INTRODUCTION: Endometriosis is a complex gynaecological disease affecting ~10% of women, causing chronic pelvic pain and infertility. It is influenced by both environmental and genetic factors. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with endometriosis. However, identification of SNPs alone cannot determine which gene(s) are responsible for endometriosis. Therefore, we need to determine if individual SNPs have downstream effects on gene expression. SNPs that influence gene expression are termed expression quantitative trait loci (eQTL).
METHODS: Blood and endometrium were collected at the Royal Women’s Hospital (n=591). Blood samples were genotyped using Human CoreExome chips. Endometrial gene expression was generated using Illumina Human HT-12 v4.0 Beadchips. eQTL analysis was performed on tissues with recoded SNP genotypes based on minor allele dosage and ﬁtted linear regression models, with menstrual cycle phases included as a covariate. eQTL gene lists were analysed by Ingenuity Pathways Analysis (IPA) for functional pathway studies.
RESULTS: GWAS have identified seven genomic regions with multiple target genes per region. LINC00339 is the most significant endometrial eQTL, with decreased expression associated with increased endometriosis risk. Vezatin was also identified as a significant eQTL; increased endometrial expression associated with increased endometriosis risk. Some significant eQTLs have been investigated at the protein level (eg. GREB1, WNT4 and VEZT). Interestingly, several SNPs have multiple significant eQTLs. IPA analysis on eQTLs reveal recognised gene pathways for endometriosis (eg. inflammation) and some novel pathways.
CONCLUSIONS: eQTL analyses are important for improving understanding of complex diseases, including endometriosis. Ongoing studies are examining the roles and pathways of these eQTLs in endometriosis pathophysiology; studies are also working to identify additional eQTLs as a means to help explain how genetic variants linked to increased endometriosis-risk cause disease.
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