Identification of neutrophil extracellular trap-related biomarkers in non-alcoholic fatty liver disease through machine learning and single-cell analysis.

ABSTRACT: Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and

SUBMITTER: Fang Z 

PROVIDER: S-EPMC11387488 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature