Evaluation the role of cuproptosis-related genes in the pathogenesis, diagnosis and molecular subtypes identification of atherosclerosis

Mengxi Wang; Liying Cheng; Qian Xiang; Ziwei Gao; Yuhan Ding; Haitao Xie; Xiaohu Chen; Peng Yu; Le Shen

doi:10.1016/j.heliyon.2023.e21158

Evaluation the role of cuproptosis-related genes in the pathogenesis, diagnosis and molecular subtypes identification of atherosclerosis

Heliyon. 2023 Oct 18;9(10):e21158. doi: 10.1016/j.heliyon.2023.e21158. eCollection 2023 Oct.

Authors

Mengxi Wang^{1

2

3}, Liying Cheng⁴, Qian Xiang^{1

2

3}, Ziwei Gao^{1

2

3}, Yuhan Ding^{1

2

3}, Haitao Xie^{1

2

3}, Xiaohu Chen^{1

2}, Peng Yu^{1

2}, Le Shen^{1

2}

Affiliations

¹ Department of Cardiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
² Department of Cardiology, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China.
³ First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing 210023, China.
⁴ State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.

Abstract

Background: At present, the pathogenesis of atherosclerosis has not been fully elucidated, and the diagnosis and treatment face great challenges. Cuproptosis is a novel cell death pattern that might be involved in the development of atherosclerosis. However, no research has reported the correlation between cuproptosis and atherosclerosis.

Methods: The differential cuproptosis-related genes (CRGs) between atherosclerosis group and control group (A-CRGs) were discovered via differential expression analysis. The correlation analysis, PPI network analysis, GO, KEGG and GSEA analysis were performed to investigate the function of A-CRGs. The differences of biological function between atherosclerosis group and control group were investigated via immune infiltration analysis and GSVA. The LASSO regression, nomogram and machine learning models were constructed to predict atherosclerosis risk. The atherosclerosis molecular subtypes clusters were discovered via unsupervised cluster analysis. Subsequently, we used the above research methods to analyze the differential CRGs between clusters (M-CRGs) and evaluate the molecular subtypes identification performance of M-CRGs. Finally, we verified the diagnostic value for atherosclerosis and role in cuproptosis of these CRGs through the validation set and in vitro experiments.

Results: Five A-CRGs were identified and they were mainly related to the biological function of copper ion metabolism and immune inflammatory response. The diagnostic models and nomogram of atherosclerosis based on 5 A-CRGs indicated that these genes had well diagnostic value. A total of two molecular subtypes clusters were obtained in the atherosclerosis group. There were many differences in biological functions between these two molecular subtypes clusters, such as mitochondrial outer membrane permeabilization and primary immunodeficiency. In addition, 3 M-CRGs were identified in the 2 clusters. Machine learning models and nomogram constructed based on M-CRGs showed that these genes had well molecular subtypes identification efficacy. In the end, the results of in vitro experiment and validation set confirmed the diagnostic value for atherosclerosis and role in cuproptosis of these genes.

Conclusion: The cuproptosis may be a potential pathogenesis of atherosclerosis and CRGs may be promising markers for the diagnosis and molecular subtypes identification of atherosclerosis.

Keywords: Atherosclerosis; Cuproptosis; Diagnosis; Molecular subtypes; Pathogenesis.