Background: Dilated cardiomyopathy (DCM) is characterized by left ventricular dilatation and systolic dysfunction. The pathogenesis and etiologies of DCM remain elusive. This study aims to identify the key genes to construct a genetic diagnosis model of DCM.
Methods: A total of 257 DCM samples from five independent cohorts were enrolled. The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify the key modules associated with DCM. The latent mechanisms and protein-protein interaction network underlying the key modules were further revealed. Subsequently, we developed and validated a LASSO diagnostic model in five independent cohorts.
Results: Two key modules were identified using WGCNA. Novel mechanisms related to the extracellular, mitochondrial matrix or IL-17 signaling pathway were pinpointed, which might significantly influence DCM. Besides, 23 key genes were screened out by combining WGCNA and differential expression analysis. Based on the key genes, a genetic diagnosis model was constructed and validated using five cohorts with excellent AUCs (0.975, 0.954, 0.722, 0.850, 0.988). Finally, significant differences in immune infiltration were observed between the two groups divided by the diagnostic model.
Conclusion: Our study revealed several novel pathways and key genes to provide potential targets and biomarkers for DCM treatment. A key genes' diagnosis model was built to offer a new tool for diagnosing DCM.
Keywords: diagnostic model; dilated cardiomyopathy; functional analysis; immune infiltration; machine learning.
Copyright © 2022 Zheng, Liu, Yang, Weng, Xu, Guo, Xing, Liu, Wang, Dang and Qiu.