Identification potential epigenetic biomarkers of a human immunodeficiency virus/tuberculosis co-infection based on weighted gene co-expression network analysis.

Tuberculosis (TB) is one of the most common opportunistic infections and a leading cause of death in patients infected with human immunodeficiency virus (HIV). However, conventional diagnostic tools have several limitations. The aim of this study was to screen key DNA methylated cytosine-phosphate-guanine dinucleotide (CpG) islands (CGIs) to identify potential diagnosis biomarkers in HIV mono-infected patients and HIV/TB co-infected patients based on a network analysis. The GSE50835 DNA methylation microarray data were downloaded from the Gene Expression Omnibus (GEO) database. Differentially methylated CpG islands analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) logistic regression were performed in 19 HIV mono-infected patients and 20 HIV/TB co-infected patients. In total, 1950 differentially methylated CpG islands were identified, and weighted co-methylation network construction and module preservation revealed one network module that can distinguish the HIV/TB co-infected patients from the HIV mono-infected patients. Based on the LASSO logistic regression, an eight-methylated CpG island diagnosis model was established that can accurately distinguish HIV/TB co-infected patients from HIV mono-infected patients with a sensitivity of 87.2%, a specificity of 88.7%, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.948. Alteration in the eight-DNA methylated CpG sites might be involved in the pathology of an HIV/TB co-infection and could be used as potential diagnosis biomarkers in HIV/TB co-infected patients.