Gut Microbiome-Based Metagenomic Signature for Non-invasive Detection of Advanced Fibrosis in Human Nonalcoholic Fatty Liver Disease

Study information

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

study design

prospective cohort

Citation

PMID PubMed identifier for scientific articles.

28467925

DOI Digital object identifier for electronic documents.

10.1016/j.cmet.2017.04.001

URI Uniform resource identifier for web resources.

Authors

Loomba R, Seguritan V, Li W, Long T, Klitgord N, Bhatt A, Dulai PS, Caussy C, Bettencourt R, Highlander SK, Jones MB, Sirlin CB, Schnabl B, Brinkac L, Schork N, Chen CH, Brenner DA, Biggs W, Yooseph S, Venter JC, Nelson KE

Journal

Cell metabolism

Year

2017

The presence of advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is the most important predictor of liver mortality. There are limited data on the diagnostic accuracy of gut microbiota-derived signature for predicting the presence of advanced fibrosis. In this prospective study, we characterized the gut microbiome compositions using whole-genome shotgun sequencing of DNA extracted from stool samples. This study included 86 uniquely well-characterized patients with biopsy-proven NAFLD, of which 72 had mild/moderate (stage 0-2 fibrosis) NAFLD, and 14 had advanced fibrosis (stage 3 or 4 fibrosis). We identified a set of 40 features (p < 0.006), which included 37 bacterial species that were used to construct a Random Forest classifier model to distinguish mild/moderate NAFLD from advanced fibrosis. The model had a robust diagnostic accuracy (AUC 0.936) for detecting advanced fibrosis. This study provides preliminary evidence for a fecal-microbiome-derived metagenomic signature to detect advanced fibrosis in NAFLD.

Experiment 1

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Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Lwaldron, WikiWorks, Aiyshaaaa

Subjects

Location of subjects: United States of America

Host species Species from which microbiome was sampled (if applicable): Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: non-alcoholic fatty liver disease fatty liver disease, nonalcoholic,fatty liver disease, nonalcoholic, susceptibility to, 1,liver disease, alcoholic, susceptibility to, 1,NAFLD - Nonalcoholic Fatty Liver Disease,NAFLD - nonalcoholic fatty liver disease,NAFLD1,non-alcoholic fatty liver,non-alcoholic fatty liver disease,Nonalcoholic Fatty Liver Disease,nonalcoholic fatty liver disease

Group 0 name Corresponds to the control (unexposed) group for case-control studies: mild/moderate fibrosis
Group 1 name Corresponds to the case (exposed) group for case-control studies: advanced fibrosis
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Based on clinical, magnetic resonance, histology assessment; Mild/Moderate NAFLD: fibrosis 0-2. Advanced NAFLD: fibrosis 3-4
Group 0 sample size Number of subjects in the control (unexposed) group: 72
Group 1 sample size Number of subjects in the case (exposed) group: 14

Lab analysis

Sequencing type: WMS

Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Statistical test: Random Forest Analysis

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes
Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, body mass index