Bioinformatics Analysis of Immune Cell Infiltration Patterns and Potential Diagnostic Markers in Atherosclerosis

Author:

Ji Haigang1,Yuan Ling1,Jiang Wenbo2,Jiang Yinke1,Jiang Mengke1,Sun Xuemei1,Chen Jing3

Affiliation:

1. Changzhou Hospital Affiliated to Nanjing University of Chinese Medicine

2. Suqian Hospital Affiliated to Nanjing University of Chinese Medicine

3. Tongde Hospital of Zhejiang Province

Abstract

Abstract Background This study aimed to investigate efficient diagnostic markers and molecular mechanisms of atherosclerosis and to analyze the role of immune infiltration through bioinformatics analysis. Results Expression profile datasets (GSE28829 and GSE43292) of patients with atherosclerosis and healthy controls were downloaded from the GEO database. Glutamine (GLN) metabolism-associated genes were obtained from the Molecular Signatures Database (MSigDB). The limma package in R was used to identify differentially expressed genes (DEGs). Significant modules were filtered using Weighted Gene Co-expression Network Analysis (WGCNA). MSigDB sets were subjected to Gene Set Enrichment Analysis and Gene Set Variation Analysis. The biological functions of DEGs were examined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. STRING and Cytoscape software were used to identify hub genes and functional modules through protein–protein interaction (PPI) network analysis. The xCell software was adopted to assess the composition patterns of immune and stromal cells. Correlation analyses were performed for key genes and immune cell subtypes. We identified 308 DEGs and GLN-associated genes. Functional enrichment analysis showed that these genes were strongly enriched in muscle contract, muscle tissue development, cutile fiber, mycobacterial, and actin binding. Enriched KEGG pathways comprised dilated cardiomyopathy, Hypergraphic cardiomyopathy, and the cAMP signaling pathway. In the PPI network analysis, 27 genes were identified as hub genes. The area under the curve (AUC) values of 27 biomarkers were relatively high, indicating high diagnostic values. The atherosclerosis group exhibited a markedly higher degree of infiltration than the control group. Conclusions This study identified 27 GLN-associated genes as potential biomarkers for the diagnosis of atherosclerosis. It provides a new perspective on immune responses that facilitates exploration of the molecular mechanisms of atherosclerosis.

Publisher

Research Square Platform LLC

Reference46 articles.

1. Smooth muscle α-actin missense variant promotes atherosclerosis through modulation of intracellular cholesterol in smooth muscle cells;Kaw K;Eur Heart J,2023

2. The changing landscape of atherosclerosis;Libby P;Nature,2021

3. Dietary recommendations for prevention of atherosclerosis;Riccardi G;Cardiovasc Res,2022

4. From Krebs to clinic: glutamine metabolism to cancer therapy;Altman BJ;Nat Rev Cancer,2016

5. Glucose feeds the TCA cycle via circulating lactate;Hui S;Nature,2017

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