. 2019 Mar 29;10(1):1406.

doi: 10.1038/s41467-019-09455-9.

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

Cyrielle Caussy^{1

2}, Anupriya Tripathi^{3

4

5

6}, Greg Humphrey⁴, Shirin Bassirian¹, Seema Singh¹, Claire Faulkner¹, Ricki Bettencourt^{1

7}, Emily Rizo¹, Lisa Richards¹, Zhenjiang Z Xu⁴, Michael R Downes⁸, Ronald M Evans⁸, David A Brenner^{1

9}, Claude B Sirlin¹⁰, Rob Knight^{3

4

11

12}, Rohit Loomba^{13

14

15}

Affiliations

¹ NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
² Université Lyon 1, Hospices Civils de Lyon, Lyon, 69002, France.
³ Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, 92093, USA.
⁴ Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.
⁵ Division of Biological Sciences, University of California San Diego, La Jolla, CA, 92093, USA.
⁶ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 93093, USA.
⁷ Division of Epidemiology, Department of Family and Preventive Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
⁸ Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
⁹ Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
¹⁰ Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92037, USA.
¹¹ Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
¹² Department of BioEngineering, University of California San Diego, La Jolla, CA, 92093, USA.
¹³ NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.
¹⁴ Division of Epidemiology, Department of Family and Preventive Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.
¹⁵ Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.

PMID: 30926798
PMCID: PMC6440960
DOI: 10.1038/s41467-019-09455-9

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

Cyrielle Caussy et al. Nat Commun. 2019.

. 2019 Mar 29;10(1):1406.

doi: 10.1038/s41467-019-09455-9.

Authors

Affiliations

¹ NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
² Université Lyon 1, Hospices Civils de Lyon, Lyon, 69002, France.
³ Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, 92093, USA.
⁴ Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.
⁵ Division of Biological Sciences, University of California San Diego, La Jolla, CA, 92093, USA.
⁶ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 93093, USA.
⁷ Division of Epidemiology, Department of Family and Preventive Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
⁸ Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
⁹ Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
¹⁰ Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92037, USA.
¹¹ Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
¹² Department of BioEngineering, University of California San Diego, La Jolla, CA, 92093, USA.
¹³ NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.
¹⁴ Division of Epidemiology, Department of Family and Preventive Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.
¹⁵ Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA. roloomba@ucsd.edu.

PMID: 30926798
PMCID: PMC6440960
DOI: 10.1038/s41467-019-09455-9

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1**
Familial association and shared microbiome among relatives is driven by shared housing. Distribution of spearman correlation coefficients between relatives in purple (n = 86) and unrelated pairs in orange (n = 18232) in the familial cohort, plotted for each phyla (a) and 16S tag sequences (b). The box plots show the quartiles and whiskers show the rest of the distribution (1.5 inter-quartile range) and the center line corresponds to the median. This analysis was done after filtering rare 16S sequences to avoid spurious correlations due to sparsity (total abundance <10E-6 across all samples in each disease group). The correlation among related individuals was significantly higher at both phylum (p = 0.023) and 16S tag sequences (p = 2.4E-41) levels. Similar plot showing the distribution of unweighted UniFrac distances between related in purple and unrelated pairs stratified by disease status (c). The beta-diversity was significantly lower among related individuals (p = 3.22E-05), non-NAFLD controls and relative in blue (n = 38 pairs) (p = 0.0011) and probands with NAFLD without AF and relatives in yellow (n = 15) (p = 0.0156) when compared to the same among unrelated pairs in orange, while the difference between NALFD-cirrhosis patients and relatives in pink (n = 33) and unrelated pairs in orange was not statistically significant (p > 0.1). When stratified by shared housing (d), beta-diversity was significantly lower among related individuals sharing a house in purple (n = 35 pairs) (p = 0.0455). Additionally, related individuals not sharing a house in white (n = 51 pairs) had significantly lower beta-diversity compared to unrelated pairs in orange (p = 0.028). All p value were determined by two-sided Kruskal-Wallis test. *p value < 0.05. Source data are provided as a Source Data file

**Fig. 2**
Gut microbiome alteration in NAFLD-cirrhosis. Comparison between non-NAFLD controls in blue (n = 51), NAFLD without advanced fibrosis in yellow (n = 17), and NAFLD-cirrhosis probands in pink (n = 25) with respect to a alpha-diversity using Faith’s Phylogenetic Diversity. Non-NAFLD controls have significantly higher alpha-diversity compared to probands with NAFLD without AF in yellow (p = 0.0163) and NAFLD-cirrhosis in pink (p = 0.0020). b Similar plot for beta-diversity using unweighted UniFrac distance metric. The beta-diversity among probands with NAFLD without AF in yellow was significantly lower than that among non-NAFLD controls in blue (p = 1.14E-18) and probands with NAFLD-cirrhosis in pink (p = 3.32E-15). The box plots show the quartiles and whiskers show the rest of the distribution (1.5 inter-quartile range) the center liner corresponds to the median. c Gut microbiome composition of non-NAFLD controls, NAFLD without AF and NALFD-cirrhosis probands shows differences at bacterial genus level. All p value were determined by two-sided Kruskal-Wallis test. *p value < 0.05. Source data are provided as a Source Data file

**Fig. 3**
Relative abundance of predictive microbial features for the prediction of NAFLD-cirrhosis. The bacterial features most predictive of NAFLD-cirrhosis (n = 25) versus non-NAFLD controls (n = 51) sorted by decreasing importance score in Random Forest classification model. Features increased (a) and decreased (b) in NAFLD-cirrhosis probands are shown. Relative abundance is plotted for each subject group in the cohort (NAFLD-cirrhosis in pink (n = 25), NAFLD without advanced fibrosis in yellow (n = 17) and non-NAFLD controls in blue (n = 51)). The feature table is normalized to a total abundance of 1 per sample and relative abundances are plotted on a log10 scale. Each bacterial feature is a unique 16S tag sequence labeled to the highest possible taxonomic rank assigned using QIIME. The box plots show the quartiles and whiskers show the rest of the distribution (1.5 inter-quartile range). The notches show 95% confidence interval. Features that are differentially abundant in addition to being important predictors are marked by asterisk. Single asterisk (*) represents significant difference between non-NAFLD controls and NAFLD-cirrhosis probands p value < 0.05; Double asterisk (**) represents the same between NAFLD without advanced fibrosis and NAFLD cirrhosis probands p value < 0.05. Differential abundance was tested using permutation-based, ranked mean test, comparing mean difference between the two groups. FDR (<0.1) was controlled using DS-FDR method. Source data are provided as a Source Data file

**Fig. 4**
High diagnostic accuracy of a gut-microbiome signature for the detection of NAFLD-cirrhosis. Receiver operating characteristic (ROC) curves evaluating ability to predict advanced Fibrosis using Random Forest classification. Each curve represents the sensitivity and specificity to distinguish subjects with NAFLD-cirrhosis (1, brown line) from non-NALFD controls (0, green line). a Mean ROC curve from cross-validation within training data comprised of NAFLD-cirrhosis probands (n = 24) and non-NAFLD controls (n = 47). Cross-validation was performed by iteratively (10 times) training the Random Forest model with 70:30 train/test split on this training data. b ROC curve representing diagnostic accuracy of Random Forest classification model tested on first-degree relatives of NAFLD-cirrhosis probands (n = 32). The negative predictive value (NPV) of the model was 91.6% and the positive predictive value was 62.5%. Source data are provided as a Source Data file

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References

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

Affiliations

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

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical