scholarly journals A polygenic risk score for coronary artery disease predicts early-onset myocardial infarction and mortality in men

2021 ◽  
Vol 13 (2) ◽  
pp. 201
Author(s):  
H.D. Manikpurage ◽  
A. Eslami ◽  
N. Perrot ◽  
Z. Li ◽  
C. Couture ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Early Onset ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Artery Disease

scholarly journals Polygenic Risk Score for Coronary Artery Disease Improves the Prediction of Early-Onset Myocardial Infarction and Mortality in Men

2021 ◽  
Author(s):  
Hasanga D. Manikpurage ◽  
Aida Eslami ◽  
Nicolas Perrot ◽  
Zhonglin Li ◽  
Christian Couture ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Predictive Accuracy ◽  
Hazard Ratio ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Artery Disease ◽  
Genetically Determined

Background: Several risk factors for coronary artery disease (CAD) have been described, some of which are genetically determined. The use of a polygenic risk score (PRS) could improve CAD risk assessment, but predictive accuracy according to age and sex is not well established. Methods: A PRS CAD including the weighted effects of >1.14 million SNPs associated with CAD was calculated in UK Biobank (n=408 422), using LDpred. Cox regressions were performed, stratified by age quartiles and sex, for incident myocardial infarction (MI) and mortality, with a median follow-up of 11.0 years. Improvement in risk prediction of MI was assessed by comparing PRS CAD to the pooled cohort equation with categorical net reclassification index using a 2% threshold (NRI 0.02 ) and continuous NRI (NRI >0 ). Results: From 7746 incident MI cases and 393 725 controls, hazard ratio for MI reached 1.53 (95% CI, 1.49–1.56; P =2.69×10 −296 ) per SD increase of PRS CAD . PRS CAD was significantly associated with MI in both sexes, with a stronger association in men (interaction P =0.002), particularly in those aged between 40 and 51 years (hazard ratio, 2.00 [95% CI, 1.86–2.16], P =1.93×10 −72 ). This group showed the highest reclassification improvement, mainly driven by the up-classification of cases (NRI 0.02 , 0.199 [95% CI, 0.157–0.248] and NRI >0 , 0.602 [95% CI, 0.525–0.683]). From 23 982 deaths, hazard ratio for mortality was 1.08 (95% CI, 1.06–1.09; P =5.46×10 −30 ) per SD increase of PRS CAD , with a stronger association in men (interaction P =1.60×10 −6 ). Conclusions: Our PRS CAD predicts MI incidence and all-cause mortality, especially in men aged between 40 and 51 years. PRS could optimize the identification and management of individuals at risk for CAD.

scholarly journals B-PO02-164 GENOME-WIDE POLYGENIC RISK SCORE PREDICTS SUDDEN ARRHYTHMIC DEATH IN PATIENTS WITH CORONARY ARTERY DISEASE

Heart Rhythm ◽  
2021 ◽  
Vol 18 (8) ◽  
pp. S164-S165
Author(s):  
Roopinder K. Sandhu ◽  
Jacqueline Dron ◽  
Yunxian Liu ◽  
Manickavasagar Vinayagamoorthy ◽  
Nancy R. Cook ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Arrhythmic Death ◽  
Genome Wide ◽  
Artery Disease

scholarly journals A Polygenic Risk Score for Coronary Artery Disease Improves the Prediction of Early-Onset Myocardial Infarction and Mortality in Men

2021 ◽  
Author(s):  
Hasanga D. Manikpurage ◽  
Aida Eslami ◽  
Nicolas Perrot ◽  
Zhonglin Li ◽  
Christian Couture ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Predictive Accuracy ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Artery Disease ◽  
Genetically Determined

