Archives of gynecology and obstetrics · 2022
Integrative analysis of the immune-related ceRNA network in fetal growth restriction based on weighted gene co-expression network analysis.
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Li Pingping, Zhao Yuebin
Аннотация
PURPOSE: Immune disorders lead to placental dysfunction and fetal growth restriction (FGR), but current research on the immune regulation mechanisms of FGR and the involvement of competing for endogenous RNA (ceRNA) is insufficient. Therefore, this study aimed to construct an immune-related ceRNA network to predict FGR onset risk.
METHODS: Microarray data from the GEO database was used for gene expression and immune infiltration analyses. Weighted gene co-expression network analysis (WGCNA) was used to screen immune-related module genes with differential expression (DE) in FGR. A ceRNA network was constructed by integrating long non-coding RNA (lncRNA)-mRNA, lncRNA-microRNA (miRNA), and miRNA-mRNA relations. The diagnostic values of key genes in the network and their relationships with immune cell were confirmed in a validation cohort.
RESULTS: By comparing FGR and normal samples, DE mRNAs, miRNAs, lncRNAs, and four types of immune cells with different infiltration levels were obtained. WGCNA then revealed 236 immune-related DE mRNAs that were involved in hormone secretion and immune cell differentiation. Based on co-expression analysis and miRNA prediction, we initially constructed a ceRNA network to screen several immune-related genes as potential diagnostic biomarkers of FGR, whose superior predictive performances were further confirmed by receiver operating characteristic curves. Among them, NEURL1 and ODF3B were found to positively correlate with M1 macrophages and may participate in the immunoregulation of FGR.
CONCLUSION: From the perspective of ceRNA mechanism, we constructed an immune-related regulatory network for the first time wherein key genes are initially proposed as potential diagnostic biomarkers of FGR to involve in M1 macrophage-mediated immunoregulation.
METHODS: Microarray data from the GEO database was used for gene expression and immune infiltration analyses. Weighted gene co-expression network analysis (WGCNA) was used to screen immune-related module genes with differential expression (DE) in FGR. A ceRNA network was constructed by integrating long non-coding RNA (lncRNA)-mRNA, lncRNA-microRNA (miRNA), and miRNA-mRNA relations. The diagnostic values of key genes in the network and their relationships with immune cell were confirmed in a validation cohort.
RESULTS: By comparing FGR and normal samples, DE mRNAs, miRNAs, lncRNAs, and four types of immune cells with different infiltration levels were obtained. WGCNA then revealed 236 immune-related DE mRNAs that were involved in hormone secretion and immune cell differentiation. Based on co-expression analysis and miRNA prediction, we initially constructed a ceRNA network to screen several immune-related genes as potential diagnostic biomarkers of FGR, whose superior predictive performances were further confirmed by receiver operating characteristic curves. Among them, NEURL1 and ODF3B were found to positively correlate with M1 macrophages and may participate in the immunoregulation of FGR.
CONCLUSION: From the perspective of ceRNA mechanism, we constructed an immune-related regulatory network for the first time wherein key genes are initially proposed as potential diagnostic biomarkers of FGR to involve in M1 macrophage-mediated immunoregulation.