Endometriosis research in the -omics era

Multi-omics integration highlights the role of ubiquitination in endometriosis fibrosis

BACKGROUND

Endometriosis, characterized by the presence of active endometrial-like tissues outside the uterus, causes symptoms like dysmenorrhea and infertility due to the fibrosis of endometrial cells, which involves excessive deposition of extracellular matrix (ECM) proteins. Ubiquitination, an important post-transcriptional modification, regulates various biological processes in human diseases. However, its role in the fibrosis process in endometriosis remains unclear.

METHODS

We employed multi-omics approaches on two cohorts of endometriosis patients with 39 samples. GO terms and KEGG pathways enrichment analyses were used to investigate the functional changes involved in endometriosis. Pearson's correlation coefficient analysis was conducted to explore the relationship between global proteome and ubiquitylome in endometriosis. The protein expression levels of ubiquitin-, fibrosis-related proteins, and E3 ubiquitin-protein ligase TRIM33 were validated via Western blot. Transfecting human endometrial stroma cells (hESCs) with TRIM33 small interfering RNA (siRNA) in vitro to explore how TRIM33 affects fibrosis-related proteins.

RESULTS

Integration of proteomics and transcriptomics showed genes with concurrent change of both mRNA and protein level which involved in ECM production in ectopic endometria. Ubiquitylomics distinguished 1647 and 1698 ubiquitinated lysine sites in the ectopic (EC) group compared to the normal (NC) and eutopic (EU) groups, respectively. Further multi-omics integration highlighted the essential role of ubiquitination in key fibrosis regulators in endometriosis. Correlation analysis between proteome and ubiquitylome showed correlation coefficients of 0.32 and 0.36 for ubiquitinated fibrosis proteins in EC/NC and EC/EU groups, respectively, indicating positive regulation of fibrosis-related protein expression by ubiquitination in ectopic lesions. We identified ubiquitination in 41 pivotal proteins within the fibrosis-related pathway of endometriosis. Finally, the elevated expression of TGFBR1/α-SMA/FAP/FN1/Collagen1 proteins in EC tissues were validated across independent samples. More importantly, we demonstrated that both the mRNA and protein levels of TRIM33 were reduced in endometriotic tissues. Knockdown of TRIM33 promoted TGFBR1/p-SMAD2/α-SMA/FN1 protein expressions in hESCs but did not significantly affect Collagen1/FAP levels, suggesting its inhibitory effect on fibrosis in vitro.

CONCLUSIONS

This study, employing multi-omics approaches, provides novel insights into endometriosis ubiquitination profiles and reveals aberrant expression of the E3 ubiquitin ligase TRIM33 in endometriotic tissues, emphasizing their critical involvement in fibrosis pathogenesis and potential therapeutic targets.

Omics-based novel strategies in the diagnosis of endometriosis

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Serum Metabolites as Diagnostic Biomarkers in Patients with Endometriosis

Endometriosis diagnosis is usually delayed. The gold standard for diagnosing endometriosis is laparoscopy, which is invasive and accompanied by several risks. Currently, there are no effective non-invasive biomarkers for diagnosing endometriosis. Here, we investigated whether metabolites whose levels are altered in patients with endometriosis hold potential as diagnostic biomarkers for the disease. This case-control study involved 32 patients with endometriosis and 29 patients with other benign gynecological disease. The diagnosis of all patients was confirmed through postoperative histopathological examination, and the patients were divided into two groups: an endometriosis group (EM) and a control group. Fasting blood was collected and used for non-targeted metabolomic-based detection. The data were processed through principal component analysis, orthogonal partial least squares discriminant analysis, and significance analysis of microarrays. A univariate receiver operating characteristic curve was used to evaluate the diagnostic value of the metabolites. The metabolite profiles of patients with endometriosis were markedly different compared with those of the controls. In addition, several metabolic pathways, including biosynthesis of unsaturated fatty acids, arginine biosynthesis, and glutathione metabolism, were altered. Ornithine and medorinone showed better potential as biomarkers for endometriosis diagnosis than CA125. We analyzed the altered metabolic profiles in patients with endometriosis and found ornithine and medorinone as potential non-invasive biomarkers for endometriosis diagnosis, whereas the combined ornithine-medorinone diagnosis is more valuable. These findings may help advance research on non-invasive diagnostic biomarkers for endometriosis. Further research with an improved study design and a larger cohort should be performed to confirm the diagnostic potential and clinical application of these biomarkers.

