Diabetes, Metabolic Syndrome and Obesity (Sep 2023)

Analysis of Methylome, Transcriptome, and Lipid Metabolites to Understand the Molecular Abnormalities in Polycystic Ovary Syndrome

  • Zhang F,
  • Ding Y,
  • Zhang B,
  • He M,
  • Wang Z,
  • Lu C,
  • Kang Y

Journal volume & issue
Vol. Volume 16
pp. 2745 – 2763

Abstract

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Fei Zhang,1 Yicen Ding,1 Bohan Zhang,1 Mengju He,1 Zhijiang Wang,2 Chunbo Lu,3 Yani Kang1 1School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Department of Pharmaceutical Engineering, Zhejiang Pharmaceutical University, Ningbo, People’s Republic of China; 3Department of Obstetrics and Gynecology, Qiuai Central Health Center, Ningbo, People’s Republic of ChinaCorrespondence: Chunbo Lu, Department of Obstetrics and Gynecology, Qiuai Central Health Center, Ningbo, 315100, People’s Republic of China, Tel +86-13567881644, Email [email protected] Yani Kang, School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, 200240, People’s Republic of China, Tel +86-13661848623, Email [email protected]: This study aimed to identify differentially methylated genes (DMGs) and differentially expressed genes (DEGs) to investigate new biomarkers for the diagnosis and treatment of polycystic ovary syndrome (PCOS).Methods: To explore the potential biomarkers of PCOS diagnosis and treatment, we performed methyl-binding domain sequencing (MBD-seq) and RNA sequencing (RNA-seq) on ovarian granulosa cells (GCs) from PCOS patients and healthy controls. MBD-seq was also performed on the ovarian tissue of constructed prenatally androgenized (PNA) mice. Differential methylation and expression analysis were implemented to identify DMGs and DEGs, respectively. The identified gene was further verified by real-time quantitative PCR (RT-qPCR) and methylation-specific PCR (MSP) in clinical samples. Furthermore, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was carried out on PCOS patients and healthy controls to identify differential lipid metabolites.Results: Compared to the control group, 13,526 DMGs related to the promoter region and 2429 DEGs were found. The function analysis of DMGs and DEGs showed that they were mainly enriched in glycerophospholipid, ovarian steroidogenesis, and other lipid metabolic pathways. Moreover, 5753 genes in DMGs related to the promoter region were screened in the constructed PNA mice. Integrating the DMGs data from PCOS patients and PNA mice, we identified the following 8 genes: CDC42EP4, ERMN, EZR, PIK3R1, ARHGEF18, NECTIN2, TSC2, and TACSTD2. RT-qPCR and MSP verification results showed that the methylation and expression of TACSTD2 were consistent with sequencing data. Additionally, 15 differential lipid metabolites were shown in the serum of PCOS patients. The differential lipids were involved in glycerophospholipid and glycerolipid metabolism.Conclusion: Using integration of methylome and lipid metabolites profiling we identified 8 potential epigenetic markers and 15 potential lipid metabolite markers for PCOS. Our results suggest that aberrant DNA methylation and lipid metabolite disorders may provide novel insights into the diagnosis and etiology of PCOS.Keywords: polycystic ovary syndrome, DNA methylation, transcriptome, lipid metabolites, granulosa cell

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