Targeted metabolomics reveals bioactive inflammatory mediators from gut into blood circulation in children with NAFLD

Figures

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  Fig. 1. Gut metabolic alterations in NAFLD. Chemical class metabolite sets plots (A) shown the chemical class metabolite of metabolites. B OPLS-DA score plots for differential metabolites in fecal samples. X axis and Y axis represent contributions of persons to the first two principal components (PC1 and PC2). C Cross-validation plot with a permutation test repeated 200 times. The intercepts of R2 and Q2 suggest that the OPLS-DA model is not overfitting. D Volcano plots shown the results of pairwise comparisons of metabolites in each case sample’s group relative to controls. The abscissa represents the variation of variation multiple of metabolites in different groups (log2 Fold Change), and the ordinate represents the significance level (−log10 p-value). The vertical dashed lines indicate the threshold for the abundance difference. The horizontal dashed line indicates the p = 0.05 threshold. Each point in the graph represents metabolites, the up-regulated metabolite red dot, the down regulated metabolite green dot. Between-group comparisons were performed using empirical Bayes hierarchical model and Kruskal-Wallis rank sum test. OPLS-DA Orthogonal Partial Least Squares Discrimination…

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  Fig. 2. Plasma metabolic alterations in NAFLD. Chemical class metabolite sets plots (A) shown the chemical class metabolite of metabolites. B OPLS-DA score plots for differential metabolites in Plasma samples. X axis and Y axis represent contributions of persons to the first two principal components (PC1 and PC2). C Cross-validation plot with a permutation test repeated 200 times. The intercepts of R2 and Q2 suggest that the OPLS-DA model is not overfitting. D Volcano plots shown the results of pairwise comparisons of metabolites in each case sample’s group relative to controls. The abscissa represents the variation of variation multiple of metabolites in different groups (log2 Fold Change), and the ordinate represents the significance level (−log10 p-value). The vertical dashed lines indicate the threshold for the abundance difference. The horizontal dashed line indicates the p = 0.05 threshold. Each point in the graph represents metabolites, the up-regulated metabolite red dot, the down regulated metabolite green dot. Between-group comparisons were performed using empirical Bayes hierarchical model and Kruskal-Wallis rank sum test. OPLS-DA Orthogonal Partial Least Squares…

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  Fig. 3. Overview of the key gut metabolic pathways in the pathogenesis of NAFLD. Pathway enrichment plots of fecal (A) and plasma (B) shown the pathway enrichment analysis by KEGG for metabolites. The pathway enrichment analysis result takes KEGG pathway as the unit, and the hypergeometric test is applied to find the pathway that is enriched in the differential metabolites against the background of all identified metabolites. Pathway enrichment analysis can determine the most important metabolic pathways and signal transduction pathways involved in the differential metabolites. An overview plot shown the key metabolic pathways in the pathogenesis of NAFLD (C). Boxplots show levels of these metabolites in the plasma samples at different stages. AAs amino acids, PCs Phosphatidylcholines, BCAAs branched-chain amino acids, ChoE cholesterol esters, CoA coenzyme A, G3P glyceraldehyde 3-phosphate, GNG gluconeogenesis, CKs Inflammatory cytokines, ROS reactive oxygen species, SFA saturated fatty acid, TCA tricarboxylic acid. NAFL nonalcoholic fatty liver, NASH non-alcoholic steatohepatitis.

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  Fig. 4. Metabolites discriminates disease severity and association of mediators with markers of inflammation, glycolipid metabolism and liver function. A heatmap of plasma (A) shown the correlation between selected gut metabolites with glycolipid metabolism, liver function and inflammatory factors indices. Red color represents positive correlation, blue color represents negative correlation. Bar chart (B) show the qRT-PCR of differentially relative expressed mRNAs of liver function and inflammation produced by THLE-3 under different treatments, C control group, NAFL nonalcoholic fatty liver, NASH non-alcoholic steatohepatitis. p < 0.05 was considered statistically significant. *p < 0.05; **p < 0.01.

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  Fig. 5. Metabolites docks to the ligand-binding domain of inflammatory receptor. The superposition of these metabolites bound to the ligand-binding domain pocket of inflammatory receptor (A). Two-dimensional interaction map of inflammatory receptor with metabolites (B). Hypothesis map of inflammatory mechanism pathway is shown in (C).

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  Fig. 6. Flow chart showing the methods used for metabolomics analysis and bioinformatics function prediction. Patient recruitment and inclusion and exclusion criteria. Various clinical samples were obtained from NAFLD patients and controls. Integrative analysis for potential harmful and beneficial gut metabolites. Targeted metabolomics (LC-MS/MS) offers a plethora of information on metabolites. NAFL, nonalcoholic fatty liver, NASH non-alcoholic steatohepatitis, LC-MS/MS liquid chromatography coupled to tandem mass spectrometry, RF random forest.