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Title:
3 CpG methylation biomarkers for the diagnosis of polycystic ovary syndrome (PCOS) in blood

Abstract:

Background: Polycystic ovary syndrome (PCOS) is a common endocrine disease in women that seriously interferes with the patient's metabolic and reproductive functions. The current diagnostic criteria for PCOS are expert-based and still disputed. Previous studies have identified changes in DNA methylation in peripheral blood of women with PCOS, but their diagnostic potential for PCOS remains to be studied.

Objective: The present study aimed to identify potential methylation biomarkers for the diagnosis of PCOS in blood.

Methods: Methylation profiles of peripheral blood were downloaded from a public database, Gene Expression Omnibus (GEO), of 30 PCOS patients (diagnosed with the revised 2003 Rotterdam consensus criteria), and 30 age-matched healthy women were recruited from the Centre of Reproductive Medicine, Linyi People’s Hospital, Shandong, China. Weighted gene co-expression network analysis (WGCNA) was utilized to identify PCOS-related co-methylation CpG sites (co-MPs). Functional enrichment analysis was performed on the localized genes of PCOS-related co-MPs. The least absolute shrinkage and selection operator (LASSO) regression was used to screen CpG methylation signatures for PCOS diagnosis and receiver operating characteristic (ROC) analysis was conducted to evaluate their diagnostic accuracy, respectively. To assess the accuracy of the combination of the investigated indicators, multivariate ROC analysis was performed on the predicted probability values obtained using binary logistic regression on the methylation levels of selected CpGs together.

Results: Seven co-methylation modules were obtained, most relevant to PCOS of which was the turquoise module, containing 194 co-MPs. The genes that these co-MPs located in were mainly associated with the immune-related pathway. According to LASSO regression, three Co-MPs (cg23464743, cg06834912, cg00103771) were identified as potential diagnostic biomarkers of PCOS. ROC analysis showed an AUC (area under the curve) of 0.7556 (sensitivity 60.0%, specificity 83.3%) for cg23464743, 0.7822 (sensitivity 70.0%, specificity 80.0%) for cg06834912, and 0.7611 (sensitivity 63.3%, specificity 83.3%) for cg00103771. The diagnostic accuracy of the combination of these 3 indicators presented to be higher than any single one of them, with an AUC of 0.8378 (sensitivity 73.3%, specificity 93.3%).

Conclusion: The combination of 3 CpG methylation signatures in blood was identified with a good diagnostic accuracy for PCOS, which may bring new insight into the development of PCOS diagnostic markers in the future.



Journal Title: Combinatorial Chemistry & High Throughput Screening

Price: $95


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