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. 2019 Oct;68(10):1884-1892.
doi: 10.1136/gutjnl-2018-317584. Epub 2018 Dec 19.

Serum metabolites detect the presence of advanced fibrosis in derivation and validation cohorts of patients with non-alcoholic fatty liver disease

Affiliations

Serum metabolites detect the presence of advanced fibrosis in derivation and validation cohorts of patients with non-alcoholic fatty liver disease

Cyrielle Caussy et al. Gut. 2019 Oct.

Abstract

Objective: Non-invasive and accurate diagnostic tests for the screening of disease severity in non-alcoholic fatty liver disease (NAFLD) remain a major unmet need. Therefore, we aimed to examine if a combination of serum metabolites can accurately predict the presence of advanced fibrosis.

Design: This is a cross-sectional analysis of a prospective derivation cohort including 156 well-characterised patients with biopsy-proven NAFLD and two validation cohorts, including (1) 142 patients assessed using MRI elastography (MRE) and(2) 59 patients with biopsy-proven NAFLD with untargeted serum metabolome profiling.

Results: In the derivation cohort, 23 participants (15%) had advanced fibrosis and 32 of 652 analysed metabolites were significantly associated with advanced fibrosis after false-discovery rate adjustment. Among the top 10 metabolites, 8 lipids (5alpha-androstan-3beta monosulfate, pregnanediol-3-glucuronide, androsterone sulfate, epiandrosterone sulfate, palmitoleate, dehydroisoandrosterone sulfate, 5alpha-androstan-3beta disulfate, glycocholate), one amino acid (taurine) and one carbohydrate (fucose) were identified. The combined area under the receiver operating characteristic curve (AUROC) of the top 10 metabolite panel was higher than FIB--4 and NAFLD Fibrosis Score (NFS) for the detection of advanced fibrosis: 0.94 (95% CI 0.897 to 0.982) versus 0.78 (95% CI0.674 to 0.891), p=0.002 and versus 0.84 (95% CI 0.724 to 0.929), p=0.017, respectively. The AUROC of the top 10 metabolite panel remained excellent in the independent validation cohorts assessed by MRE or liver biopsy: c-statistic of 0.94 and 0.84, respectively.

Conclusion: A combination of 10 serum metabolites demonstrated excellent discriminatory ability for the detection of advanced fibrosis in an derivation and two independent validation cohorts with greater diagnostic accuracy than the FIB-4-index and NFS. This proof-of-concept study demonstrates that a non-invasive blood-based diagnostic test can provide excellent performance characteristics for the detection of advanced fibrosis.

Keywords: hepatic fibrosis; magnetic resonance imaging; nonalcoholic steatohepatitis.

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Conflict of interest statement

Competing interests: CBS consults, advises and is on the speakers’ bureau for Bayer. He received grants from GE Healthcare

Figures

Figure 1
Figure 1
Fold change of the top 10 serum metabolite panel associated with advanced fibrosis The variation of the top 10 serum metabolites including 5alpha-androstan-3beta monosulfate, pregnanediol-3-glucuronide, androsterone sulfate, epiandrosterone sulfate, palmitoleate, dehydroisoandrosterone sulfate, 5alpha-androstan-3beta disulfate, glycocholate, taurine and fucose, coloured based on five subpathways is depicted as log fold change in participants with advanced fibrosis (AF) versus no advanced fibrosis.
Figure 2
Figure 2
Top 10 metabolite panel has higher area under the receiver operating characteristic curve (AUROC) than NAFLD Fibrosis Score (NFS) and FIB-4 index in derivation and validation cohorts The AUROC of the 10 serum metabolites panel including 5alpha-androstan-3beta monosulfate, pregnanediol-3-glucuronide, androsterone sulfate, epiandrosterone sulfate, palmitoleate, dehydroisoandrosterone sulfate, 5alpha-androstan-3beta disulfate, glycocholate, taurine and fucose, NFS and FIB-4 index for the detection of advanced fibrosis is shown in (A) the derivation biopsy-proven cohort, (B) the validation Twin and Family Cohort and (C) the independent biopsy-proven NAFLD validation cohort. *The AUROC of the 10 serum metabolites was higher than NFS and FIB-4 in the derivation cohort and validation cohorts.

Comment in

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