Integrated Transcriptomic and Single-Cell RNA Sequencing Analyses Identify Shared Inflammation-Related Candidate Genes in Psoriasis and Acute Myocardial Infarction

Psoriasis and acute myocardial infarction (AMI) are both closely associated with immune-inflammatory dysregulation; however, the shared molecular features of psoriasis-AMI comorbidity remain incompletely characterized. To address this gap, this study aimed to identify novel shared inflammation-related candidate genes between psoriasis and AMI and to characterize their cellular expression patterns using public transcriptomic and single-cell RNA sequencing data. The main finding was the identification of shared inflammation-related candidate genes and their cell-type-specific expression patterns in psoriasis-AMI comorbidity.

Transcriptomic datasets related to psoriasis and AMI were obtained from the Gene Expression Omnibus (GEO) database. GSE30999 and GSE66360 were used as discovery cohorts. Differentially expressed genes (DEGs) were identified using limma with adjusted P value < 0.05 and |log2FC| ≥ 1.0. Shared DEGs between the two diseases were extracted. GO and KEGG enrichment analyses were performed, and a PPI network was constructed using STRING and Cytoscape. Consensus hub genes were selected using six cytoHubba algorithms. Candidate gene expression differences were evaluated in the external validation datasets GSE201827 and GSE59867, and ROC curve analysis assessed their discriminatory performance. Finally, scRNA-seq datasets GSE220116 and GSE269269 were analyzed to characterize the cell-type distribution of the final candidate genes.

A total of 57 shared DEGs were identified in the psoriasis and AMI discovery cohorts, including 51 commonly upregulated and 6 commonly downregulated genes. Enrichment analysis showed that these genes were mainly involved in processes related to cellular response to lipopolysaccharide, chemotaxis, cytokine activity and chemokine activity, and were significantly enriched in the IL-17, NF-κB, TNF and chemokine signaling pathways, as well as lipid and atherosclerosis-related pathways. PPI network and cytoHubba analyses identified 9 consensus hub genes. External validation and ROC analyses showed that S100A9, S100A12 and CXCL1 were significantly upregulated in both psoriasis and AMI validation datasets and showed moderate discriminatory performance between groups. Single-cell analysis showed that S100A9 and S100A12 exhibited prominent myeloid inflammation-related expression profiles in psoriatic lesions and AMI peripheral immune cells, whereas CXCL1 expression was relatively restricted, suggesting that it may primarily reflect chemokine-mediated inflammatory cell recruitment.

This study identified S100A9, S100A12 and CXCL1 as candidate genes potentially associated with shared inflammatory features of psoriasis-AMI comorbidity. These findings suggest that myeloid cell activation and chemokine-mediated recruitment of inflammatory cells may contribute to the molecular link between the two diseases; however, further clinical and experimental validation is required.