Linking common genetic variants to complex traits requires large-scale comparison. A genome-wide association study, or GWAS, scans hundreds of thousands to millions of genetic markers across many individuals to find statistical associations with a disease or trait.

Participants are genotyped, and allele frequencies are compared between cases and controls or correlated with quantitative measures. Associated loci often lie in non-coding regions and point to regulatory mechanisms. Replication in independent cohorts is essential for confidence.

GWAS have identified thousands of loci for traits such as height, diabetes, and schizophrenia. Effect sizes for common variants are usually small; polygenic risk scores sum many variants to estimate overall predisposition. The method has transformed the study of complex disease genetics.

• Study linking genetic variants to traits across the genome
• Compares large groups of individuals
• Identifies associated loci statistically
• Useful for complex polygenic traits