysis of blood lipid levels in >66,000 individuals
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Nature ResearchCitation
Selvaraj, M. S., Li, X., Li, Z., Pampana, A., Zhang, D. Y., Park, J., Aslibekyan, S., Bis, J. C., Brody, J. A., Cade, B. E., Chuang, L.-M., Chung, R.-H., Curran, J. E., de las Fuentes, L., de Vries, P. S., Duggirala, R., Freedman, B. I., Graff, M., Guo, X., … NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium. (2022). Whole genome sequence analysis of blood lipid levels in >66,000 individuals. Nature Communications, 13(1).Journal
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Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
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. © 2022, The Author(s).Note
Open access journalISSN
2041-1723PubMed ID
36220816Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1038/s41467-022-33510-7
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.

