Identification and Validation of Potential Diagnostic Biomarkers for Pulmonary Arterial Hypertension Based on Gene Expression Profiling.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41221472", "kind": "science-record", "revision": 4, "content_hash": "sha256:ca08a0f2fef917e33d3cfbfa3115697c88aa1209e4f3603eed4161cc9b226891", "created_at": "2026-11-01T20:31:15Z", "updated_at": "2026-11-01T22:57:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Potential Diagnostic Biomarkers for Pulmonary Arterial Hypertension Based on Gene Expression Profiling.", "doi": "10.1002/pul2.70207", "pmid": "41221472", "authors": ["Huan Liu", "Mengyu Wu", "Guanming Qi", "Feifei Ma", "Yunshan Cao"], "journal": "Pulmonary circulation", "year": 2025, "abstract": "Pulmonary arterial hypertension (PAH) is a life-threatening condition characterized by elevated pulmonary vascular resistance. Despite recent advances, early diagnosis remains challenging due to nonspecific symptoms. By utilizing RNA sequencing (RNA-seq) data from the GEO database, we conducted bioinformatics analyses to identify potential diagnostic biomarkers. Differentially expressed genes (DEGs) were screened in blood from PAH patients, followed by functional enrichment and protein-protein interaction (PPI) network analyses. Thirteen overlapping DEGs were identified, which were enriched in erythrocyte development, heme biosynthesis, and chloride transport. Five hub genes (SLC4A1, AHSP, ALAS2, FECH, and CA1), exhibited strong diagnostic potential, with an area under the curve (AUC) ≥ 0.7 in training datasets (GSE38267, GSE22356). External validation using datasets GSE33463 and GSE117261 confirmed their efficacy in blood samples, although AHSP showed reduced performance in lung tissue. Experimental validation in hypoxic human pulmonary artery smooth muscle cells (hPASMCs) supported the bioinformatics findings. These results underscore SLC4A1, AHSP, ALAS2, FECH, and CA1 as promising noninvasive diagnostic biomarkers for PAH, linking transcriptional dysregulation to clinical application.", "claims": [{"id": "claim-method", "statement": "The R package “limma” was utilized to identify DEGs between PAH and normal control samples in the GSE38267 and GSE22356 datasets [14], applying a significance criterion of |Log2FC| > 1 and a p‐value < 0.05 [15]. 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Other data available on request of the authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Five hub genes—SLC4A1, AHSP, ALAS2, FECH, and CA1—showed strong diagnostic potential for PAH, with AUC values ≥ 0.7 in the training datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41221472", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Five hub genes (SLC4A1, AHSP, ALAS2, FECH, and CA1), exhibited strong diagnostic potential, with an area under the curve (AUC) ≥ 0.7 in training datasets (GSE38267, GSE22356)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Five hub genes—SLC4A1, AHSP, ALAS2, FECH, and CA1—showed strong diagnostic potential for PAH, with AUC values ≥ 0.7 in the training datasets.", "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:41221472"], "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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By utilizing RNA sequencing (RNA-seq) data from the GEO database, we conducted bi", "ng due to nonspecific symptoms. By utilizing RNA sequencing (RNA-seq) data from the GEO database, we con"], "order_basis": "paper_text_order:322", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["lmonary artery smooth muscle cells (hPASMCs) cultured in smooth muscle cell medium (No. 1101, ScienCe", "lmonary artery smooth muscle cells (hPASMCs) cultured in smooth muscle cell medium (No. 1101, Scie"], "order_basis": "paper_text_order:1489", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["% O2 and 5% CO2 for 24 h. The Analysis of RT‐qPCR for Hub Genes To further validate the expres", "nostic biomarkers for PAH. The results of RT‐qPCR for top five genes in hPASMC. The expression", "P, ALAS2, FECH, and CA1 was determined by RT‐qPCR (n = 4). hPASMCs, human pulmonary artery smo"], "order_basis": "paper_text_order:1975", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The R package “limma” was utilized to identify DEGs between PAH and normal control samples in the GSE38267 and GSE22356 datasets [14], applying a significance criterion of |Log2FC| > 1 and a p‐value < 0.05 [15]. Following this, the Robust Rank Aggregation (RRA) algorithm was employed to combine the ranking lists based on a probability model, and DEGs that were common to both datasets were chosen as candidate DEGs."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}