Multi-omics Integration with GWAS Unveils Molecular Mechanistic Insights for Type 2 Diabetes

Area of Science:

• Genetics
• Molecular Biology
• Metabolic Disorders

Background:

• Type 2 Diabetes (T2D) is a complex metabolic disorder influenced by genetic and environmental factors.
• Genome-wide association studies (GWAS) have identified numerous T2D-associated variants, but many lack functional characterization.
• Integrating GWAS with molecular data aids in understanding the biological relevance of genetic variants.

Purpose of the Study:

• To investigate the functional impact of GWAS-identified variants, including sub-threshold ones, on gene and protein expression.
• To assign biological relevance to genetic variants associated with Type 2 Diabetes.
• To link molecular changes to T2D pathophysiology.

Main Methods:

• Expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) analyses were performed using whole-genome sequencing data and plasma protein profiles.
• Genetic variants from the GWAS Catalog were analyzed for their association with mRNA and protein levels in discovery and validation cohorts.
• Associations were tested using multiple linear regression, with stringent criteria for significance and replication.

Main Results:

• Identified 1,291 eQTLs affecting 97 mRNAs and 1,273 pQTLs affecting 22 proteins.
• Found 10 differentially expressed mRNAs and 5 proteins between diabetic and non-diabetic individuals.
• Key genes involved in lipid metabolism, beta-cell regulation, and immune response showed molecular effects consistent with T2D mechanisms.

Conclusions:

• Genetic variants below conventional GWAS significance thresholds can significantly impact gene and protein expression.
• Prioritizing biological relevance alongside statistical significance is crucial for understanding complex diseases like T2D.
• This study demonstrates the utility of molecular phenotyping in functionally characterizing T2D-associated genetic variants.