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Clinical Trial
. 2013;8(4):e60042.
doi: 10.1371/journal.pone.0060042. Epub 2013 Apr 2.

Modulation of the metabiome by rifaximin in patients with cirrhosis and minimal hepatic encephalopathy

Jasmohan S Bajaj  1 , Douglas M Heuman, Arun J Sanyal, Phillip B Hylemon, Richard K Sterling, R Todd Stravitz, Michael Fuchs, Jason M Ridlon, Kalyani Daita, Pamela Monteith, Nicole A Noble, Melanie B White, Andmorgan Fisher, Masoumeh Sikaroodi, Huzefa Rangwala, Patrick M Gillevet
Affiliations
Clinical Trial

Modulation of the metabiome by rifaximin in patients with cirrhosis and minimal hepatic encephalopathy

Jasmohan S Bajaj et al. PLoS One. 2013.

Abstract

Hepatic encephalopathy (HE) represents a dysfunctional gut-liver-brain axis in cirrhosis which can negatively impact outcomes. This altered gut-brain relationship has been treated using gut-selective antibiotics such as rifaximin, that improve cognitive function in HE, especially its subclinical form, minimal HE (MHE). However, the precise mechanism of the action of rifaximin in MHE is unclear. We hypothesized that modulation of gut microbiota and their end-products by rifaximin would affect the gut-brain axis and improve cognitive performance in cirrhosis. Aim To perform a systems biology analysis of the microbiome, metabolome and cognitive change after rifaximin in MHE.

Methods: Twenty cirrhotics with MHE underwent cognitive testing, endotoxin analysis, urine/serum metabolomics (GC and LC-MS) and fecal microbiome assessment (multi-tagged pyrosequencing) at baseline and 8 weeks post-rifaximin 550 mg BID. Changes in cognition, endotoxin, serum/urine metabolites (and microbiome were analyzed using recommended systems biology techniques. Specifically, correlation networks between microbiota and metabolome were analyzed before and after rifaximin.

Results: There was a significant improvement in cognition(six of seven tests improved, p<0.01) and endotoxemia (0.55 to 0.48 Eu/ml, p = 0.02) after rifaximin. There was a significant increase in serum saturated (myristic, caprylic, palmitic, palmitoleic, oleic and eicosanoic) and unsaturated (linoleic, linolenic, gamma-linolenic and arachnidonic) fatty acids post-rifaximin. No significant microbial change apart from a modest decrease in Veillonellaceae and increase in Eubacteriaceae was observed. Rifaximin resulted in a significant reduction in network connectivity and clustering on the correlation networks. The networks centered on Enterobacteriaceae, Porphyromonadaceae and Bacteroidaceae indicated a shift from pathogenic to beneficial metabolite linkages and better cognition while those centered on autochthonous taxa remained similar.

Conclusions: Rifaximin is associated with improved cognitive function and endotoxemia in MHE, which is accompanied by alteration of gut bacterial linkages with metabolites without significant change in microbial abundance.

Trial registration: ClinicalTrials.gov NCT01069133.

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Conflict of interest statement

Competing Interests: JSB and AJS have been consultants to Salix Pharmaceuticals. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Consort Flowchart of the Open-label trial.
Figure 2
Figure 2. A: Principal Component Analysis of Microbiota.
There was no significant change in the PCO of microbiota before and after rifaximin therapy (yellow dots are before and red dots are after rifaximin) B and C: Composition of microbiota families before (figure 2B) and after (figure 2C) rifaximin. There was a significant decrease in Veillonellaceae and increase in Eubacteriaceae abundance after rifaximin therapy (marked in red).
Figure 3
Figure 3. Univariate serum metabolomic analysis.
There was a significant increase in fatty acids and intermediates of carbohydrate metabolism after rifaximin therapy in the serum.
Figure 4
Figure 4. Correlation networks before and after rifaximin.
Legend common for figures 4A, 4B and 4C: The complex correlation network represented parameters that were linked with a correlation coefficient >0.6 (negative or positive) and with a p value <0.05. Red nodes represent bacterial taxa, green ones the serum metabolites, yellow nodes indicate urinary metabolites while blue ones indicate clinical parameters. Red edges represent negative correlation between connected nodes and blue edges indicate positive correlations. A: Correlation network before rifaximin (BCN) with r>0.6 or <−0.6 and p<0.001. B: Correlation network after rifaximin (ACN) with r>0.6 or <−0.6 and p<0.001. C: is the intersection of 5A and B. It demonstrates those nodes and correlations that remain exactly same before and after rifaximin. D: Cumulative Degree Function curve. This graph plots the cumulative degree function of the node frequency distributions before and after rifaximin. It shows that after rifaximin therapy there was a significant reduction in network complexity (p<0.0001). Blue line: before and red line: after rifaximin. E: Correlation difference before and after rifaximin. This figure shows the correlations that significantly changed between the before and after rifaximin state; i.e. if two nodes were connected positively in the before rifaximin network but aftr rifaximin changed to negative, they are represented here. While the color coding of the nodes is similar, red edges demonstrate linkages that were positive in the BCN but became negative in ACN, while blue edges represent correlations that changed from negative to positive after the use of rifaximin.
Figure 5
Figure 5. Subset of correlation differences before and after rifaximin.
This figure is limited to the metabolomics and clinical/cognitive features that changed with rifaximin and their interaction with the bacterial taxa. The linkages that significantly changed in nature (positive to negative or vice-versa) or intensity (less to more or vice-versa while remaining positive or negative) with p
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