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Study Question: Are genetic effects on endometrial gene expression tissue specific and/or associated with reproductive traits and diseases?, Summary Answer: Analyses of RNA-sequence data and individual genotype data from the endometrium identified novel and disease associated, genetic mechanisms regulating gene expression in the endometrium and showed evidence that these mechanisms are shared across biologically similar tissues., What Is Known Already: The endometrium is a complex tissue vital for female reproduction and is a hypothesized source of cells initiating endometriosis. Understanding genetic regulation specific to, and shared between, tissue types can aid the identification of genes involved in complex genetic diseases., Study Design, Size, Duration: RNA-sequence and genotype data from 206 individuals was analysed and results were compared with large publicly available datasets., Participants/materials, Setting, Methods: RNA-sequencing and genotype data from 206 endometrial samples was used to identify the influence of genetic variants on gene expression, via expression quantitative trait loci (eQTL) analysis and to compare these endometrial eQTLs with those in other tissues. To investigate the association between endometrial gene expression regulation and reproductive traits and diseases, we conducted a tissue enrichment analysis, transcriptome-wide association study (TWAS) and summary data-based Mendelian randomisation (SMR) analyses. Transcriptomic data was used to test differential gene expression between women with and without endometriosis., Main Results and the Role of Chance: A tissue enrichment analysis with endometriosis genome-wide association study summary statistics showed that genes surrounding endometriosis risk loci were significantly enriched in reproductive tissues. A total of 444 sentinel cis-eQTLs (P < 2.57 × 10-9) and 30 trans-eQTLs (P < 4.65 × 10-13) were detected, including 327 novel cis-eQTLs in endometrium. A large proportion (85%) of endometrial eQTLs are present in other tissues. Genetic effects on endometrial gene expression were highly correlated with the genetic effects on reproductive (e.g. uterus, ovary) and digestive tissues (e.g. salivary gland, stomach), supporting a shared genetic regulation of gene expression in biologically similar tissues. The TWAS analysis indicated that gene expression at 39 loci is associated with endometriosis, including five known endometriosis risk loci. SMR analyses identified potential target genes pleiotropically or causally associated with reproductive traits and diseases including endometriosis. However, without taking account of genetic variants, a direct comparison between women with and without endometriosis showed no significant difference in endometrial gene expression., Large Scale Data: The eQTL dataset generated in this study is available at http://reproductivegenomics.com.au/shiny/endo&#95;eqtl&#95;rna/. Additional datasets supporting the conclusions of this article are included within the article and the supplementary information files, or are available on reasonable request., Limitations, Reasons for Caution: Data are derived from fresh tissue samples and expression levels are an average of expression from different cell types within the endometrium. Subtle cell-specifc expression changes may not be detected and differences in cell composition between samples and across the menstrual cycle will contribute to sample variability. Power to detect tissue specific eQTLs and differences between women with and without endometriosis was limited by the sample size in this study. The statistical approaches used in this study identify the likely gene targets for specific genetic risk factors, but not the functional mechanism by which changes in gene expression may influence disease risk., Wider Implications of the Findings: Our results identify novel genetic variants that regulate gene expression in endometrium and the majority of these are shared across tissues. This allows analysis with large publicly available datasets to identify targets for female reproductive traits and diseases. Much larger studies will be required to identify genetic regulation of gene expression that will be specific to endometrium., Study Funding/competing Interest(s): This work was supported by the National Health and Medical Research Council (NHMRC) under project grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321, GNT1083405 and GNT1107258. G.W.M is supported by a NHMRC Fellowship (GNT1078399). J.Y is supported by an ARC Fellowship (FT180100186). There are no competing interests., (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.)