Association of endometriosis with Sjögren's syndrome: Genetic insights (Review)

Patients with a history of endometriosis have an increased risk of developing various autoimmune diseases such as rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, multiple sclerosis and celiac disease. There is a potential association between endometriosis and an increased susceptibility for Sjögren's syndrome (SS). SS is a common chronic, inflammatory, systemic, autoimmune, multifactorial disease of complex pathology, with genetic, epigenetic and environmental factors contributing to the development of this condition. It occurs in 0.5‑1% of the population, is characterized by the presence of ocular dryness, lymphocytic infiltrations and contributes to neurological, gastrointestinal, vascular and dermatological manifestations. Endometriosis is an inflammatory, estrogen‑dependent, multifactorial, heterogeneous gynecological disease, affecting ≤10% of reproductive‑age women. It is characterized by the occurrence of endometrial tissue outside the uterine cavity, mainly in the pelvic cavity, and is associated with pelvic pain, dysmenorrhea, deep dyspareunia and either subfertility or infertility. It is still unclear whether SS appears as a secondary response to endometriosis, or it is developed due to any potential shared mechanisms of these conditions. The aim of the present review was to explore further the biological basis only of the co‑occurrence of these disorders but not their association at clinical basis, focusing on the analysis of the partially shared genetic background between endometriosis and SS, and the clarification of the possible similarities in the underlying pathogenetic mechanisms and the relevant molecular pathways.

Molecular Mechanisms of Endometriosis Revealed Using Omics Data

Endometriosis is a gynecological disorder prevalent in women of reproductive age. The primary symptoms include dysmenorrhea, irregular menstruation, and infertility. However, the pathogenesis of endometriosis remains unclear. With the advent of high-throughput technologies, various omics experiments have been conducted to identify genes related to the pathophysiology of endometriosis. This review highlights the molecular mechanisms underlying endometriosis using omics. When genes identified in omics experiments were compared with endometriosis disease genes identified in independent studies, the number of overlapping genes was moderate. However, the characteristics of these genes were found to be equivalent when functional gene set enrichment analysis was performed using gene ontology and biological pathway information. These findings indicate that omics technology provides invaluable information regarding the pathophysiology of endometriosis. Moreover, the functional characteristics revealed using enrichment analysis provide important clues for discovering endometriosis disease genes in future research.

TGFBI as a candidate biomarker for non-invasive diagnosis of early-stage endometriosis

STUDY QUESTION

Can cartilage oligomeric matrix protein (COMP) and transforming growth factor-β-induced protein ig-h3 (TGFBI) alone or in combination with cancer antigen 125 (CA-125) be considered as potential blood biomarkers of endometriosis?

SUMMARY ANSWER

The results of this study indicate that COMP has no diagnostic value. TGFBI has potential as a non-invasive biomarker of the early stages of endometriosis, while TGFBI together with CA-125 has similar diagnostic characteristics as CA-125 alone for all stages of endometriosis.

WHAT IS KNOWN ALREADY

Endometriosis is a common, chronic gynecological disease that significantly affects patient quality of life by causing pain and infertility. The gold standard for diagnosis is visual inspection of pelvic organs by laparoscopy, therefore there is an urgent need for discovery of non-invasive biomarkers for endometriosis to reduce diagnostic delays and allow earlier treatment of patients. The potential biomarkers for endometriosis evaluated in this study (COMP and TGFBI) were previously identified by our proteomic analysis of peritoneal fluid samples.

STUDY DESIGN, SIZE, DURATION

This is a case-control study divided into a discovery (n = 56 patients) and a validation phase (n = 237 patients). All patients were treated between 2008 and 2019 in a tertiary medical center.

PARTICIPANTS/MATERIALS, SETTING, METHOD

Patients were stratified based on the laparoscopic findings. The discovery phase included 32 endometriosis patients (cases) and 24 patients with confirmed absence of endometriosis (controls). The validation phase included 166 endometriosis and 71 control patients. Concentrations of COMP and TGFBI were measured by ELISA in plasma samples, whereas concentration of CA-125 was measured using a clinically validated assay for serum samples. Statistical and receiver operating characteristic (ROC) curve analyses were performed. The classification models were built using the linear support vector machine (SVM) method with the SVM built-in feature ranking method.

MAIN RESULTS AND THE ROLE OF CHANCE

The discovery phase revealed significantly increased concentration of TGFBI, but not COMP, in plasma samples of patients with endometriosis compared to controls. In this smaller cohort, univariate ROC analysis showed fair diagnostic potential of TGFBI, with an AUC value of 0.77, sensitivity of 58%, and specificity of 84%. The classification model built using linear SVM and combining TGFBI and CA-125 showed an AUC value of 0.91, sensitivity of 88% and specificity of 75% in distinguishing patients with endometriosis from controls. The validation phase results revealed similar diagnostic characteristics of the SVM model combining TGFBI and CA-125, with an AUC value of 0.83, sensitivity of 83% and specificity of 67% and CA-125 alone with AUC value of 0.83, sensitivity of 73% and specificity of 80%. TGFBI exhibited good diagnostic potential for early-stage endometriosis (revised American Society for Reproductive Medicine stage I-II), with an AUC value of 0.74, sensitivity of 61% and specificity of 83% compared to CA-125, which had an AUC value of 0.63, sensitivity of 60% and specificity of 67%. An SVM model combining TGFBI and CA-125 showed a high AUC value of 0.94 and sensitivity of 95% for diagnosing moderate-to-severe endometriosis.

LIMITATIONS, REASONS FOR CAUTION

The diagnostic models were built and validated from a single endometriosis center, and thus further validation and technical verification in a multicenter study with a larger cohort is needed. Additional limitation was lack of histological confirmation of disease for some patients in the validation phase.

WIDER IMPLICATIONS OF THE FINDINGS

This study revealed for the first time increased concentration of TGFBI in plasma samples of patients with endometriosis, particularly those with minimal-to-mild endometriosis, compared to controls. This is the first step in considering TGFBI as a potential non-invasive biomarker for the early stages of endometriosis. It also opens a path for new basic research to investigate the importance of TGFBI in the pathophysiology of endometriosis. Further studies are needed to confirm the diagnostic potential of a model based on TGFBI and CA-125 for the non-invasive diagnosis of endometriosis.

STUDY FUNDING/COMPETING INTEREST(S)

The preparation of this manuscript was supported by grant J3-1755 from the Slovenian Research Agency to T.L.R and EU H2020-MSCA-RISE project TRENDO (grant 101008193). All authors declare that they have no conflicts of interest.

TRIAL REGISTRATION NUMBER

NCT0459154.

New Insights into Genetics of Endometriosis-A Comprehensive Literature Review

This comprehensive review explores the genetic contributions to endometriosis and their potential impact on improving diagnostic techniques. The review begins by defining endometriosis and discussing its prevalence, emphasizing the need for a deeper understanding of the genetic basis of the condition. It highlights recent genome-wide association studies (GWAS) that have identified specific genetic variants associated with endometriosis, shedding light on the molecular pathways and mechanisms involved. The review addresses genetic heterogeneity across different populations and ethnicities, emphasizing the importance of considering population-specific markers in diagnostic approaches. It explores the diagnostic implications of genetic insights, including the potential use of genetic markers for precise and early detection, as well as risk prediction. The review also delves into the integration of genetic information with clinical parameters and imaging findings, and the exploration of multi-omics approaches for a comprehensive understanding of endometriosis. It discusses recent studies on genetic and epigenetic biomarkers, their potential as diagnostic tools, and the need for validation in independent cohorts. The review highlights the impact of new genomic technologies, such as next-generation sequencing, in improving diagnostic accuracy and personalized management. It identifies the challenges and future directions in translating genetic findings into diagnostic tools and emphasizes the transformative potential of genetic insights in endometriosis diagnosis. This review provides a roadmap for future research and underscores the significance of genetic insights in improving diagnostic precision and personalized care for individuals with endometriosis.

The DNA demethylation-regulated SFRP2 dictates the progression of endometriosis via activation of the Wnt/β-catenin signaling pathway

Background

Endometriosis cause decreases in life quality and pelvic pain in reproductive-age women. Methylation abnormalities played a functional role in the progression of endometriosis, this study aimed to explore the mechanisms mediated by abnormal methylation in the development of EMS.

Materials and methods

Next-generation sequencing dataset and methylation profiling dataset were used to screen out the key gene SFRP2. Western bolt, Real-time PCR, Aza-2?deoxycytidine treatment, luciferase reporter assay, Methylation-specific PCR , Bisulfite sequencing PCR and lentivirus infection were carried out to detect the methylation status and signaling pathway with the primary epithelial cells. Transwell assay and wound scratch assay were implemented to observe the differences of migration ability with the intervening with the expression of SFRP2.

Results

To define the role of the DNA methylation-regulated genes in the pathogenesis of EMS, we performed both DNA methylomic and expression analyses of ectopic endometrium and ectopic endometrium epithelial cells(EEECs) and found that SFRP2 is demethylated/upregulated in ectopic endometrium and EEECs. The expression of lentivirus carrying SFRP2 cDNA up-regulates the activity of Wnt signaling and the protein expression of ?-catenin in EEECs. SFRP2 impact on the invasion and migration of ectopic endometrium by modulating the activities of the Wnt/?-catenin signaling pathway. The invasion and migration ability of EEECs were significantly strengthened after demethylation treatment including 5-Aza and the knockdown of DNMT1.

Conclusion

In summary, the increased SFRP2 expression-induced Wnt/?-catenin signaling due to the demethylation of the SFRP2 promoter plays an important role in the pathogenesis of EMS, suggesting that SFRP2 might be a therapeutic target for EMS treatment.

What Do the Transcriptome and Proteome of Menstrual Blood-Derived Mesenchymal Stem Cells Tell Us about Endometriosis?

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data are for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. This is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial–mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓ in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, IL6 STAT3 signaling, and response to hypoxia via HIF1A targets (↑ in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

Genes Relating to Biological Processes of Endometriosis: Expression Changes Common to a Mouse Model and Patients

Endometriosis is one of the most common gynecological diseases in women of reproductive age. Retrograde menstruation is considered a major reason for the development of endometriosis. The syngeneic transplantation mouse model is an endometriosis animal model that is considered to mimic retrograde menstruation. However, it remains poorly understood which genetic signatures of endometriosis are reflected in this model. Here, we employed an in vivo syngeneic mouse endometriosis model and identified differentially expressed genes (DEGs) between the ectopic and eutopic tissues using microarray analysis. Three gene expression profile datasets, GSE5108, GSE7305, and GSE11691, were downloaded from the Gene Expression Omnibus database and DEGs between ectopic and eutopic tissues from the same patients were identified. Gene ontology analysis of the DEGs revealed that biological processes including cell adhesion, the inflammatory response, the response to mechanical stimulus, cell proliferation, and extracellular matrix organization were enriched in both the model and patients. Of the 195 DEGs common to the model and patients, 154 showed the same expression pattern, and 28 of these 154 DEGs came up when PubMed was searched for each gene along with the terms "endometriosis" and "development". This is the first comparison of the DEGs of the mouse syngeneic endometriosis model and those of patients, and we identified the biological processes common to the model and patients at the transcriptional level. This model may be useful to evaluate the efficacy of drugs which target these biological processes.

Multi-Omics Integrative Approach of Extracellular Vesicles: A Future Challenging Milestone

In the era of multi-omic sciences, dogma on singular cause-effect in physio-pathological processes is overcome and system biology approaches have been providing new perspectives to see through. In this context, extracellular vesicles (EVs) are offering a new level of complexity, given their role in cellular communication and their activity as mediators of specific signals to target cells or tissues. Indeed, their heterogeneity in terms of content, function, origin and potentiality contribute to the cross-interaction of almost every molecular process occurring in a complex system. Such features make EVs proper biological systems being, therefore, optimal targets of omic sciences. Currently, most studies focus on dissecting EVs content in order to either characterize it or to explore its role in various pathogenic processes at transcriptomic, proteomic, metabolomic, lipidomic and genomic levels. Despite valuable results being provided by individual omic studies, the categorization of EVs biological data might represent a limit to be overcome. For this reason, a multi-omic integrative approach might contribute to explore EVs function, their tissue-specific origin and their potentiality. This review summarizes the state-of-the-art of EVs omic studies, addressing recent research on the integration of EVs multi-level biological data and challenging developments in EVs origin.

Is there a role for small molecule metabolite biomarkers in the development of a diagnostic test for endometriosis?

Endometriosis is a disease defined by the presence of benign lesions of endometrial-like glands and stroma outside the endometrial cavity. Affecting an estimated 11.4% of Australian women, symptoms include chronic pelvic pain, dysmenorrhea and infertility. The current gold standard of diagnosis requires an expensive and invasive laparoscopic surgery, resulting in delayed time to treatment. The identification of a non-invasive endometriosis biomarker - a measurable factor correlating with disease presence or activity - has therefore become a priority in endometriosis research, although no biomarker has yet been validated. As small molecule metabolites and lipids have emerged as a potential focus, this review with systematic approach, aims to summarize studies examining metabolomic biomarkers of endometriosis in order to guide future research. EMBASE, PubMed and Web of Science were searched using keywords: lipidomics OR metabolomics OR metabolome AND diagnostic tests OR biomarkers AND endometriosis, and only studies written in English from August 2000 to August 2020 were included. Twenty-nine studies met inclusion and exclusion criteria and were included. These studies identified potential biomarkers in serum, ectopic tissue, eutopic endometrium, peritoneal fluid, follicular fluid, urine, cervical swabs and endometrial fluid. Glycerophospholipids were identified as potential biomarkers in all specimens, except urine and cervical swab specimens. However, no individual molecule or metabolite combination has reached clinical diagnostic utility. Further research using large study populations with robust patient phenotype and specimen characterisation is required if we are to make progress in identifying and validating a non-invasive diagnostic test for endometriosis.

[Avenues of reflection for endometriosis research in France]

Endometriosis is a chronic disease in which lesions resembling endometrial tissue are found outside the uterus, mainly in the pelvis or abdomen. It may affect 10% of women of childbearing age. It is the cause of a significant alteration in quality of life and a major cost to the health system. Few research teams are working on this subject, and its pathophysiology is still poorly understood. This article proposes avenues of reflection for research on endometriosis in France, notably based on the mobilization of related scientific communities (involved in cancer, development, epigenetics, and neurosciences research studies).

Identification and analysis of novel endometriosis biomarkers via integrative bioinformatics

Endometriosis is a gynecological disease prevalent in women of reproductive age, and it is characterized by the ectopic presence and growth of the eutopic endometrium. The pathophysiology and diagnostic biomarkers of endometriosis have not yet been comprehensively determined. To discover molecular markers and pathways underlying the pathogenesis of endometriosis, we identified differentially expressed genes (DEGs) in three Gene Expression Omnibus microarray datasets (GSE11691, GSE23339, and GSE7305) and performed gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analyses. We also validated the identified genes via immunohistochemical analysis of tissues obtained from patients with endometriosis or healthy volunteers. A total of 118 DEGs (79 upregulated and 39 downregulated) were detected in each dataset with a lower (fold change) FC cutoff (log2|FC| > 1), and 17 DEGs (11 upregulated and six downregulated) with a higher FC cutoff (log2|FC| > 2). KEGG and GO functional analyses revealed enrichment of signaling pathways associated with inflammation, complement activation, cell adhesion, and extracellular matrix in endometriotic tissues. Upregulation of seven genes (C7, CFH, FZD7, LY96, PDLIM3, PTGIS, and WISP2) out of 17 was validated via comparison with external gene sets, and protein expression of four genes (LY96, PDLIM3, PTGIS, and WISP2) was further analyzed by immunohistochemistry and western blot analysis. Based on these results, we suggest that TLR4/NF-κB and Wnt/frizzled signaling pathways, as well as estrogen receptors, regulate the progression of endometriosis. These pathways may be therapeutic and diagnostic targets for endometriosis.

Text Mining and Hub Gene Network Analysis of Endometriosis

This study is aimed at systematically characterizing the endometriosis-associated genes based on text mining and at annotating the functions, pathways, and networks of endometriosis-associated hub genes. We extracted endometriosis-associated abstracts published between 1970 and 2020 from the PubMed database. A neural-named entity recognition and multitype normalization tool for biomedical text mining was used to recognize and normalize the genes and proteins embedded in the abstracts. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted to annotate the functions and pathways of recognized genes. Protein-protein interaction analysis was conducted on the genes significantly cooccurring with endometriosis to identify the endometriosis-associated hub genes. A total of 433 genes were recognized as endometriosis-associated genes (P < 0.05), and 154 pathways were significantly enriched (P < 0.05). A network of endometriosis-associated genes with 278 gene nodes and 987 interaction links was established. The 15 proteins that interacted with 20 or more other proteins were identified as the hub proteins of the endometriosis-associated protein network. This study provides novel insights into the hub genes that play key roles in the development of endometriosis and have implications for developing targeted interventions for endometriosis.

The Potential of Non-Invasive Biomarkers for Early Diagnosis of Asymptomatic Patients with Endometriosis

Endometriosis is a disease that affects women of reproductive age and has a significantly negative impact on their well-being. The main symptoms are dysmenorrhoea, chronic pelvic pain and infertility. In many patients the diagnostic process is very long and can take up to 8-12 years. Laparoscopy, an invasive method, is still necessary to confirm the diagnosis. Therefore, development of more effective diagnostic markers appears to be of the utmost importance for early diagnosis of endometriosis and provision of appropriate treatment. From a clinical point of view, detection of early-stage endometriosis in asymptomatic patients is an ideal situation since early diagnosis of endometriosis may delay the onset of symptoms as well as prevent progression and complications. In the meantime, Cancer Antigen 125 (CA-125) is still the most frequently studied and used marker. Other glycoproteins, growth factors and immune markers seem to play an important role. However, the search for an ideal endometriosis marker is still underway. Further studies into the pathogenesis of endometriosis will help to identify biomarkers or sets of biomarkers with the potential to improve and speed up the diagnostic process in a non-invasive way.

Metabolomics in endometriosis: challenges and perspectives for future studies

Endometriosis is a complex disease characterized by inflammation and the growth of endometrial- like glands and stroma outside the uterine cavity. The pathophysiology of endometriosis is not entirely understood, however, with a prevalence of ~10% of women in their reproductive years, the disease symptoms significantly affect the quality of life of millions of women globally. Metabolomic studies have previously identified specific metabolites that could be a signature of endometriosis. This approach could potentially be used as a non-invasive tool for early diagnosis and provide a better understanding of endometriosis pathophysiology. This review aims to provide insight as to how endometriosis affects the metabolome by reviewing different studies that have used this approach to design follow-up studies. The search query included the term 'endometriosis' in combination with 'metabolomics', 'lipidomics', or 'sphingolipidomics' published between 2012 and 2020. We included studies in humans and animal models. Most studies reported differences in the metabolome of subjects with endometriosis in comparison to healthy controls and used samples taken from serum, endometrial tissue, follicular fluid, urine, peritoneal fluid, or endometrial fluid. Statistically significant metabolites contributed to group separation between patients and healthy controls. Reported metabolites included amino acids, lipids, organic acids, and other organic compounds. Differences in methods, analytical techniques, and the presence of confounding factors can interfere with results and interpretation of data. Metabolomics seems to be a promising tool for identifying significant metabolites in patients with endometriosis. Nonetheless, more investigation is needed in order to understand the significance of the study results.

Lay summary

Endometriosis is a chronic disease affecting the quality of life in one out of every ten women during their reproductive years, causing pain and infertility. It is characterized by inflammation and growth of tissue like the endometrium (uterus lining) outside the uterine cavity. Studies have searched for a predictor of endometriosis-associated changes by observing small molecules necessary for metabolism on a large scale (metabolomics). Metabolomics could serve to resolve one of the biggest challenges that patients with endometriosis face: a delay in diagnosis. In this review, the authors summarize identified potential biomarkers from various bodily fluids and tissues that are characteristic of metabolic processes observed in endometriosis. Biomarkers include cell growth, cell survival, high energy demand, oxidative stress, and fatty acid levels. A metabolomics approach offers promise as a non-invasive tool to identify significant metabolite changes in patients with endometriosis, potentially leading to earlier diagnoses and new opportunities for back-translational strategies.

Demetra Application: An integrated genotype analysis web server for clinical genomics in endometriosis

Demetra Application is a holistic integrated and scalable bioinformatics web-based tool designed to assist medical experts and researchers in the process of diagnosing endometriosis. The application identifies the most prominent gene variants and single nucleotide polymorphisms (SNPs) causing endometriosis using the genomic data provided for the patient by a medical expert. The present study analyzed >28.000 endometriosis-related publications using data mining and semantic techniques aimed towards extracting the endometriosis-related genes and SNPs. The extracted knowledge was filtered, evaluated, annotated, classified, and stored in the Demetra Application Database (DAD). Moreover, an updated gene regulatory network with the genes implements in endometriosis was established. This was followed by the design and development of the Demetra Application, in which the generated datasets and results were included. The application was tested and presented herein with whole-exome sequencing data from seven related patients with endometriosis. Endometriosis-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information were classified, annotated and analyzed in a consolidated patient profile with clinical significance information. Probable genes associated with the patient's genomic profile were visualized using several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, in an effort to obtain a representative number of the most credible candidate genes and biological pathways associated with endometriosis. An evaluation analysis was performed on seven patients from a three-generation family with endometriosis. All the recognized gene variants that were previously considered to be associated with endometriosis were properly identified in the output profile per patient, and by comparing the results, novel findings emerged. This novel and accessible webserver tool of endometriosis to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/.

Genetic, Epigenetic, and Steroidogenic Modulation Mechanisms in Endometriosis

Endometriosis is a chronic gynecological disease, affecting up to 10% of reproductive-age women. The exact cause of the disease is unknown; however, it is a heritable condition affected by multiple genetic, epigenetic, and environmental factors. Previous studies reported variations in the epigenetic patterns of numerous genes known to be involved in the aberrant modulation of cell cycle steroidogenesis, abnormal hormonal, immune and inflammatory status in endometriosis, apoptosis, adhesion, angiogenesis, proliferation, immune and inflammatory processes, response to hypoxia, steroidogenic pathway and hormone signaling are involved in the pathogenesis of endometriosis. Accumulating evidence suggest that various epigenetic aberrations may contribute to the pathogenesis of endometriosis. Among them, DNA methyltransferases, histone deacetylators, and non-coding microRNAs demonstrate differential expression within endometriotic lesions and in the endometrium of patients with endometriosis. It has been indicated that the identification of epigenetic differences within the DNA or histone proteins may contribute to the discovery of a useful prognostic biomarker, which could aid in the future earlier detection, timely diagnosis, and initiation of a new approach to the treatment of endometriosis, as well as inform us about the effectiveness of treatment and the stage of the disease. As the etiology of endometriosis is highly complex and still far from being fully elucidated, the presented review focuses on different approaches to identify the genetic and epigenetic links of endometriosis and its pathogenesis.