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Metabolism of human liver on a genome scale in non-alcoholic fatty liver disease
Background and Aims : Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. By using patient-matched liver transcriptomics and serum metabolomics data from the EPoS European NAFLD Registry cohort, we conducted genome-scale metabolic mo...
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Published in: | Journal of hepatology 2020-08, Vol.73 (Suppl. 1), p.S671-S672 |
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Main Authors: | , , , , , , , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Background and Aims : Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. By using patient-matched liver transcriptomics and serum metabolomics data from the EPoS European NAFLD Registry cohort, we conducted genome-scale metabolic modeling (GSMM) to dissect hepatic metabolism across the full spectrum of NAFLD, from steatosis (NAFL) to NASH-cirrhosis.
Method : We compared the genome-scale metabolic networks across different stages of NAFLD together with healthy controls (HC, n = 10), with the patients divided into three groups: steatosis (n = 60), NASH (n = 139; F0: n = 4, F1 n = 28, F2: n = 53, F3: n = 54) and cirrhosis (n = 14). Based on transcriptomics data obtained from the liver biopsy of the patients enrolled in the European NAFLD Registry, genome-scale metabolic models of the liver were developed and contextualized for these conditions. GSMM, as a scaffold, connects metabolic genes (i.e., enzymes) and metabolic pathways. Moreover, genome-scale networks can be constrained with multi-‘omics’ datasets, and thus connect an organism’s genotype to phenotype.
Results : GSMM revealed that similar metabolic functions are perturbed in NAFL and NASH, while additional metabolic processes were regulated in advanced fibrosis/cirrhosis. The primary liver processes such as glycerophospholipid metabolism, chondroitin/heparan sulfate, bile acid and fatty acid biosynthesis and oxidation (carnitine shuttle in mitochondria) were affected. Lipid precursors for VLDL particles were upregulated in NAFL. Integrative analysis of transcriptomics and serum metabolomics data also revealed that several microbial pathways are up-regulated in NAFLD and may contribute to pathogenesis.
Conclusion : A GSMM approach has identified common and specific liver metabolic pathways across different stages of NAFLD progression. Data were cross-validated by serum metabolomics, where in addition analysis also revealed that specific microbially-produced metabolites are elevated in NAFLD as compared to controls. These results provide important insights into the changes in hepatic metabolism occurring during NAFLD/NASH pathogenesis. |
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ISSN: | 0168-8278 1600-0641 |
DOI: | 10.1016/S0168-8278(20)31805-5 |