| Literature DB >> 32610095 |
Tae Gyu Oh1, Susy M Kim2, Cyrielle Caussy3, Ting Fu1, Jian Guo4, Shirin Bassirian2, Seema Singh2, Egbert V Madamba2, Ricki Bettencourt5, Lisa Richards2, Ruth T Yu1, Annette R Atkins1, Tao Huan4, David A Brenner6, Claude B Sirlin7, Michael Downes1, Ronald M Evans8, Rohit Loomba9.
Abstract
Dysregulation of the gut microbiome has been implicated in the progression of non-alcoholic fatty liver disease (NAFLD) to advanced fibrosis and cirrhosis. To determine the diagnostic capacity of this association, we compared stool microbiomes across 163 well-characterized participants encompassing non-NAFLD controls, NAFLD-cirrhosis patients, and their first-degree relatives. Interrogation of shotgun metagenomic and untargeted metabolomic profiles by using the random forest machine learning algorithm and differential abundance analysis identified discrete metagenomic and metabolomic signatures that were similarly effective in detecting cirrhosis (diagnostic accuracy 0.91, area under curve [AUC]). Combining the metagenomic signature with age and serum albumin levels accurately distinguished cirrhosis in etiologically and genetically distinct cohorts from geographically separated regions. Additional inclusion of serum aspartate aminotransferase levels, which are increased in cirrhosis patients, enabled discrimination of cirrhosis from earlier stages of fibrosis. These findings demonstrate that a core set of gut microbiome species might offer universal utility as a non-invasive diagnostic test for cirrhosis.Entities:
Keywords: NAFLD; NASH; biomarker; cirrhosis; fatty liver; liver fibrosis; metabolomics; metagenomics; microbiome; microbiota; non-alcoholic fatty liver disease; non-alcoholic steatohepatitis
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Year: 2020 PMID: 32610095 PMCID: PMC7822714 DOI: 10.1016/j.cmet.2020.06.005
Source DB: PubMed Journal: Cell Metab ISSN: 1550-4131 Impact factor: 27.287