Study Question: Do genetic effects regulate gene expression in human endometrium?, Summary Answer: This study demonstrated strong genetic effects on endometrial gene expression and some evidence for genetic regulation of gene expression in a menstrual cycle stage-specific manner., What Is Known Already: Genetic effects on expression levels for many genes are tissue specific. Endometrial gene expression varies across menstrual cycle stages and between individuals, but there are limited data on genetic control of expression in endometrium., Study Design, Size, Duration: We analysed genome-wide genotype and gene expression data to map cis expression quantitative trait loci (eQTL) in endometrium., Participants/materials, Setting, Methods: We recruited 123 women of European ancestry. DNA samples from blood were genotyped on Illumina HumanCoreExome chips. Total RNA was extracted from endometrial tissues. Whole-transcriptome profiles were characterized using Illumina Human HT-12 v4.0 Expression Beadchips. We performed eQTL mapping with ~8 000 000 genotyped and imputed single nucleotide polymorphisms (SNPs) and 12 329 genes., Main Results and the Role of Chance: We identified a total of 18 595 cis SNP-probe associations at a study-wide level of significance (P < 1 × 10-7), which correspond to independent eQTLs for 198 unique genes. The eQTLs with the largest effect in endometrial tissue were rs4902335 for CHURC1 (P = 1.05 × 10-32) and rs147253019 for ZP3 (P = 8.22 × 10-30). We further performed a context-specific eQTL analysis to investigate if genetic effects on gene expression regulation act in a menstrual cycle-specific manner. Interestingly, five cis-eQTLs were identified with a significant stage-by-genotype interaction. The strongest stage interaction was the eQTL for C10ORF33 (PYROXD2) with SNP rs2296438 (P = 2.0 × 10-4), where we observe a 2-fold difference in the average expression levels of heterozygous samples depending on the stage of the menstrual cycle., Large Scale Data: The summary eQTL results are publicly available to browse or download., Limitations, Reasons for Caution: A limitation of the present study was the relatively modest sample size. It was not powered to identify trans-eQTLs and larger sample sizes will also be needed to provide better power to detect cis-eQTLs and cycle stage-specific effects, given the substantial changes in expression across the menstrual cycle for many genes., Wider Implications of the Findings: Identification of endometrial eQTLs provides a platform for better understanding genetic effects on endometriosis risk and other endometrial-related pathologies., Study Funding/competing Interest(s): Funding for this work was provided by NHMRC Project Grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321 and APP1083405. There are no competing interests., (© The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com)

Study Question: Do endometriosis risk-associated single nucleotide polymorphisms (SNPs) found at the 12q22 locus have effects on vezatin ( ITALIC! VEZT) expression?, Summary Answer: The original genome-wide association study (GWAS) SNP (rs10859871), and other newly identified association signals, demonstrate strong evidence for ITALIC! cis-expression quantitative trait loci (eQTL) effects on ITALIC! VEZT expression., What Is Known Already: GWAS have identified several disease-risk loci (SNPs) associated with endometriosis. The SNP rs10859871 is located within the ITALIC! VEZT gene. ITALIC! VEZT expression is altered in the endometrium of endometriosis patients and is an excellent candidate for having a causal role in endometriosis. Most of the SNPs identified from GWAS are not located within the coding region of the genome. However, they are likely to have an effect on the regulation of gene expression. Genetic variants that affect levels of gene expression are called expression quantitative trait loci (eQTL)., Study Design, Size, Duration: Samples for genotyping and ITALIC! VEZT variant screening were drawn from women recruited for genetic studies in Australia/New Zealand and women undergoing surgery in a tertiary care centre. Coding variants for ITALIC! VEZT were screened in blood from 100 unrelated individuals (endometriosis-dense families) from the QIMR Berghofer Medical Research Institute dataset. SNPs at the 12q22 locus were imputed and reanalysed for their association with endometriosis. Reanalysis of endometriosis risk-association was performed on a final combined Australian dataset of 2594 cases and 4496 controls. Gene expression was performed on 136 endometrial samples. eQTL analysis in whole blood was performed on 862 individuals from the Brisbane Systems Genetics Study. Endometrial tissue-specific eQTL analysis was performed on 122 samples (eutopic endometrium) collected following laparoscopic surgery. VEZT protein expression studies employed ITALIC! n = 56 (western blotting) and ITALIC! n = 42 (immunohistochemistry) endometrial samples., Participants/materials, Setting, Methods: The women recruited for this study provided blood and/or endometrial tissue samples in a hospital setting. Genomic DNA was screened for common and coding variants. SNPs of interest in the 12q22 region were genotyped using Agena MassARRAY technology or Taqman SNP genotyping assay. Gene expression profiles from RNA extracted from blood and endometrial tissue