ReviewEuropean journal of human genetics : EJHG2025
Twenty years of genome-wide association studies: Health translation challenges and AI opportunities.
Review in European journal of human genetics : EJHG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Enhanced identification of key bacterial motility genes via a cross-species genomic hybrid feature machine learning approach.BMC genomics · 2026Article
- Association of the TNFRSF1A genotype with lung function impairment in patients with sarcoidosis.Scientific reports · 2026Article
- Alzheimer's disease: genetic background in the era of next-generation sequencing technologies.Brain communications · 2026Review
- Genome-wide association study of post-harvest physiological deterioration in cassava (Frontiers in plant science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.