A metabonomics approach as a means for identification of potential biomarkers for early diagnosis of endometriosis

Plasma metabolites associated with endometriosis in adolescents and young adults

STUDY QUESTION

What are the plasma metabolomics profiles associated with endometriosis in adolescents and young adults?

SUMMARY ANSWER

Our findings show dysregulation of plasma metabolomic profiles in adolescents and young adults with endometriosis, revealing systemic elevation of fatty acyls and ceramides in endometriosis cases compared to controls.

WHAT IS KNOWN ALREADY

Endometriosis is a gynecologic disease often presenting with severe pelvic pain impacting around 200 million reproductive-aged women worldwide. However, little is known about the pathophysiology and molecular features of endometriosis diagnosed during adolescence and young adulthood.

STUDY DESIGN, SIZE, DURATION

We conducted a cross-sectional analysis including 190 laparoscopically confirmed endometriosis cases and 120 controls who participated in The Women's Health Study: From Adolescence to Adulthood, which enrolled participants from 2012 to 2018. Control participants were females without a diagnosis of endometriosis enrolled from the same clinics as the cases or recruited from the general population. Among the cases, 81 had blood samples collected before and after surgery.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Plasma metabolites were measured in blood collected at enrollment using liquid chromatography-tandem mass spectrometry, and a total of 430 known metabolites were evaluated in our analysis. We used linear regression adjusting for age at blood draw, BMI, hormone use, and fasting status at blood draw. Metabolite set enrichment analysis (MSEA) was used to identify metabolite classes. Number of effective tests (NEF) and false discovery rate (FDR) were used for multiple testing correction.

MAIN RESULTS AND THE ROLE OF CHANCE

The median age was 17 years for endometriosis cases and 22 years for controls. The majority of endometriosis cases had rASRM stage I or II (>95%). We identified 63 plasma metabolites associated with endometriosis (NEF < 0.05). Endometriosis cases had higher levels of plasma metabolites associated with proinflammatory response [e.g. eicosatrienoic acid (β = 0.61, 95% CI = 0.37, 0.86)], increased oxidative stress response [e.g. xanthine (β = 0.64, 95% CI = 0.39, 0.88)], and downregulation of metabolites related to apoptosis [glycocholic acid (β = -0.80, 95% CI = -1.04, -0.56)]. MSEA revealed increased fatty acyls (FDR = 2.3e-4) and ceramides (FDR = 6.0e-3) and decreased steroids and steroid derivatives (FDR = 1.3e-4) in endometriosis cases compared to controls. When we examined the changes in plasma metabolite profiles before and after surgery among endometriosis cases, 55 endometriosis-associated metabolites significantly changed from before to after surgery. MSEA revealed steroids and steroid derivatives (FDR = 8.1e-4) significantly increased after surgery, while fatty acyls (FDR = 1.2e-4) significantly decreased after surgery. Ceramides did not change from pre- to post-surgery and were elevated in post-surgical blood compared to controls (FDR = 3.9e-3).

LIMITATIONS, REASONS FOR CAUTION

Our study population mainly consists of self-reported non-Hispanic, white individuals and endometriosis cases with superficial peritoneal lesions only, so the generalizability may be limited. Furthermore, despite our large study population of adolescents and young adults with endometriosis, sample size was limited to conduct detailed stratified analyses of plasma metabolomic profiles, especially by post-surgical pelvic pain outcomes.

WIDER IMPLICATIONS OF THE FINDINGS

Our study includes the utilization of state-of-the-art metabolomics technology with high reproducibility to comprehensively investigate the metabolites that were associated with endometriosis diagnosed in adolescents and young adults. Our results suggest a positive impact of endometriosis-related surgery for some, but not all, on systemic metabolic dysregulation in young patients with endometriosis. These results warrant further investigation on whether and how persistent systemic changes despite treatment may lead to long-term chronic disease risk among those diagnosed with endometriosis.

STUDY FUNDING/COMPETING INTEREST(S)

Financial support for establishment of and data collection within the A2A cohort was provided by the J. Willard and Alice S. Marriott Foundation, and support for assay costs was in part provided by the Peery family. This project was funded by Eunice Kennedy Shriver National Institute of Child Health and Human Development R21HD107266. S.A.M., A.L.S., and K.L.T. were supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD094842. S.A.M. received grant funding from AbbVie, National Institutes of Health, Department of Defense, and Marriott Family Foundation; received honoraria from WERF, Huilun Shanghai, and University of Kansas Medical Center; travel support from SRI, ESHRE, FWGBD, University of Michigan, MIT, ASRM, LIDEA Registry, Taiwan Endometriosis Society, SEUD, Japan Endometriosis Society, NASEM, Endometriosis Foundation of America, Gedeon Richter Symposium at ESHRE; Board member receiving financial remuneration from AbbVie, Roche, LIDEA Registry, Editor of Frontiers in Reproductive Health, Roundtable participation for Abbott; Board member without financial remuneration from NextGen Jane and Statistical Advisory Board member of Human Reproduction; leadership role in Society for Women's Health Research, World Endometriosis Society, World Endometriosis Research Foundation, ASRM, ESHRE. N.S. and K.L.T. receive grant funding from Aspira Women's Health unrelated to this project. The remaining authors have no disclosures relevant to this manuscript.

TRIAL REGISTRATION NUMBER

N/A.

Biomarkers of endometriosis

Endometriosis represents a diverse disease characterized by three distinct phenotypes: superficial peritoneal lesions, ovarian endometriomas, and deep infiltrating endometriosis. The most widely accepted pathophysiological hypothesis for endometriosis is rooted in retrograde menstruation, a phenomenon observed in most patients. Endometriosis is closely linked to infertility, but having endometriosis does not necessarily imply infertility. The disease can impact fertility through various mechanisms affecting the pelvic cavity, ovaries, and the uterus itself. MicroRNAs (miRNAs) indeed represent a fascinating and essential component of the regulatory machinery within cells. Discovered in the early 1990s, miRNAs have since been identified as critical players in gene expression control. Unfortunately, ovarian endometrioma is a common gynecologic disorder for which specific serum markers are currently lacking. Some have examined urocortin for its ability to differentiate endometriomas from other benign ovarian cysts. Another potential marker, Cancer Antigen 125 (CA-125) is a well-established indicator for epithelial cell ovarian cancer and its levels can be elevated in conditions such as endometriosis. CA-125 is derived from coelomic epithelia, including the endometrium, fallopian tube, ovary, and peritoneum. In this review we examine the pathophysiologic basis for endometriosis and highlight potential markers to more fully characterize the underlying biochemical processes linked to this multifaceted disease state.

Histone lactylation-mediated overexpression of RASD2 promotes endometriosis progression via upregulating the SUMOylation of CTPS1

Histone lactylation is crucial in a variety of physiopathological processes; however, the function and mechanism of histone lactylation in endometriosis remain poorly understood. Therefore, the objective of this investigation was to illuminate the function and mechanism of histone lactylation in endometriosis. Immunohistochemistry was used to investigate the expression of histone lactylation. Cell Counting Kit-8 assay (CCK8), Transwell assay, and endometriosis mouse models were used to investigate the effects of histone lactylation in vitro and in vivo. Transcriptomics and immunoprecipitation-mass spectrometry (IP-MS), Western blot, co-immunoprecipitation (Co-IP), quantitative reverse transcription polymerase chain reaction (qRT-PCR), and chromatin immunoprecipitation-qPCR (ChIP-qPCR) were used to explore the intrinsic mechanisms. In this study, we found that histone lactylation was upregulated in endometriosis and could promote endometriosis progression both in vivo and in vitro. Mechanistically, histone lactylation H3K18la promoted the transcription of Ras homolog enriched in striatum (RASD2), and RASD2, in turn, increased the stability of CTP synthase 1 (CTPS1) by promoting the SUMOylation and inhibiting the ubiquitination of CTPS1, thereby promoting endometriosis progression. Overall, our findings indicated that histone lactylation could promote the progression of endometriosis through the RASD2/CTPS1 axis. This investigation uncovered a novel mechanism and identified prospective targets for endometriosis diagnosis and therapy.NEW & NOTEWORTHY Our finding reveals a novel mechanism that promotes the progression of endometriosis, namely the histone lactylation/RASD2/CTPS1 axis. This finding suggests that inhibiting histone lactylation or inhibiting RASD2 and CTPS1 might be a potential therapeutic strategy to inhibit endometriosis lesion growth.