samples were generated using Illumina whole-genome expression chips (Human HT-12 v4.0). Whole protein extracted from endometrium was used for VEZT western blots, and paraffin sections of endometrium were employed for VEZT immunohistochemistry semi-quantitative analysis., Main Results and the Role of Chance: A total of 11 coding variants of ITALIC! VEZT (including one novel variant) were identified from an endometriosis-dense cohort. Polymorphic coding and imputed SNPs were combined with previous GWAS data to reanalyse the endometriosis risk association of the 12q22 region. The disease association signal at 12q22 was due to coding variants in ITALIC! VEZT or ITALIC! FGD6 (FYVE, RhoGEF and PH domain-containing 6) and SNPs with the strongest signals were either intronic or intergenic. We found strong evidence for ITALIC! VEZT cis-eQTLs with the sentinel SNP (rs10859871) in blood and endometrium, where the endometriosis risk allele (C) was associated with an increase in ITALIC! VEZT expression. We could not demonstrate this genotype-specific effect on VEZT protein expression in endometrium. However, we did observe a menstrual cycle stage specific increase in VEZT protein expression in endometrial glands, specific to the secretory phase ( ITALIC! P = 2.0 × 10(-4))., Limitations, Reasons for Caution: In comparison to the blood sample datasets, the study numbers of endometrial tissues were substantially reduced. Protein studies failed to complement RNA results, also likely a reflection of the low study numbers in these experiments. ITALIC! In silico prediction tools used in this investigation are typically based on cell lines different to our tissues of interest, thus any functional annotations drawn from these approaches should be considered carefully. Therefore, functional studies on VEZT and related pathway components are still warranted to unequivocally implicate a causal role for VEZT in endometriosis pathophysiology., Wider Implications of the Findings: GWAS have proven to be very valuable tools for deciphering complex diseases. Endometriosis is a text-book example of a complex disease, involving genetic, lifestyle and environmental influences. Our focused investigation of the 12q22 region validates an association with increased endometriosis risk. Endometriosis risk SNPs (including rs10859871) located within this locus demonstrated evidence for ITALIC! cis-eQTLs on ITALIC! VEZT expression. By examining women who possess an enhanced genetic risk of developing endometriosis, we have identified an effect on ITALIC! VEZT expression and therefore a potential gene/gene pathway in endometriosis disease establishment and development., Study Funding/competing Interests: Funding for this work was provided by NHMRC Project Grants GNT1012245, GNT1026033, GNT1049472 and GNT1046880. G.W.M. is supported by the NHMRC Fellowship scheme (GNT1078399). S.J.H.-C. is supported by the J.N. Peters Bequest Fellowship. The authors declare no competing interests., Trial Registration Number: N/A., (© The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

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 proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes., Limitations, Reasons for Caution: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples., Wider Implications of the Findings: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology., Study Funding/competing Interests: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests., (© The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Endometriosis is a common estrogen-dependent gynecological disease influenced by multiple genetic and environmental factors. Genome-wide association studies (GWAS) have identified eight genomic regions with strong evidence for association with endometriosis risk and excellent replication in multiple studies. The results represent a significant breakthrough toward understanding endometriosis. However, the significance can be realized only when the associated DNA sequence variation is linked to the altered regulation and/or function of specific genes and pathways modifying endometriosis risk. This review sets out the multiple steps required to interpret the genetic association results, identify the specific genes likely to be responsible for the altered risk within each region, and obtain the necessary genomic evidence connecting the genetic results to the target genes. Strategies include fine mapping, functional annotation, genomics, and target gene identification through gene expression, epigenetics, and cell-based studies to define direct interactions between causal single nucleotide polymorphisms (SNPs) and target genes. To help decode GWAS "hits" affecting endometriosis from multiple regions, there is an urgent need for well-powered genome-wide studies of the regulation of gene expression and epigenetic mechanisms in the endometrium and other reproductive tissues. The system genetics and genomic studies needed to follow-up GWAS signals will also provide insights into gene regulation influencing other reproductive functions. These studies require multidisciplinary research combining genetics, genomics, functional biology, and clinical research to determine the biological pathways responsible and translate the new knowledge into better outcomes for patients., (© 2015 by the Society for the Study of Reproduction, Inc.)