In patients with MHE on PHES, the relative abundance of salivary Lactobacillaceae, Streptococcaceae, Sutterellaceae, and Clostridiaceae was higher, whereas it was lower for Prevotellaceae, Saccharibacteria, Fusobacteriaceae, and Eubacteriaceae (Figure 2c). Using ICT, again there was a higher relative abundance of Lactobacillaceae and it was lower for Saccharibacteria and constituents of Proteobacteria in those with MHE. On Stroop, in patients with MHE, again a higher relative abundance of Lactobacillaceae and Streptococcaceae and a lower relative abundance of Proteobacteria, Fusobacteria, and Prevotellaceae were observed.
LEFSe in patients without prior OHE
Patients with MHE on PHES had a higher Lactobacillaceae and Micrococcaceae and a lower relative abundance of Lachnospiraceae, Acidaminococcaceae, and Cyanobacteria compared with those without MHE (Figure 2b). Using ICT, there were again higher Lactobacillaceae, Enterobacteriaceae, and Streptococcaceae and lower Bacteroidaceae and Peptococcaceae in those with MHE. When Stroop was used, there was a higher relative abundance of Lactobacillaceae, Bifidobacteriaceae, Micrococcaceae, and Gammaproteobacteria and a lower relative abundance of Cyanobacteria and Clostridiales cluster XIII in those with MHE.
PHES-associated MHE was associated with higher relative abundance of Lactobacillaceae and lower Proteobacteria, Chloroplast and several members of the Firmicutes phylum (Figure 2d). Using Stroop, there was a higher relative abundance of Lactobacillaceae and Streptococcaceae and a lower relative abundance of Proteobacteria in those with MHE. Patients with MHE on ICT had higher Veillonellaceae and lower Proteobacteria, Staphylococcaceae, and Acetobacteraceae compared with those without MHE.
As shown in Table 6, several microbial families in the stool and saliva samples were associated with MHE independent of the input clinical variables. Specifically, Lachnospiraceae were associated with protection from MHE on PHES and Stroop, whereas Veillonellaceae were associated with ICT-associated MHE. In the saliva samples, Streptococcaceae and Coriobacteriaceae were associated with MHE on the 3 modalities, whereas Clostridiales cluster XI and Prevotellaceae were associated with protection against MHE.
Genus-level changes in taxa found on logistic regression.
In the stool samples of all patients, the specific genera in Lachnospiraceae associated with protection from MHE, as assessed by PHES, were Blautia, Dorea, Roseburia, Clostridium XIVb, Robinsoniella, Coprococcus, and Ruminococcus. Using ICT, Ruminococcus, Clostridium XIVb, and Cellulosilyticum were found, and using Stroop, Clostridium XIVb and Lachnospira were found. Only in the stool samples of patients without prior OHE, the similar Lachnospiraceae genera were higher in those without MHE based on the PHES and Stroop assessment, whereas Veillonella was higher in ICT-associated MHE.
In saliva samples, Streptococcus was associated with MHE determined by the Stroop and PHES assessment in the entire group. In those without prior OHE, Lactobacillus and Paralactobacillus were higher in MHE determined by PHES and Prevotella was higher in those with MHE based on Stroop performance. In those without MHE determined by ICT, Abiotrophia from Aerococcaceae and Clostridium XIVb of Lachnospiraceae were in greater relative abundance.
The current study results demonstrate that patients with cirrhosis and MHE defined according to specific cognitive assessment strategies have unique microbial signatures in the stool and saliva samples. These microbial changes are associated with the diagnosis of MHE independent of clinical criteria, and the presence of specific bacterial taxa is indicative of normal cognition in this population.
Patients with cirrhosis and MHE suffer from a poor health-related quality of life, a greater likelihood to progress to OHE, and increased need for hospitalization and have a worse survival compared with those without MHE (22,23). It is often difficult to diagnose these patients because of logistic concerns related to the available cognitive assessment methodologies including the relatively poor diagnostic agreement between these tests (24). Consistent with the literature, we found a similar discordance between PHES, Stroop, and ICT in our patient population (4–6). These tests interrogate different parts of the brain with psychomotor speed being a common denominator between the tests. The psychometric hepatic encephalopathy score places a strong demand on a subject's visual-motor coordination and abstraction ability (14). In contrast to the PHES, the EncephalApp Stroop emphasizes cognitive flexibility, with the ICT assessing working memory and response inhibition (25,26). Given that each of the 3 cognitive methods used in this study emphasizes differing cognitive skill sets, it is not surprising that MHE classification, based on the individual test results compared with locally derived norms, would vary (27). However, the specific underlying factors associated with these neurobehavioral changes in MHE patients remain uncertain.
