Fig. 1

The flowchart of the bioinformatics analysis. GSE117261, GSE113439 and GSE53408 datasets were downloaded from the GEO database. After pre-processing and normalization of the data, the differentially expressed genes (DEGs) were identified in GSE117261 and the functional enrichment analyses of Gene Ontology and KEGG were performed. GSEA was conducted to investigate the potential biological pathways using the entire gene set. The immune landscape in the dataset was determined by the CIBERSORT algorithm. Lasso regression analysis was performed to identify 17 feature genes, and fivefold cross-validation was performed using RF and LR in GSE117261. ROC curve of 17 feature genes was performed to construct PAH prediction model in GSE53408 and GSE113439. WGCNA was performed to identify the modules associated with PAH. The intersection of genes in the modules screened and DEGs were used to construct PPI network and identification of the core genes. After the intersection of 17 feature genes and 100 core genes, four hub genes were identified. Pearson correlation analysis was performed to analyze the correlation between the hub genes and immune cell infiltration