Background
This study aimed to identify and validate potential blood biomarkers for intracranial aneurysms (IAs) using bioinformatics analysis.
Methods
GSE54083 dataset was downloaded, then differently expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were used to identify the consistently differential expression genes from non-IAs to rupture IAs. We then calculated the areas under the receiver operating characteristic curve (AUC) of each gene to evaluate their diagnostic capability. Moreover, the XCell algorithm was used to integrate the expression data to score the relative abundance of the vascular microenvironment. Lastly, qRT-PCR and ELISA assays were performed to validate potential biomarkers using our clinical samples.
Results
Six hub genes (TNFRSF19, FBXO38, SLC26A10, C11orf24, P2RX6, and RORC) were identified by AUCs greater than 0.9 in our bioinformatics analysis. From non-IAs to RIAs, the abundances of B cell types were increased while T cell types were decreased. NK T cells had the most cell abundance with a significant elevating trend. The qRT-PCR assay revealed that the expression trend of TNFRSF19, FBXO38, and RORC were consistent with the bioinformatics analysis. Eventually, the ELISA assay revealed that TNFRSF19 (TROY) was significantly elevated in patients with UIAs and RIAs. What’s more, the plasma TROY was positively correlated with CRP (r = 0.46), D-dimer (r = 0.39), and number of Neutrophil and white blood cells.
Conclusions
TNFRSF19 (TROY) might play a key role in the development of IAs and could be a novel blood-based biomarker for diagnosing IAs and monitoring the progression of IAs.