Comparing the metabolomic landscape of polycystic ovary syndrome within urban and rural environments

Abstract

Background: Polycystic Ovary Syndrome (PCOS) affects up to 10% of women of reproductive age, characterized by hormonal imbalances and metabolic complications. Environmental factors potentially influence the biochemical expression of this condition. This study aims to examine the impact of urban versus rural environments on metabolite profiles in women with PCOS.

Methods: Thirty women aged between 18 and 40, diagnosed with PCOS according to the Rotterdam 2003 criteria, were recruited from June 2022 to May 2023, 16 from urban settings and 14 from rural settings. Serum samples were analyzed using liquid chromatography-tandem mass spectrometry. Principal component analysis and orthogonal partial least squares discriminant analysis were performed to identify metabolic patterns and differences between the two groups.

Results: This study reveals significant differences in metabolite profiles between women with PCOS from various environmental backgrounds. Rural participants exhibit higher levels of lipid-related metabolites, especially Palmitone, indicating specific dietary influences. Urban participants show distinct changes in carbohydrate and nucleotide metabolism pathways, likely due to processed food consumption. Multivariate analyses demonstrate a clear separation between the groups, emphasizing the environmental impact on PCOS expression.

Conclusions: This research highlights potential environment-related biomarkers for PCOS, emphasizing the importance of developing tailored treatment strategies considering environmental factors. The distinct metabolic profiles observed between urban and rural women provide new insights into the syndrome's complex mechanisms, indicating that environmental influences play a critical role in its biochemical expression and may affect its clinical manifestations.

Fig. 1. Analytical characterization and comparative metabolomic profiling in urban-PCOS and rural-PCOS.

Initial chromatograms (panels a–d) illustrate distinct peak intensities across ionization modes, the Venn diagram (panel e) enumerates metabolites contributing to the study, and PCA (panels f, g) elucidates the distinct metabolic clustering between the cohorts.

Fig. 2. Metabolomic analysis reveals distinct metabolite profiles between rural and urban PCOS patients.

a Volcano plot visualizing significantly altered metabolites, with log2 fold-change (FC) on the x-axis and -log10 p-value on the y-axis, demarcating the threshold of significance. Metabolites to the right are predominantly upregulated in Urban-PCOS, and those to the left are upregulated in Rural-PCOS. b Fold-change plot categorizing metabolites by the magnitude of their expression differences between the groups. c–o Violin plots showing the distribution of selected significant metabolites across the two cohorts, with statistical annotations (p-values) indicating the significance level. Statistical comparisons were performed using an unpaired two-tailed t-test. These plots elucidate the specific metabolite alterations within the comparative context of rural versus urban living environments in PCOS patients.

Fig. 3. Metabolomic differentiation of PCOS in rural versus urban environments.

a PLS-DA scatter plot distinguishing Rural-PCOS (green) and Urban-PCOS (purple) groups along two principal components representing the most significant variance within the dataset. b OPLS-DA score plot enhances the metabolite-based separation between the groups, with T-scores depicting the discriminatory power. c VIP scores from the PLS-DA model rank the metabolites by their contribution to the group differentiation, with higher scores indicating greater importance. d The permutation test validated the PLS-DA model, with observed R2 and Q2 values far exceeding those from randomly permuted data, underscoring model reliability. e The feature importance plot displays the magnitude and reliability of each metabolite’s contribution to the model. f SAM plots for significant differential expression of metabolites between groups at a specified delta, demonstrating robust statistical significance with a low false discovery rate.

Fig. 4. Comparative metabolomic profiling in PCOS of rual and urban subjects.

a Correlation heatmaps depicting the serum metabolite associations in Rural-PCOS versus Urban-PCOS patients, b the Pearson correlation of the relationship between metabolites and biochemical parameters across both cohorts.

Fig. 5. Hierarchical clustering dendrogram of PCOS features in rural and urban subjects using Spearman’s rank correlation.

The dendrogram segregates subjects into distinct clusters based on the similarity of their features, with a clear delineation between rural and urban populations.

Fig. 6. Integrated biomarker analysis of metabolomic profiles in PCOS.

a ROC curves with AUC values for models incorporating different numbers of metabolites. b illustrates the predictive accuracies across models, identifying an optimal number of features for maximal accuracy. c–h present box plots and ROC curves for selected high-AUC metabolites, emphasizing their role as key biomarkers in differentiating Rural-PCOS from Urban-PCOS phenotypes. Statistical significance in box plots was assessed using an unpaired two-tailed t-test.

Fig. 7. Pathway analysis of the differential metabolites between rural-PCOS versus urban-PCOS.

a Enrichment analysis of metabolic pathways. The bar chart illustrates the enrichment ratios of significantly altered metabolite sets, with color intensity denoting the statistical significance (p-value) for each pathway. Statistical significance was determined using a hypergeometric test, and p-values were adjusted using the Benjamini–Hochberg method for multiple testing correction. b Pathway enrichment analysis of differential metabolites between PCOS and control groups. Significant metabolites were identified using an unpaired two-tailed t-test with FDR correction (p < 0.05). Pathway enrichment was performed using the over-representation method based on the hypergeometric test. c Network plot displaying the interconnectedness of metabolically altered pathways in PCOS.