Functional evaluation of genetic variants associated with endometriosis near GREB1

• Published in: Human reproduction (Oxford) 2015-05, Vol.30 (5), p.1263-1275
• Main Authors: Fung, Jenny N., Holdsworth-Carson, Sarah J., Sapkota, Yadav, Zhao, Zhen Zhen, Jones, Lincoln, Girling, Jane E., Paiva, Premila, Healey, Martin, Nyholt, Dale R., Rogers, Peter A. W., Montgomery, Grant W.
• Format: Article
• Language: English
• Subjects: Chromosome Mapping; Computational Biology; Endometriosis - genetics; Endometrium - metabolism; Endometrium - pathology; Female; Gene Expression Regulation; Genetic Variation; Genome-Wide Association Study; Genotype; Humans; Immunohistochemistry; Neoplasm Proteins - genetics; Phenotype; Polymorphism, Single Nucleotide; Quantitative Trait Loci
• ISSN: 0268-1161; 1460-2350
• DOI: 10.1093/humrep/dev051

STUDY QUESTION Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2–45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT–PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late