ABSTRACTBackgroundSeveral risk factors for coronary artery disease (CAD) have been described, some of which are genetically determined. The use of a polygenic risk score (PRS) could improve CAD risk assessment, but predictive accuracy according to age and sex is not well established.MethodsA PRSCAD including the weighted effects of >1.14 million SNPs associated with CAD was calculated in UK Biobank (n=408,422), using LDPred. Cox regressions were performed, stratified by age quartiles and sex, for incident MI and mortality, with a median follow-up of 11.0 years. Improvement in risk prediction of MI was assessed by comparing PRSCAD to the pooled cohort equation with categorical net reclassification index using a 2% threshold (NRI0.02) and continuous NRI (NRI>0).ResultsFrom 7,746 incident MI cases and 393,725 controls, hazard ratio (HR) for MI reached 1.53 (95% CI [1.49-1.56], p=2.69e-296) per standard deviation (SD) increase of PRSCAD. PRSCAD was significantly associated with MI in both sexes, with a stronger association in men (interaction p=0.002), particularly in those aged between 40-51 years (HR=2.00, 95% CI [1.86-2.16], p=1.93e-72). This group showed the highest reclassification improvement, mainly driven by the up-classification of cases (NRI0.02=0.199, 95% CI [0.157-0.248] and NRI>0=0.602, 95% CI [0.525-0.683]). From 23,982 deaths, HR for mortality was 1.08 (95% CI [1.06-1.09], p=5.46e-30) per SD increase of PRSCAD, with a stronger association in men (interaction p=1.60e-6).ConclusionOur PRSCAD predicts MI incidence and all-cause mortality, especially in men aged between 40-51 years. PRS could optimize the identification and management of individuals at risk for CAD.

scholarly journals POLYGENIC RISK SCORE FOR CORONARY ARTERY DISEASE ASSOCIATES WITH INCIDENCE OF CALCIFIC AORTIC STENOSIS

2021 ◽  
Vol 77 (18) ◽  
pp. 1725
Author(s):  
Shady Abohashem ◽  
Michael Osborne ◽  
Taimur Abbasi ◽  
Hadil Zureigat ◽  
Tawseef Dar ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Aortic Stenosis ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Calcific Aortic Stenosis ◽  
Polygenic Risk ◽  
Artery Disease

scholarly journals Predictive Accuracy of a Polygenic Risk Score–Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease

JAMA ◽  
2020 ◽  
Vol 323 (7) ◽  
pp. 636 ◽  
Author(s):  
Joshua Elliott ◽  
Barbara Bodinier ◽  
Tom A. Bond ◽  
Marc Chadeau-Hyam ◽  
Evangelos Evangelou ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Prediction Model ◽  
Risk Score ◽  
Predictive Accuracy ◽  
Polygenic Risk Score ◽  
Clinical Risk Score ◽  
Polygenic Risk ◽  
Clinical Risk ◽  
Artery Disease

scholarly journals Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction

2021 ◽  
Vol 14 (2) ◽  
Author(s):  
Fernando Riveros-Mckay ◽  
Michael E. Weale ◽  
Rachel Moore ◽  
Saskia Selzam ◽  
Eva Krapohl ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Disease Risk ◽  
The United States ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Artery Disease

Background: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. Methods: Using the UK Biobank resource, we developed our own polygenic risk score for coronary artery disease (CAD). We used an additional 60 000 UK Biobank individuals to develop an integrated risk tool (IRT) that combined our polygenic risk score with established risk tools (either the American Heart Association/American College of Cardiology pooled cohort equations [PCE] or UK QRISK3), and we tested our IRT in an additional, independent set of 186 451 UK Biobank individuals. Results: The novel CAD polygenic risk score shows superior predictive power for CAD events, compared with other published polygenic risk scores, and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an IRT, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared with 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI, 4.7–7.0). When individuals were stratified into age-by-sex subgroups, the improvement was larger for all subgroups (range, 8.3%–15.4%), with the best performance in 40- to 54-year-old men (15.4% [95% CI, 11.6–19.3]). Comparable results were found using a different risk tool (QRISK3) and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12 000 deaths in the United States over a 5-year period. Conclusions: An IRT that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person’s polygenic risk.

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