Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P<5 × 10−8), implicating genes involved in sex steroid hormone pathways (FN1, CCDC170, ESR1, SYNE1 and FSHB). Conditional analysis identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near specific genes with important roles in sex steroid hormone signalling and function, and offer unique opportunities for more targeted functional research efforts.
STUDY QUESTION Can plasma miRNAs be used for the non-invasive diagnosis of endometriosis in infertile women? SUMMARY ANSWER miRNA-based diagnostic models for endometriosis failed the test of independent validation. WHAT IS KNOWN ALREADY Circulating miRNAs have been described to be differentially expressed in patients with endometriosis compared with women without endometriosis, suggesting that they could be used for the non-invasive diagnosis of endometriosis. However, these studies have shown limited consistency or conflicting results, and no miRNA-based diagnostic test has been validated in an independent patient cohort. STUDY DESIGN, SIZE, DURATION We performed genome-wide miRNA expression profiling by small RNA sequencing to identify a set of plasma miRNAs with discriminative potential between patients with and without endometriosis. Expression of this set of miRNAs was confirmed by RT-qPCR. Diagnostic models were built using multivariate logistic regression with stepwise feature selection. In a final step, the models were tested for validation in an independent patient cohort. PARTICIPANTS/MATERIALS, SETTINGS, METHODS Plasma of all patients was available in the biobank of the Leuven Endometriosis Centre of Excellence. Biomarker discovery and model development were performed in a discovery cohort of 120 patients (controls = 38, endometriosis = 82), and models were tested for validation in an independent cohort of 90 patients (controls = 30, endometriosis = 60). RNA was extracted with the miRNeasy Plasma Kit. Genome-wide miRNA expression analysis was done by small RNA sequencing using the NEBNext small RNA library prep kit and the NextSeq 500 System. cDNA synthesis and qPCR were performed using the Qiagen miScript technology. MAIN RESULTS AND THE ROLE OF CHANCE We identified a set of 42 miRNAs with discriminative power between patients with and without endometriosis based on genome-wide miRNA expression profiling. Expression of 41 miRNAs was confirmed by RT-qPCR, and 3 diagnostic models were built. Only the model for minimal–mild endometriosis (Model 2: hsa-miR-125b-5p, hsa-miR-28-5p and hsa-miR-29a-3p) had diagnostic power above chance performance in the independent validation (AUC = 60%) with an acceptable sensitivity (78%) but poor specificity (37%). LIMITATIONS, REASONS FOR CAUTION The diagnostic models were built and tested for validation in two patient cohorts from a single tertiary endometriosis centre. Further validation tests in large cohorts with patients from multiple endometriosis centres are needed. WIDER IMPLICATION OF THE FINDINGS Our study supports a possible biological link between certain miRNAs and endometriosis, but the potential of these miRNAs as clinically useful biomarkers is questionable in women with infertility. Large studies in well-described patient cohorts, with rigorous methodology for miRNA expression analysis, sufficient statistical power and an independent validation step, are necessary to answer the question of whether miRNAs can be used as diagnostics markers for endometriosis. STUDY FUNDING/COMPETING INTEREST(S) The project was funded by a grant from the Research Foundation - Flanders (FWO). A.V., D.F.O. and D.P. are PhD fellows from the FWO. T.D. is vice president and Head of Global Medical Affairs Fertility, Research and Development, Merck KGaA, Darmstadt, Germany. He is also a professor in Reproductive Medicine and Biology at the Department of Development and Regeneration, Group Biomedical Sciences, KU Leuven (University of Leuven), Belgium and an adjunct professor at the Department of Obstetrics and Gynecology in the University of Yale, New Haven, USA. Neither his corporate role nor his academic roles represent a conflict of interest with respect to the work done by him for this study. The other co-authors have no conflict of interest. Trial registration number Not applicable.
Endometriosis is an estrogen-dependent inflammatory disease that affects approximately 10% of women. Debilitating pelvic or abdominal pain is one of its major clinical features. Current animal models of endometriosis-associated pain require surgery either to implant tissue or to remove the ovaries. Moreover, existing models do not induce spontaneous pain, which is the primary symptom of patients with chronic pain, including endometriosis. A lack of models that accurately recapitulate the disease phenotype must contribute to the high failure rate of clinical trials for analgesic drugs directed at chronic pain, including those for endometriosis. We set out to establish a murine model of endometriosis-associated pain. Endometriosis was induced nonsurgically by injecting a dissociated uterine horn into a recipient mouse. The induced lesions exhibited histological features that resemble human lesions along with an increase in proinflammatory cytokines and recruitment of immune cells. We also observed the presence of calcitonin gene–related peptide–, TRPA1-, and TRPV1-expressing nerve fibers in the lesions. This model induced mechanical allodynia, spontaneous abdominal pain, and changes in thermal selection behavior that indicate discomfort. These behavioral changes were reduced by drugs used clinically for endometriosis, specifically letrozole (aromatase inhibitor) and danazol (androgen). Endometriosis also induced neuronal changes as evidenced by activation of the NF-κB signaling pathway in TRPA1- and TRPV1-expressing dorsal root ganglion neurons. In conclusion, we have established a model of endometriosis-associated pain that responds to clinically active drugs and can, therefore, be used to identify novel therapies.
