Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning.

ABSTRACT:

Background and aims

Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).

Method

The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein-protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.

Results

Four datasets co

SUBMITTER: Ouyang G 

PROVIDER: S-EPMC10562635 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature