ArticleCurrent medicinal chemistry2024
Identification of a Novel Diagnosis Model based on 5 Hub Genes for Chronic Thromboembolic Pulmonary Hypertension.
Article in Current medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 2 citations in OpenAlex.
- Complementary multi-omics profiling of chronic thromboembolic pulmonary hypertension reveals immune cell alterations, epigenetic changes, and genetically supported candidate genes.Animal models and experimental medicine · 2026Article
- Circulating Pin1 Levels in Patients With Chronic Thromboembolic Pulmonary Hypertension: A Case-Control Study.Pulmonary circulation · 2025Article
- Paeoniflorin Improves Stroke by Modulating the ESR1 Pathway: Data Mining and Validation Based on Network Approaches.Pharmaceuticals (Basel, Switzerland) · 2025Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundAs a type of precapillary pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) results from incomplete pulmonary embolism resolution. In this study, we aimed to determine biomarker genes for predicting the prognosis of CTEPH.
methodsRNAseq of CTEPH was collected from the public database, namely Gene Expression Omnibus (GEO), including GSE84538 and GSE188938, which combined a dataset (GSE). Differentially expressed genes (DEG) or miRNA (DEM) were identified by limma package. Functional enrichment analysis was performed by the WebGestaltR package. Then, the miRNA-mRNA network was presented by Cytoscape, and the protein-protein interactions (PPI) network was constructed by STRING. MCODE was mined by mature MCODE algorithm. Immune infiltration analysis was conducted by ESTIMATER and ssGSEA analysis. A diagnosis model was established by SVM algorithm.
resultsIn the GSE dataset, CTEPH samples had a lower GOBP_RESPONSE_- TO_OXIDATIVE_STRESS score. A total of 628 DEGs and 31 DEMs were identified between CTEPH and normal samples. Afterward, DEGs were intersected with genes, which correlated with the GOBP_RESPONSE_TO_OXIDATIVE_STRESS score. A 26 DEMs-152 DEGs network was constructed, and a PPI network was established based on 152 DEGs to find 149 target genes. From the above 149 target genes, 3 modules were extracted to obtain 15 core targets. Finally, 5 hub genes were obtained by the intersection of 15 core targets and genes in MCODE2. A total of 5 hub genes were positively correlated with most immune cell scores as well as GOBP_RESPONSE_TO_OXIDATIVE_ STRESS. It was found that a diagnosis model based on 5 hub genes had a well diagnostic ability for CTEPH.
conclusionWe identified 5 hub genes associated with oxidative stress. It can be concluded that they may be beneficial in diagnosing CTEPH.
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