Micro-RNAs involved in cellular proliferation have altered expression profiles in granulosa of young women with diminished ovarian reserve

Woo, Irene; Christenson, Lane K.; Gunewardena, Sumedha; Ingles, Sue A.; Thomas, S.; Ahmady, Ali; Chung, Karine; Bendikson, Kristin; Paulson, Richard J.; McGinnis, Lynda K.

doi:10.1007/s10815-018-1239-9

Cited by 40 publications

(34 citation statements)

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“…We also observed a moderate, statistically significant correlation between decreased serum H19 expression and decreased AMH. Altered expression profiles of microRNAs, another class of noncoding RNAs, has been linked with poor ovarian reserve in plasma and serum [24,25], whole ovaries [26], follicular fluid [27], granulosa cells [28][29][30], and oocytes [31], and two studies have reported differential expression of piwi-interacting RNAs in GCs and oocytes from women with DOR [31,32]. However, little is known about the role of long noncoding RNAs such as H19 in ovarian aging.…”

Section: Discussionmentioning

confidence: 99%

The relationship between H19 and parameters of ovarian reserve

Xia

Burn

Chen

et al. 2020

Reprod Biol Endocrinol

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Context: The H19 long noncoding RNA (lncRNA) belongs to a highly conserved, imprinted gene cluster involved in embryonic development and growth control. We previously described a novel mechanism whereby the Antimullerian hormone (Amh) appears to be regulated by H19. However, the relationship between circulating H19 and markers of ovarian reserve including AMH not been investigated. Objective: To determine whether H19 expression is altered in women with decreased ovarian reserve.

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Section: Discussionmentioning

confidence: 99%

The relationship between H19 and parameters of ovarian reserve

Xia

Burn

Chen

et al. 2020

Reprod Biol Endocrinol

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“…E-MTAB-391′s platform was the A-MEXP-1564-IIIumina HumanRef-8 WG-DASL v3 Expression BeadChip. We directly extracted the data from the DOR miRNAs used in a previous study ( Woo et al, 2018 ).…”

Section: Methodsmentioning

confidence: 99%

“…Considering this coadjutant relationship between oocyte and GC, exploring the alteration of GCs from women with DOR may provide a deeper understanding for DOR pathogenesis. Previous studies have investigated the mRNA expression profiles of ovarian CCs ( Greenseid et al, 2011 ) and GCs ( Chin et al, 2002 ; Skiadas et al, 2012 ) in addition to miRNA expression patterns ( Chen et al, 2017 ; Woo et al, 2018 ) in DOR patients. These studies typically had different inclusion criteria for DOR patients.…”

Section: Introductionmentioning

confidence: 99%

“…In this study, we performed bioinformatic analyses on the mRNA expression profiles of DOR GCs from the publicly available dataset E-MTAB-391 in order to identify differentially expressed genes (DEGs). We constructed protein-protein interaction (PPI) networks based on the DEGs, and a miRNA-mRNA network using the differentially expressed miRNAs (DEMs) extracted from a previous study ( Woo et al, 2018 ). Small molecule drugs with potential synergistic or antagonistic effects on DOR were also screened using the Connectivity Map (CMap) database ( Lamb et al, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

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

Zhao

Yang

et al. 2020

PeerJ

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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.

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“…Considering this coadjutant relationship between oocyte and GC, exploring the alteration of GCs from women with DOR may provide a deeper understanding for DOR pathogenesis. Previous studies have investigated the mRNA expression profiles of ovarian CCs (Greenseid et al, 2011) and GCs (Chin et al, 2002;Skiadas PeerJ reviewing PDF | (2020:03:46424:2:0:NEW 1 Aug 2020) Manuscript to be reviewed et al, 2012) in addition to miRNA expression patterns (Chen et al, 2017;Woo et al, 2018) in DOR patients. These studies typically had different inclusion criteria for DOR patients.…”

Section: Introductionmentioning

confidence: 99%

Peer Review #2 of "Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve (v0.1)"

2020

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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 endproduct)-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.

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Micro-RNAs involved in cellular proliferation have altered expression profiles in granulosa of young women with diminished ovarian reserve

Abstract: The miRNA pattern identified critical functions in cell proliferation and survival associated with DOR. GC in women with DOR seems to respond differently to the LH surge.

Cited by 40 publications

References 51 publications

The relationship between H19 and parameters of ovarian reserve

The relationship between H19 and parameters of ovarian reserve

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

Peer Review #2 of "Using bioinformatics and metabolomics to identify altered granulosa cells in patients with diminished ovarian reserve (v0.1)"

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