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ORIGINAL RESEARCH ARTICLE

Bioinformatics analysis of the GEO database for the identification of novel biomarkers and potential targeted drugs for pulmonary hypertension

Zhen-Dong Lu1 ,  Zhi-Liang Jiang2 ,  Wahab Hussain2 ,  Xin-Ying Ji2,3* ,  Umair Ali Khan Saddozai4*
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1 Department of Medical Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
2 Henan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng, Henan, China
3 Henan International Joint Laboratory for Nuclear Protein Regulation, The First Affiliated Hospital of Henan University, Kaifeng, Henan, China
4 Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China
GPD, 025080018 https://doi.org/10.36922/GPD025080018
Received: 23 February 2025 | Revised: 4 August 2025 | Accepted: 11 August 2025 | Published online: 29 August 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Pulmonary arterial hypertension (PAH) is a progressive and life-threatening cardiopulmonary disorder. This study integrated two PAH datasets (GSE117261 and GSE113439) from the Gene Expression Omnibus database to screen novel PAH biomarkers using bioinformatics methods and explore immune cell infiltration and potential therapeutic drugs. After batch effect correction, 311 differentially expressed genes (DEGs), comprising 182 upregulated and 129 downregulated genes, were identified using the Linear Models for Microarray Data analysis. Weighted gene co-expression network analysis revealed 11 significant modules, and intersecting these with DEGs yielded 24 module DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated enrichment in extracellular matrix organization, exosome-related functions, and inflammation-related pathways, including the positive regulation of inflammatory response and acute-phase response. A protein-protein interaction network analysis identified 10 hub genes: Upregulated periostin, osteoblast-specific factor (POSTN), OGN, asporin, and downregulated S100 calcium-binding protein A12, LCN2, SPP1, S100 calcium-binding protein A9, CD163, S100A8, and AQP9. Immune infiltration analysis (CIBERSORT, dataset GSE169471) revealed markedly altered levels of monocytes, dendritic cells, neutrophils, resting cluster of differentiation 4-positive memory T cells, and macrophages. Single-cell RNA sequencing analysis further confirmed hub gene expression. Notably, macrophage-associated genes (SPP1, S100A8/A9/A12, CD163, POSTN, AQP9, and LCN2) were implicated in vascular inflammation, endothelial dysfunction, and fibrosis, underscoring their role in immune-mediated vascular remodeling in PAH. Finally, drug prediction using the Comparative Toxicogenomic Database identified retinol, arsenic trioxide, and active vitamin D as potential therapeutics with significant regulatory effects on hub genes. This integrated bioinformatics analysis reveals key genes, pathways, and immune cell alterations in PAH, emphasizing macrophage-associated mechanisms in vascular remodeling and immune dysregulation. The findings provide potential biomarkers and therapeutic targets for improved PAH management.

Keywords
Pulmonary arterial hypertension
Immune infiltration
Single-cell RNA sequencing
Weighted gene co-expression network analysis
Funding
The study was funded by the Cultivation Project for Innovation Team in Teachers’ Teaching Proficiency by Zhengzhou Health College (No. 2024jxcxtd01).
Conflict of interest
Xin-Ying Ji is an Associate Editor and Umair Ali Khan Saddozai is an Editorial Board Member of this journal, but were not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. Separately, other authors declared that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
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