An altered gut-liver-brain axis is believed to be a central pathogenic factor accounting for the spectrum of cognitive impairment in cirrhosis, and indeed, most HE-related therapies are focused on the gut (2,28). Therefore, the changes in brain function underlying impaired performances on these tests could be related to alterations in gut microbiota. Changes in microbiota in cirrhosis have been shown in the stool, intestinal mucosa, serum, and saliva samples (7,29–32). This is likely related to changes in underlying immune function in cirrhosis, which allows these alterations in microbiota to occur (13,33). Patients with cirrhosis, especially those with advanced cirrhosis and OHE, have lower relative abundance of autochthonous bacterial taxa and higher potentially pathogenic ones (11). These are also associated with salivary bacterial changes (19). Therefore, specific microbial signatures that were found in our study that are linked to specific microbiota are intriguing.
We found that Shannon diversity indexes varied according to the test used and patients who were positive on PHES and Stroop, but not ICT, had lower diversity in the stool and salivary microbiota. This trend continued to a large extent in those without prior OHE and was despite similar dietary practices between the groups with and without MHE (34). This could be a function of liver disease severity as patients with MHE on PHES in the entire group had a higher MELD score compared with the rest. However, there are likely other factors at play because the MELD score was similar in patients without prior OHE who were positive on PHES and yet their diversity was lower. Nevertheless, the basic concept of diversity of the microbiota already showed differentiating features between the three modes of MHE diagnosis.
Specific bacterial taxa in the stool and saliva differentiated between patients with and without MHE, but Lactobacillaceae were overrepresented in the MHE group (30). In the stool samples, Lactobacillaceae are associated with the use of lactulose, which was prescribed to most of the prior OHE patients. However, we found a higher relative abundance of Lactobacillaceae in the stool of patients without prior OHE who had MHE and in the saliva as well. Because patients without OHE were not treated with lactulose and were not on specific probiotics, it is highly unlikely that this was an iatrogenic change. In previous studies based on 16srRNA and metagenomic sequencing, Lactobacillaceae have been associated with more advanced liver disease and to be linked with ammonia-associated changes on brain MRI (9,35). In animal models of cirrhosis, lactic acid has been associated with cerebral edema (36). In the logistic regression, both Lactobacillus and Paralactobacillus were found to be higher in the saliva of patients with MHE determined by PHES. The intriguing aspect is that this increase in relative abundance of Lactobacillaceae was greater in the group without prior OHE and was found to be higher in patients with MHE, regardless of the modality used. Although there have been studies evaluating the role of Lactobacillus-only probiotics in cirrhosis, they have not consistently resulted in cognitive improvement (37). Also, there are several species within Lactobacillus that are associated with pathogenic outcomes in addition to being probiotic in nature (38). Lactobacillus spp have also been associated with superinfections with other organisms and can increase after immunosuppressive therapy (39,40). Although Lactobacillaceae changes did not remain significant after logistic regression, these relatively consistent differences are intriguing and further analyses of the role of these microbes in gut-brain axis alterations in cirrhosis are needed.
On the other hand, genera belonging to Lachnospiraceae were present in greater relative abundance in patients without MHE in the stool in those with PHES and Stroop, even on logistic regression independent of clinical factors. Specific genera included Blautia, Roseburia, Clostridium XIVb, and Ruminococcus. These taxa are associated with intestinal barrier integrity and short-chain fatty acid production and are usually found in higher relative abundances in patients with good cognition in previous studies (31,41,42). Specific Clostridia are responsible for synthesizing the neuroprotective 3-indolepropionic acid as well (43). The interesting aspect is that the presence of these taxa, especially Clostridium XIVb and Ruminococcus, indicates better cognitive function on all 3 testing strategies and could be a method to exclude significant cognitive dysfunction in patients with cirrhosis. However, further prospective studies are needed to confirm these findings in other populations.
In the saliva, apart from the Lactobacillaceae changes, there was a higher relative abundance of Veillonella and Streptococcus in patients with cognitive impairment, even on logistic regression. Streptococcaceae are associated with production of ammonia through urease activity, which could be associated with the cognitive dysfunction, and were found in greater relative abundance when the entire group was studied rather than those without OHE (44). Of interest, these oral-origin taxa were not consistently higher in the stool of patients with MHE, likely because of the similar proportion of PPI use across the groups with and without MHE (45).
The association of altered biological processes in the determination of brain dysfunction in cirrhosis is relevant from a clinical and pathophysiological perspective. In previous studies, PHES and electroencephalogram have been separately linked with systemic inflammation and ammonia metabolism in patients with cirrhosis (8). Both modalities were independently associated with poor outcomes, regardless of the pathogenesis. There is published evidence that changes in microbial composition can be associated with hospitalizations, HE episodes, and death and recovery of brain function posttransplant (46–49). Previous reports have also focused differentially on specific gut microbiota and associated ammonia-related and inflammation-related consequences on brain magnetic resonance imaging in cirrhosis (9). A previous study from China has found a higher stool Streptococcaceae relative abundance linked with ammonia in patients with cognitive impairment on paper pencil tests (44). The current results extend these results further by including the entire spectrum of cognitive dysfunction, using multiple methods of cognitive impairment to define MHE and by using salivary microbiota.
Our study is limited by its cross-sectional design and by relatively small numbers of patients who underwent Stroop compared with other modalities. We also had a relatively smaller number of salivary microbiota analyses compared with the stool. Also because of logistic concerns, not all patients underwent all MHE testing modalities or saliva collection. We did not focus on differentiating prior OHE compared with those without prior OHE in this analysis because those data have been published extensively and are usually confounded by disease severity and therapeutic options for OHE that can affect the microbiota.
We conclude that there is a specific microbial signature in the stool and salivary microbiota that is associated with individual cognitive impairment in patients with cirrhosis. These microbial changes are associated with cognitive impairment independent of clinical factors. Specific microbial taxa are associated with good cognitive function, regardless of MHE testing modality, and could potentially be used to circumvent MHE testing as a beneficial biomarker of a healthy gut-liver-brain axis in cirrhosis.
CONFLICTS OF INTEREST
Guarantor of the article: Jasmohan S. Bajaj, MD.
Specific author contributions: J.S.B. conceptualized the study; M.B.W., A.F., and C.A. helped with cognitive testing and recruitment; D.M.H., M.F., and B.V.J. helped with recruitment; J.B.W. and P.B.H. were involved in drafting and critical appraisal; and P.M.G. and M.S. were involved in microbiota and bio-informatics analysis.
Financial support: Partly supported by R21TR0202024 and VA Merit Review I0CX001076 and McGuire Research Institute Funds to JSB. The sponsors had no role in study design, data analysis, or decision to publish.
Potential competing interests: None.
WHAT IS KNOWN
- ✓ Minimal hepatic encephalopathy is an epidemic neurocognitive disorder in cirrhosis with serious medical and psychosocial consequences.
- ✓ Several tests, such as PHES, ICT, and EncephalApp Stroop, used to diagnose MHE have poor concordance, which makes it difficult to diagnose MHE routinely.
- ✓ Patients with cirrhosis have an altered gut-brain axis, but the individual microbial signatures related to specific MHE tests and potential use of microbiota to evaluate normal cognition are uncertain.
WHAT IS NEW HERE
- ✓ In outpatients with cirrhosis, there were different microbial signatures in stool and saliva samples of patients who tested positive for MHE based on individual modalities.
- ✓ Lactobacillaceae were higher in relative abundance in patients with MHE, regardless of the modality used in the stool and saliva samples.
- ✓ Specific genera belonging to autochthonous Lachnospiraceae were associated with normal cognition independent of clinical variables, regardless of MHE testing modality, and could potentially be used as a beneficial biomarker of a healthy gut-liver-brain axis in cirrhosis.
1. Stepanova M, De Avila L, Afendy M, et al. Direct and indirect economic burden of chronic liver disease in the United States. Clin Gastroenterol Hepatol 2017;15:759–66.
2. Vilstrup H, Amodio P, Bajaj J, et al. Hepatic encephalopathy in chronic liver disease: 2014 practice guideline by the American Association for the study of liver diseases and the European Association for the study of the liver. Hepatology 2014;60:715–35.
3. Bajaj JS, Cordoba J, Mullen KD, et al. Review article: The design of clinical trials in hepatic encephalopathy—An international society for hepatic encephalopathy and nitrogen metabolism (ISHEN) consensus statement. Aliment Pharmacol Ther 2011;33:739–47.
4. Montagnese S, Balistreri E, Schiff S, et al. Covert hepatic encephalopathy: Agreement and predictive validity of different indices. World J Gastroenterol 2014;20:15756–62.
5. Goldbecker A, Weissenborn K, Hamidi Shahrezaei G, et al. Comparison of the most favoured methods for the diagnosis of hepatic encephalopathy in liver transplantation candidates. Gut 2013;62:1497–504.
6. Lauridsen MM, Jepsen P, Vilstrup H. Critical flicker frequency and continuous reaction times for the diagnosis of minimal hepatic encephalopathy: A comparative study of 154 patients with liver disease. Metab Brain Dis 2011;26:135–9.
7. Iebba V, Guerrieri F, Di Gregorio V, et al. Combining amplicon sequencing and metabolomics in cirrhotic patients highlights distinctive microbiota features involved in bacterial translocation, systemic inflammation and hepatic encephalopathy. Sci Rep 2018;8:8210.
8. Montagnese S, Biancardi A, Schiff S, et al. Different biochemical correlates for different neuropsychiatric abnormalities in patients with cirrhosis. Hepatology 2011;53:558–66.
9. Ahluwalia V, Betrapally NS, Hylemon PB, et al. Impaired gut-liver-brain axis in patients with cirrhosis. Sci Rep 2016;6:26800.
10. Shawcross DL, Davies NA, Williams R, et al. Systemic inflammatory response exacerbates the neuropsychological effects of induced hyperammonemia in cirrhosis. J Hepatol 2004;40:247–54.
11. Bajaj JS, Betrapally NS, Gillevet PM. Decompensated cirrhosis and microbiome interpretation. Nature 2015;525:E1–2.
12. Bajaj JS, Heuman DM, Hylemon PB, et al. Altered profile of human gut microbiome is associated with cirrhosis and its complications. J Hepatol 2014;60:940–7.
13. Albillos A, Lario M, Alvarez-Mon M. Cirrhosis-associated immune dysfunction: Distinctive features and clinical relevance. J Hepatol 2014;61:1385–96.
14. Weissenborn K, Ennen JC, Schomerus H, et al. Neuropsychological characterization of hepatic encephalopathy. J Hepatol 2001;34:768–73.
15. Bajaj JS, Hafeezullah M, Franco J, et al. Inhibitory control test for the diagnosis of minimal hepatic encephalopathy. Gastroenterology 2008;135:1591–600 e1.
16. Bajaj JS, Heuman DM, Sterling RK, et al. Validation of EncephalApp, smartphone-based Stroop test, for the diagnosis of covert hepatic encephalopathy. Clin Gastroenterol Hepatol 2015;13:1828–35.
17. Allampati S, Duarte-Rojo A, Thacker LR, et al. Diagnosis of minimal hepatic encephalopathy using Stroop EncephalApp: A multicenter US-based, norm-based study. Am J Gastroenterol 2016;111:78–86.
18. Amodio P, Ridola L, Schiff S, et al. Improving the inhibitory control task to detect minimal hepatic encephalopathy. Gastroenterology 2010;139:510–8, 518.e1–2.
19. Bajaj JS, Betrapally NS, Hylemon PB, et al. Salivary microbiota reflects changes in gut microbiota in cirrhosis with hepatic encephalopathy. Hepatology 2015;62:1260–71.
20. Hamady M, Knight R. Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res 2009;19:1141–52.
21. Segata N, Izard J, Waldron L, et al. Metagenomic biomarker discovery and explanation. Genome Biol 2011;12:R60.
22. Ampuero J, Simón M, Montoliú C, et al. Minimal hepatic encephalopathy and critical flicker frequency are associated with survival of patients with cirrhosis. Gastroenterology 2015;149:1483–9.
23. Patidar KR, Thacker LR, Wade JB, et al. Covert hepatic encephalopathy is independently associated with poor survival and increased risk of hospitalization. Am J Gastroenterol 2014;109:1757–63.