The Current Applications of Metabolomics in Understanding Endometriosis: A Systematic Review

Endometriosis is a common gynecological disease that affects approximately 10-15% of reproductive-aged women worldwide. This debilitating disease has a negative impact on the quality of life of those affected. Despite this condition being very common, the pathogenesis is not well understood. Metabolomics is the study of the array of low-weight metabolites in a given sample. This emerging field of omics-based science has proved to be effective at furthering the understanding of endometriosis. In this systematic review, we seek to provide an overview of the application of metabolomics in endometriosis. We highlight the use of metabolomics in locating biomarkers for identification, understanding treatment mechanisms and symptoms, and relating external factors to endometriosis. The literature search took place in the Web of Science, Pubmed, and Google Scholar based on the keywords "metabolomics" AND "endometriosis" or "metabolome" AND "endometriosis". We found 58 articles from 2012 to 2024 that met our search criteria. Significant alterations of lipids, amino acids, as well as other compounds were present in human and animal models. Discrepancies among studies of significantly altered metabolites make it difficult to make general conclusions on the metabolic signature of endometriosis. However, several individual metabolites were elevated in multiple studies of women with endometriosis; these include 3-hydroxybutyrate, lactate, phosphatidic acids, succinate, pyruvate, tetradecenoylcarnitine, hypoxanthine, and xanthine. Accordingly, L-isoleucine and citrate were reduced in multiple studies of women with endometriosis. Including larger cohorts, standardizing testing methods, and studying the individual phenotypes of endometriosis may lead to more separable results.

Metabolomics for the identification of biomarkers in endometriosis

BACKGROUND

Endometriosis affects the quality of life in women during their reproductive years, causing immense pain and can result in infertility. It is characterized by inflammation and the growth of the endometrium outside the uterine cavity. Metabolomics has the potential to resolve the major bottleneck of endometriosis which is delay in diagnosis due to the invasive diagnostic approach.In this review, the author has summarized the identified biomarkers of endometriosis from different bodily fluids. Metabolomics promises a non-invasive diagnostic approach for endometriosis that could aid in earlier diagnosis and prognosis.

METHODS

Patients with endometriosis keywords were searched in correspondence with the assigned keywords, including metabolomics from PubMed, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study.

RESULTS

This article provides information regarding metabolomics studies in endometrisis.

CONCLUSIONS

We demonstrated that metabolomics is about to change the world of endometriosis by analyzing and detecting the diagnosis, prognosis, mortality and treatment response biomarkers.

Gut Microbiota, Circulating Metabolites and Risk of Endometriosis: A Two-Step Mendelian Randomization Study

Epidemiological studies and animal models have suggested a possible link between gut microbiota (GM), circulating metabolites, and endometriosis (EMs) pathogenesis. However, whether these associations are causal or merely due to confounding factors remains unclear. We conducted a two-sample and two-step Mendelian randomization (MR) study to elucidate the potential causal relationship between GM and EMs, and the mediating role of circulating metabolites. Our MR analysis revealed that higher abundances of class Negativicutes, and order Selenomonadales, as well as genera Dialister, Enterorhabdus, Eubacterium xylanophilum group, Methanobrevibacter were associated with an increased risk of EMs (Odds Ratio (OR) range: 1.0019-1.0037). Conversely, higher abundances of genera Coprococcus 1 and Senegalimassilia were linked to reduced risk of EMs (OR range: 0.9964-0.9967). Additionally, elevated levels of circulating metabolites such as 1-eicosatrienoyl-glycerophosphocholine and 1-oleoylglycerophosphocholine were found to be associated with heightened risk of EMs (OR range: 2.21-3.16), while higher concentrations of 3-phenylpropionate and dihomo-linolenate were protective (OR range: 0.285-0.535). Two-step MR analysis indicated that specific microbial taxa, notably genus Enterorhabdus and order Selenomonadales, might function as mediators linking circulating metabolites to the risk of EMs. Our findings suggest a probable causal relationship between GM, circulating metabolites, and EMs, indicating that GM may mediate the influence of circulating metabolites on the pathophysiology of EMs. These results offer new leads for future mechanistic studies and could inform clinical translational research.

Causal effects of genetically determined circulating metabolites on endometriosis: A Mendelian randomization study

Endometriosis (EMs) is a common gynecological disease accompanied by metabolic disturbances. However, the causality between metabolites and the risk of EMs remains unclear. We conducted a 2-sample Mendelian randomization (MR) analysis using the publicly available genome-wide association study (GWAS) of 486 circulating metabolites and EMs. The inverse variance weighted (IVW) was mainly used for assessing causality. MR-Egger intercept, MR-PRESSO Global, leave-one-out, and Cochran Q test analyses were used for sensitivity analyses. A total of 25 causal metabolites related to EMs have been identified, including 13 known and 12 unknown ones. Among the known metabolites, caffeine (OR = 0.86, 95% CI: 0.76-0.98, P = .026), cortisol (OR = 0.64, 95% CI: 0.41-0.99, P = .047), glycocholate (OR = 0.67, 95% CI: 0.51-0.87, P = .003), adrenate 22:4n6 (OR = 0.52, 95% CI: 0.35-0.77, P = .001), and ergothioneine (OR = 0.62, 95% CI: 0.47-0.81, P = .000) were protective factors for EMs, while mannose (OR = 1.43, 95% CI: 1.01-2.03, P = .044), 4-acetamidobutanoate (OR = 1.92, 95% CI: 1.27-2.89, P = .002), 1-linoleoylglycerol (OR = 1.36, 95% CI: 1.10-1.68, P = .005), bilirubin (Z, Z) (OR = 1.15, 95% CI: 1.01-1.31, P = .032), threonate (OR = 1.42, 95% CI: 1.14-1.77, P = .002), bilirubin (E, E) (OR = 1.18, 95% CI: 1.01-1.38, P = .039), erythronate (OR = 1.59, 95% CI: 1.01-2.52, P = .047), and dimethylarginine (SDMA + ADMA) (OR = 2.07, 95% CI: 1.19-3.62, P = .010) were risk factors for EMs. Additionally, there was no evidence of heterogeneity or pleiotropy of the known metabolites. Leave-one-out analysis indicated that the MR findings were robust. Our findings provide valuable circulating biomarkers as well as therapeutic targets for the screening, prevention, and treatment of EMs.

Follicular Fluid and Blood Monitorization of Infertility Biomarkers in Women with Endometriosis

Infertility is recognized globally as a social disease and a growing medical condition, posing a significant challenge to modern reproductive health. Endometriosis, the third-most frequent gynecologic disorder, is one of the most common and intricate conditions that can lead to female infertility. Despite extensive research, the etiology, malignant transformation, and biological therapy of endometriosis remain unknown. Blood and follicular fluid are two matrices that have been carefully studied and can provide insights into women's health. These matrices are clinically significant because they contain metabolites closely associated with women's illness stage and reproductive outcomes. Nowadays, the application of metabolomic analysis in biological matrices may be able to predict the outcome of assisted reproductive technologies with greater precision. From a molecular viewpoint on reproductive health, we evaluate and compare the utilization of human follicular fluid and blood as matrices in analysis for diagnostic and assisted reproductive technology (ART) predictors of success for endometriosis patients. In the follicular fluid (FF), plasma, and serum of endometriosis-affected women, researchers identified dysregulations of oxidative stress, upregulation of several immune factors, and aberrations in energy metabolic pathways. The altered signatures negatively correlate with the overall oocyte and embryo quality and fertilization rate.

Exploring the potential effect of electroacupuncture on cardiovascular function and lipid profiles in spontaneously hypertensive rats

Background

Investigating the effects of electroacupuncture (EA) treatment on cardiovascular function and aortic lipid profiles in spontaneously hypertensive rats (SHR) constitutes the foundational focus of this study. The overarching goal is to comprehensively elucidate the alterations brought about by EA treatment and to assess its potential as an alternative therapy for hypertension.

Methods

Consecutive EA treatments were administered to SHR, and the effects on systolic blood pressure, cardiac function, and hypertension-related neuronal signals were assessed. Aortic lipid profiles in vehicle-treated SHR and EA-treated SHR groups were analyzed using mass spectrometry-based lipid profiling. Additionally, the expression of Cers2 and GNPAT, enzymes involved in the synthesis of specific aortic lipids, was examined.

Results

The study demonstrated that consecutive EA treatments restored systolic blood pressure, improved cardiovascular function, and normalized hypertension-related neuronal signals in SHR. Analysis of the aortic lipid profiles revealed distinct differences between the vehicle-treated SHR group and the EA-treated SHR group. Specifically, EA treatment significantly altered the levels of aortic sphingomyelin and phospholipids, including very long-chain fatty acyl-ceramides and ether phosphatidylcholines. These changes in aortic lipid profiles correlated significantly with systolic blood pressure and cardiac function indicators. Furthermore, EA treatment significantly altered the expression of Cers2 and GNPAT.

Conclusions

The findings suggest that EA may influence cardiovascular functions and aortic lipid profiles in SHR.

Artificial Intelligence in the Management of Women with Endometriosis and Adenomyosis: Can Machines Ever Be Worse Than Humans?

Artificial intelligence (AI) is experiencing advances and integration in all medical specializations, and this creates excitement but also concerns. This narrative review aims to critically assess the state of the art of AI in the field of endometriosis and adenomyosis. By enabling automation, AI may speed up some routine tasks, decreasing gynecologists' risk of burnout, as well as enabling them to spend more time interacting with their patients, increasing their efficiency and patients' perception of being taken care of. Surgery may also benefit from AI, especially through its integration with robotic surgery systems. This may improve the detection of anatomical structures and enhance surgical outcomes by combining intra-operative findings with pre-operative imaging. Not only that, but AI promises to improve the quality of care by facilitating clinical research. Through the introduction of decision-support tools, it can enhance diagnostic assessment; it can also predict treatment effectiveness and side effects, as well as reproductive prognosis and cancer risk. However, concerns exist regarding the fact that good quality data used in tool development and compliance with data sharing guidelines are crucial. Also, professionals are worried AI may render certain specialists obsolete. This said, AI is more likely to become a well-liked team member rather than a usurper.

A comprehensive multiplatform metabolomic analysis reveals alterations of 2-hydroxybutyric acid among women with deep endometriosis related to the pesticide trans-nonachlor

BACKGROUND

Exposure to persistent organic pollutants (POPs) has been related to the risk of endometriosis however the mechanisms remain unclear. The objective of the present study was to characterize the metabolic profiles underpinning the associations between POPs and endometriosis risk.

METHODOLOGY

A hospital-based case-control study was conducted in France to recruit women with and without surgically confirmed deep endometriosis. Women's serum was analyzed using gas and liquid chromatography coupled to high-resolution mass spectrometry (HRMS) to measure the levels of polychlorinated biphenyls (PCBs), organochlorinated pesticides (OCPs) and per-/polyfluoroalkyl substances (PFAS). A comprehensive metabolomic profiling was conducted using targeted HRMS and 1H nuclear magnetic resonance (1H NMR) to cover polar and non-polar fractions. A "meet-in-the-middle" statistical framework was applied to identify the metabolites related to endometriosis and POP levels, using multivariate linear and logistic regressions adjusting for confounding variables.

RESULTS

Fourteen PCBs, six OCPs and six PFAS were widely found in almost all serum samples. The pesticide trans-nonachlor was the POP most strongly and positively associated with deep endometriosis risk, with odds ratio (95 % confidence interval) of 2.42 (1.49; 4.12), followed by PCB180 and 167. Women with endometriosis exhibited a distinctive metabolic profile, with elevated serum levels of lactate, ketone bodies and multiple amino acids and lower levels of bile acids, phosphatidylcholines (PCs), cortisol and hippuric acid. The metabolite 2-hydroxybutyrate was simultaneously associated to endometriosis risk and exposure to trans-nonachlor.

CONCLUSIONS

To the best of our knowledge, this is the first comprehensive metabolome-wide association study of endometriosis, integrating ultra-trace profiling of POPs. The results confirmed a metabolic alteration among women with deep endometriosis that could be also associated to the exposure to POPs. Further observational and experimental studies will be required to delineate the causal ordering of those associations and gain insight on the underlying mechanisms.

An integrated multi-tissue approach for endometriosis candidate biomarkers: a systematic review

Biomarker identification could help in deciphering endometriosis pathophysiology in addition to their use in the development of non invasive diagnostic and prognostic approaches, that are essential to greatly improve patient care. Despite extensive efforts, no single potential biomarker or combination has been clinically validated for endometriosis.Many studies have investigated endometriosis-associated biological markers in specific tissues, but an integrative approach across tissues is lacking. The aim of this review is to propose a comprehensive overview of identified biomarkers based on tissue or biological compartment, while taking into account endometriosis phenotypes (superficial, ovarian or deep, or rASRM stages), menstrual cycle phases, treatments and symptoms.We searched PubMed and Embase databases for articles matching the following criteria: 'endometriosis' present in the title and the associated term 'biomarkers' found as Medical Subject Headings (MeSH) terms or in all fields. We restricted to publications in English and on human populations. Relevant articles published between 01 January 2005 (when endometriosis phenotypes start to be described in papers) and 01 September 2022 were critically analysed and discussed.Four hundred forty seven articles on endometriosis biomarkers that included a control group without endometriosis and provided specific information on endometriosis phenotypes are included in this review. Presence of information or adjustment controlling for menstrual cycle phase, symptoms and treatments is highlighted, and the results are further summarized by biological compartment. The 9 biological compartments studied for endometriosis biomarker research are in order of frequency: peripheral blood, eutopic endometrium, peritoneal fluid, ovaries, urine, menstrual blood, saliva, feces and cervical mucus. Adjustments of results on disease phenotypes, cycle phases, treatments and symptoms are present in 70%, 29%, 3% and 6% of selected articles, respectively. A total of 1107 biomarkers were identified in these biological compartments. Of these, 74 were found in several biological compartments by at least two independent research teams and only 4 (TNF-a, MMP-9, TIMP-1 and miR-451) are detected in at least 3 tissues with cohorts of 30 women or more.Integrative analysis is a crucial step to highlight potential pitfalls behind the lack of success in the search for clinically relevant endometriosis biomarkers, and to illuminate the physiopathology of this disease.

Assessing the Utility of artificial intelligence in endometriosis: Promises and pitfalls

Endometriosis, a chronic condition characterized by the growth of endometrial-like tissue outside of the uterus, poses substantial challenges in terms of diagnosis and treatment. Artificial intelligence (AI) has emerged as a promising tool in the field of medicine, offering opportunities to address the complexities of endometriosis. This review explores the current landscape of endometriosis diagnosis and treatment, highlighting the potential of AI to alleviate some of the associated burdens and underscoring common pitfalls and challenges when employing AI algorithms in this context. Women's health research in endometriosis has suffered from underfunding, leading to limitations in diagnosis, classification, and treatment approaches. The heterogeneity of symptoms in patients with endometriosis has further complicated efforts to address this condition. New, powerful methods of analysis have the potential to uncover previously unidentified patterns in data relating to endometriosis. AI, a collection of algorithms replicating human decision-making in data analysis, has been increasingly adopted in medical research, including endometriosis studies. While AI offers the ability to identify novel patterns in data and analyze large datasets, its effectiveness hinges on data quality and quantity and the expertise of those implementing the algorithms. Current applications of AI in endometriosis range from diagnostic tools for ultrasound imaging to predicting treatment success. These applications show promise in reducing diagnostic delays, healthcare costs, and providing patients with more treatment options, improving their quality of life. AI holds significant potential in advancing the diagnosis and treatment of endometriosis, but it must be applied carefully and transparently to avoid pitfalls and ensure reproducibility. This review calls for increased scrutiny and accountability in AI research. Addressing these challenges can lead to more effective AI-driven solutions for endometriosis and other complex medical conditions.

Recent progress in metabolomics for analyzing common infertility conditions that affect ovarian function

Background

Numerous efforts have been undertaken to identify biomarkers associated with embryo and oocyte quality to improve the success rate of in vitro fertilization. Metabolomics has gained traction for its ability to detect dynamic biological changes in real time and provide comprehensive metabolite profiles. This review synthesizes the most recent findings on metabolomic analysis of follicular fluid (FF) in clinical conditions leading to infertility, with a focus on the dynamics of energy metabolism and oocyte quality, and discusses future research directions.

Methods

A literature search was conducted without time constraints.

Main findings

The metabolites present in FF originate from five primary pathways: glycolysis, oxidative phosphorylation, lipid metabolism and β-oxidation, nucleic acid synthesis, and ketogenesis. Metabolomic profiling can broadly categorize infertile women into two groups: those with infertility due to aging and endometriosis, and those with infertility associated with polycystic ovarian syndrome and obesity. In the former group, glycolysis and lipid metabolism are upregulated to compensate for mitochondrial dysfunction, whereas the latter group exhibits the opposite trend. Assessing the levels of glucose, pyruvate, lactate, and plasmalogens in FF may be valuable for evaluating oocyte quality.

Conclusion

Metabolomic analysis, particularly focusing on energy metabolism in FF, holds promise for predicting female reproductive outcomes.

Self-report symptom-based endometriosis prediction using machine learning

Endometriosis is a chronic gynecological condition that affects 5-10% of reproductive age women. Nonetheless, the average time-to-diagnosis is usually between 6 and 10 years from the onset of symptoms. To shorten time-to-diagnosis, many studies have developed non-invasive screening tools. However, most of these studies have focused on data obtained from women who had/were planned for laparoscopy surgery, that is, women who were near the end of the diagnostic process. In contrast, our study aimed to develop a self-diagnostic tool that predicts the likelihood of endometriosis based only on experienced symptoms, which can be used in early stages of symptom onset. We applied machine learning to train endometriosis prediction models on data obtained via questionnaires from two groups of women: women who were diagnosed with endometriosis and women who were not diagnosed. The best performing model had AUC of 0.94, sensitivity of 0.93, and specificity of 0.95. The model is intended to be incorporated into a website as a self-diagnostic tool and is expected to shorten time-to-diagnosis by referring women with a high likelihood of having endometriosis to further examination. We also report the importance and effectiveness of different symptoms in predicting endometriosis.

Integrative analysis of transcriptomic and metabolomic profiles reveals abnormal phosphatidylinositol metabolism in follicles from endometriosis‐associated infertility patients

Endometriosis is a common gynecological disorder that causes female infertility. Our recent research found that excessive oxidative stress in ovaries of endometriosis patients induced senescence of cumulus granulosa cells. Here, we analyzed the transcriptomic and metabolomics profiles of follicles in a mouse model of endometriosis and in patients with endometriosis and investigated the potential function of changed metabolites in granulosa cells. RNA-sequencing indicated that both endometriosis lesions and oxidative stress in mice induced abnormalities of reactive oxidative stress, steroid hormone biosynthesis, and lipid metabolism. The mouse model and women with endometriosis showed altered lipid metabolism. Nontargeted metabolite profiling of follicular fluid from endometriosis and male-factor infertility patients by liquid chromatography mass spectrometry identified 55 upregulated and 67 downregulated metabolites. These differential metabolites were mainly involved in steroid hormone biosynthesis and glycerophospholipid metabolism. Phosphatidylinositol (PI 16:0/18:2) was significantly elevated in follicular fluid from endometriosis patients compared with controls (p < 0.05), while lysophosphatidylinositol (LPI 18:2, 20:2, 18:1, 20:3 and 18:3) was reduced (p < 0.05). Upregulated PI and downregulated LPI correlated with oocyte retrieval number and mature oocyte number. LPI inhibited cellular reactive oxidative stress induced by hemin in granulosa cells. Cell proliferation inhibition, senescence, and apoptosis induced by hemin were partially reversed by LPI. Moreover, LPI administration rescued hemin blocking of cumulus-oocyte complex expansion and stimulated expression of ovulation-related genes. Transcriptomic Switching mechanism at 5' end of the RNA transcript sequencing and western blot revealed that LPI effects on granulosa cells were associated with its regulation of MAPK-ERK1/2 signaling, which was suppressed in the presence of hemin. In conclusion, our results revealed the dysregulation of lipid metabolism in endometriotic follicles. LPI may represent a novel agent for in vitro follicular culture that reverses the excessive oxidative stress from endometriotic lesions. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Gut microbiota and microbiota-derived metabolites promotes endometriosis

Endometriosis is a pathological condition of the female reproductive tract characterized by the existence of endometrium-like tissue at ectopic sites, affecting 10% of women between the age 15 and 49 in the USA. However, currently there is no reliable non-invasive method to detect the presence of endometriosis without surgery and many women find hormonal therapy and surgery as ineffective in avoiding the recurrences. There is a lack of knowledge on the etiology and the factors that contribute to the development of endometriosis. A growing body of recent evidence suggests an association between gut microbiota and endometriosis pathophysiology. However, the direct impact of microbiota and microbiota-derived metabolites on the endometriosis disease progression is largely unknown. To understand the causal role of gut microbiota and endometriosis, we have implemented a novel model using antibiotic-induced microbiota-depleted (MD) mice to investigate the endometriosis disease progression. Interestingly, we found that MD mice showed reduced endometriotic lesion growth and, the transplantation of gut microbiota by oral gavage of feces from mice with endometriosis rescued the endometriotic lesion growth. Additionally, using germ-free donor mice, we indicated that the uterine microbiota is dispensable for endometriotic lesion growth in mice. Furthermore, we showed that gut microbiota modulates immune cell populations in the peritoneum of lesions-bearing mice. Finally, we found a novel signature of microbiota-derived metabolites that were significantly altered in feces of mice with endometriosis. Finally, we found one the altered metabolite, quinic acid promoted the survival of endometriotic epithelial cells in vitro and lesion growth in vivo, suggesting the disease-promoting potential of microbiota-derived metabolites. In summary, these data suggest that gut microbiota and microbiota-derived metabolome contribute to lesion growth in mice, possibly through immune cell adaptations. Of translational significance, these findings will aid in designing non-invasive diagnostics using stool metabolites for endometriosis.

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study

BACKGROUND

Endometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography-mass spectrometer (GC-MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers.

METHODS

Twenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC-MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis.

RESULTS

Partial least squares discriminant analysis was performed to determine the differences between the two groups (p = 0.003). Threonic acid, 3-hydroxybutyric acid, and proline increased significantly in endometriosis patients, while alanine and valine decreased. ROC curves were built to test the diagnostic power of metabolites. The pathway analysis identified the synthesis and degradation of ketone bodies and the biosynthesis of phenylalanine, tyrosine, and tryptophan as the most altered pathways.

CONCLUSIONS

The metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers.

Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis

Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.

Emerging hallmarks of endometriosis metabolism: A promising target for the treatment of endometriosis

Endometriosis, characterized by ectopic endometrium growth in the extrauterine environment, is one of the most notable diseases of the female reproductive system. Worldwide, endometriosis affects nearly 10 % of women in their reproductive years and causes a significant decline in quality of life. Despite extensive investigations of endometriosis over the past years, the mechanisms of endometriosis pathogenesis remain unclear. In recent years, metabolic factors have increasingly been considered factors in endometriosis. There is compelling evidence regarding the progress of endometriosis in the context of severe metabolic dysfunction. Hence, the curative strategies and ongoing attempts to conquer endometriosis might start with metabolic pathways. This review focuses on metabolic mechanisms and summarizes current research progress. These findings provide valuable information for the non-intrusive diagnosis of the disease and may contribute to the understanding of the pathogenesis of endometriosis.

Clinical use of artificial intelligence in endometriosis: a scoping review

Endometriosis is a chronic, debilitating, gynecologic condition with a non-specific clinical presentation. Globally, patients can experience diagnostic delays of ~6 to 12 years, which significantly hinders adequate management and places a significant financial burden on patients and the healthcare system. Through artificial intelligence (AI), it is possible to create models that can extract data patterns to act as inputs for developing interventions with predictive and diagnostic accuracies that are superior to conventional methods and current tools used in standards of care. This literature review explored the use of AI methods to address different clinical problems in endometriosis. Approximately 1309 unique records were found across four databases; among those, 36 studies met the inclusion criteria. Studies were eligible if they involved an AI approach or model to explore endometriosis pathology, diagnostics, prediction, or management and if they reported evaluation metrics (sensitivity and specificity) after validating their models. Only articles accessible in English were included in this review. Logistic regression was the most popular machine learning method, followed by decision tree algorithms, random forest, and support vector machines. Approximately 44.4% (n = 16) of the studies analyzed the predictive capabilities of AI approaches in patients with endometriosis, while 47.2% (n = 17) explored diagnostic capabilities, and 8.33% (n = 3) used AI to improve disease understanding. Models were built using different data types, including biomarkers, clinical variables, metabolite spectra, genetic variables, imaging data, mixed methods, and lesion characteristics. Regardless of the AI-based endometriosis application (either diagnostic or predictive), pooled sensitivities ranged from 81.7 to 96.7%, and pooled specificities ranged between 70.7 and 91.6%. Overall, AI models displayed good diagnostic and predictive capacity in detecting endometriosis using simple classification scenarios (i.e., differentiating between cases and controls), showing promising directions for AI in assessing endometriosis in the near future. This timely review highlighted an emerging area of interest in endometriosis and AI. It also provided recommendations for future research in this field to improve the reproducibility of results and comparability between models, and further test the capacity of these models to enhance diagnosis, prediction, and management in endometriosis patients.

Endometriosis biomarkers of the disease: an update

PURPOSE OF REVIEW

Endometriosis is a complex benign gynaecologic condition with heterogenous presentations and a large impact on the global healthcare system and on the quality of life for millions of women. Currently, the gold standard for diagnosis involves direct visualization of lesions during surgery confirmed by histopathological diagnosis, resulting in an average delay in its initial diagnosis of 8-10 years. Therefore, the search for noninvasive diagnostic testing options has been subject to a large body of research.

RECENT FINDINGS

Multiple potential biomarkers have been explored for noninvasive testing for endometriosis, including glycoproteins, inflammatory cytokines, immunological molecules, angiogenesis markers, hormones, micro RNAs (miRNAs), proteomics, metabolomics, genomics and the microbiome.

SUMMARY

Although there are challenges to consider, areas for real promise and advancement in the noninvasive diagnosis of endometriosis are currently being explored with real promise in the area of miRNAs, proteomics, metabolomics, genomics and the microbiome.

Presurgical blood metabolites and risk of postsurgical pelvic pain in young patients with endometriosis

OBJECTIVE

To identify metabolites in presurgical blood associated with risk of persistent postsurgical pelvic pain 1 year after endometriosis surgery in adolescent and young adult patients.

DESIGN

Prospective observational study within the Women's Health Study: From Adolescence to Adulthood, a US-based longitudinal cohort of adolescents and women enrolled from 2012-2018.

SETTING

Two tertiary care hospitals.

PATIENT(S)

Laparoscopically confirmed endometriosis patients (n = 180) with blood collected before their endometriosis surgery. Of these, 77 patients additionally provided blood samples 5 weeks to 6 months after their surgery. We measured plasma metabolites using liquid chromatography tandem mass spectrometry, and a total of 390 known metabolites were included in our analysis.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Persistent postsurgical pelvic pain, defined as severe, life-impacting pelvic pain 1 year after endometriosis surgery.

RESULT(S)

Most patients (>95%) were at stage I/II of the revised American Society for Reproductive Medicine classification. Their average age at diagnosis was 18.7 years, with 36% reporting persistent postsurgical pelvic pain. Of the 21 metabolites in presurgical blood that were associated with risk of persistent postsurgical pelvic pain, 19 metabolites, which were mainly lipid metabolites, were associated with increased risk. Only 2 metabolites-pregnenolone sulfate (odds ratio = 0.64, 95% confidence interval = 0.44-0.92) and fucose (odds ratio = 0.69, 95% confidence interval = 0.47-0.97)-were associated with decreased risk. Metabolite set enrichment analysis revealed that higher levels of lysophosphatidylethanolamines (false discovery rate = 0.01) and lysophosphatidylcholines (false discovery rate = 0.01) in presurgical blood were associated with increased risk of persistent postsurgical pelvic pain.

CONCLUSION(S)

Our results suggest that dysregulation of multiple groups of lipid metabolites may play a role in the persistence of pelvic pain postsurgery among young endometriosis patients.

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.

Integrative metabolomic profiling reveals aberrations in myometrium associated with adenomyosis: a pilot study

BACKGROUND

Uterine adenomyosis is a common gynecologic disease in premenopausal women, the pathological mechanism of which remains largely unknown. The aim of this study was to identify metabolic biomarkers significantly altered in the myometrium of adenomyosis patients.

METHODS

The comprehensive metabolomic profiles of 17 myometrium specimens from adenomyosis patients and 25 control specimens were analyzed using untargeted approach by combination of gas chromatography-mass spectrometry and high performance liquid chromatography-mass spectrometry. Metabolic data were filtered using orthogonal partial least square-discriminant analysis and univariate statistics.

RESULTS

We firstly demonstrated that the myometrial metabolome of women with adenomyosis is distinct from that of women without adenomyosis. A total of 106 metabolites, mainly including nucleosides, lipids (including acylcarnitines), amino acids, organic acids and carbohydrates, were found to be differentially expressed in myometrium of uteri with adenomyosis compared to the control subjects. Functional inferences of these perturbed metabolites indicated that inflammation, oxidative stress, cell proliferation and apoptosis, and energy metabolism appeared to be involved in the progress of adenomyosis.

CONCLUSION

This study firstly described the integrated metabolic signatures of the adenomyosis uterus, which provided novel insights for the pathogenesis study of this disease.

Dysregulated sphingolipid metabolism and autophagy in granulosa cells of women with endometriosis

We evaluated metabolic profiles between cumulus cells (CCs) and mural granulosa cells (MGCs) derived from women with endometriosis to identify their correlations with oocyte quality. CCs and MGCs were collected from women with and without endometriosis undergoing in vitro fertilization/intracytoplasmic sperm injection treatment. The metabolomics of CCs and MGCs were measured by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) followed by a quantitative polymerase chain reaction to further confirm the genes involved in the metabolic results. LC-MS/MS analysis revealed differences in 24 metabolites of CCs and 71 metabolites of MGCs between groups. Among them, five metabolites were upregulated and 19 metabolites were downregulated in CCs with endometriosis, whereas three metabolites were upregulated and 68 metabolites were downregulated in MGCs with endometriosis. Metabolites related to sphingolipid metabolism, which included palmitic acid (PA) and docosahexaenoic acid, increased significantly only in CCs with endometriosis, whereas sphingosine and PA were significantly downregulated in MGCs with endometriosis compared with CCs and MGCs without endometriosis. Gene expression involved in ceramide synthesis (CERS1, SPTL1, and SMPD1) and autophagy (BECN1, LAMP, and PC3) were significantly higher in CCs with endometriosis according to FASN, BECN1, and LAMP protein expressions. However, gene expression involved in ceramide synthesis (SPHK1, ASAH1, and SGPP1) and autophagy (BECN1, LAMP, and PC3) were significantly lower in MGCs with endometriosis, whereas CERS1 and UGCG expression increased. There are differences in sphingolipid metabolites in CCs and MGCs with endometriosis compared with women without endometriosis. These differences seem to be involved in the regulation of autophagic cell death in preovulatory follicles.

The Investigation of Metabonomic Pathways of Serum of Iranian Women with Recurrent Miscarriage Using 1H NMR

Purpose

Recurrent miscarriage applies to pregnancy loss expulsion of the fetus within the first 24 weeks of pregnancy. This study is aimed at comparatively investigating the sera of women with RM with those who have no record of miscarriages to identify if there were any metabolite and metabolic pathway differences using ¹H NMR spectroscopy.

Methods

Serum samples were collected from women with RM (n = 30) and those who had no records of RM (n = 30) to obtain metabolomics information. ¹H NMR spectroscopy was carried out on the samples using Carr Purcell Meiboom Gill spin echo; also, Partial Least Squares Discriminant Analysis was performed in MATLAB software using the ProMetab program to obtain the classifying chemical shifts; the metabolites were identified by using the Human Metabolome Database (HMDB) in both the experimental and control groups. The pathway analysis option of the Metaboanalyst.ca website was used to identify the changed metabolic pathways.

Results

The results of the study revealed that 14 metabolites were different in the patients with RM. Moreover, the pathway analysis showed that taurine and hypotaurine metabolism along with phenylalanine, tyrosine, and tryptophan biosynthesis was significantly different in patients with RM.

Conclusion

The present study proposes that any alteration in the above metabolic pathways might lead to metabolic dysfunctions which may result in a higher probability of RM.

Symptomatology and Serum Nuclear Magnetic Resonance Metabolomics; Do They Predict Endometriosis in Fertile Women Undergoing Laparoscopic Sterilisation? A Prospective Cross-sectional Study

Endometriosis is a common, chronic inflammatory condition, thought to have a higher incidence in symptomatic women, yet, commonly associated symptoms do not always correlate with the presence or severity of disease and diagnosis requires surgery. We prospectively collected data and assessed symptomology and NMR spectroscopy-based metabolomics of 102 women undergoing laparoscopic sterilisation at a tertiary referral centre in a cross-sectional study. Twelve women were incidentally diagnosed with endometriosis (11.7%). According to the pre-operative questionnaire, presence and absence of many symptoms usually attributed to endometriosis were declared at similar frequencies in women with or without endometriosis. Women with endometriosis reported apparently more persistent heavy periods (50% vs 18.9%), prolonged periods (25% versus 7.8%) and problems conceiving (27.3% versus 9%) than those without endometriosis. NMR could not discern any distinguishable differences in the serum metabolome between those with and without endometriosis. Our paper highlights the complex symptomology experienced by women, regardless of a surgical diagnosis of endometriosis. Previous literature and the current study failed to identify clear, distinguishable symptoms or biomarkers pertinent to surgically confirmed endometriosis in the general population. Therefore, development of effective, non-invasive tests for identifying this heterogenous benign condition, endometriosis, is likely to be challenging.

Discovery and validation of peritoneal endometriosis biomarkers in peritoneal fluid and serum

RESEARCH QUESTION

What are the potential biomarkers for peritoneal endometriosis in peritoneal fluid and serum?

DESIGN

Case-control studies composed of independent discovery and validation sets were conducted. In the discovery set, untargeted liquid chromatography-mass spectrometry (LC-MS/MS) metabolomics, multivariable and univariable analyses were conducted to generate global metabolomic profiles of peritoneal fluid for endometriosis and to identify potential metabolites that could distinguish peritoneal endometriosis (n = 10) from controls (n = 31). The identified metabolites from the discovery set were validated in independent peritoneal fluid (n =19 peritoneal endometriosis and n = 20 controls) and serum samples (n = 16 peritoneal endometriosis and n = 19 controls) using targeted metabolomics. The area under the receiver-operating characteristics curve (AUC) analysis was used to evaluate the diagnostic performance of peritoneal endometriosis metabolites.

RESULTS

In the discovery set, peritoneal fluid phosphatidylcholine (34:3) and phenylalanyl-isoleucine were significantly increased in peritoneal endometriosis groups compared with control groups, with AUC 0.77 (95% CI 0.61 to 0.92; P = 0.018) and AUC 0.98 (95% CI 0.95 to 1.02; P < 0.001), respectively. In the validation set, phenylalanyl-isoleucine retained discriminatory performance to distinguish peritoneal endometriosis from controls in both peritoneal fluid (AUC 0.77, 95% CI 0.61 to 0.92; P = 0.006) and serum samples (AUC 0.81, 95% CI 0.64 to 0.99; P = 0.004), with notably stronger discrimination between peritoneal endometriosis and controls in proliferative phase.

CONCLUSION

Our preliminary results propose phenylalanyl-isoleucine as a potential biomarker of peritoneal endometriosis, which may be used as a minimally invasive diagnostic biomarker of peritoneal endometriosis.

Global metabolome profiling of exhaled breath condensates in male smokers with asthma COPD overlap and prediction of the disease

Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease characterised by persistent airflow limitation, which manifests features of both asthma and COPD. These patients have a worse prognosis, in terms of more frequent and severe exacerbations, more frequent symptoms, worse quality of life, increased comorbidities and a faster lung function decline. In absence of clear diagnostic or therapeutic guidelines, ACO presents as a challenge to clinicians. The present study aims to investigate whether ACO patients have a distinct exhaled breath condensate (EBC) metabolic profile in comparison to asthma and COPD. A total of 132 age and BMI matched male smokers were recruited in the exploratory phase which consisted of (i) controls = 33 (ii) asthma = 34 (iii) COPD = 30 and (iv) ACO = 35. Using nuclear magnetic resonance (NMR) metabolomics, 8 metabolites (fatty acid, propionate, isopropanol, lactate, acetone, valine, methanol and formate) were identified to be significantly dysregulated in ACO subjects when compared to both, asthma and COPD. The expression of these dysregulated metabolites were further validated in a fresh patient cohort consisting of (i) asthma = 32 (ii) COPD = 32 and (iii) ACO = 40, which exhibited a similar expression pattern. Multivariate receiver operating characteristic (ROC) curves generated using these metabolites provided a robust ACO classification model. The findings were also integrated with previously identified serum metabolites and inflammatory markers to develop a robust predictive model for differentiation of ACO. Our findings suggest that NMR metabolomics of EBC holds potential as a platform to identify robust, non-invasive biomarkers for differentiating ACO from asthma and COPD.

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.

Adenomyosis is associated with specific proton nuclear magnetic resonance (1H-NMR) serum metabolic profiles

OBJECTIVE

To determine whether the adenomyosis phenotype affects the proton nuclear magnetic resonance (¹H-NMR)-based serum metabolic profile of patients.

DESIGN

Cohort study.

SETTING

University hospital-based research center.

PATIENTS

Seventy-seven patients who underwent laparoscopy for a benign gynecologic condition.

INTERVENTIONS

Pelvic magnetic resonance imaging and collection of a venous peripheral blood sample were performed during the preoperative workup. The women were allocated to the adenomyosis group (n = 32), or the control group (n = 45). The adenomyosis group was further subdivided into two groups: diffuse adenomyosis of the inner myometrium (n = 14) and focal adenomyosis of the outer myometrium (n = 18). Other adenomyosis phenotypes were excluded.

MAIN OUTCOME MEASURES

Metabolomic profiling based on ¹H-NMR spectroscopy in combination with statistical approaches.

RESULTS

The serum metabolic profiles of the patients with adenomyosis indicated lower concentrations of 3-hydroxybutyrate, glutamate, and serine compared with controls. Conversely, the concentrations of proline, choline, citrate, 2-hydroxybutyrate, and creatinine were higher in the adenomyosis group. The focal adenomyosis of the outer myometrium and the diffuse adenomyosis phenotypes also each exhibited a specific metabolic profile.

CONCLUSION

Serum metabolic changes were detected in women with features of adenomyosis compared with their disease-free counterparts, and a number of specific metabolic pathways appear to be engaged according to the adenomyosis phenotype. The metabolites with altered levels are particularly involved in immune activation as well as cell proliferation and cell migration. Nevertheless, this study did find evidence of a correlation between metabolite levels and symptoms thought to be related to adenomyosis. Further studies are required to determine the clinical significance of these differences in metabolic profiles.

GC-MS analysis combined with sensory analysis revealed the various aroma characteristics of black tea resulted from different grafting rootstocks

The study was aim to investigate the effects of grafting on volatile compounds and sensory quality of black tea. Seven groups of black tea were prepared from one nongrafted tea tree "Yinghong9 (YJ)" and six grafted tea trees by grafting scion of "YingHong9" on different rootstocks. Sensory analysis indicated marked/slight variations among seven samples, among which, the one grafting on HuangZhiXiangDanCong (HZX) stood out with floral and fruity aroma. The result of chemometrics analysis suggested various effects on compounds caused by different rootstocks. A total of 38 differential compounds were identified, showing mainly quantitative variations, with 36 being identified in all samples. The significant higher contents of volatiles, such as geraniol, phenylethyl alcohol, (E)-nerolidol, decanal, and linalool oxides, in HZX compared with YJ were observed, which explained why floral and fruity aroma stood out among the whole aroma profile of HZX. Both results of sensory and instrumental analysis suggested certain correlation between compound variations and aroma characteristics. Moreover, different rootstocks influenced the aroma quality in different ways. PRACTICAL APPLICATION: In conclusion, the study illuminates the various effects of grafting on the volatile compounds and aroma quality, which enlightens the possibility of changing aroma quality of black tea by grafting scions on different rootstocks. And thus, it can help guide the practical production when cultivating new varieties.

Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review

This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.

Antihypertensive activity of oleanolic acid is mediated via downregulation of secretory phospholipase A2 and fatty acid synthase in spontaneously hypertensive rats

Oleanolic acid (OA) is reported to possess antihypertensive activity via the regulation of lipid metabolism; however, the mechanisms underlying lipid regulation by OA are yet to be fully elucidated. The aim of the present study was to evaluate the mechanisms via which OA regulates lipid metabolism in spontaneously hypertensive rats (SHRs) via ultra‑performance liquid chromatography‑quadrupole/Orbitrap‑mass spectrometry (MS)‑based lipidomics analysis. SHRs were treated with OA (1.08 mg/kg) for 4 weeks. The liver tissues were excised, homogenized in dichloromethane and centrifuged, and subsequently the supernatant layer was collected and concentrated under vacuum to dryness. The dichloromethane extract was subjected to MS analysis and database searching, and comparison of standards was performed to identify potential biomarkers. Partial least squares‑discriminant analysis performed on the liver lipidome revealed a total of 14 endogenous metabolites that were significantly changed in the SHR model group (SH group) compared with Wistar Kyoto rats [normal control (NC group)], including glycerophospholipids, sphingolipids and glycerides. Heatmaps revealed that the liver lipid profiles in the OA group were clustered more closely compared with those observed in the NC group, indicating that the antihypertensive effect of OA was mediated via regulation of liver lipid metabolites. It was observed that the protein levels of secretory phospholipase A2 (sPLA2) and fatty acid synthase (FAS) were increased in the SH group compared with the NC group. In addition, the levels of lysophosphatidylcholine and triglycerides in the liver were elevated, whereas the levels of low‑density lipoprotein cholesterol and high‑density lipoprotein cholesterol were reduced in the SH group. Upon treatment with OA, the mRNA and protein levels of PLA2 and FAS were observed to be downregulated. Collectively, the present study indicated that the antihypertensive activity of OA was mediated via downregulation of sPLA2 and FAS in SHRs, and that treatment with OA resulted in significant improvements in blood pressure and associated abnormalities in the lipid metabolites.

Endometriosis phenotypes are associated with specific serum metabolic profiles determined by proton-nuclear magnetic resonance

RESEARCH QUESTION

What is the correlation between serum metabolic profile and endometriosis phenotype?

DESIGN

A pilot study nestled in a prospective cohort study at a university hospital, including 46 patients with painful endometriosis who underwent surgery and 21 controls who did not have macroscopic endometriotic lesions. Endometriosis was strictly classified into two groups of 23 patients each: endometrioma (OMA) and deep infiltrating endometriosis (DIE). Serum samples were collected before surgery for metabolomic profiling based on proton-nuclear magnetic resonance spectroscopy in combination with statistical approaches. Comparative identification of the metabolites in the serum from endometriosis patients and from controls was carried out, including an analysis according to endometriosis phenotype.

RESULTS

The serum metabolic profiles of the endometriosis patients revealed significantly lower concentrations of several amino acids compared with the controls, whereas the concentrations of free fatty acids and ketone bodies were significantly higher. The OMA and the DIE phenotypes each had a specific metabolic profile, with higher concentrations of two ketone bodies in the OMA group, and higher concentrations of free fatty acids and lipids in the DIE group.

CONCLUSION

Proton-nuclear magnetic resonance-based metabolomics of serum samples were found to have ample potential for identifying metabolic changes associated with endometriosis phenotypes. This information may improve our understanding of the pathogenesis of endometriosis.

Metabolomics in Central Sensitivity Syndromes

Central sensitization syndromes are a collection of frequently painful disorders that contribute to decreased quality of life and increased risk of opiate abuse. Although these disorders cause significant morbidity, they frequently lack reliable diagnostic tests. As such, technologies that can identify key moieties in central sensitization disorders may contribute to the identification of novel therapeutic targets and more precise treatment options. The analysis of small molecules in biological samples through metabolomics has improved greatly and may be the technology needed to identify key moieties in difficult to diagnose diseases. In this review, we discuss the current state of metabolomics as it relates to central sensitization disorders. From initial literature review until Feb 2020, PubMed, Embase, and Scopus were searched for applicable studies. We included cohort studies, case series, and interventional studies of both adults and children affected by central sensitivity syndromes. The majority of metabolomic studies addressing a CSS found significantly altered metabolites that allowed for differentiation of CSS patients from healthy controls. Therefore, the published literature overwhelmingly supports the use of metabolomics in CSS. Further research into these altered metabolites and their respective metabolic pathways may provide more reliable and effective therapeutics for these syndromes.

Endometriosis research in the -omics era

Endometriosis is a pathological condition extensively studied, but its pathogenesis is not completely understood, since its pathophysiology stems from a broad spectrum of environmental influences and genetic factors. Moreover, the nature of this condition is heterogeneous and includes different anatomical entities. Scientists actively pursue discovery of novel biomarkers in the hope of better identifying susceptible individuals in early stages of the disease. High-throughput technologies have substantially revolutionized medical research and, as a first step, the advent of genotyping arrays led to large-scale genome-wide association studies (GWAS) and enabled the assessment of global transcript levels, thus giving rise to integrative genetics. In this framework, comprehensive studies have been conducted at multiple biological levels by using the "omics" platforms, thus allowing to re-examine endometriosis at a greater degree of molecular resolution. -Omics technologies can detect and analyze hundreds of markers in the same experiment and their increasing use in the field of gynecology comes from an urgent need to find new diagnostic and therapeutic tools that improve the diagnosis of endometriosis and the efficacy of assisted reproductive techniques. Proteomics and metabolomics have been introduced recently into the every day methodology of researchers collaborating with gynecologists and, importantly, multi-omics approach is advantageous to gain insight of the total information that underlies endometriosis, compared to studies of any single -omics type. In this review, we expect to present multiple studies based on the high-throughput-omics technologies and to shed light in all considerable advantages that they may confer to a proper management of endometriosis.

Biomarkers for the Noninvasive Diagnosis of Endometriosis: State of the Art and Future Perspectives

BACKGROUND

Early and accurate diagnosis of endometriosis is crucial for the management of this benign, yet debilitating pathology. Despite the advances of modern medicine, there is no common ground regarding the pathophysiology of this disease as it continues to affect the quality of life of millions of women of reproductive age. The lack of specific symptoms often determines a belated diagnosis. The gold standard remains invasive, surgery followed by a histopathological exam. A biomarker or a panel of biomarkers is easy to measure, usually noninvasive, and could benefit the clinician in both diagnosing and monitoring the treatment response. Several studies have advanced the idea of biomarkers for endometriosis, thereby circumventing unnecessary invasive techniques. Our paper aims at harmonizing the results of these studies in the search of promising perspectives on early diagnosis.

METHODS

We selected the papers from Google Academic, PubMed, and CrossRef and reviewed recent articles from the literature, aiming to evaluate the effectiveness of various putative serum and urinary biomarkers for endometriosis.

RESULTS

The majority of studies focused on a panel of biomarkers, rather than a single biomarker and were unable to identify a single biomolecule or a panel of biomarkers with sufficient specificity and sensitivity in endometriosis.

CONCLUSION

Noninvasive biomarkers, proteomics, genomics, and miRNA microarray may aid the diagnosis, but further research on larger datasets along with a better understanding of the pathophysiologic mechanisms are needed.

Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path?

Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome - the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.

Endometrium and endometriosis tissue mitochondrial energy metabolism in a nonhuman primate model

BACKGROUND

Endometriosis is the growth of uterine lining (endometrium) outside of the uterus. In other chronic inflammatory diseases, mitochondrial dysfunction is suspected of playing a role in disease pathogenesis. However, little is known about endometriosis mitochondrial function or its effects on tissue metabolism. The objectives of this study were to analyze mitochondrial function in nonhuman primate (NHP) endometrium and endometriosis tissue and to identify the metabolic features of these tissues that may contribute to disease.

METHODS

Mitochondrial function in endometriosis tissue and endometrium was measured using mitochondrial respirometry analysis to determine if changes in oxidative phosphorylation exist in endometrium and endometriosis tissue compared to control endometrium from clinically healthy NHPs. Targeted metabolomics and multidimensional statistical analysis were applied to quantify key metabolites in energy and amino acid biosynthesis pathways.

RESULTS

Mitochondrial respirometry assays showed endometrium from NHPs with endometriosis had reduced complex II-mediated oxygen consumption rates (OCR) across all energy states (basal, p = 0.01; state 3, p = 0.02; state 3u, p = 0.04; state 4o, p = 0.008) and endometriosis tissue had reduced state 3, complex I-mediated OCR (p = 0.02) and respiratory control rates (p = 0.01) compared to normal endometrium. Targeted metabolomics performed on tissue revealed carnitine (p = 0.001), creatine phosphate (p = 0.01), NADH (p = 0.0001), FAD (p = 0.001), tryptophan (p = 0.0009), and malic acid (p = 0.005) were decreased in endometriosis tissue compared to normal endometrium samples. FAD (p = 0.004), tryptophan (p = 0.0004) and malic acid (p = 0.03) were significantly decreased in endometrium from NHPs with endometriosis compared to normal endometrium. Significant metabolites identified in endometriosis and endometrium samples from animals with endometriosis were part of amino acid biosynthesis or energy metabolism pathways.

CONCLUSIONS

Here, endometrial mitochondrial energy production and metabolism were decreased in endometrium and endometriosis tissue. Decreased mitochondrial energy production may be due to oxidative stress-induced damage to mitochondrial DNA or membranes, a shift in cell metabolism, or decreased energy substrate; however, the exact cause remains unknown. Additional research is needed to determine the implications of reduced mitochondrial energy production and metabolism on endometriosis and endometrium.

Bacterial diversity and metabolite profiles of curd prepared by natural fermentation of raw milk and back sloping of boiled milk

Preparation of curd vary worldwide due to which its taste, texture and impact on human health also differ. In Assam, curd prepared from raw milk (RMC) is preferred over curd prepared from boiled milk (BMC), a tradition believed to have originated from the Mongoloid customs. Microbial diversity of raw milk (RM), boiled milk (BM), RMC and BMC collected from three farms were investigated by culture dependent and independent techniques. Additionally, metabolite profiles of RMC and BMC were studied by gas chromatography and mass spectroscopy. A total of 59 bacterial isolates were identified from the four different dairy products. In RM, lactic acid bacteria such as Lactococcus, Enterococcus, Lactobacillus and Leuconostoc were obtained along with the environmental bacteria like Bacillus, Staphylococcus, Acetobacter, Chryseobacterium, Streptococcus, Acinetobacter, Kocuria, Klebsiella and Macrococcus. Additionally, Prevotella, Oscillospira, Phascolarctobacterium and Akkermansia were also detected in BM by culture independent technique. In RMC and BMC, Lactococcus, Leuconostoc and Lactobacillus were prevalent. RM and RMC shared Enterococcus, Lactococcus, Streptococcus and Acinetobacter as common bacterial genera. However, no bacterial genus was common in BM and BMC. The correlation analysis revealed that Lactobacillus was negatively correlated to other bacterial genera. Oligotyping analysis revealed that Lactobacillus brevis and L.fermentum were abundant in RMC and BMC, respectively. In metabolomic study, ascorbic acid, dodecanoic acid and hexadecanoic acid were found to be significantly higher in RMC. Presence of different types of probiotics in these curds samples opens a new avenue to understand their effects on human health.

