Abstract
Gut microbiome dysbiosis has been known to be associated with all stages of non-alcoholic fatty liver disease (NAFLD), but questions remain about microbial profiles in progression and homogeneity across NAFLD stages. We performed a meta-analysis of three publicly shotgun datasets and built predictive models to determine diagnostic capacity. Here, we found consistently microbiome shifts across NAFLD stages, of which co-occurrence patterns and core sets of new biomarkers significantly correlated with NAFLD progression were identified. Machine learning models that are able to distinguish patients with any NAFLD stage from healthy controls remained predictive when applied to patients with other NAFLD stages, suggesting the homogeneity across stages once again. Focusing on species and metabolic pathways specifically associated with progressive stages, we found that increased toxic metabolites and decreased protection of butyrate and choline contributed to advanced NAFLD. We further built models discriminating one stage from the others with an average of 0.86 of area under the curve. In conclusion, this meta-analysis firmly establishes generalizable microbiome dysbiosis and predictive taxonomic and functional signatures as a basis for future diagnostics across NAFLD stages.
Highlights
Non-alcoholic fatty liver disease (NAFLD) is defined as the pathological accumulation of lipid droplets in >5% of hepatocytes (Sberna et al, 2018), developing from simple non-alcoholic fatty liver (NAFL), progressing toward non-alcoholic steatohepatitis (NASH), which can present with liver fibrosis, the main prognostic lesion for disease progression, and leading to cirrhosis or hepatocellular carcinoma (Fingas et al, 2016)
Our study aims to find a panel of gut microbiomederived biomarkers generally associated with nonalcoholic fatty liver disease (NAFLD) across stages or linking NAFLD progression, which help to develop a non-invasive diagnosis of NAFLD
We contrasted the effect of disease-associated heterogeneity on microbiome composition with potential confounders [patient age, body mass index (BMI), and sex], and this analysis revealed BMI to have an impact on species composition as predominant as disease (Supplementary Figure 1A), since patients with NAFLD often present with obesity
Summary
Non-alcoholic fatty liver disease (NAFLD) is defined as the pathological accumulation of lipid droplets in >5% of hepatocytes (Sberna et al, 2018), developing from simple non-alcoholic fatty liver (NAFL), progressing toward non-alcoholic steatohepatitis (NASH), which can present with liver fibrosis, the main prognostic lesion for disease progression, and leading to cirrhosis or hepatocellular carcinoma (Fingas et al, 2016). We collected currently available NAFLD shotgun metagenomic datasets (Boursier et al, 2016; Loomba et al, 2017; Shen et al, 2017), re-classified 107 patients with NAFL, NASH, fibrosis, or cirrhosis and 120 healthy controls according to clinical diagnosis, performed an integrated analysis combining all datasets, and assessed prediction accuracies of the gut microbiome for the detection of the different stages in NAFLD progression. Our study aims to find a panel of gut microbiomederived biomarkers generally associated with NAFLD across stages or linking NAFLD progression, which help to develop a non-invasive diagnosis of NAFLD
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