Polygenic risk scores for cardiovascular diseases and type 2 diabetes.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science

Cardiovascular Diseases*/genetics ; Diabetes Mellitus, Type 2*/genetics ; Coronary Artery Disease*/genetics ; Atrial Fibrillation* ; Hypertension*/genetics ; Stroke*; Humans ; Risk Factors

Polygenic risk scores (PRSs) are a promising approach to accurately predict an individual's risk of developing disease. The area under the receiver operating characteristic curve (AUC) of PRSs in their population are often only reported for models that are adjusted for age and sex, which are known risk factors for the disease of interest and confound the association between the PRS and the disease. This makes comparison of PRS between studies difficult because the genetic effects cannot be disentangled from effects of age and sex (which have a high AUC without the PRS). In this study, we used data from the UK Biobank and applied the stacked clumping and thresholding method and a variation called maximum clumping and thresholding method to develop PRSs to predict coronary artery disease, hypertension, atrial fibrillation, stroke and type 2 diabetes. We created case-control training datasets in which age and sex were controlled by design. We also excluded prevalent cases to prevent biased estimation of disease risks. The maximum clumping and thresholding PRSs required many fewer single-nucleotide polymorphisms to achieve almost the same discriminatory ability as the stacked clumping and thresholding PRSs. Using the testing datasets, the AUCs for the maximum clumping and thresholding PRSs were 0.599 (95% confidence interval [CI]: 0.585, 0.613) for atrial fibrillation, 0.572 (95% CI: 0.560, 0.584) for coronary artery disease, 0.585 (95% CI: 0.564, 0.605) for type 2 diabetes, 0.559 (95% CI: 0.550, 0.569) for hypertension and 0.514 (95% CI: 0.494, 0.535) for stroke. By developing a PRS using a dataset in which age and sex are controlled by design, we have obtained true estimates of the discriminatory ability of the PRSs alone rather than estimates that include the effects of age and sex.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: CKW, GSD, LW, NMM and RA are employees of Genetic Technologies Limited. Aspects of this manuscript are covered by Provisional Patent Application AU 2020903793, Methods of assessing risk of developing a disease. CKW, GSD, NMM and RA are named inventors on the patent application, which is assigned to Genetic Technologies Limited. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2022 Wong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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MC_PC_17228 United Kingdom MRC_ Medical Research Council; MC_QA137853 United Kingdom MRC_ Medical Research Council

Date Created: 20221202 Date Completed: 20221206 Latest Revision: 20230308

20240628

PMC9718402

10.1371/journal.pone.0278764

36459520