Twenty years of genome-wide association studies: Health translation challenges and AI opportunities

A landmark genome-wide association study (GWAS) in 2005 led to a major discovery about the genetics of age-related macular degeneration. Since then, thousands of GWAS have been published and tens of thousands of genomic loci have been reported for association with human traits ranging from established ones (e.g. height, cardiovascular disease) to unconventional ones (e.g. same-sex sexual behavior, family income). While some claim that GWAS has already fulfilled its promises, we argue that it has yet to fully showcase its power in unraveling the secrets of the human genome and its links to phenotypes. The March 2025 bankruptcy of 23andMe serves as a stark reminder of the limited translational value of GWAS to the general public. The GWAS research community can achieve more only if we begin with a sober and objective assessment. Here, we first outline "Four Persistent Obstacles" that continue to hinder GWAS progress and discuss how a "Global Research Ecosystem" may be well-positioned to overcome them. We also highlight the transformative rise of artificial intelligence (AI) exemplified by AlphaFold's unprecedented power in predicting protein structures. Finally, we introduce a novel concept, the "trait efficiency locus (TEL)", as a complement to the widely used quantitative trait locus (QTL) framework, providing a new lens for evaluating genetic discoveries. One could also term it "structural trait locus (STL)", but "TEL" emphasizes the central idea that efficiency is what ultimately matters.