Exploring potential causal genetic variants and genes for endometrial cancer: Open Targets Genetics, Mendelian randomization, and multi-tissue transcriptome-wide association analysis.

BACKGROUND

Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods.

METHODS

We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC.

RESULTS

The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, and , exhibiting a significant pleiotropic association with EC. Cross-tissue TWAS identified 31 genes whose expression was significantly associated with EC after correction for multiple testing, with four genes (, , , and ) also confirmed by gene colocalization in the OTG analysis.

CONCLUSIONS

We confirmed the involvement of in the pathogenesis of EC and identified several other genes that may contribute to EC development. These findings offer new insights into the genetic mechanisms underlying EC and may inform future research and therapeutic strategies.