Metabolomic Biomarkers in Polycystic Ovary Syndrome: A Review of the Evidence

Potential Causal Association between Plasma Metabolites, Immunophenotypes, and Female Reproductive Disorders: A Two-Sample Mendelian Randomization Analysis

BACKGROUND

While extensive research highlighted the involvement of metabolism and immune cells in female reproductive diseases, causality remains unestablished.

METHODS

Instrumental variables for 486 circulating metabolites (N = 7824) and 731 immunophenotypes (N = 3757) were derived from a genome-wide association study (GWAS) meta-analysis. FinnGen contributed data on 14 female reproductive disorders. A bidirectional two-sample Mendelian randomization study was performed to determine the relationships between exposures and outcomes. The robustness of results, potential heterogeneity, and horizontal pleiotropy were examined through sensitivity analysis.

RESULTS

High levels of mannose were found to be causally associated with increased risks of gestational diabetes (GDM) (OR [95% CI], 6.02 [2.85-12.73], p = 2.55 × 10-6). A genetically predicted elevation in the relative count of circulating CD28-CD25++CD8+ T cells was causally related to increased female infertility risk (OR [95% CI], 1.26 [1.14-1.40], p = 1.07 × 10-5), whereas a high absolute count of NKT cells reduced the risk of ectopic pregnancy (OR [95% CI], 0.87 [0.82-0.93], p = 5.94 × 10-6). These results remained consistent in sensitivity analyses.

CONCLUSIONS

Our study supports mannose as a promising GDM biomarker and intervention target by integrating metabolomics and genomics.

LC-MS/MS based quantification of steroidal biomarkers in polycystic ovary syndrome induced rats

Polycystic ovary syndrome (PCOS) is a common endocrine disorder that causes reproductive hormones imbalance, missed periods, infertility and distributed steroidogenesis. Reportedly, during PCOS, the endogenous levels of P4 (Progesterone), 17OHP4 (17-α hydroxy progesterone), and T4 (Testosterone) were significantly altered. Thus, quantification of steroid biomarkers involved in the steroidogenesis pathway of PCOS, such as P4, 17OHP4, and T4, holds significant importance. One important drawback of current methods is steroid metabolome traceability. Without adequate traceability, the findings of these techniques will be less reliable for identifying P4, 17OHP4, and T4. These methods also need a high sample size, especially for the most important biomarker that initiates steroidogenesis. To address these challenges, we require a new liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for steroid biomarker analysis. Herein the present work, using validated LC-MS/MS, PCOS biomarkers were measured and compared between normal control rats and PCOS-induced rats before and after analyte administration. The experiment utilized an isocratic separation method employing an analytical C18 column. The mobile phase consisted of acetonitrile (ACN) and aqueous 0.1% formic acid (FA) in a ratio of 90:10 (v/v). The plasma samples were processed with protein precipitation (PPT) followed by the liquid-liquid extraction (LLE) method. The lower limit of quantification (LLOQ) was 0.5 ng/mL in plasma. According to USFDA criteria, the method's systematic validation took into account linearity (r2 > 0.99), accuracy and precision of intra- and inter-batch measurements, stability, biomarker recovery (60-85%) and matrix effect (<± 15%), all of which were determined to be within range ( ± 15%). The pharmacokinetic data showed that, as compared to normal rats, PCOS-induced animals had significantly higher Cmax values for 17OHP4 and T4 (∼2 fold), while lower Cmax values for P4 (∼2 fold). The present work is novel and provides scientific information to explore systematic processes involved in steroidogenesis and boost clinical applicability for PCOS therapy.

Challenges and Opportunities for Data Science in Women's Health

The intersection of women's health and data science is a field of research that has historically trailed other fields, but more recently it has gained momentum. This growth is being driven not only by new investigators who are moving into this area but also by the significant opportunities that have emerged in new methodologies, resources, and technologies in data science. Here, we describe some of the resources and methods being used by women's health researchers today to meet challenges in biomedical data science. We also describe the opportunities and limitations of applying these approaches to advance women's health outcomes and the future of the field, with emphasis on repurposing existing methodologies for women's health.

Alterations of bacteriome, mycobiome and metabolome characteristics in PCOS patients with normal/overweight individuals

To characterize the gut bacteriome, mycobiome and serum metabolome profiles in polycystic ovary syndrome (PCOS) patients with normal/overweight individuals and evaluate a potential microbiota-related diagnostic method development for PCOS, 16S rRNA and ITS2 gene sequencing using 88 fecal samples and 87 metabolome analysis from serum samples are conducted and PCOS classifiers based on multiomics markers are constructed. There are significant bacterial, fungal community and metabolite differences among PCOS patients and healthy volunteers with normal/overweight individuals. Healthy individuals with overweight/obesity display less abnormal metabolism than PCOS patients and uniquely higher abundance of the fungal genus Mortierella. Nine bacterial genera, 4 predicted pathways, 11 fungal genera and top 30 metabolites are screened out which distinguish PCOS from healthy controls, with AUCs of 0.84, 0.64, 0.85 and 1, respectively. The metabolite-derived model is more accurate than the microbe-based model in discriminating normal BMI PCOS (PCOS-LB) from normal BMI healthy (Healthy-LB), PCOS-HB from Healthy-HB. Featured bacteria, fungi, predicted pathways and serum metabolites display higher associations with free androgen index (FAI) in the cooccurrence network. In conclusion, our data reveal that hyperandrogenemia plays a central role in the dysbiosis of intestinal microecology and the change in metabolic status in patients with PCOS and that its effect exceeds the role of BMI. Healthy women with high BMI showed unique microbiota and metabolic features.The priority of predictive models in discriminating PCOS from healthy status in this study were serum metabolites, fungal taxa and bacterial taxa.

