Genetic variants of metabolism and inflammatory pathways, and PCOS risk -Systematic review, meta-analysis, and in-silico analysis

Gut microbiota in diabetic-linked polycystic ovarian syndrome: Mechanisms and therapeutic insights

Polycystic ovarian syndrome (PCOS) is a complex multisystem disorder prevalent among women of reproductive age, commonly marked by insulin resistance, hyperinsulinemia, and metabolic disruptions such as hypertension and dyslipidemia, which elevate risks of cardiovascular disease and hepatic steatosis. Recent advances underscore the gut microbiome's critical role in modulating insulin resistance and metabolic homeostasis in PCOS. This review highlights novel insights into gut dysbiosis-driven inflammation, gut-brain hormonal signaling, and immune modulation as underlying mechanisms connecting PCOS with metabolic dysfunction and diabetes. We comprehensively analyzed studies up to September 2024 on gut microbiota, diabetes, PCOS, and metformin, exploring emerging perspectives on the microbiome's therapeutic potential in managing PCOS. Metformin's dual role in insulin sensitivity improvement and gut microbiome modulation is emphasized, including its indirect effects on weight management. This review also identifies gaps in current research, urging a shift toward precision therapies targeting microbiome-related pathways in PCOS. Further exploration of the gut-brain axis, pathogen-associated molecular patterns, and the need for controlled clinical trials are discussed to enhance therapeutic approaches.

Investigating the self-healing potential of polycystic ovary syndrome in a mouse model: Implications for offspring health

Polycystic ovarian syndrome (PCOS) is a prevalent metabolic endocrine disorder in reproductive-aged women. This study aims to investigate the self-healing ability of PCOS and its potential impact on offspring. Methods: Female C57 BL/6J mice aged 4-5 weeks were administered letrozole (1 mg/kg/d) and a high-fat diet for 21 days to establish a PCOS model, and a control group was established. After modeling, the mice were divided into a PCOS model group and a self-healing group. After 14 days, the mice were mated, and the growth of their offspring was recorded. Subsequently, all mice were euthanized to collect serum, ovaries, and testes. The results showed that the self-healing group PCOS phenotype has shown improvement when compared to the model group. The findings from the offspring study indicate that all offspring in the model group died, while the self-healing group had offspring with a lower weight at 7 days and higher blood glucose levels. Additionally, the testicular morphology of male offspring in the self-healing group was poor. The conclusion drawn is that, after removing the pathogenic factors, the PCOS model group can self-heal. However, fertility remains impaired, which has an impact on their offspring.

Metabolism-related proteins as biomarkers for predicting prognosis in polycystic ovary syndrome

OBJECTIVE

The study aimed to explore the role of metabolism-related proteins and their correlation with clinical data in predicting the prognosis of polycystic ovary syndrome (PCOS).

METHODS

This research involves a secondary analysis of proteomic data derived from endometrial samples collected from our study group, which includes 33 PCOS patients and 7 control subjects. A comprehensive identification and analysis of 4425 proteins were conducted to screened differentially expressed proteins (DEPs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were subsequently performed on the DEPs. To identify independent prognostic metabolism-related proteins, univariate Cox regression and LASSO regression were applied. The expression levels of these proteins were then used to develop a prognostic model, with their predictive accuracy evaluated through receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves. Furthermore, we also investigate the correlation between clinical data and prognostic proteins.

RESULTS

The study identified 285 DEPs between the PCOS and control groups. GO enrichment analysis revealed significant involvement in metabolic processes, while KEGG pathway analysis highlighted pathways such as glycolysis/gluconeogenesis and glucagon signaling. Ten key metabolism-related proteins (ACSL5, ANPEP, CYB5R3, ENOPH1, GLS, GLUD1, LDHB, PLCD1, PYCR2, and PYCR3) were identified as significant predictors of PCOS prognosis. Patients were separated into high and low-risk groups according to the risk score. The ROC curves for predicting outcomes at 6, 28, and 37 weeks demonstrated excellent predictive performance, with AUC values of 0.98, 1.0, and 1.0, respectively. The nomogram constructed from these proteins provided a reliable tool for predicting pregnancy outcomes. DCA indicated a net benefit of the model across various risk thresholds, and the calibration curve confirmed the model's accuracy. Additionally, we also found BMI exhibited a significant negative correlation with the expression of GLS (r =-0.44, p = 0.01) and CHO showed a significant positive correlation with the expression of LDHB (r = 0.35, p = 0.04).

CONCLUSION

The identified metabolism-related proteins provide valuable insights into the prognosis of PCOS. The protein based prognostic model offers a robust and reliable tool for risk stratification and personalized management of PCOS patients.

The melanocortin receptor genes are linked to and associated with the risk of polycystic ovary syndrome in Italian families

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder occurring in women of reproductive age. The disease is caused by a complex interplay of genetic and environmental factors including genes encoding components of the hypothalamic-pituitary-adrenal (HPA) axis. We have recently reported the association of melanocortin receptor genes (MC1R, MC2R, MC3R, MC4R, and MC5R) with the risk of type 2 diabetes (T2D) and/or major depressive disorder (MDD). The latter 2 disorders are comorbid with PCOS. In this study, we used microarray to test 12 single nucleotide polymorphisms (SNPs) in the MC1R gene, 10 SNPs in the MC2R gene, 5 SNPs in the MC3R gene, 6 SNPs in the MC4R gene, and 4 SNPs in the MC5R gene in 212 original Italian families with PCOS. We identified 1 SNP in MC1R, 1 SNP in MC2R, 2 SNPs in MC3R, and 2 SNPs in MC5R significantly linked and/or associated to/with the risk of PCOS in Italian families. This is the first study to report the novel implication of melanocortin receptor genes (MC1R, MC2R, and MC5R) in PCOS. MC3R and MC4R were previously reported in PCOS. However, functional studies are needed to validate these results.

Epigenetic/circadian clocks and PCOS

Polycystic ovary syndrome (PCOS) affects 6-20% of reproductive-aged women. It is associated with increased risks of metabolic syndrome, Type 2 diabetes, cardiovascular diseases, mood disorders, endometrial cancer and non-alcoholic fatty liver disease. Although various susceptibility loci have been identified through genetic studies, they account for ∼10% of PCOS heritability. Therefore, the etiology of PCOS remains unclear. This review explores the role of epigenetic changes and modifications in circadian clock genes as potential contributors to PCOS pathogenesis. Epigenetic alterations, such as DNA methylation, histone modifications, and non-coding RNA changes, have been described in diseases related to PCOS, such as diabetes, cardiovascular diseases, and obesity. Furthermore, several animal models have illustrated a link between prenatal exposure to androgens or anti-Müllerian hormone and PCOS-like phenotypes in subsequent generations, illustrating an epigenetic programming in PCOS. In humans, epigenetic changes have been reported in peripheral blood mononuclear cells (PBMC), adipose tissue, granulosa cells (GC), and liver from women with PCOS. The genome of women with PCOS is globally hypomethylated compared to healthy controls. However, specific hypomethylated or hypermethylated genes have been reported in the different tissues of these women. They are mainly involved in hormonal regulation and inflammatory pathways, as well as lipid and glucose metabolism. Additionally, sleep disorders are present in women with PCOS and disruptions in clock genes' expression patterns have been observed in their PBMC or GCs. While epigenetic changes hold promise as diagnostic biomarkers, the current challenge lies in distinguishing whether these changes are causes or consequences of PCOS. Targeting epigenetic modifications potentially opens avenues for precision medicine in PCOS, including lifestyle interventions and drug therapies. However, data are still lacking in large cohorts of well-characterized PCOS phenotypes. In conclusion, understanding the interplay between genetics, epigenetics, and circadian rhythms may provide valuable insights for early diagnosis and therapeutic strategies in PCOS in the future.

Molecular role of non-exonic variants in CALPAIN 10 gene in polycystic ovarian syndrome in Saudi women

Introduction

Non-diabetic women with polycystic ovarian syndrome (PCOS) often have abnormal insulin regulation. Calpain 10 (CALP10) is a biomarker of type 2 diabetes mellitus, with some of its single-nucleotide polymorphisms (SNPs) influencing PCOS development.

Methods

In this case-control study on 90 women each with and without PCOS, we explored the molecular role of five CALP10 SNPs using biochemical parameters and Sanger sequencing analyses.

Results

Different genetic models, genotypes, and allele frequencies were significantly associated with UCSNP-19 (rs3842570; p=0.01), UCSNP-44 (rs2975760; p=0.009), UCSNP-56 (rs2975762; p<0.0001), and UCSNP-63 (rs5030952; p=0.0003) in women with PCOS. The multiple logistic regression model showed a strong association of CALP10 SNPs with fasting blood glucose (p<0.001). ANOVA showed significant associations with various biochemical parameters such as FSH (p=0.0001) in UCSNP-19 (rs3842570), FI (p=0.002), TG (p=0.01) in UCSNP-56 (rs2975762) and FBG (p=0.001), FI (p=0.004), FSH (p=0.02) & LDLc (p=0.04) in UCSNP-63 (rs5030952) SNPs. Haplotype analysis also revealed significant associations between different combinations of alleles in the studied 5 SNPs in women with PCOS (p<0.05). Generalized multifactor dimensionality reduction analysis showed the best gene-gene interactions among the five SNPs in CALP10I (p<0.05). However, dendrogram and graphical depletion models found no strong association in women with PCOS.

Conclusion

In conclusion, this study confirms rs3842570, rs2975760, rs2975767, and rs5030952 SNPs in CALP10 gene is associated in diagnosed PCOS women in the Saudi Arabia.

The Physiological Function of nNOS-Associated CAPON Proteins and the Roles of CAPON in Diseases

In this review, the structure, isoform, and physiological role of the carboxy-terminal PDZ ligand of neuronal nitric oxide synthase (CAPON) are summarized. There are three isoforms of CAPON in humans, including long CAPON protein (CAPON-L), short CAPON protein (CAPON-S), and CAPON-S' protein. CAPON-L includes three functional regions: a C-terminal PDZ-binding motif, carboxypeptidase (CPE)-binding region, and N-terminal phosphotyrosine (PTB) structural domain. Both CAPON-S and CAPON-S' only contain the C-terminal PDZ-binding motif. The C-terminal PDZ-binding motif of CAPON can bind with neuronal nitric oxide synthase (nNOS) and participates in regulating NO production and neuronal development. An overview is given on the relationship between CAPON and heart diseases, diabetes, psychiatric disorders, and tumors. This review will clarify future research directions on the signal pathways related to CAPON, which will be helpful for studying the regulatory mechanism of CAPON. CAPON may be used as a drug target, which will provide new ideas and solutions for treating human diseases.