Comprehensive profiling of candidate biomarkers and immune infiltration landscape in metabolic dysfunction-associated steatohepatitis.

BACKGROUND

The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing, with an incompletely understood pathophysiology involving multiple factors, particularly innate and adaptive immune responses. Given the limited pharmacological treatments available, identification of novel immune metabolic targets is urgently needed. In this study, we aimed to identify hub immune-related genes and potential biomarkers with diagnostic and predictive value for MASH patients.

METHODS

The GSE164760 dataset from the Gene Expression Omnibus was utilized for analysis, and the R package was used to identify differentially expressed genes. Immune-related differentially expressed genes (IR-DEGs) were identified by comparing the overlap of differentially expressed genes with well-known immune-related genes. Furthermore, the biological processes and molecular functions of the IR-DEGs were analyzed. To characterize the hub IR-DEGs, we employed a protein-protein interaction network. The diagnostic and predictive values of these hub IR-DEGs in MASH were confirmed using GSE48452 and GSE63067 datasets. Finally, the significance of the hub IR-DEGs was validated using a mouse model of MASH.

RESULTS

A total of 91 IR-DEGs were identified, with 61 upregulated and 30 downregulated genes. Based on the protein-protein interaction network, FN1, RHOA, FOS, PDGFRα, CCND1, PIK3R1, CSF1, and FGF3 were identified as the hub IR-DEGs. Moreover, we found that these hub genes are closely correlated with immune cells. Notably, the validation across two independent cohorts as well as a murine MASH model confirmed their high diagnostic potential.

CONCLUSION

The hub IR-DEGs, such as FN1, RHOA, FOS, PDGFRα, CCND1, PIK3R1, CSF1, and FGF3, may enhance the diagnosis and prognosis of MASH by modulating immune homeostasis.