The article highlights the ongoing issue of genomic diversity in genome-wide association studies (GWAS). Despite an increase in the representation of non-European populations, particularly in Asian studies, the overall diversity remains limited. The analysis by Alice B. Popejoy and Stephanie M. Fullerton reveals that while the proportion of non-European participants in GWAS has increased to nearly 20%, the majority of this growth is due to studies in East Asia, South Asia, and Southeast Asia. Populations of African and Latin American ancestry, Hispanic people, and indigenous peoples remain underrepresented, accounting for less than 4% of all samples. This bias is attributed to logistical, systemic, and historical factors, including the preference for existing cohorts and the lack of awareness of diverse data sets. The underrepresentation of these populations means that important information about disease biology and drug responses is being missed, leading to potential inaccuracies and inefficiencies in precision medicine. The authors advocate for more diverse cohorts, financial incentives from funding agencies, and cultural shifts to address this issue.The article highlights the ongoing issue of genomic diversity in genome-wide association studies (GWAS). Despite an increase in the representation of non-European populations, particularly in Asian studies, the overall diversity remains limited. The analysis by Alice B. Popejoy and Stephanie M. Fullerton reveals that while the proportion of non-European participants in GWAS has increased to nearly 20%, the majority of this growth is due to studies in East Asia, South Asia, and Southeast Asia. Populations of African and Latin American ancestry, Hispanic people, and indigenous peoples remain underrepresented, accounting for less than 4% of all samples. This bias is attributed to logistical, systemic, and historical factors, including the preference for existing cohorts and the lack of awareness of diverse data sets. The underrepresentation of these populations means that important information about disease biology and drug responses is being missed, leading to potential inaccuracies and inefficiencies in precision medicine. The authors advocate for more diverse cohorts, financial incentives from funding agencies, and cultural shifts to address this issue.