Prediction of disease risk is an essential part of preventative medicine, often guiding clinical
management. Risk prediction typically includes risk factors such as age, sex, family history …

Recent advances in genome-wide association studies have stimulated interest in the genomic
prediction of disease risk, potentially enabling individual-level risk estimates for early …

Background : Coronary artery disease (CAD) has substantial heritability and a polygenic
architecture. However, the potential of genomic risk scores to help predict CAD outcomes has …

We present the Polygenic Score (PGS) Catalog ( https://www.PGSCatalog.org ), an open
resource of published scores (including variants, alleles and weights) and consistently curated …

Principal component analysis (PCA) is routinely used to analyze genome-wide single-nucleotide
polymorphism (SNP) data, for detecting population structure and potential outliers. …

Aims Genetics plays an important role in coronary heart disease (CHD) but the clinical utility
of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk …

Motivation Principal component analysis (PCA) is a crucial step in quality control of genomic
data and a common approach for understanding population genetic structure. With the …

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of
disease prevention. Clinical risk scores have been widely used for predicting CVD risk from …

The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular
disease and all-cause mortality. Here, we characterize biological processes associated …

Background Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease
(CVD) risk groups. We aimed to quantify the potential advantage of adding information on …