Identification of immune subtypes associated with neutrophils in tuberculosis infection based on weighted gene co-expression network analysis

Abstract

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is a major global health concern. Neutrophils play a significant role in TB infection and patient outcomes. This study aimed to identify gene modules associated with neutrophil infiltration in TB samples using WGCNA. Gene ontology and enrichment analyses were performed, and a random forest model was constructed to identify differentially expressed genes. K-means clustering was used to classify samples into subtypes, and immune-related scores, PD-L1 expression, HLA expression, and gene enrichment analysis were evaluated. The blue module showed significant correlation with neutrophils and enrichment in immune-related processes. The model exhibited good classification performance, and subtype 1 demonstrated higher immune-related scores, PD-L1 expression, HLA class I molecule expression, and immune-related pathway enrichment. These findings enhance our understanding of TB pathogenesis and provide potential targets for diagnosis and treatment strategies.