World journal of clinical cases · 2024
Functional investigation and two-sample Mendelian randomization study of primary biliary cholangitis hub genes.
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Yang Yun-Chuan, Ma Xiang, Zhou Chi, Xu Nan, Ding Ding, Ma Zhong-Zheng, Zhou Lei, Cui Pei-Yuan
Аннотация
BACKGROUND: The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis (PBC) and finding relevant biomarkers for diagnosis and therapeutic evaluation.
AIM: To determine PBC-associated hub genes and assess their clinical utility for disease prediction.
METHODS: PBC expression data were obtained from the Gene Expression Omnibus database. Overlapping genes from differential expression analysis and weighted gene co-expression network analysis (WGCNA) were identified as key genes for PBC. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes. Hub genes were identified in protein-protein interaction (PPI) networks using the Degree algorithm in Cytoscape software. The relationship between hub genes and immune cells was investigated. Finally, a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.
RESULTS: We identified 71 overlapping key genes using differential expression analysis and WGCNA. These genes were primarily enriched in pathways related to cytokine-cytokine receptor interaction, and Th1, Th2, and Th17 cell differentiation. We utilized Cytoscape software and identified five hub genes (CD247, IL10, CCL5, CCL3, and STAT3) in PPI networks. These hub genes showed a strong correlation with immune cell infiltration in PBC. However, inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.
CONCLUSION: Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment, thereby offering significant clinical utility.
AIM: To determine PBC-associated hub genes and assess their clinical utility for disease prediction.
METHODS: PBC expression data were obtained from the Gene Expression Omnibus database. Overlapping genes from differential expression analysis and weighted gene co-expression network analysis (WGCNA) were identified as key genes for PBC. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes. Hub genes were identified in protein-protein interaction (PPI) networks using the Degree algorithm in Cytoscape software. The relationship between hub genes and immune cells was investigated. Finally, a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.
RESULTS: We identified 71 overlapping key genes using differential expression analysis and WGCNA. These genes were primarily enriched in pathways related to cytokine-cytokine receptor interaction, and Th1, Th2, and Th17 cell differentiation. We utilized Cytoscape software and identified five hub genes (CD247, IL10, CCL5, CCL3, and STAT3) in PPI networks. These hub genes showed a strong correlation with immune cell infiltration in PBC. However, inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.
CONCLUSION: Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment, thereby offering significant clinical utility.