STUDY QUESTION Is there a shared genetic or causal association of endometriosis with asthma or what biological mechanisms may underlie their potential relationships? SUMMARY ANSWER Our results confirm a significant but non-causal association of endometriosis with asthma implicating shared genetic susceptibility and biological pathways in the mechanisms of the disorders, and potentially, their co-occurrence. WHAT IS KNOWN ALREADY Some observational studies have reported a pattern of co-occurring relationship between endometriosis and asthma; however, there is conflicting evidence and the aetiology, as well as the underlying mechanisms of the relationship, remain unclear. STUDY DESIGN, SIZE, DURATION We applied multiple statistical genetic approaches in the analysis of well-powered, genome-wide association study (GWAS) summary data to comprehensively assess the relationship of endometriosis with asthma. Endometriosis GWAS from the International Endogene Consortium (IEC, 17 054 cases and 191 858 controls) and asthma GWAS from the United Kingdom Biobank (UKB, 26 332 cases and 375 505 controls) were analysed. Additional asthma data from the Trans-National Asthma Genetic Consortium (TAGC, 19 954 cases and 107 715 controls) were utilized for replication testing. PARTICIPANTS/MATERIALS, SETTING, METHODS We assessed single-nucleotide polymorphism (SNP)-level genetic overlap and correlation between endometriosis and asthma using SNP effect concordance analysis (SECA) and linkage disequilibrium score regression analysis (LDSC) methods, respectively. GWAS meta-analysis, colocalization (GWAS-PW), gene-based and pathway-based functional enrichment analysis methods were applied, respectively, to identify SNP loci, genomic regions, genes and biological pathways shared by endometriosis and asthma. Potential causal associations between endometriosis and asthma were assessed using Mendelian randomization (MR) methods. MAIN RESULTS AND THE ROLE OF CHANCE SECA revealed significant concordance of SNP risk effects across the IEC endometriosis and the UKB asthma GWAS. Also, LDSC analysis found a positive and significant genetic correlation (rG = 0.16, P = 2.01 × 10−6) between the two traits. GWAS meta-analysis of the IEC endometriosis and UKB asthma GWAS identified 14 genome-wide significant (Pmeta-analysis < 5.0 × 10−8) independent loci, five of which are putatively novel. Three of these loci were consistently replicated using TAGC asthma GWAS and reinforced in colocalization and gene-based analyses. Additional shared genomic regions were identified in the colocalization analysis. MR found no evidence of a significant causal association between endometriosis and asthma. However, combining gene-based association results across the GWAS for endometriosis and asthma, we identified 17 shared genes with a genome-wide significant Fisher’s combined P-value (FCPgene) <2.73 × 10−6. Additional analyses (independent gene-based analysis) replicated evidence of gene-level genetic overlap between endometriosis and asthma. Biological mechanisms including ‘thyroid hormone signalling’, ‘abnormality of immune system physiology’, ‘androgen biosynthetic process’ and ‘brain-derived neurotrophic factor signalling pathway’, among others, were significantly enriched for endometriosis and asthma in a pathway-based analysis. LARGE SCALE DATA The GWAS for endometriosis data were sourced from the International Endogen Consortium (IEC) and can be accessed by contacting the consortium. The GWAS data for asthma are freely available online at Lee Lab (https://www.leelabsg.org/resources) and from the Trans-National Asthma Genetic Consortium (TAGC). LIMITATIONS, REASONS FOR CAUTION Given we analysed GWAS datasets from mainly European populations, our results may not be generalizable to other ancestries. WIDER IMPLICATIONS OF THE FINDINGS This study provides novel insights into mechanisms underpinning endometriosis and asthma, and potentially their observed relationship. Findings support a co-occurring relationship of endometriosis with asthma largely due to shared genetic components. Agents targeting ‘selective androgen receptor modulators’ may be therapeutically relevant in both disorders. Moreover, SNPs, loci, genes and biological pathways identified in our study provide potential targets for further investigation in endometriosis and asthma. STUDY FUNDING/COMPETING INTEREST(S) National Health and Medical Research Council (NHMRC) of Australia (241,944, 339,462, 389,927, 389,875, 389,891, 389,892, 389,938, 443,036, 442,915, 442,981, 496,610, 496,739, 552,485, 552,498, 1,026,033 and 1,050,208), Wellcome Trust (awards 076113 and 085475) and the Lundbeck Foundation (R102-A9118 and R155-2014-1724). All researchers had full independence from the funders. Authors do not have any conflict of interest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.