Identification of Important Genes of Keratoconus and Construction of the Diagnostic Model

OBJECTIVE: The aim of the study is to investigate the potential role of keratoconus (KC) in the diagnosis of keratoconus (KC). METHODS: GSE151631 and GSE77938 were downloaded from the comprehensive gene expression database (GEO). By using the random forest model (RF), support vector machine model (SVM), and generalized linear model (GLM), important immune-related genes were identified as biomarkers for KC diagnosis. RESULTS: Through the LASSO, RFE, and RF algorithms and comparing the three sets of DEGs, a total of 8 overlapping DEGs were obtained. We took 8 DEGs as the final optimal combination of DEGs: AREG, BBC3, DUSP2, map3k8, Smad7, CDKN1A, JUN, and LIF. CONCLUSION: Abnormal cell proliferation, apoptosis, and autophagy defects are related to KC, which may be the etiology and potential target of KC.