ArticleAmerican journal of human genetics2026
Higher eQTL power reveals signals that boost GWAS colocalization.
Article in American journal of human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Assessing molecular gene by treatment interactions using a population of neural progenitors exposed to valproic acid and lithium.Molecular psychiatry · 2026Article
- Integrative genetic analysis identifies shared regulation of DNA methylation and gene expression in migraine risk.The journal of headache and pain · 2026Article
- Design and interpretation of eQTL-GWAS colocalisation studies: Lessons from a large-scale evaluation.PLoS genetics · 2026Article
- A meta-analysis of chromatin-associated loci provides insights into mechanistic interpretations of trait heritability.bioRxiv : the preprint server for biology · 2026Article
- Liver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits.American journal of human genetics · 2026Article
- Integrative single-cell eQTL and multi-omics analyses reveal AIM1 and ANXA1 as immune-related hub genes and potential therapeutic targets in head and neck cancer.Frontiers in oncology · 2026Article
- Quantification method affects replicability of eQTL analysis, colocalization, and TWAS.bioRxiv : the preprint server for biology · 2025Article
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Abstract
Expression quantitative trait locus (eQTL) studies in human cohorts typically detect at least one regulatory signal per gene and have been proposed as a way to explain mechanisms of genetic liability for other traits, as discovered in genome-wide association studies (GWASs). In particular, eQTL signals may colocalize with GWAS signals, suggesting gene expression as a possible mediator. However, recent studies have noted that colocalization occurs infrequently, even when expression is measured in biologically relevant tissues. Most eQTL studies to date include only hundreds of individuals and are underpowered to discover distal regulatory signals explaining smaller fractions of gene expression variance. Using evidence from recent eQTL studies, we demonstrate that limited statistical power due to sample size skews the detection of eQTL signals identified at various signal strengths. We estimate that a sample size of 500 detects <0.1% to 60% of eQTLs for a range of signal strengths and that a sample size of 2,000 detects 36.8% of eQTLs. We show that eQTL signals only discoverable in larger studies exhibit characteristics more similar to those of GWAS signals, including greater distance to the regulated gene and a higher probability of loss-of-function intolerance in the associated gene. Finally, using results from recent eQTL studies and meta-analyses, we observe a large increase in detected colocalizations with GWAS signals compared to previous studies. These findings caution against overinterpreting the absence of colocalization in underpowered studies and provide guidance for designing future eQTL experiments to improve power and complement perturbation-based approaches in characterizing gene-trait mechanisms.
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