{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T21:00:50Z","timestamp":1792443650831,"version":"4.5.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T00:00:00Z","timestamp":1663113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"Objective<\/jats:title>Abdominal aortic aneurysm (AAA) is a lethal peripheral vascular disease. Inflammatory immune cell infiltration is a central part of the pathogenesis of AAA. It\u2019s critical to investigate the molecular mechanisms underlying immune infiltration in early-stage AAA and look for a viable AAA marker.<\/jats:p><\/jats:sec>Methods<\/jats:title>In this study, we download several mRNA expression datasets and scRNA-seq datasets of the early-stage AAA models from the NCBI-GEO database. mMCP-counter and CIBERSORT<\/jats:italic> were used to assess immune infiltration in early-stage experimental AAA. The scRNA-seq datasets were then utilized to analyze AAA-related gene modules of monocytes\/macrophages infiltrated into the early-stage AAA by Weighted Correlation Network analysis (WGCNA). After that, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis for the module genes was performed by ClusterProfiler. The STRING database was used to create the protein-protein interaction (PPI) network. The Differentially Expressed Genes (DEGs) of the monocytes\/macrophages were explored by Limma-Voom and the key gene set were identified. Then We further examined the expression of key genes in the human AAA dataset and built a logistic diagnostic model for distinguishing AAA patients and healthy people. Finally, real-time quantitative polymerase chain reaction (RT-qPCR) and Enzyme Linked Immunosorbent Assay (ELISA) were performed to validate the gene expression and serum protein level between the AAA and healthy donor samples in our cohort.<\/jats:p><\/jats:sec>Results<\/jats:title>Monocytes\/macrophages were identified as the major immune cells infiltrating the early-stage experimental AAA. After pseudocell construction of monocytes\/macrophages from scRNA-seq datasets and WGCNA analysis, four gene modules from two datasets were identified positively related to AAA, mainly enriched in Myeloid Leukocyte Migration, Collagen-Containing Extracellular matrix, and PI3K-Akt signaling pathway by functional enrichment analysis. Thbs1<\/jats:italic>, Clec4e<\/jats:italic>, and Il1b<\/jats:italic> were identified as key genes among the hub genes in the modules, and the high expression of Clec4e<\/jats:italic>, Il1b<\/jats:italic>, and Thbs1<\/jats:italic> was confirmed in the other datasets. Then, in human AAA transcriptome datasets, the high expression of CLEC4E<\/jats:italic>, IL1B<\/jats:italic> was confirmed and a logistic regression model based on the two gene expressions was built, with an AUC of 0.9 in the train set and 0.79 in the validated set. Additionally, in our cohort, we confirmed the increased serum protein levels of IL-1\u03b2 and CLEC4E in AAA patients as well as the increased expression of these two genes in AAA aorta samples.<\/jats:p><\/jats:sec>Conclusion<\/jats:title>This study identified monocytes\/macrophages as the main immune cells infiltrated into the early-stage AAA and constructed a logistic regression model based on monocytes\/macrophages related gene set. This study could aid in the early diagnostic of AAA.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fcvm.2022.950961","type":"journal-article","created":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T05:13:02Z","timestamp":1663132382000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Identification of key monocytes\/macrophages related gene set of the early-stage abdominal aortic aneurysm by integrated bioinformatics analysis and experimental 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