A gut microbiome signature for cirrhosis due to nonalcoholic fatty liver disease

Cyrielle Caussy, Anupriya Tripathi, Greg Humphrey, Shirin Bassirian, Seema Singh, Claire Faulkner, Ricki Bettencourt, Emily Rizo, Lisa Richards, Zhenjiang Z. Xu, Michael R. Downes, Ronald M. Evans, David A. Brenner, Claude B. Sirlin, Rob Knight and Rohit Loomba ()
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Cyrielle Caussy: University of California San Diego
Anupriya Tripathi: University of California San Diego
Greg Humphrey: University of California San Diego
Shirin Bassirian: University of California San Diego
Seema Singh: University of California San Diego
Claire Faulkner: University of California San Diego
Ricki Bettencourt: University of California San Diego
Emily Rizo: University of California San Diego
Lisa Richards: University of California San Diego
Zhenjiang Z. Xu: University of California San Diego
Michael R. Downes: Salk Institute for Biological Studies
Ronald M. Evans: Salk Institute for Biological Studies
David A. Brenner: University of California San Diego
Claude B. Sirlin: University of California at San Diego
Rob Knight: University of California San Diego
Rohit Loomba: University of California San Diego

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: Abstract The presence of cirrhosis in nonalcoholic-fatty-liver-disease (NAFLD) is the most important predictor of liver-related mortality. Limited data exist concerning the diagnostic accuracy of gut-microbiome-derived signatures for detecting NAFLD-cirrhosis. Here we report 16S gut-microbiome compositions of 203 uniquely well-characterized participants from a prospective twin and family cohort, including 98 probands encompassing the entire spectrum of NAFLD and 105 of their first-degree relatives, assessed by advanced magnetic-resonance-imaging. We show strong familial correlation of gut-microbiome profiles, driven by shared housing. We report a panel of 30 features, including 27 bacterial features with discriminatory ability to detect NAFLD-cirrhosis using a Random Forest classifier model. In a derivation cohort of probands, the model has a robust diagnostic accuracy (AUROC of 0.92) for detecting NAFLD-cirrhosis, confirmed in a validation cohort of relatives of proband with NAFLD-cirrhosis (AUROC of 0.87). This study provides evidence for a fecal-microbiome-derived signature to detect NAFLD-cirrhosis.

Date: 2019
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DOI: 10.1038/s41467-019-09455-9

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