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Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve.

ABSTRACT: Background:During fertility treatment, diminished ovarian reserve (DOR) is a challenge that can seriously affect a patient's reproductive potential. However, the pathogenesis of DOR is still unclear and its treatment options are limited. This study aimed to explore DOR's molecular mechanisms. Methods:We used R software to analyze the mRNA microarray dataset E-MTAB-391 downloaded from ArrayExpress, screen for differentially expressed genes (DEGs), and perform functional enrichment analyses. We also constructed the protein-protein interaction (PPI) and miRNA-mRNA networks. Ovarian granulosa cells (GCs) from women with DOR and the control group were collected to perform untargeted metabolomics analyses. Additionally, small molecule drugs were identified using the Connectivity Map database. Results:We ultimately identified 138 DEGs. Our gene ontology (GO) analysis indicated that DEGs were mainly enriched in cytokine and steroid biosynthetic processes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG), the DEGs were mainly enriched in the AGE (advanced glycation end-product)-RAGE (receptor for AGE) signaling pathway in diabetic complications and steroid biosynthesis. In the PPI network, we determined that JUN, EGR1, HMGCR, ATF3, and SQLE were hub genes that may be involved in steroid biosynthesis and inflammation. miRNAs also played a role in DOR development by regulating target genes. We validated the differences in steroid metabolism across GCs using liquid chromatography-tandem mass spectrometry (LC-MS/MS). We selected 31 small molecules with potentially positive or negative influences on DOR development. Conclusion:We found that steroidogenesis and inflammation played critical roles in DOR development, and our results provide promising insights for predicting and treating DOR.

SUBMITTER: He R

PROVIDER: S-EPMC7457930 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve.

He Ruifen R Zhao Zhongying Z Yang Yongxiu Y Liang Xiaolei X

PeerJ 20200828

<h4>Background</h4>During fertility treatment, diminished ovarian reserve (DOR) is a challenge that can seriously affect a patient's reproductive potential. However, the pathogenesis of DOR is still unclear and its treatment options are limited. This study aimed to explore DOR's molecular mechanisms.<h4>Methods</h4>We used R software to analyze the mRNA microarray dataset E-MTAB-391 downloaded from ArrayExpress, screen for differentially expressed genes (DEGs), and perform functional enrichment ...[more]

PMID: 32923184

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Project description:Background: Infertility is one of the major health problems and the third most common disease, and diminished ovarian reserve (DOR) is a common cause of infertility. DOR is defined as decreased number or quality of oocytes in reproductive-age women, but the underlying molecular mechanisms remain unclear. Long noncoding RNAs (lncRNAs) has been recognized to play an important role in physiological and pathological processes of the human body, but it is unknown whether lncRNAs are involved in the development of DOR. Methods: The ovarian granulosa cells from infertility women with DOR and normal ovarian reserve (NOR) were obtained and subjected to high-throughput sequencing. A comprehensive bioinformatics analysis was conducted to characterize the mRNAs and lncRNAs expression profiles between DOR and NOR women. Then, the sequencing results were validated by selected randomly lncRNAs using real-time quantitative PCR. Results: A total of 92,853 lncRNAs transcripts were identified between DOR and NOR GCs. Compared with NOR control, 244 lncRNAs were upregulated (53 known and 191 novel) and 222 lncRNAs were downregulated (36 known and 186 novel) in the DOR group. Similarly, 457 differently expressed mRNAs were found between the two groups, with 169 and 288 up- and downregulated respectively. Further functional analysis revealed that differentially expressed genes of mRNA and lncRNA were significantly enriched in various biological processes such as cell adhesion and apoptosis, steroid biosynthesis, and immune system. The results of correlated expression networks between lncRNAs and their predicted target genes uncovered the possible involvement of the thyroid hormone signaling pathway and protein binding, digestion and absorption in the pathogenesis of DOR and showed that SLC16A10 is positively regulated by multiple lncRNAs. In addition, it was verified that the expression patterns of three of the seven selected differentially expressed lncRNAs were consistent with RNA-Seq. Aberrant lncRNAs might be used to develop new diagnostic biomarkers or drugs to target DOR. Conclusion: This study is the first to elucidate the lncRNA and mRNA expression profiles between NOR and DOR patients in the ovarian granulosa cells using sequencing technology. The lncRNAs identified in this study can potentially be novel diagnostic biomarkers and therapeutic targets for DOR.

Dataset Information

Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve.

Publications

Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve.

Similar Datasets

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