This article discusses the challenges of interpreting genome-wide association studies (GWASs) in the presence of confounding factors. It highlights that while family-based GWASs are often considered to provide unbiased estimates of direct genetic effects, they can still be affected by genetic confounding. The study shows that genetic confounding can lead to biased estimates of direct effects, especially when effect-size estimates are used in polygenic scores (PGSs). The authors analyze various sources of genetic confounding, including assortative mating, population structure, and stabilizing selection on GWAS traits. They demonstrate that family-based estimates of indirect genetic effects can also suffer from significant confounding. The study concludes that while family-based studies have improved the rigor of GWAS estimation, they still face subtle interpretation issues due to confounding. The article provides a theoretical analysis of how confounding influences effect-size estimates in both population-based and family-based GWASs, emphasizing the importance of understanding and addressing these confounding factors in genetic research.This article discusses the challenges of interpreting genome-wide association studies (GWASs) in the presence of confounding factors. It highlights that while family-based GWASs are often considered to provide unbiased estimates of direct genetic effects, they can still be affected by genetic confounding. The study shows that genetic confounding can lead to biased estimates of direct effects, especially when effect-size estimates are used in polygenic scores (PGSs). The authors analyze various sources of genetic confounding, including assortative mating, population structure, and stabilizing selection on GWAS traits. They demonstrate that family-based estimates of indirect genetic effects can also suffer from significant confounding. The study concludes that while family-based studies have improved the rigor of GWAS estimation, they still face subtle interpretation issues due to confounding. The article provides a theoretical analysis of how confounding influences effect-size estimates in both population-based and family-based GWASs, emphasizing the importance of understanding and addressing these confounding factors in genetic research.