Validating candidate biomarkers for different stages of non-alcoholic fatty liver disease

Proteomic Analysis of Hepatic Fibrosis in Human Immunodeficiency Virus-Associated Nonalcoholic Fatty Liver Disease Demonstrates Up-regulation of Immune Response and Tissue Repair Pathways

BACKGROUND

Human immunodeficiency virus (HIV)-associated nonalcoholic fatty liver disease (NAFLD) is characterized by a high prevalence of hepatic fibrosis as a strong clinical predictor of all-cause and liver-specific mortality risk.

METHODS

We leveraged data from an earlier clinical trial to define the circulating proteomic signature of hepatic fibrosis in HIV-associated NAFLD. A total of 183 plasma proteins within 2 high-multiplex panels were quantified at baseline and at 12 months (Olink Cardiovascular III; Immuno-Oncology).

RESULTS

Twenty proteins were up-regulated at baseline among participants with fibrosis stages 2-3 versus 0-1. Proteins most differentially expressed included matrix metalloproteinase 2 (P < .001), insulin-like growth factor-binding protein 7 (P = .001), and collagen α1(I) chain (P = .001). Proteins were enriched within pathways including response to tumor necrosis factor and aminopeptidase activity. Key proteins correlated directly with visceral adiposity and glucose intolerance and inversely with CD4+ T-cell count. Within the placebo-treated arm, 11 proteins differentially increased among individuals with hepatic fibrosis progression over a 12-month period (P < .05).

CONCLUSIONS

Among individuals with HIV-associated NAFLD, hepatic fibrosis was associated with a distinct proteomic signature involving up-regulation of tissue repair and immune response pathways. These findings enhance our understanding of potential mechanisms and biomarkers of hepatic fibrosis in HIV.

Identification of the Non-Alcoholic Fatty Liver Disease Molecular Subtypes Associated With Clinical and Immunological Features via Bioinformatics Methods

Background

Non-alcoholic fatty liver disease (NAFLD) is a manifestation of metabolic syndrome in the liver with varying severity. Heterogeneity in terms of molecules and immune cell infiltration drives NAFLD from one stage to the next. However, a precise molecular classification of NAFLD is still lacking, and the effects of complex clinical phenotypes on the efficacy of drugs are usually ignored.

Methods

We introduced multiple omics data to differentiate NAFLD subtypes via consensus clustering, and a weighted gene co-expression network analysis was used to identify eight co-expression modules. Further, eigengenes of eight modules were analyzed with regard to Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, the infiltration rates of 22 immune cell types were calculated with CIBERSORT and the ESTIMATE algorithm.

Results

In total, 111 NAFLD patients from three independent GEO datasets were divided into four molecular subtypes, and the corresponding clinical features and immune cell infiltration traits were determined. Based on high gene expression correlations, four molecular subtypes were further divided into eight co-expression modules. We also demonstrated a significant correlation between gene modules and clinical phenotypes. Moreover, we integrated phenotypic, immunologic, and genetic data to assess the potential for progression of different molecular subtypes. Furthermore, the efficacy of drugs against various NAFLD molecular subtypes was discussed to aid in individualized therapy.

Conclusion

Overall, this study could provide new insights into the underlying pathogenesis of and drug targets for NAFLD.