Key result
EGR1 and KLF4 expression levels accurately diagnosed abdominal aortic aneurysm, achieving a combined Area Under the Curve of 0.948 in the discovery cohort and 0.898 in the clinical validation cohort.
Why the study?
Pathological processes and molecular mechanisms of AAA formation and development are unclear, prompting exploration of the association between PVAT and AAA.
Observational (n=115)
No
Effect estimate: AUC 0.948
PVAT immune and FOS signatures may refine AAA biomarker panels; leaves open whether modulating PVAT alters progression.
Background Formation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA. Methods We analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index). Results A total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells. Conclusion EGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells.
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Guo et al. (2022) conducted an observational in Abdominal Aortic Aneurysm (n=115). EGR1 and KLF4 expression vs. Normal controls was evaluated on Diagnostic efficacy (Area Under the Curve) for AAA (AUC 0.948). EGR1 and KLF4 expression levels accurately diagnosed abdominal aortic aneurysm, achieving a combined Area Under the Curve of 0.948 in the discovery cohort and 0.898 in the clinical validation cohort.
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