AUTHOR=Wang Xuming , He Bin , Deng Yisen , Liu Jingwen , Zhang Zhaohua , Sun Weiliang , Gao Yanxiang , Liu Xiaopeng , Zhen Yanan , Ye Zhidong , Liu Peng , Wen Jianyan
TITLE=Identification of a biomarker and immune infiltration in perivascular adipose tissue of abdominal aortic aneurysm
JOURNAL=Frontiers in Physiology
VOLUME=13
YEAR=2022
URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.977910
DOI=10.3389/fphys.2022.977910
ISSN=1664-042X
ABSTRACT=Objective: Abdominal aortic aneurysm (AAA) refers to unusual permanent dilation of the abdominal aorta, and gradual AAA expansion can lead to fatal rupture. However, we lack clear understanding of the pathogenesis of this disease. The effect of perivascular adipose tissue (PVAT) on vascular functional status has attracted increasing attention. Here, we try to identify the potential mechanisms linking AAA and PVAT.
Methods: We downloaded dataset GSE119717, including 30 dilated AAA PVAT samples and 30 non-dilated aorta PVAT samples from AAA cases, from Gene Expression Omnibus to identify differentially expressed genes (DEGs). We performed pathway enrichment analysis by Metascape, ClueGo and DAVID to annotate PVAT functional status according to the DEGs. A protein-protein interaction network, the support vector machine (SVM)-recursive feature elimination and the least absolute shrinkage and selection operator regression model were constructed to identify feature genes. Immune infiltration analysis was explored by CIBERSORT. And the correlation between feature gene and immune cells was also calculated. Finally, we used the angiotensin II (Ang II)-ApoE−/− mouse model of AAA to verify the effect of feature gene expression by confirming protein expression using immunohistochemistry and western blot.
Results: We identified 22 DEGs, including 21 upregulated genes and 1 downregulated gene. The DEGs were mainly enriched in neutrophil chemotaxis and IL-17 signaling pathway. FOS was identified as a good diagnostic feature gene (AUC = 0.964). Immune infiltration analysis showed a higher level of T cells follicular helper, activated NK cells, Monocytes, activated Mast cells in AAA group. And FOS was correlated with immune cells. Immunohistochemistry and western blot confirmed higher FOS expression in PVAT of the AAA mouse model compared to control group.
Conclusion: The differentially expressed genes and pathways identified in this study provide further understanding of how PVAT affects AAA development. FOS was identified as the diagnostic gene. There was an obvious difference in immune cells infiltration between normal and AAA groups.