Bioinformatics analysis of the molecular mechanism of obesity in polycystic ovary syndrome

Background: Obesity is an important part of polycystic ovary syndrome (PCOS) pathologies. The present study utilized the bioinformatics method to identify the molecular mechanism of obesity status in PCOS. Methods: Six transcriptome profiles of adipose tissue were obtained from online databases. The background correction and normalization were performed, and the DEGs were detected with the settings p < 0.05. The GO, KEGG pathway enrichment, and PPI network analysis were performed with the detected DEGs. Results: A total of 37 DGEs were found between obesity PCOS and healthy controls, and 8 of them were tested significant in the third database. The expression patterns of the 8 detected DGEs were then measured in another two datasets based on lean/obesity PCOS patients and healthy controls. The gene CHRDL1 was found to be in linear regression with the BMI index in PCOS patients (p = 0.0358), but such a difference was not found in healthy controls (p = 0.2487). The expression of CHRDL1 was significantly higher in obesity PCOS cases than the BMI matched healthy controls (p = 0.0415). Further enrichment research demonstrated the CHRDL1 might function as an inhibitor of the BMP4 or IGF1 signalling. Conclusion: In summary, the present study identified CHRDL1 as a candidate gene responsible for the obesity of PCOS patients.