Polymorphisms and endometriosis: a systematic review and meta-analyses

Abstract

AbstractBACKGROUNDEndometriosis is an estrogen-dependent gynecological disorder that affects at least 10% of women of reproductive age. It may lead to infertility and non-specific symptoms such as chronic pelvic pain. Endometriosis screening and diagnosis are difficult and time-consuming. Late diagnosis (with a delay ranging from 3.3 to 10.7 years) is a major problem and may contribute to disease progression and a worse response to treatment once initiated. Efficient screening tests might reduce this diagnostic delay. As endometriosis is presumed to be a complex disease with several genetic and non-genetic pathogenic factors, many researchers have sought to identify polymorphisms that predispose to this condition.OBJECTIVE AND RATIONALEWe performed a systematic review and meta-analysis of the most regularly reported polymorphisms in order to identify those that might predispose to endometriosis and might thus be of value in screening.SEARCH METHODSThe MEDLINE database was searched for English-language publications on DNA polymorphisms in endometriosis, with no date restriction. The PubTator text mining tool was used to extract gene names from the selected publications’ abstracts. We only selected polymorphisms reported by at least three studies, having applied strict inclusion and exclusion criteria to their control populations. No stratification based on ethnicity was performed. All steps were carried out according to PRISMA guidelines.OUTCOMESThe initial selection of 395 publications cited 242 different genes. Sixty-two genes (corresponding to 265 different polymorphisms) were cited at least in three publications. After the application of our other selection criteria (an original case-control study of endometriosis, a reported association between endometriosis and at least one polymorphism, data on women of reproductive age and a diagnosis of endometriosis in the cases established by surgery and/or MRI and confirmed by histology), 28 polymorphisms were eligible for meta-analysis. Only five of the 28 polymorphisms were found to be significantly associated with endometriosis: interferon gamma (IFNG) (CA) repeat, glutathione S-transferase mu 1 (GSTM1) null genotype, glutathione S-transferase pi 1 (GSTP1) rs1695 and wingless-type MMTV integration site family member 4 (WNT4) rs16826658 and rs2235529. Six others showed a significant trend towards an association: progesterone receptor (PGR) PROGINS, interCellular adhesion molecule 1 (ICAM1) rs1799969, aryl-hydrocarbon receptor repressor (AHRR) rs2292596, cytochrome family 17 subfamily A polypeptide 1 (CYP17A1) rs743572, CYP2C19 rs4244285 and peroxisome proliferator-activated receptor gamma (PPARG) rs1801282), and 12 showed a significant trend towards the lack of an association: tumor necrosis factor (TNF) rs1799964, interleukin 6 (IL6) rs1800796, transforming growth factor beta 1 (TGFB1) rs1800469, estrogen receptor 1 (ESR1) rs2234693, PGR rs10895068, FSH receptor (FSHR) rs6166, ICAM1 rs5498, CYP1A1 rs4646903, CYP19A1 rs10046, tumor protein 53 (TP53) rs1042522, X-ray repair complementing defective repair in Chinese hamster cells 1 (XRCC1) rs25487 and serpin peptidase inhibitor clade E member 1 (SERPINE1) rs1799889; however, for the 18 polymorphisms identified in the latter two groups, further studies of the potential association with the endometriosis risk are needed. The remaining five of the 28 polymorphisms were not associated with endometriosis: glutathione S-transferase theta 1 (GSTT1) null genotype, vascular endothelial growth factor alpha (VEGFA) rs699947, rs833061, rs2010963 and rs3025039.WIDER IMPLICATIONSBy carefully taking account of how the control populations were defined, we identified polymorphisms that might be candidates for use in endometriosis screening and polymorphisms not associated with endometriosis. This might constitute the first step towards identifying polymorphism combinations that predispose to endometriosis (IFNG (CA) repeat, GSTM1 null genotype, GSTP1 rs1695, WNT4 rs16826658 and WNT4 rs2235529) in a large cohort of patients with well-defined inclusion criteria. In turn, these results might improve the diagnosis of endometriosis in primary care. Lastly, our present findings may enable a better understanding of endometriosis and improve the management of patients with this disease.