Insights into genetic variants associated with NASH-fibrosis from metabolite profiling

• Published in: Human molecular genetics Vol. 29; no. 20; pp. 3451 - 3463
• Main Authors: Mann, Jake P, Pietzner, Maik, Wittemans, Laura B, Rolfe, Emmanuela De Lucia, Kerrison, Nicola D, Imamura, Fumiaki, Forouhi, Nita G, Fauman, Eric, Allison, Michael E, Griffin, Jules L, Koulman, Albert, Wareham, Nicholas J, Langenberg, Claudia
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 18.12.2020
• Subjects: Adult; Aged; Association Studies; Female; Genetic Association Studies; Genetic Predisposition to Disease; Humans; Liver Cirrhosis - complications; Liver Cirrhosis - genetics; Liver Cirrhosis - metabolism; Liver Cirrhosis - pathology; Male; Metabolome; Middle Aged; Non-alcoholic Fatty Liver Disease - complications; Non-alcoholic Fatty Liver Disease - genetics; Non-alcoholic Fatty Liver Disease - metabolism; Non-alcoholic Fatty Liver Disease - pathology; Polymorphism, Single Nucleotide; Prognosis; Prospective Studies
• ISSN: 0964-6906; 1460-2083; 1460-2083
• DOI: 10.1093/hmg/ddaa162

Abstract Several genetic discoveries robustly implicate five single-nucleotide variants in the progression of non-alcoholic fatty liver disease to non-alcoholic steatohepatitis and fibrosis (NASH-fibrosis), including a recently identified variant in MTARC1. To better understand these variants as potential therapeutic targets, we aimed to characterize their impact on metabolism using comprehensive metabolomics data from two population-based studies. A total of 9135 participants from the Fenland study and 9902 participants from the EPIC-Norfolk cohort were included in the study. We identified individuals with risk alleles associated with NASH-fibrosis: rs738409C>G in PNPLA3, rs58542926C>T in TM6SF2, rs641738C>T near MBOAT7, rs72613567TA>T in HSD17B13 and rs2642438A>G in MTARC1. Circulating levels of 1449 metabolites were measured using targeted and untargeted metabolomics. Associations between NASH-fibrosis variants and metabolites were assessed using linear regression. The specificity of variant-metabolite associations were compared to metabolite associations with ultrasound-defined steatosis, gene variants linked to liver fat (in GCKR, PPP1R3B and LYPLAL1) and gene variants linked to cirrhosis (in HFE and SERPINA1). Each NASH-fibrosis variant demonstrated a specific metabolite profile with little overlap (8/97 metabolites) comprising diverse aspects of lipid metabolism. Risk alleles in PNPLA3 and HSD17B13 were both associated with higher 3-methylglutarylcarnitine and three variants were associated with lower lysophosphatidylcholine C14:0. The risk allele in MTARC1 was associated with higher levels of sphingomyelins. There was no overlap with metabolites that associated with HFE or SERPINA1 variants. Our results suggest a link between the NASH-protective variant in MTARC1 to the metabolism of sphingomyelins and identify distinct molecular patterns associated with each of the NASH-fibrosis variants under investigation.