Zhang Ruyi,Yang Fang,Guan Youtao,et al.Potential diagnostic markers for aortic valve calcification:A study based on bioinformatics and machine learning[J].Journal of Chongqing Medical University,2023,48(12):1493-1500.
Zhang Ruyi,Yang Fang,Guan Youtao,et al.Potential diagnostic markers for aortic valve calcification:A study based on bioinformatics and machine learning[J].Journal of Chongqing Medical University,2023,48(12):1493-1500. DOI: 10.13406/j.cnki.cyxb.003399.
Potential diagnostic markers for aortic valve calcification:A study based on bioinformatics and machine learning
To identify potential diagnostic markers for aortic valve calcification using machine learning algorithms from the three aspects of immune response,stem cell activity,and osteogenesis.
Methods
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R language was used for the homogenization,integration,and analysis of the data from GSE51472,GSE12644,and GSE55492 datasets in the GEO database to obtain differentially expressed genes. The gene sets associated with immune,stem cell,and osteogenesis were obtained from the Amigo database,which were intersected with the differentially expressed genes,respectively,to obtain the abnormally expressed genes associated with immune,stem cell,and osteogenesis in calcified valve tissue. Machine learning techniques were used to identify potential diagnostic biomarkers among the differentially expressed genes. In addition,Gene Set Enrichment Analysis(GSEA) was performed,and the diagnostic markers were validated using clinical specimens and cytology tests.
Results
2
A total of 102 differentially expressed genes were identified through the integration and analysis of the three datasets,among which there were 51 genes associated with immune response,1 gene associated with stem cells,and 2 genes associated with osteogenesis. The GSEA analysis showed that the genes associated with immune response,stem cells,and osteogenesis were all involved in immune regulatory pathways. The analysis based on multiple machine learning techniques showed that interleukin 7 receptor(IL7R) had the highest value in the diagnosis of calcific aortic valve disease (CAVD),but the results of bioinformatics analysis were not supported by clinical specimens. Cell experiments showed that IL7R could promote the proliferation of valvular interstitial cells and induce osteogenic calcification.
Conclusion
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IL7R may not be a peripheral blood marker for diagnosing CAVD,but it may play an important role in the progression of CAVD,and therefore,it is necessary to further investigate the role of IL7R in CAVD.
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references
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