Efficacy of Acupoint Application on In Vitro Fertilization Outcome in Patients with Polycystic Ovary Syndrome: A UHPLC-MS-Based Metabolomic Study

Objective

To explore the clinical effect of acupoint application on the outcome of in vitro fertilization-embryo transfer (IVF-ET) in patients with polycystic ovary syndrome (PCOS) of the phlegm-dampness type and elucidate its possible mechanism of action from the perspective of follicular fluid metabolomics.

Methods

A total of 90 patients undergoing IVF-ET due to infertility were selected and divided into three groups: the treatment group (PCOS with acupoint application, n = 30), the control group (PCOS without acupoint application, n = 30), and the normal group (non-PCOS, n = 30). All patients received a gonadotropin-releasing hormone agonist (GnRH-a) long protocol for controlled ovarian hyperstimulation (COH). Among them, the treatment group was also given the acupoint application from the day of pituitary downregulation to the day of the human chorionic gonadotrophin (hCG) trigger. Ultrahigh-performance liquid chromatography connected with quadrupole time-of-flight mass spectrometry (UHPLC-MS) was adopted for untargeted metabolomic analysis of follicular fluid collected from the three groups of patients on the day of oocyte pick-up (OPU). The significantly differential metabolites were screened using univariate and multivariate statistical analysis, and the related metabolic pathways were identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Results

Metabolomic analysis showed that the treatment group's follicular fluid samples were aggregated with the normal group and separated from the control group. A total of 34 significantly differential metabolites were found in the follicular fluid of patients with phlegm-dampness PCOS and normal people. With the intervention of acupoint application, seven metabolites (pseudouridine, phenol, 2-oxoadipic acid, 9R,10S-EpOME, DL-lactate, nicotinamide, and DL-indole-3-lactic acid) were all downregulated, mainly involving the pathways of pyruvate metabolism, nicotinate and nicotinamide metabolism, protein digestion and absorption, biosynthesis of amino acids, and pyrimidine metabolism.

Conclusions

Acupoint application can effectively improve the clinical symptoms and the outcome of IVF-ET treatment in patients with PCOS of the phlegm-dampness type, and its mechanism of action may be related to the regulation of the pathways of pyruvate metabolism, nicotinate and nicotinamide metabolism, protein digestion and absorption, biosynthesis of amino acids, and pyrimidine metabolism.

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.

Characteristics and possible mechanisms of metabolic disorder in overweight women with polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a kind of endocrine and metabolic disorder, disturbing the females of reproductive age. Here, we aimed to investigate the metabolic characteristics of overweight women with PCOS and analyze the possible mechanisms.

METHODS

We conducted a cross-sectional study on 947 patients with PCOS, who were classified according to body mass index (BMI) as overweight (BMI ≥ 24 kg/m²) or non-overweight (BMI ≤ 23.9 kg/m²). The clinical symptoms, endocrine features, metabolic status, and inflammatory levels of the patients were comprehensively assessed and compared between the patients of the two groups. Additionally, a predictive study on the correlation between inflammation and metabolism was performed using STRING and Cytoscape software, and the possible mechanisms of metabolic disorders involved in the overweight PCOS were preliminarily explored.

RESULTS

Overweight PCOS was associated with increased average age, waist-to-hip ratio, and the incidence of acanthosis nigricans. These patients were susceptible to familial hypertension and diabetes, and exhibited evident characteristics of low levels of luteinizing hormone (LH) and the ratio of LH to follicle-stimulating hormone, and were more inclined to insulin resistance (IR). Furthermore, overweight PCOS presented with a chronic low-grade inflammation state with increased levels of inflammatory cytokines complement components C5/C5α, CXCL12/SDF-1, MIF, and Serpin E1/PAI-1 evidently compared with those in non-overweight PCOS. Pearson analysis showed that these inflammatory cytokines were directly or indirectly correlated with IR. The STRING and Cytoscape network analysis predicted that inflammatory cytokines CXCL12/SDF-1, Serpin E1/PAI-1 and MIF might be crucial for inducing IR in overweight PCOS women through various biological functions and signal transductions including the JAK-STAT cascade, ATP biosynthesis, and HIF-1 signaling.

CONCLUSIONS

Overweight patients with PCOS are prone to low gonadal levels, IR, and chronic low-grade inflammation. Inflammatory cytokines CXCL12/SDF-1, Serpin E1/PAI-1and MIF might lead to IR through multiple biological functions and signal transductions in overweight PCOS.