Identification through machine learning of potential immune- related gene biomarkers associated with immune cell infiltration in myocardial infarction.

Autor: Dong H; Department of Cardiovascular Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Yan SB; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Li GS; Department of Cardiothoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Huang ZG; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Li DM; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Tang YL; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Le JQ; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Pan YF; Department of Pathology, Hospital of Guangxi Liugang Medical Co.LTD./Guangxi Liuzhou Dingshun Forensic Expert Institute, No.9, Queershan Rd, Liuzhou, Guangxi Zhuang Autonomous Region, 545002, People's Republic of China., Yang Z; Department of Gerontology, NO.923 Hospital of Chinese People's Liberation Army, No. 1 Tangcheng Rd, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Pan HB; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Chen G; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Li MJ; Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China. limingjie@stu.gxmu.edu.cn.
Jazyk: angličtina
Zdroj: BMC cardiovascular disorders [BMC Cardiovasc Disord] 2023 Mar 28; Vol. 23 (1), pp. 163. Date of Electronic Publication: 2023 Mar 28.
DOI: 10.1186/s12872-023-03196-w
Abstrakt: Background: To investigate the potential role of immune-related genes (IRGs) and immune cells in myocardial infarction (MI) and establish a nomogram model for diagnosing myocardial infarction.
Methods: Raw and processed gene expression profiling datasets were archived from the Gene Expression Omnibus (GEO) database. Differentially expressed immune-related genes (DIRGs), which were screened out by four machine learning algorithms-partial least squares (PLS), random forest model (RF), k-nearest neighbor (KNN), and support vector machine model (SVM) were used in the diagnosis of MI.
Results: The six key DIRGs (PTGER2, LGR6, IL17B, IL13RA1, CCL4, and ADM) were identified by the intersection of the minimal root mean square error (RMSE) of four machine learning algorithms, which were screened out to establish the nomogram model to predict the incidence of MI by using the rms package. The nomogram model exhibited the highest predictive accuracy and better potential clinical utility. The relative distribution of 22 types of immune cells was evaluated using cell type identification, which was done by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. The distribution of four types of immune cells, such as plasma cells, T cells follicular helper, Mast cells resting, and neutrophils, was significantly upregulated in MI, while five types of immune cell dispersion, T cells CD4 naive, macrophages M1, macrophages M2, dendritic cells resting, and mast cells activated in MI patients, were significantly downregulated in MI.
Conclusion: This study demonstrated that IRGs were correlated with MI, suggesting that immune cells may be potential therapeutic targets of immunotherapy in MI.
(© 2023. The Author(s).)
Databáze: MEDLINE
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