Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning.

ABSTRACT:

Background

NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial.

Methods

We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes.

Results

We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell

SUBMITTER: Li R 

PROVIDER: S-EPMC10781485 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature