Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry

Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints

Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.

Integrated lipid metabolomics and proteomics analysis reveal the pathogenesis of polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is an endocrinological and metabolic disorder that can lead to female infertility. Lipid metabolomics and proteomics are the new disciplines in systems biology aimed to discover metabolic pathway changes in diseases and diagnosis of biomarkers. This study aims to reveal the features of PCOS to explore its pathogenesis at the protein and metabolic level.

METHODS

We collected follicular fluid samples and granulosa cells of women with PCOS and normal women who underwent in vitro fertilization(IVF) and embryo transfer were recruited. The samples were for the lipidomic study and the proteomic study based on the latest metabolomics and proteomics research platform.

RESULTS

Lipid metabolomic analysis revealed abnormal metabolism of glycerides, glycerophospholipids, and sphingomyelin in the FF of PCOS. Differential lipids were strongly linked with the rate of high-quality embryos. In total, 144 differentially expressed proteins were screened in ovarian granulosa cells in women with PCOS compared to controls. Go functional enrichment analysis showed that differential proteins were associated with blood coagulation and lead to follicular development disorders.

CONCLUSION

The results showed that the differential lipid metabolites and proteins in PCOS were closely related to follicle quality,which can be potential biomarkers for oocyte maturation and ART outcomes.

Arachidonic acid inhibit granulosa cell function by affecting metabolic function of liver in brown adipose transplantation rats

BACKGROUND

Polycystic ovary syndrome (PCOS) is a gynecological endocrine disease and could be considered a metabolic disease because it is often accompanied by obesity and insulin resistance. Brown adipose tissue (BAT) transplantation has been shown to be effective in treating PCOS rats.

RESULTS

The study demonstrated that BAT successfully recovered the reproductive and metabolic phenotype of PCOS rats. The disorder estrous cycle, abnormal hyperglycemia and the expression of liver factors were improved. Differentially expressed metabolites were analyzed, among them, arachidonic acid may play a role in inhibiting cell proliferation, enhancing oxidative stress reaction, promoting estrogen expression, and reducing progesterone level in KGN cells.

CONCLUSION

Our findings suggest that BAT transplantation may be a therapeutic strategy for PCOS by changing the expression of some cytokines and metabolites. Differentially expressed metabolites might be crucially important for the pathogenesis of PCOS.

Multi-omics insights and therapeutic implications in polycystic ovary syndrome: a review

Polycystic ovary syndrome (PCOS) is a common gynecological disease that causes adverse effects in women in their reproductive phase. Nonetheless, the molecular mechanisms remain unclear. Over the last decade, sequencing and omics approaches have advanced at an increased pace. Omics initiatives have come to the forefront of biomedical research by presenting the significance of biological functions and processes. Thus, multi-omics profiling has yielded important insights into understanding the biology of PCOS by identifying potential biomarkers and therapeutic targets. Multi-omics platforms provide high-throughput data to leverage the molecular mechanisms and pathways involving genetic alteration, epigenetic regulation, transcriptional regulation, protein interaction, and metabolic alterations in PCOS. The purpose of this review is to outline the prospects of multi-omics technologies in PCOS research by revealing novel biomarkers and therapeutic targets. Finally, we address the knowledge gaps and emerging treatment strategies for the management of PCOS. Future PCOS research in multi-omics at the single-cell level may enhance diagnostic and treatment options.

Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome

Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.

The complex metabolic interactions of liver tissue and hepatic exosome in PCOS mice at young and middle age

Polycystic ovary syndrome (PCOS) is a common age-related endocrinopathy that promotes the metabolic disorder of the liver. Growing evidence suggests that the pathophysiology of this disorder is closely associated with the interaction between the liver and its exosome. However, the underlying mechanism of the interactions remains unclear. In this study, we aimed to investigate the metabolite profiles of liver tissues and hepatic exosomes between normal (n = 11) and PCOS (n = 13) mice of young- and middle-age using gas chromatograph-mass spectrometry (GC-MS) based metabolomics analysis. Within the 145 identified metabolites, 7 and 48 metabolites were statistically different (p < 0.05, q < 0.05) in the liver tissue and exosomes, respectively, between PCOS and normal groups. The greater disparity in exosome indicated its potential to reflect the metabolic status of the liver. Based on hepatic exosome metabolome, the downregulations of glycolysis and TCA cycle were related to hepatic pathophysiology of PCOS independent of age. Fatty acids were the preferred substrates in young-age-PCOS liver while amino acids were the main substrates in middle-age-PCOS liver for the processes of gluconeogenesis. Overall, this study enables us to better understand the metabolic status of the PCOS liver at different ages, and exosome metabolomics shows its potential to gain the metabolic insights of parental cell or source organ.

Urinary metabolomics identified metabolic disturbance associated with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder. Nevertheless, its accurate mechanisms remain unclear. Metabolomics is a powerful technique to identify small molecules that could be used to discover pathogenesis and therapeutical targets of disease. In the present study, a urinary untargeted metabolomics combined with targeted quantification analysis was performed to uncover metabolic disturbance associated with PCOS. A total of thirty-eight metabolites were obtained between PCOS patients and healthy controls, which were mainly involved in lipids (39.5%), organic acids and derivatives (23.7%), and organic oxygen compounds (18.4%). Based on enrichment analysis, fourteen metabolic pathways were found to be perturbed in PCOS, particularly glycerophospholipid metabolism and tryptophan metabolism. Targeted quantification profiling of tryptophan metabolism demonstrated that seven compounds (tryptophan, kynurenine, kynurenic acid, quinolinic acid, xanthurenic acid, 3-hydroxyanthranilic acid and 3-hydroxykynurenine) were up-regulated in PCOS. And these tryptophan-kynurenine metabolites showed significant correlations with PCOS clinical features, such as positively associated with testosterone, free androgen index, and the ratio of luteinizing hormone to follicle stimulating hormone. Thus, this study disclosed urinary metabolome changes associated with PCOS, and might provide new insights into PCOS pathogenesis elucidation and therapeutical target development.

