The vast majority of genome-wide association study (GWAS) findings reported to date are
from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic …

Background Accurate assessment of health disparities requires unbiased knowledge of
genetic risks in different populations. Unfortunately, most genome-wide association studies …

This study investigates the creation of polygenic scores (PGS) s for human population
research. PGSs are a linear, usually weighted, combination of risk alleles that estimate the …

African populations are vastly underrepresented in genetic studies but have the most
genetic variation and face wide-ranging environmental exposures globally. Because …

Polygenic risk scores (PRSs) are weighted sums of risk allele counts of single‐nucleotide
polymorphisms (SNPs) associated with a disease or trait. PRSs are typically constructed …

Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects
across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast …

The genotyping of millions of human samples has made it possible to evaluate variants
across the human genome for their possible association with risks for numerous diseases …

As most existing genome-wide association studies (GWASs) were conducted in European-
ancestry cohorts, and as the existing polygenic risk score (PRS) models have limited …

Polygenic risk scores suffer reduced accuracy in non-European populations, exacerbating
health disparities. We propose PolyPred, a method that improves cross-population …

Logistic regression is often used instead of Cox regression to analyse genome-wide
association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease …