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Targeted plasma metabolomics in pediatric NAFLD patients

ABSTRACT: Several adult omics studies have been conducted to understand the pathophysiology of nonalcoholic fatty liver disease (NAFLD). However, the histological features of children are different from those of adults, and the onset and progression of pediatric NAFLD are not fully understood. In this study, we aimed to evaluate the metabolome profile and metabolic pathway changes associated with pediatric NAFLD to elucidate its pathophysiology. We analyzed the metabolic profiles of healthy control, lean NAFLD, overweight control and overweight NAFLD groups of children and adolescent participants (n = 165) by assessing plasma samples, and identified 18 NAFLD-specific metabolic features and metabolic changes in lipid, glutathione-related amino acid, and branched-chain amino acid metabolism by comparing control and NAFLD group in pediatric population with overweight. Metabolome changes in the plasma of pediatric patients with NAFLD are associated with the pathophysiology of the disease and can be utilized as a less-invasive approach to diagnose the disease.

ORGANISM(S): Human Homo Sapiens

TISSUE(S): Blood

DISEASE(S): Fatty Liver Disease

SUBMITTER: Woori Chae

PROVIDER: ST002269 | MetabolomicsWorkbench | Sun Aug 07 00:00:00 BST 2022

REPOSITORIES: MetabolomicsWorkbench

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Project description:Background and aims: Youth populations with overweight/obesity (OW/OB) exhibit heterogeneity in cardiometabolic health phenotypes (e.g. fasting glucose, serum triglycerides, etc.). The underling mechanisms for those differences are still unclear. This study aimed to analyze the whole blood transcriptome profile (RNA-seq) of children with metabolic healthy overweight/obesity (MHO) and metabolic unhealthy overweight/obesity (MUO) phenotypes. Methods: 27 children with OW/OB (10.14 ± 1.3 years, 59% boys) from the ActiveBrains project were included. MHO was defined as having none of the following criteria for metabolic syndrome: elevated fasting glucose, high serum triglycerides, low high-density lipoprotein cholesterol, and high systolic or diastolic blood pressure, while MUO was defined as presenting one or more of these criteria. Inflammatory markers interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), epidermal growth factor (EGF) and, vascular endothelial growth factor A (VEGF) were additionally determined. Total-blood RNA was analyzed by 5’-end RNA sequencing. Two different bioinformatics approaches were performed: 1) Differential gene expression analyses using Limma R/Bioconductor software package (analyses adjusted by sex and maturational status) and 2) weighted gene coexpression network analyses (WGCNA). Results: Children with MHO had lower values of pro-inflammatory cytokines TNF-α and IL-6 compared to MUO (p < 0.05). 40 genes were differentially expressed (FDR < 0.05) in children with MHO compared to MUO. WGCNA analysis identified 23 gene coexpression modules (i.e. clusters of genes) with low preservation (Zsummary < 2) in children with MHO compared to MUO. Differential and WGCNA gene expression patterns identified 32 genes linked to metabolism, mitochondrial and immune functions. Conclusions: Whole blood transcriptome analysis revealed a distinct pattern of gene expression in children with MHO compared to MUO children. The identified gene expression patterns related to metabolism, mitochondrial and immune functions can promote a better understanding of cardiovascular disease prognosis in individuals with MHO.

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Targeted plasma metabolomics in pediatric NAFLD patients

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