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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

A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin

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Author: Leal, Luis G.1; Hoggart, Clive2; Jarvelin, Marjo‐Riitta3,4,5,6,7;
Organizations: 1Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom
2Department of Medicine, Imperial College London, London, United Kingdom
3Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulu, Finland
4Biocenter Oulu, University of Oulu, Oulu, Finland
5Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
6Department of Epidemiology and Biostatistics, MRC‐PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
7Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Middlesex, United Kingdom
8Research Unit of Biomedicine, Oulu University, Oulu, Oulu University Hospital and Medical Research Center Oulu, Oulu, Finland
9Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020091169356
Language: English
Published: John Wiley & Sons, 2020
Publish Date: 2020-09-11
Description:

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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Series: Molecular genetics & genomic medicine
ISSN: 2324-9269
ISSN-E: 2324-9269
ISSN-L: 2324-9269
Volume: 8
Issue: 6
Article number: e1248
DOI: 10.1002/mgg3.1248
OADOI: https://oadoi.org/10.1002/mgg3.1248
Type of Publication: A1 Journal article – refereed
Field of Science: 3111 Biomedicine
3142 Public health care science, environmental and occupational health
3121 General medicine, internal medicine and other clinical medicine
Subjects:
hypercholesterolemia
lipids
polygenic risk score
risk stratification
Article
Funding: Luis G. Leal is supported by the President's PhD Scholarship Scheme from Imperial College London. Alessia David is supported by the Wellcome Trust [grant WT/104955/Z/14/Z]. Clive Hoggart is supported by the European Union's Horizon 2020 research and innovation program [grant 668303]. The NFBC1966 received financial support from the Academy of Finland [project grants 104781, 120315, 129269, 1114194, and 24300796], University Hospital Oulu, Biocenter, University of Oulu, Finland [75617], National Heart, Lung, and Blood Institute [5R01HL087679‐ 02] through the STAMPEED program [1RL1MH083268‐01], National Institutes of Health/The National Institute of Mental Health [5R01MH63706:02], the Medical Research Council, UK [MR/M013138/1]. The program is currently being funded by the DynaHEALTH action [H2020‐633595] and Academy of Finland EGEA‐project [285547]. The DNA extractions, sample quality controls, biobank up‐keeping, and aliquotting was performed in the National Public Health Institute, Biomedicum Helsinki, Finland and supported financially by the Academy of Finland and Biocentrum Helsinki. The eMERGE Network was initiated and funded by The National Human Genome Research Institute, in conjunction with additional funding from National Institute of General Medical Sciences through the following grants: [U01‐HG‐004610] Group Health Cooperative/University of Washington; [U01‐ HG‐004608] Marshfield Clinic Research Foundation and Vanderbilt University Medical Center; [U01‐HG‐04599] Mayo Clinic; [U01HG004609] Northwestern University; [U01‐HG‐04603] Vanderbilt University Medical Center, also serving as the Administrative Coordinating Center; [U01HG004438] Center for Inherited Disease Research and [U01HG004424] the Broad Institute serving as Genotyping Centers.
EU Grant Number: (633595) DYNAHEALTH - Understanding the dynamic determinants of glucose homeostasis and social capability to promote Healthy and active aging
Academy of Finland Grant Number: 285547
Detailed Information: 285547 (Academy of Finland Funding decision)
Copyright information: © 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/