한빛사논문
- 조회2,093
Tae Gyu Oh1, Susy M. Kim2, Cyrielle Caussy2,3, Ting Fu1, Jian Guo4, Shirin Bassirian2, Seema Singh2, Egbert V. Madamba2, Ricki Bettencourt2,5, Lisa Richards2, Manuela Raffatellu6,7, Pieter C. Dorrestein8,9,10, Ruth T. Yu1, Annette R. Atkins1, Tao Huan4, David A. Brenner2,11, Claude B. Sirlin12, Rob Knight9,10,13,14, Michael Downes1, Ronald M. Evans1,15,*, Rohit Loomba2,5,11,16,*
1Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
2NAFLD Research Center, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
3Université Lyon 1, Hospices Civils de Lyon, Lyon, France
4Department of Chemistry, UBC Faculty of Science, Vancouver Campus, Vancouver, BC V6T 1Z4, Canada
5Division of Epidemiology, Department of Family and Preventative Medicine, University of California, San Diego, La Jolla, CA 92093, USA
6Division of Host-Microbe Systems and Therapeutics, Department of Pediatrics, and Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
7Chiba University-UC San Diego Center for Mucosal Immunity, Allergy, and Vaccines (CU-UCSD cMAV), La Jolla, CA 92093, USA
8Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093, USA
9Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
10UCSD Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
11Division of Gastroenterology, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
12Liver Imaging Group, Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
13Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA
14Department of Engineering, University of California, San Diego, La Jolla, CA 92093, USA
15Howard Hughes Medical Institute, the Salk Institute for Biological Studies, La Jolla, CA 92037, USA
16Lead Contact
*Corresponding author
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.
논문정보
- Research article
- 2020년 06월 (BRIC 등록일 2020-08-28)
- 국외 연구진
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