The article examines the impact of population structure on large-scale genetic association studies, which are crucial for understanding the genetic basis of common human diseases. The authors analyze approximately 15,000 genome-wide single-nucleotide polymorphisms (SNPs) typed in three population groups (European Americans, African Americans, and Asians) to assess the consequences of population structure. They find that the effects of population structure on association outcomes increase with sample size, and even modest levels of population structure within population groups can lead to significant issues. The authors also evaluate the Genomic Control method for correcting population structure, noting that it may not be effective if too few loci are used and can overcorrect in other settings, leading to a loss of power. The results highlight the importance of accounting for population structure in the design of large-scale association studies to avoid false positives and missed genuine associations.The article examines the impact of population structure on large-scale genetic association studies, which are crucial for understanding the genetic basis of common human diseases. The authors analyze approximately 15,000 genome-wide single-nucleotide polymorphisms (SNPs) typed in three population groups (European Americans, African Americans, and Asians) to assess the consequences of population structure. They find that the effects of population structure on association outcomes increase with sample size, and even modest levels of population structure within population groups can lead to significant issues. The authors also evaluate the Genomic Control method for correcting population structure, noting that it may not be effective if too few loci are used and can overcorrect in other settings, leading to a loss of power. The results highlight the importance of accounting for population structure in the design of large-scale association studies to avoid false positives and missed genuine associations.