A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis
Tae Gyu Oh
1
,
Susy M Kim
2
,
Cyrielle Caussy
3, 4
,
Ting Fu
1
,
Jian Guo
5
,
Shirin Bassirian
2
,
Seema Singh
2
,
Egbert V Madamba
2
,
Ricki Bettencourt
3
,
Lisa Richards
2
,
Ruth T. Yu
1
,
Annette Atkins
1
,
Tao Huan
5
,
David M. Brenner
6
,
Claude Sirlin
7
,
Michael S Downes
1
,
Ronald Evans
1
,
Rohit S. Loomba
3
4
5
Department of Chemistry, UBC Faculty of Science, Vancouver Campus, Vancouver, BC V6T 1Z4, Canada
|
Publication type: Journal Article
Publication date: 2020-11-01
scimago Q1
wos Q1
SJR: 11.989
CiteScore: 45.5
Impact factor: 30.9
ISSN: 15504131, 19327420
PubMed ID:
32610095
Molecular Biology
Cell Biology
Physiology
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.
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Total citations:
233
Citations from 2024:
95
(40.95%)
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GOST
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Oh T. G. et al. A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis // Cell Metabolism. 2020. Vol. 32. No. 5. pp. 878-888000000.
GOST all authors (up to 50)
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Oh T. G., Kim S. M., Caussy C., Fu T., Guo J., Bassirian S., Singh S., Madamba E. V., Bettencourt R., Richards L., Yu R. T., Atkins A., Huan T., Brenner D. M., Sirlin C., Downes M. S., Evans R., Loomba R. S. A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis // Cell Metabolism. 2020. Vol. 32. No. 5. pp. 878-888000000.
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TY - JOUR
DO - 10.1016/j.cmet.2020.06.005
UR - https://doi.org/10.1016/j.cmet.2020.06.005
TI - A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis
T2 - Cell Metabolism
AU - Oh, Tae Gyu
AU - Kim, Susy M
AU - Caussy, Cyrielle
AU - Fu, Ting
AU - Guo, Jian
AU - Bassirian, Shirin
AU - Singh, Seema
AU - Madamba, Egbert V
AU - Bettencourt, Ricki
AU - Richards, Lisa
AU - Yu, Ruth T.
AU - Atkins, Annette
AU - Huan, Tao
AU - Brenner, David M.
AU - Sirlin, Claude
AU - Downes, Michael S
AU - Evans, Ronald
AU - Loomba, Rohit S.
PY - 2020
DA - 2020/11/01
PB - Elsevier
SP - 878-888000000
IS - 5
VL - 32
PMID - 32610095
SN - 1550-4131
SN - 1932-7420
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2020_Oh,
author = {Tae Gyu Oh and Susy M Kim and Cyrielle Caussy and Ting Fu and Jian Guo and Shirin Bassirian and Seema Singh and Egbert V Madamba and Ricki Bettencourt and Lisa Richards and Ruth T. Yu and Annette Atkins and Tao Huan and David M. Brenner and Claude Sirlin and Michael S Downes and Ronald Evans and Rohit S. Loomba},
title = {A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis},
journal = {Cell Metabolism},
year = {2020},
volume = {32},
publisher = {Elsevier},
month = {nov},
url = {https://doi.org/10.1016/j.cmet.2020.06.005},
number = {5},
pages = {878--888000000},
doi = {10.1016/j.cmet.2020.06.005}
}
Cite this
MLA
Copy
Oh, Tae Gyu, et al. “A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis.” Cell Metabolism, vol. 32, no. 5, Nov. 2020, pp. 878-888000000. https://doi.org/10.1016/j.cmet.2020.06.005.