Metabolomic profile as a noninvasive adjunct tool for the diagnosis of Grades III and IV endometriosis-related infertility

The aim of the present case-control study was to develop a noninvasive adjuvant tool for the diagnosis of endometriosis. Serum samples from 100 patients undergoing intracytoplasmic sperm injection were split into two groups according to the cause of infertility: an endometriosis group (n = 50), consisting of samples derived from patients with Grade III and IV endometriosis, and a control group (n = 50), comprising samples derived from patients with isolated male factor infertility. The metabolomic profile of each sample was obtained, through mass spectrometry. Partial least squares discriminant analysis was able to clearly classify the endometriosis and control groups. Ten potential biomarkers were selected based on their importance for model prediction. These ions were used to build the receiver-operating characteristic curve, which presented an area under the curve of 0.904 (95% confidence interval: 0.796-0.985). To validate the model, 30 other samples from infertile women without any evidence of endometriosis were tested. Considering these ions as possible biomarkers, the model was able to correctly classify 84% of the patients. Finally, a similar prediction potential was observed in the model validated set, when samples from the disease-free group were tested. Serum metabolomics may be useful as a noninvasive adjunct tool for the selection of patients who must undergo laparoscopy for definitive endometriosis diagnosis.

Metabolomic signatures of asthma-COPD overlap (ACO) are different from asthma and COPD

INTRODUCTION

Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features, and existence as a unique disease entity remains unclear. Individuals with ACO have a faster lung function decline, more frequent exacerbations, and worse quality of life than those with COPD or asthma alone.

OBJECTIVES

The present study aims to determine whether ACO has a distinct metabolic profile in comparison to asthma and COPD.

METHODS

Two different groups of patients were recruited as discovery (D) and validation (V) cohorts. Serum samples obtained from moderate and severe asthma patients diagnosed as per GINA guidelines [n = 34(D); n = 32(V)], moderate and severe COPD cases identified by GOLD guidelines [n = 30(D); 32(V)], ACO patients diagnosed by joint GOLD and GINA guidelines [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using nuclear magnetic resonance (NMR) spectrometry.

RESULTS

Multivariate and univariate analysis indicated that 12 metabolites [lipid, isoleucine, N-acetylglycoproteins (NAG), valine, glutamate, citric acid, glucose, L-leucine, lysine, asparagine, phenylalanine and histidine] were dysregulated in ACO patients when compared with both asthma and COPD. These metabolites were further validated in a fresh cohort of patients, which again exhibited a similar expression pattern.

CONCLUSIONS

Our findings suggest that ACO has an enhanced energy and metabolic burden associated with it as compared to asthma and COPD. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.

Identification of potential endometriosis biomarkers in peritoneal fluid and blood plasma via shotgun lipidomics

Endometriosis is a recurrent and benign gynecological disorder, defined by the ectopic presence of endometrium. About 10% of reproductive-aged women suffer from endometriosis. There are no non-invasive or minimally invasive tests available in clinical practice to accurately diagnose endometriosis today. Here, we present our efforts to determine the diagnostic accuracy of biomarkers in peritoneal fluid and blood plasma using flow injection analysis with electrospray ionization tandem mass spectrometry (ESI-MS/MS) in 70 women with endometriosis and 20 women from a control group. The presence of endometriosis was confirmed by surgical findings and post-operative pathological examination. A qualitative and quantitative evaluation of the lipids in peritoneal fluids and blood plasma was carried out using electrospray ionization mass spectrometry (ESI-MS). The analysis revealed more than 140 molecular species of lipids, most of which pertained to five classes: phosphatidylcholines, phosphatidylethanolamines, sphingomyelins, di- and triglycerides. The data were analyzed using a statistical multifactorial method (i.e., PLS-DA). It was found that 9 potential biomarkers of endometriosis (LPC 16:0, PE O-20:0, PE O 34:1, PC 36:2, PC 36:4, PC 36:5, PC 38:4, PC 38:6 and SM 34:1) are common in blood plasma and peritoneal fluid, supporting connection with the pathological process. The sensitivity of the method developed for plasma was 93% with a specificity of 95%; for peritoneal fluid, the sensitivity was 90% and the specificity 95%. Accordingly, plasma is the most suitable biological fluid for clinical diagnostics of endometriosis. Further validation of these lipids as serologic biomarkers may enhance non-invasive diagnostic tools for patients with suspected endometriosis and reduce the frequency of diagnostic laparoscopy.

Targeted metabolomics for serum amino acids and acylcarnitines in patients with lung cancer

Lung cancer is one of the most prevalent types of cancer, but accurate diagnosis remains a challenge. The aim of the present study was to create a model using amino acids and acylcarnitines for lung cancer screening. Serum samples were obtained from two groups of patients with lung cancer recruited in 2015 (including 40 patients and 100 matched controls) and 2017 (including 17 patients and 30 matched controls). Using a metabolomics method, 21 metabolites (13 types of amino acids and 8 types of acylcarnitines) were measured using liquid chromatography-tandem mass spectrometry. Data (from the 2015 and 2017 data sets) were analysed using a Mann-Whitney U test, Student's t-test, Welch's F test, receiver-operator characteristic curve or logistic regression in order to investigate the potential biomarkers. Six metabolites (glycine, valine, methionine, citrulline, arginine and C16-carnitine) were indicated to be involved in distinguishing patients with lung cancer from healthy controls. The six discriminating metabolites from the 2017 data set were further analysed using Partial least squares-discriminant analysis (PLS-DA). The PLS-DA model was verified using Spearman's correlation analysis and receiver operating characteristic curve analysis. These results demonstrated that the PLS-DA model using the six metabolites (glycine, valine, methionine, citrulline, arginine and C16-carnitine) had a strong ability to identify lung cancer. Therefore, the PLS-DA model using glycine, valine, methionine, citrulline, arginine and C16-carnitine may become a novel screening tool in patients with lung cancer.

NMR metabolic profiling of follicular fluid for investigating the different causes of female infertility: a pilot study

INTRODUCTION

Several metabolomics studies have correlated follicular fluid (FF) metabolite composition with oocyte competence to fertilization, embryo development and pregnancy but there is a scarcity of research examining the metabolic effects of various gynaecological diseases.

OBJECTIVES

In this study we aimed to analyze and correlate the metabolic profile of FF from women who were following in vitro fertilization (IVF) treatments with their different infertility pathologies.

METHODS

We selected 53 women undergoing IVF who were affected by: tubal diseases, unexplained infertility, endometriosis, polycystic ovary syndrome (PCOS). FF of the study participants was collected at the time of oocytes retrieval. Metabolomic analysis of FF was performed by nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

FF presents some significant differences in various infertility pathologies. Although it was not possible to discriminate between FF of control participants and women with tubal diseases and unexplained infertility, comparison of FF metabolic profile from control women with patients with endometriosis and PCOS revealed significant differences in some metabolites that can be correlated to the causes of infertility.

CONCLUSION

NMR-based metabolic profiling may be successfully applied to find diagnostic biomarkers for PCOS and endometriosis and it might be also used to predict oocyte developmental potential and subsequent outcome.

Long term treatment of metformin impedes development of chemoresistance by regulating cancer stem cell differentiation through taurine generation in ovarian cancer cells

Development of resistance poses a significant challenge to effective first-line platinum based therapy for epithelial ovarian cancer patients. Cancer Stem Cells are envisaged as a critical underlying factor for therapy resistance. Thus, there is a critical need for developing approaches to diminish the enrichment of cancer stem cells and acquirement of resistance. Administration of metformin, a commonly prescribed drug against Type II diabetes exhibited promising effect in the management of ovarian cancer. However, the effect of long term administration of low dose of metformin as an adjuvant to cisplatin and paclitaxel during acquirement of chemoresistant phenotype has not been investigated so far. Using two isogenic cellular chemoresistant models (A2780 and OAW42) developed in the presence or absence of metformin, we demonstrated the ability of metformin to impede the development of resistance through increased drug sensitivity, increased proliferation, and reduced migratory abilities of the resistant cells. Metformin introduction also decreased the cancer stem cell population, expression of specific biomarkers and pluripotent genes. Further metabolic profiling of these cells using ¹H-Nuclear Magnetic Resonance spectroscopy revealed significant modulation in taurine and histidine levels in resistant cells developed in the presence of metformin. Intriguingly, taurine treatment considerably reduced the cancer stem cell population and chemoresistance in resistant cells, indicating a novel role of taurine in differentiation of ovarian cancer stem cells. Altogether this is the first report on the potential role of metformin for targeting the cancer stem cell population via up regulation of taurine, leading to impediment in the acquirement of chemoresistance.