Consensus Genome-Wide Expression Quantitative Trait Loci and Their Relationship with Human Complex Trait Disease

Area of Science:

• Genetics
• Genomics
• Molecular Biology

Background:

• Genome-wide association (GWA) studies identify disease risk loci but often lack biological insight.
• Expression quantitative trait loci (eQTL) studies link genetic variations to gene expression, potentially explaining disease susceptibility.
• Low reproducibility in eQTL studies hinders interpretation of genetic contributions to disease.

Purpose of the Study:

• To generate a robust set of consensus eQTLs by integrating diverse public datasets.
• To investigate the role of eQTLs in common human diseases by linking them to known GWA risk loci.
• To determine the proportion of disease risk loci potentially explained by altered gene expression.

Main Methods:

• Integrated publicly available eQTL data across different human populations and cell types to establish high-confidence eQTLs.
• Compiled a dataset of 335 disease risk loci from GWA studies for seven complex human diseases.
• Matched consensus eQTLs with disease risk loci to assess the contribution of expression changes to disease susceptibility.

Main Results:

• Identified over 4000 genes with high-confidence eQTL relationships.
• Found that approximately 50% of the investigated disease risk loci are consistent with an underlying gene expression change mechanism.
• Demonstrated a significant overlap between eQTLs and loci associated with complex traits including bipolar disorder, coronary artery disease, and diabetes.

Conclusions:

• Consensus eQTL analysis provides a more reliable method for identifying genetic factors influencing gene expression.
• Gene expression variation mediated by eQTLs is a significant mechanism contributing to the genetic basis of common human diseases.
• This approach enhances the biological interpretation of GWA findings and aids in understanding disease etiology.