AB028. Identifying the functional role of VEZT gene for endometriosis risk

Endometriosis is a common, chronic gynaecological disease characterised by pelvic pain and sub-fertility. It is a complex genetic disease affecting of 6-10% women of reproductive age and up to 50% of women with infertility. Evidence from genomewide association (GWA) imputed and meta-analysis studies in women with and without endometriosis identified association on chromosome 12q22, located close to the putative candidate gene VEZT. Fine-mapping this region in our 1,029 Australian cases and 958 controls confirmed strong evidence of association for non-coding variants in the 12q22 GWA region with the best imputed SNP rs4762347 in the 3’UTR of VEZT (P=0.036; 95% CI, 1.01-1.38; OR =1.18) and four top imputed SNPs in high linkage disequilibrium (LD) with rs4762347. Bioinformatic analysis for potential functional roles for these SNPs using ENCODE data show rs4762347 is highly conserved and alters a regulatory motif for the transcription factor Nkx3. We conducted an initial experiment to evaluate gene expression of VEZT in 36 samples of endometrial tissue from endometriosis cases and controls using high-throughput gene expression RT-qPCR on a microfluidic dynamic array IFC 48x48 chip (Fluidigm Biomark). The results showed that VEZT was expressed in endometrial samples from cases and controls. There was a trend for increased expression levels of VEZT mRNAs in endometriosis cases compared to controls as well as during the secretory phase compared to proliferative phase of menstrual cycle, although these differences were not statistically significant. The top imputed SNP rs4762347 was chosen to test for its allelic effects on VEZT expression. There was suggestive evidence for differences in VEZT mRNA expression observed in allelic groups of rs4762347. VEZT mRNA expression decreased for transcripts in carriers of minor C allele (CC and CT) of rs4762347 compared to non carriers (TT) (P<0.01), but the differences were no longer significant after corrections for multiple testing, hence further gene expression studies should be conducted in a larger sample size.