A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin
Leal, Luis G.; Hoggart, Clive; Jarvelin, Marjo‐Riitta; Herzig, Karl‐Heinz; Sternberg, Michael J. E.; David, Alessia (2020-04-19)
Leal, LG, Hoggart, C, Jarvelin, M‐R, Herzig, K‐H, Sternberg, MJE, David, A. A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin. Mol Genet Genomic Med. 2020; 8:e1248. https://doi.org/10.1002/mgg3.1248
© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2020091169356
Tiivistelmä
Abstract
Background: Severe hypercholesterolemia (HC, LDL‐C > 4.9 mmol/L) affects over 30 million people worldwide. In this study, we validated a new polygenic risk score (PRS) for LDL‐C.
Methods: Summary statistics from the Global Lipid Genome Consortium and genotype data from two large populations were used.
Results: A 36‐SNP PRS was generated using data for 2,197 white Americans. In a replication cohort of 4,787 Finns, the PRS was strongly associated with the LDL‐C trait and explained 8% of its variability (p = 10–41). After risk categorization, the risk of having HC was higher in the high‐ versus low‐risk group (RR = 4.17, p < 1 × 10−7). Compared to a 12‐SNP LDL‐C raising score (currently used in the United Kingdom), the PRS explained more LDL‐C variability (8% vs. 6%). Among Finns with severe HC, 53% (66/124) versus 44% (55/124) were classified as high risk by the PRS and LDL‐C raising score, respectively. Moreover, 54% of individuals with severe HC defined as low risk by the LDL‐C raising score were reclassified to intermediate or high risk by the new PRS.
Conclusion: The new PRS has a better predictive role in identifying HC of polygenic origin compared to the currently available method and can better stratify patients into diagnostic and therapeutic algorithms.
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