Xia Yu1, Ying Chen2, Li He2, Hong Liu3, Zhenglin Yang4, Yonghong Lin5. 1. Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China. 2. Department of Obstetrics and Gynecology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, No.1617 Ri Yue Street, Chengdu, 610091, Sichuan, China. 3. Department of Surgical, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China. 4. Sichuan Provincial Key Laboratory for Human Disease Gene Study and Institute of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No.32 The First Ring Road West 2, Chengdu, 610071, Sichuan, China. zliny@yahoo.com. 5. Department of Obstetrics and Gynecology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, No.1617 Ri Yue Street, Chengdu, 610091, Sichuan, China. linyhcd2011@163.com.
Abstract
INTRODUCTION AND HYPOTHESIS: The pathogenesis of pelvic organ prolapse (POP) remains unknown. Herein, we aim to reveal the molecular profile of POP by transcriptomic and metabolomic analysis. METHODS: We selected 12 samples of uterosacral ligaments (USLs) from 6 POP patients and 6 controls for transcriptomic and metabolomic analyses. Differentially expressed genes (DEGs) were identified using the R package edgeR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using clusterProfiler, and a protein-protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. Metabolomic profiling was performed by a liquid chromatography-tandem mass spectrometry system. RESULTS: Transcriptomic analysis identified 487 DEGs between the POP and control groups. Functional enrichment analysis revealed that they were mostly related to immune response terms, including "adaptive immune response," "T cell differentiation," and "T cell activation." In addition, PTPRC, LCK, CD247, IL2RB, CD2, CXR5, JUN, CD3E, IL2RG, and PRF1 were the 10 nodes with the highest node degrees in the PPI network. Metabolomic profiling revealed 290 differentially expressed metabolites, which significantly enriched in "glycerophospholipid metabolism," "nicotinate and nicotinamide metabolism," "glycine, serine, and threonine metabolism," "arginine and proline metabolism," "pyrimidine metabolism," and "purine metabolism." Finally, integrated analysis revealed that the DEGs involved in these significantly enriched metabolic pathways included NT5C1A, GMPR, SDS, ALAS2, CARNS1, PYCR1, P4HA3, PGS1, and NMRK2. CONCLUSIONS: Our findings demonstrate that the immune response and metabolic regulatory pathways are intertwined in POP and might provide new therapeutic targets.
INTRODUCTION AND HYPOTHESIS: The pathogenesis of pelvic organ prolapse (POP) remains unknown. Herein, we aim to reveal the molecular profile of POP by transcriptomic and metabolomic analysis. METHODS: We selected 12 samples of uterosacral ligaments (USLs) from 6 POP patients and 6 controls for transcriptomic and metabolomic analyses. Differentially expressed genes (DEGs) were identified using the R package edgeR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using clusterProfiler, and a protein-protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. Metabolomic profiling was performed by a liquid chromatography-tandem mass spectrometry system. RESULTS: Transcriptomic analysis identified 487 DEGs between the POP and control groups. Functional enrichment analysis revealed that they were mostly related to immune response terms, including "adaptive immune response," "T cell differentiation," and "T cell activation." In addition, PTPRC, LCK, CD247, IL2RB, CD2, CXR5, JUN, CD3E, IL2RG, and PRF1 were the 10 nodes with the highest node degrees in the PPI network. Metabolomic profiling revealed 290 differentially expressed metabolites, which significantly enriched in "glycerophospholipid metabolism," "nicotinate and nicotinamide metabolism," "glycine, serine, and threonine metabolism," "arginine and proline metabolism," "pyrimidine metabolism," and "purine metabolism." Finally, integrated analysis revealed that the DEGs involved in these significantly enriched metabolic pathways included NT5C1A, GMPR, SDS, ALAS2, CARNS1, PYCR1, P4HA3, PGS1, and NMRK2. CONCLUSIONS: Our findings demonstrate that the immune response and metabolic regulatory pathways are intertwined in POP and might provide new therapeutic targets.
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