Difficulty identifying causal variants: GWAS can find statistical associations, but pinpointing the exact causal variant and understanding the underlying biology is challenging.

European-ancestry bias: Most GWAS are based on populations of European ancestry, limiting our understanding of genetics across diverse populations and creating potential inequities in clinical applications.

Clinical application of disease risk estimates: Using disease risk estimates from GWAS in clinical care remains unclear, and translating findings into practical treatments is challenging.

Inequity in clinical translation: The lack of diverse representation in GWAS can cause skewed results, potentially leading to biased or less effective clinical treatments for non-European populations.

Learn: Association Analysis (Genomics)