A Comprehensive Overview of Common Polymorphic Variants in Genes Related to Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is one of the most common endocrine-metabolic disorders in women of reproductive age. It is characterized by an increase in the biosynthesis of androgens, anovulation, and infertility. PCOS has been reported as a polygenic entity in which multiple single nucleotide polymorphisms (SNPs) are associated with the clinical features of the pathology. Herein, we describe the common polymorphic variants in genes related to PCOS, their role in its pathogenesis, and etiology. Whole-genome association studies have been focused on women from Asian and European populations. The most common genes associated with PCOS are DENND1A, THADA, FSHR, and LHCGR. However, other genes have been associated with PCOS such as AMH, AMHR2, ADIPOQ, FTO, HNF1A, CYP19, YAP1, HMGA2, RAB5B, SUOX, INSR, and TOX3. Nevertheless, the relationship between the biological functions of these genes and the development of the pathology is unclear. Studies in each gene in different populations do not always comply with a general pattern, so researching these variants is essential for better understanding of this polygenic syndrome. Future population studies should be carried out to evaluate biological processes, incidence rates, allelic and genotypic frequencies, and genetic susceptibility factors that predispose PCOS.

Metabolomic Insight into Polycystic Ovary Syndrome-An Overview

Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.

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.

MTHFR C677T polymorphism is associated with follicle-stimulating hormone levels and controlled ovarian hyperstimulation response: a retrospective study from the clinical database

OBJECTIVE

To evaluate the impact of methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism with clinical data analysis in controlled ovarian hyperstimulation (COH) of infertile women in the Intravenous Infusion Safety Evaluation Center of Hunan Province, People's Republic of China.

DESIGN

Genetic Association Study.

SETTING

Reproductive medicine clinical.

PATIENT(S)

This genetic association study included 722 infertile women who received the standard long treatment protocol with accessible and complete electronic medical records.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The clinical parameters were obtained from the Intravenous Infusion Safety Evaluation center.

RESULT(S)

Basal FSH levels in the TT group were significantly higher than those of the CC group. The FSH levels after down-regulation in the TT group were higher than those of CC/CT genotypes. The TT genotype patients received significantly higher total doses of GnRH agonist and FSH compared with CC/CT genotypes, whereas the total dose of hCG was higher in the CT genotypes compared with the CC/TT genotypes. Further association analysis between hormone levels and COH outcomes indicated significantly negative correlation of basal FSH levels with antral follicle count and number of oocytes as well as the down-regulation FSH levels with the number of metaphase II oocytes and oocytes.

CONCLUSION(S)

The MTHFR C677T polymorphism was associated with high doses of ovarian stimulation medications, as well as higher FSH levels. The negative correlation between FSH levels and the number of oocytes suggested that C677T polymorphism may play a role in the poor prognosis of COH oocytes. This needs to be studied in future prospective studies with longer follow-up.

Metabolomics-A Promising Approach to Pituitary Adenomas

Background: Metabolomics-the novel science that evaluates the multitude of low-molecular-weight metabolites in a biological system, provides new data on pathogenic mechanisms of diseases, including endocrine tumors. Although development of metabolomic profiling in pituitary disorders is at an early stage, it seems to be a promising approach in the near future in identifying specific disease biomarkers and understanding cellular signaling networks. Objectives: To review the metabolomic profile and the contributions of metabolomics in pituitary adenomas (PA). Methods: A systematic review was conducted via PubMed, Web of Science Core Collection and Scopus databases, summarizing studies that have described metabolomic aspects of PA. Results: Liquid chromatography tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR) spectrometry, which are traditional techniques employed in metabolomics, suggest amino acids metabolism appears to be primarily altered in PA. N-acetyl aspartate, choline-containing compounds and creatine appear as highly effective in differentiating PA from healthy tissue. Deoxycholic and 4-pyridoxic acids, 3-methyladipate, short chain fatty acids and glucose-6-phosphate unveil metabolite biomarkers in patients with Cushing's disease. Phosphoethanolamine, N-acetyl aspartate and myo-inositol are down regulated in prolactinoma, whereas aspartate, glutamate and glutamine are up regulated. Phosphoethanolamine, taurine, alanine, choline-containing compounds, homocysteine, and methionine were up regulated in unclassified PA across studies. Intraoperative use of ultra high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which allows localization and delineation between functional PA and healthy pituitary tissue, may contribute to achievement of complete tumor resection in addition to preservation of pituitary cell lines and vasopressin secretory cells, thus avoiding postoperative diabetes insipidus. Conclusion: Implementation of ultra high performance metabolomics analysis techniques in the study of PA will significantly improve diagnosis and, potentially, the therapeutic approach, by identifying highly specific disease biomarkers in addition to novel molecular pathogenic mechanisms. Ultra high mass resolution MALDI-MSI emerges as a helpful clinical tool in the neurosurgical treatment of pituitary tumors. Therefore, metabolomics appears to be a science with a promising prospect in the sphere of PA, and a starting point in pituitary care.