Higher eQTL power reveals signals that boost GWAS colocalization.

Area of Science:

• Genetics
• Genomics
• Molecular Biology

Background:

• Expression quantitative trait locus (eQTL) studies aim to link genetic variation to gene expression levels.
• eQTLs are proposed to mediate genetic liability for complex traits identified via genome-wide association studies (GWASs).
• Limited statistical power in current eQTL studies may hinder the detection of biologically relevant regulatory signals.

Purpose of the Study:

• To investigate the impact of sample size on eQTL detection power.
• To characterize eQTLs that are only detectable in larger sample sizes.
• To re-evaluate the colocalization of eQTL and GWAS signals with increased power.

Main Methods:

• Analysis of existing eQTL study data to estimate detection rates across different sample sizes.
• Comparison of characteristics (genomic distance, gene intolerance) of detectable vs. undetectable eQTLs.
• Meta-analysis of eQTL and GWAS data to assess colocalization frequency.

Main Results:

• Sample size significantly impacts eQTL detection; a sample size of 2,000 detects only 36.8% of eQTLs.
• eQTLs detectable in larger studies are located further from the regulated gene and associated with more intolerant genes.
• Increased sample size and meta-analysis reveal a higher rate of colocalization between eQTL and GWAS signals.

Conclusions:

• Underpowered eQTL studies may underestimate the role of gene expression in mediating GWAS-identified traits.
• Larger sample sizes are essential for comprehensive eQTL discovery and robust colocalization analysis.
• Future eQTL study designs should prioritize increased sample size to improve power and complement perturbation-based methods.