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Open AccessJournal ArticleDOI

Clinical Utility of Lipoprotein(a) and LPA Genetic Risk Score in Risk Prediction of Incident Atherosclerotic Cardiovascular Disease

TLDR
Both measured lipoprotein(a) and LPA GRS were associated with comparable risk of incident ASCVD events and both yielded modest improvements in the discrimination of ASCVD risk relative to the Pooled Cohort Equations or QRISK3.
Abstract
Importance Lipoprotein(a) is a highly heritable biomarker independently associated with atherosclerotic cardiovascular disease (ASCVD). It is unclear whether measured lipoprotein(a) or genetic factors associated with lipoprotein(a) can provide comparable or additional prognostic information for primary prevention. Objective To determine whether a genetic risk score (GRS) comprising 43 variants at theLPAgene, which encodes apolipoprotein(a), has clinical utility in assessing ASCVD risk compared with and in addition to lipoprotein(a) measurement. Design, Setting, and Participants The UK Biobank is a prospective observational study of approximately 500 000 volunteers aged 40 to 69 years who were recruited from 22 sites across the United Kingdom between 2006 and 2010. Using externally derived weights, anLPAGRS was calculated for 374 099 unrelated individuals with array-derived genotypes and lipoprotein(a) measures. Data were analyzed from April 2020 to March 2020. Exposures Measured lipoprotein(a) andLPAGRS. Main Outcomes and Measures We estimated the associations between measured lipoprotein(a) andLPAGRS with the incidence of ASCVD (peripheral arterial disease, coronary artery disease, myocardial infarction, ischemic stroke, and cardiovascular mortality) using Cox proportional hazards models. To determine the utility of using measured lipoprotein(a) andLPAGRS as risk enhancers for ASCVD, we assessed the potential improvement in ASCVD risk discrimination by QRISK3 and Pooled Cohort Equations among individuals with borderline to intermediate risk (n = 113 703 and 144 350, respectively). Results The mean age of the overall study population was 57.6 years, and 204 355 individuals were female (54.6%). During a median follow-up of 11.1 years (interquartile range, 1.4 years), 15 444 individuals developed an incident ASCVD event (5.1%). TheLPAGRS explained approximately 60% of the variation in measured lipoprotein(a) for White/European individuals. Independently, both lipoprotein(a) andLPAGRS were associated with incident, composite ASCVD (hazard ratio per 120 nmol/L increase, 1.26; 95% CI, 1.23-1.28 vs hazard ratio, 1.29; 95% CI, 1.26-1.33;P  Conclusions and Relevance When indicated, cardiovascular risk assessment with lipoprotein(a) at middle-age may include direct measurement or anLPAGRS.

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Protein-coding repeat polymorphisms strongly shape diverse human phenotypes.

TL;DR: In this paper, the relationship of VNTRs to most pheno-nomenclature domains was investigated and it was shown that the relationship was not robust to variations in the number of tandem repeat (VNTR) in protein coding exons.
Journal ArticleDOI

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

TL;DR: The contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases are reviewed and 5 cardiometabolic diseases are selected and response to drug therapy is selected to offer provisional guidance to health care professionals, researchers, policymakers, and patients.
Journal ArticleDOI

Lipoprotein(a) beyond the kringle IV repeat polymorphism: The complexity of genetic variation in the LPA gene

TL;DR: A comprehensive overview of the complex genetic architecture of the Lp(a) concentrations in plasma can be found in this article , where a hypervariable coding copy number variation (the kringle IV type-2 repeat, KIV-2) generates >40 apolipoprotein (a) protein isoforms and determines the median LDL-1 concentrations.
Journal ArticleDOI

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

- 23 Aug 2022 - 
TL;DR: A review of the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases is presented in this article , where five cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy are selected.
References
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mice: Multivariate Imputation by Chained Equations in R

TL;DR: Mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs.
Journal ArticleDOI

pROC: an open-source package for R and S+ to analyze and compare ROC curves

TL;DR: pROC as mentioned in this paper is a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface.
Journal ArticleDOI

2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular riskThe Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS)

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