Hormone-dependent cancers (HDC) are among the leading causes of death worldwide among both men and women. Some of the established risk factors of HDC include unhealthy lifestyles, environmental factors, and genetic influences. Numerous studies have been conducted to understand gene–cancer associations. Transcriptome-wide association studies (TWAS) integrate data from genome-wide association studies (GWAS) and gene expression (expression quantitative trait loci – eQTL) to yield meaningful information on biological pathways associated with complex traits/diseases. Recently, TWAS have enabled the identification of novel associations between HDC risk and protein-coding genes.
In the present study, we performed a TWAS analysis using the summary data-based Mendelian randomization (SMR)–heterogeneity in dependent instruments (HEIDI) method to identify microRNAs (miRNAs), a group of non-coding RNAs (ncRNAs) associated with HDC risk. We obtained eQTL and GWAS summary statistics from the ncRNA-eQTL database and the National Human Genome Research Institute–European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog.
We identified 13 TWAS-significant miRNAs at
Overall, identifying risk-associated miRNAs across a group of related cancers may help to understand cancer biology and provide novel insights into cancer genetic mechanisms. This customized approach can be applied to identify significant miRNAs in any trait/disease of interest.