The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians · 2025
Placental transcriptomic profiling showed disturbance of chemokine activities and lymphocyte chemotaxis in pregnancy with fetal growth restriction.
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Li Xiaohui, He Xin, Tong Jiamei, Hu Yanan, Li Zhengpeng, Chen Yi
Аннотация
OBJECTIVE: Fetal growth restriction (FGR) is a serious pathological complication associated with perinatal death and adverse pregnancy outcomes, which is largely related to placental dysfunction. This study aimed to identify FGR-related placenta transcriptomic features and provide insight into the pathologic mechanisms of FGR.
METHODS: In this research, transcriptomic data were obtained by RNA sequencing on placenta samples from eight FGR patients and eight normal term-pregnant women. Differential expression analysis was used to identify the differentially expressed genes (DEGs) between groups, then function and pathway enrichment analysis by DEGs was performed. After correlation analysis between DEGs and clinical indicators of FGR, validation of DEGs by Gene Expression Omnibus (GEO) dataset was carried out. Receiver operating characteristic (ROC) analysis was used to calculate the diagnostic ability of DEG biomarkers.
RESULTS: We identified seven candidate DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed candidate DEGs primarily involved in chemokine activities and lymphocyte chemotaxis. Correlation analysis found that the expression level of DPPA4 and CTAG2 gene were significantly positively correlated with neonatal birth weight (p < 0.05). The expression level of IGSF21 was significantly negatively correlated with placenta weight, neonatal birth weight and neonatal birth weight percentile (p < 0.05). The expression level of CXCL11 showed a negative correlation with neonatal birth weight and neonatal birth weight percentile (p < 0.05). Additionally, the expression level of CXCL10 exhibited a negative correlation to neonatal birth weight percentile (p < 0.05). The expression level of HLA-DQA1, CXCL10 and CXCL11 in the GEO dataset were in good agreement with our results. We conducted the ROC analysis and found the area under the curve (AUC) values based on each DEG alone were 80% for HLA-DQA1, 79%f or CXCL11 and 76% for CXCL10, suggesting that the above three DEGs had potential significance for FGR diagnosis.
CONCLUSION: This study gives an insight into transcriptional features in FGR mechanism and discovers novel genes that may provide evidence for predicting and managing FGR.
METHODS: In this research, transcriptomic data were obtained by RNA sequencing on placenta samples from eight FGR patients and eight normal term-pregnant women. Differential expression analysis was used to identify the differentially expressed genes (DEGs) between groups, then function and pathway enrichment analysis by DEGs was performed. After correlation analysis between DEGs and clinical indicators of FGR, validation of DEGs by Gene Expression Omnibus (GEO) dataset was carried out. Receiver operating characteristic (ROC) analysis was used to calculate the diagnostic ability of DEG biomarkers.
RESULTS: We identified seven candidate DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed candidate DEGs primarily involved in chemokine activities and lymphocyte chemotaxis. Correlation analysis found that the expression level of DPPA4 and CTAG2 gene were significantly positively correlated with neonatal birth weight (p < 0.05). The expression level of IGSF21 was significantly negatively correlated with placenta weight, neonatal birth weight and neonatal birth weight percentile (p < 0.05). The expression level of CXCL11 showed a negative correlation with neonatal birth weight and neonatal birth weight percentile (p < 0.05). Additionally, the expression level of CXCL10 exhibited a negative correlation to neonatal birth weight percentile (p < 0.05). The expression level of HLA-DQA1, CXCL10 and CXCL11 in the GEO dataset were in good agreement with our results. We conducted the ROC analysis and found the area under the curve (AUC) values based on each DEG alone were 80% for HLA-DQA1, 79%f or CXCL11 and 76% for CXCL10, suggesting that the above three DEGs had potential significance for FGR diagnosis.
CONCLUSION: This study gives an insight into transcriptional features in FGR mechanism and discovers novel genes that may provide evidence for predicting and managing FGR.