scholarly journals Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status

2020 ◽  
Vol 44 (2) ◽  
pp. 125-138 ◽  
Author(s):  
Damian Gola ◽  
Jeannette Erdmann ◽  
Bertram Müller‐Myhsok ◽  
Heribert Schunkert ◽  
Inke R. König
Keyword(s):  
Machine Learning ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Disease Status ◽  
Risk Scores ◽  
Learning Methods ◽  
Polygenic Risk ◽  
Machine Learning Methods ◽  
Artery Disease ◽  
Coronary Artery Disease Status

scholarly journals Polygenic risk scores for coronary artery disease and subsequent event risk amongst established cases

2020 ◽  
Vol 29 (8) ◽  
pp. 1388-1395
Author(s):  
Laurence J Howe ◽  
Frank Dudbridge ◽  
Amand F Schmidt ◽  
Chris Finan ◽  
Spiros Denaxas ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Scores ◽  
Effect Estimate ◽  
Inverse Association ◽  
Uk Biobank ◽  
Case Control Studies ◽  
Polygenic Risk ◽  
Increased Risk ◽  
Artery Disease

Abstract Background There is growing evidence that polygenic risk scores (PRSs) can identify individuals with elevated lifetime risk of coronary artery disease (CAD). Whether they can also be used to stratify the risk of subsequent events among those surviving a first CAD event remain uncertain, with possible biological differences between CAD onset and progression, and the potential for index event bias. Methods Using two baseline subsamples of UK Biobank: prevalent CAD cases (N = 10 287) and individuals without CAD (N = 393 108), we evaluated associations between a CAD PRS and incident cardiovascular and fatal outcomes. Results A 1 SD higher PRS was associated with an increased risk of incident myocardial infarction (MI) in participants without CAD (OR 1.33; 95% CI 1.29, 1.38), but the effect estimate was markedly attenuated in those with prevalent CAD (OR 1.15; 95% CI 1.06, 1.25) and heterogeneity P = 0.0012. Additionally, among prevalent CAD cases, we found an evidence of an inverse association between the CAD PRS and risk of all-cause death (OR 0.91; 95% CI 0.85, 0.98) compared with those without CAD (OR 1.01; 95% CI 0.99, 1.03) and heterogeneity P = 0.0041. A similar inverse association was found for ischaemic stroke [prevalent CAD (OR 0.78; 95% CI 0.67, 0.90); without CAD (OR 1.09; 95% CI 1.04, 1.15), heterogeneity P < 0.001]. Conclusions Bias induced by case stratification and survival into UK Biobank may distort the associations of PRS derived from case-control studies or populations initially free of disease. Differentiating between effects of possible biases and genuine biological heterogeneity is a major challenge in disease progression research.

scholarly journals Validation of genome-wide polygenic risk scores for coronary artery disease in French Canadians

2019 ◽  
Author(s):  
Florian Wünnemann ◽  
Ken Sin Lo ◽  
Alexandra Langford-Avelar ◽  
David Busseuil ◽  
Marie-Pierre Dubé ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Scores ◽  
French Canadian ◽  
French Canadians ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Artery Disease ◽  
The Impact ◽  
Cad Risk

AbstractCoronary artery disease (CAD) represents one of the leading causes of morbidity and mortality worldwide. Given the healthcare risks and societal impacts associated with CAD, their clinical management would benefit from improved prevention and prediction tools. Polygenic risk scores (PRS) based on an individual’s genome sequence are emerging as potentially powerful biomarkers to predict the risk to develop CAD. Two recently derived genome-wide PRS have shown high specificity and sensitivity to identify CAD cases in European-ancestry participants from the UK Biobank. However, validation of the PRS predictive power and transferability in other populations is now required to support their clinical utility. We calculated both PRS (GPSCAD and metaGRSCAD) in French-Canadian individuals from three cohorts totaling 3639 prevalent CAD cases and 7382 controls, and tested their power to predict prevalent, incident and recurrent CAD. We also estimated the impact of the founder French-Canadian familial hypercholesterolemia deletion (LDLR delta > 15kb deletion) on CAD risk in one of these cohorts and used this estimate to calibrate the impact of the PRS. Our results confirm the ability of both PRS to predict prevalent CAD comparable to the original reports (area under the curve (AUC) = 0.72-0.84). Furthermore, the PRS identified about 6-7% of individuals at CAD risk similar to carriers of the LDLR delta > 15kb mutation, consistent with previous estimates. However, the PRS did not perform as well in predicting incident (AUC= 0.56 - 0.60) or recurrent (AUC= 0.56 - 0.60) CAD. This result suggests that additional work is warranted to better understand how ascertainment biases and study design impact PRS for CAD. Collectively, our results confirm that novel, genome-wide PRS are able to predict CAD in French-Canadians; with further improvements, this is likely to pave the way towards more targeted strategies to predict and prevent CAD-related adverse events.

Polygenic Risk Scores in Coronary Artery Disease and Atrial Fibrillation

2020 ◽  
Vol 29 (4) ◽  
pp. 634-640 ◽  
Author(s):  
Patrick A. Gladding ◽  
Malcolm Legget ◽  
Diane Fatkin ◽  
Peter Larsen ◽  
Robert Doughty
Keyword(s):  
Atrial Fibrillation ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Artery Disease
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