Bioinformatic exploration of the immune related molecular mechanism underlying pulmonary arterial hypertension

ABSTRACT

This study aimed to explore the molecular mechanisms related to immune and hub genes related to pulmonary arterial hypertension (PAH). The differentially expressed genes (DEGs) of GSE15197 were identified as filters with adjusted P value <0.05, and |Log2 fold change|> 1. Biofunctional and pathway enrichment annotation of DEGs indicated that immunity and inflammation may play an important role in the molecular mechanism of PAH. The CIBERSORT algorithm further analyzed the immune cell infiltration characteristics of the PAH and control samples. Subsequently, 16 hub genes were identified from DEGs using the least absolute shrinkage and selection operator (LASSO) algorithm. An immune related gene CX3CR1 was further selected from the intersection results of the 16 hub genes and the top 20 genes with the most adjacent nodes in the protein-protein interaction (PPI) network. GSE113439, GSE48149, and GSE33463 datasets were used to validate and proved CX3CR1 with a remarkable score of AUC to distinguish PAH samples caused by various reasons from the control group.

Graphical Abstract

KEYWORDS:

• Biomarker
• Pulmonary arterial hypertension
• CIBERSORT
• Immune and inflammation

Highlights:

1. Inflammation and immune response play important roles in the pathogenesis of pulmonary arterial hypertension.

2. CX3CR1 is an important regulatory target and potential biomarker in pulmonary arterial hypertension.

3. Immune related targeted drugs may be effective in the treatment of pulmonary arterial hypertension.

Acknowledgements

We would like to thank the Gene Expression Omnibus (GEO) database for the precious data used for free in scientific research. The patients involved in the database have obtained ethical approval. Our study is based on open source data, so there are no ethical issues and other conflicts of interest.

Disclosure statement

The authors declared that they have no conflicts of interests to this work. We declare that we do not have any commercial or associative interests that represents a conflict of interests in connection with the work submitted.

Notes on contributors

Ruina Huang and Xifeng Zheng were involved in the conception and design of the study. Ruina Huang was responsible for article writing. Xifeng Zheng was responsible for visualization and scientific supervision. Junxian Wang provided effective scientific suggestions for this study. All authors reviewed and approved the final manuscript.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the Gene Expression Omnibus (GEO) database.

Supplementary material

Supplemental data for this article can be accessed here.