Integrated bioinformatics analysis reveals marker genes and immune infiltration for pulmonary arterial hypertension.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35710932", "kind": "science-record", "revision": 5, "content_hash": "sha256:9b0ad601f69dcccc6826718962bed6c6d81c82f9d09912a754d9a4aa0ba98fa1", "created_at": "2026-11-01T18:14:41Z", "updated_at": "2026-11-01T22:49:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated bioinformatics analysis reveals marker genes and immune infiltration for pulmonary arterial hypertension.", "doi": "10.1038/s41598-022-14307-6", "pmid": "35710932", "authors": ["Shengxin Tang", "Yue Liu", "Bin Liu"], "journal": "Scientific reports", "year": 2022, "abstract": "Pulmonary arterial hypertension (PAH) is a chronic cardiopulmonary syndrome with high pulmonary vascular load and eventually causing RV heart failure even death. However, the mechanism of pulmonary hypertension remains unclear. The purpose of this research is to detect the underlying key genes and potential mechanism of PAH using several bioinformatic methods. The microarrays GSE22356, GSE131793 and GSE168905 were acquired from the GEO. Subsequently, a host of bioinformatics techniques such as DAVID, STRING, R language and Cytoscape were utilized to investigate DEGs between PAH and healthy controls and conduct GO annotation, KEGG enrichment analysis and PPI network construction etc. Additionally, we predicted the transcription factors regulating DEGs through iRegulon plugin of Cytoscape and CIBERSORT was used to conduct immune infiltration analysis. One thousand two hundred and seventy-seven DEGs (403 up-regulated and 874 down-regulated) were identified from peripheral blood samples of 32 PAH patients and 29 controls, among which SLC4A1, AHSP, ALAS2, CA1, HBD, SNCA, HBM, SELENBP1, SERPINE1 and ITGA2B were detected as hub genes. The functional enrichment changes of DEGs were mainly enriched in protein binding, extracellular exosome, extracellular space, extracellular region and integral component of plasma membrane. The hub genes are chiefly enriched at extracellular exosome, hemoglobin complex, blood microparticle, oxygen transporter activity. Among TF-DEGs network, 42 target DEGs and 6 TFs were predicted with an NES > 4 (TEAD4, TGIF2LY, GATA5, GATA1, GATA2, FOS). Immune infiltration analysis showed that monocytes occupied the largest proportion of immune cells. The trend analysis results of infiltration immune cells illustrated that PAH patients had higher infiltration of NK cell activation, monocyte, T cell CD4 memory activation, and mast cell than healthy controls and lower infiltration of T cell CD4 naive. We detected SLC4A1, AHSP, ALAS2, CA1, HBD, SNCA, HBM, SELENBP1, SERPINE1 and ITGA2B as the most significant markers of PAH. The PAH patients had higher infiltration of NK cell activation, monocyte, T cell CD4 memory activation, and mast cell than healthy controls and lower infiltration of T cell CD4 naive. These identified genes and these immune cells probably have precise regulatory relationships in the development of PAH.", "claims": [{"id": "claim-method", "statement": "For the purpose of identifying the significant DEGs between the PAH and the healthy group, Limma (linear models for microarray data) package was adopted processing three datasets with |log2 fold change (FC)|≥ 1 and adjusted p value < 0.05 as the thresholds21.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35710932", "locator": "sections[12] \"Identification of DEGs\" paragraph 2", "quote": "For the purpose of identifying the significant DEGs between the PAH and the healthy group, Limma (linear models for microarray data) package was adopted processing three datasets with |log2 fold change (FC)|≥ 1 and adjusted p value < 0.05 as the thresholds21."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression profiles of GSE22356, GSE131793 and GSE168905 were downloaded from Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22356, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131793 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168905).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35710932", "locator": "sections[21] \"Data availability\" paragraph 2", "quote": "The gene expression profiles of GSE22356, GSE131793 and GSE168905 were downloaded from Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22356, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131793 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168905)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Then, we merged up- regulated and down-regulated DEGs in the three datasets, which revealed a total of 403 up-regulated DEGs and 874 down-regulated DEGs in the microarrays.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35710932", "locator": "sections[3] \"Identification of DEGs in PAH\" paragraph 2", "quote": "Then, we merged up- regulated and down-regulated DEGs in the three datasets, which revealed a total of 403 up-regulated DEGs and 874 down-regulated DEGs in the microarrays."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Then, we merged up- regulated and down-regulated DEGs in the three datasets, which revealed a total of 403 up-regulated DEGs and 874 down-regulated DEGs in the microarrays.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35710932"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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