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In Oxidative medicine and cellular longevity

Calcific aortic valve stenosis (CAVS) is the most common heart valve disorder among humans. To date, no effective method has been identified to prevent this disease. Herein, we aimed to identify novel diagnostic and mitochondria-related biomarkers of CAVS, based on two machine learning algorithms. We further explored their association with infiltrating immune cells and studied their potential function in CAVS. The GSE12644, GSE51472, and GSE83453 expression profiles were downloaded from the Gene Expression Omnibus (GEO) repository. The GSE12644 and GSE51472 datasets were integrated to identify differentially expressed genes (DEGs). GSE12644 contains 10 normal and 10 CAVS samples, whereas GSE51472 contains 5 normal and 10 CAVS samples. GO and KEGG assays of DEGs were conducted, and the correlation between matrix metalloproteinase 9 (MMP9) expression and immune cell infiltration was explored, using CIBERSORT. The LASSO regression model and SVM-RFE analysis were used to identify diagnostic genes. The expression of MMP9 in CAVS and non-CAVS samples was measured using RT-PCR, western blotting and immunohistochemistry. A series of functional experiments were performed to explore the potential role of MMP9 in mitochondrial metabolism and oxidative stress during CAVS progression. Twenty-two DEGs were identified, of which six genes (SCG2, PPBP, TREM1, CCL19, WIF1, and MMP9) were ultimately distinguished as diagnostic genes in CAVS. Of these, MMP9 was indicated as a mitochondria-related gene, the expression and diagnostic value of which were further confirmed in the GSE83453 dataset. Correlation analysis revealed a positive correlation between MMP9 and infiltrating immune cells. In our cohort, MMP9 expression was distinctly increased in CAVS samples, and its inhibition attenuated the calcification of valve interstitial cells (VICs) by suppressing mitochondrial damage and oxidative stress. Taken together, our findings suggest MMP9 as a novel mitochondrial dysfunction biomarker and therapeutic target for CAVS.

Liu Cong, Liu Ruixue, Cao Zhezhe, Guo Qiao, Huang He, Liu Liangming, Xiao Yingbin, Duan Chenyang, Ma Ruiyan