24. Bajaj JS. Diagnosing minimal hepatic encephalopathy: From the ivory tower to the real world. Gastroenterology 2015;149:1330–3.
25. Garavan H, Ross TJ, Stein EA. Right hemispheric dominance of inhibitory control: An event-related functional MRI study. Proc Natl Acad Sci U S A 1999;96:8301–6.
26. Pardo JV, Pardo PJ, Janer KW, et al. The anterior cingulate cortex mediates processing selection in the Stroop attentional conflict paradigm. Proc Natl Acad Sci U S A 1990;87:256–9.
27. Felipo V, Urios A, Gimenez-Garzo C, et al. Non invasive blood flow measurement in cerebellum detects minimal hepatic encephalopathy earlier than psychometric tests. World J Gastroenterol 2014;20:11815–25.
28. Kang DJ, Betrapally NS, Ghosh SA, et al. Gut microbiota drive the development of neuroinflammatory response in cirrhosis in mice. Hepatology 2016;64:1232–48.
29. Santiago A, Pozuelo M, Poca M, et al. Alteration of the serum microbiome composition in cirrhotic patients with ascites. Sci Rep 2016;6:25001.
30. Bajaj JS, Ridlon JM, Hylemon PB, et al. Linkage of gut microbiome with cognition in hepatic encephalopathy. Am J Physiol Gastrointest Liver Physiol 2012;302:G168–75.
31. Bajaj JS, Hylemon PB, Ridlon JM, et al. Colonic mucosal microbiome differs from stool microbiome in cirrhosis and hepatic encephalopathy and is linked to cognition and inflammation. Am J Physiol Gastrointest Liver Physiol 2012;303:G675–85.
32. Chen Y, Yang F, Lu H, et al. Characterization of fecal microbial communities in patients with liver cirrhosis. Hepatology 2011;54:562–72.
33. Patel VC, Shawcross DL. Salivary microbiota-immune profiling in cirrhosis: Could this be the noninvasive strategy that will revolutionize prognostication in hepatology? Hepatology 2015;62:1001–3.
34. Bajaj JS, Idilman R, Mabudian L, et al. Diet affects gut microbiota and modulates hospitalization risk differentially in an international cirrhosis cohort. Hepatology 2018;68:234–47.
35. Dubinkina VB, Tyakht AV, Odintsova VY, et al. Links of gut microbiota composition with alcohol dependence syndrome and alcoholic liver disease. Microbiome 2017;5:141.
36. Bosoi CR, Zwingmann C, Marin H, et al. Increased brain lactate is central to the development of brain edema in rats with chronic liver disease. J Hepatol 2014;60:554–60.
37. Bajaj JS, Heuman DM, Hylemon PB, et al. Randomised clinical trial: Lactobacillus GG modulates gut microbiome, metabolome and endotoxemia in patients with cirrhosis. Aliment Pharmacol Ther 2014;39:1113–25.
38. Salminen MK, Rautelin H, Tynkkynen S, et al. Lactobacillus bacteremia, clinical significance, and patient outcome, with special focus on probiotic L. rhamnosus GG. Clin Infect Dis 2004;38:62–9.
39. Reynolds LA, Smith KA, Filbey KJ, et al. Commensal-pathogen interactions in the intestinal tract: Lactobacilli promote infection with, and are promoted by, helminth parasites. Gut Microbes 2014;5:522–32.
40. Xu X, Zhang X. Effects of cyclophosphamide on immune system and gut microbiota in mice. Microbiol Res 2015;171:97–106.
41. Rios-Covian D, Sanchez B, Salazar N, et al. Different metabolic features of Bacteroides fragilis growing in the presence of glucose and exopolysaccharides of bifidobacteria. Front Microbiol 2015;6:825.
42. Morrison DJ, Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 2016;7:189–200.
43. Wikoff WR, Anfora AT, Liu J, et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Natl Acad Sci U S A 2009;106:3698–703.
44. Zhang Z, Zhai H, Geng J, et al. Large-scale survey of gut microbiota associated with MHE via 16S rRNA-based pyrosequencing. Am J Gastroenterol 2013;108:1601–11.
45. Bajaj JS, Acharya C, Fagan A, et al. Proton pump inhibitor initiation and withdrawal affects gut microbiota and readmission risk in cirrhosis. Am J Gastroenterol 2018;113:1177–86.
46. Bajaj JS, Betrapally NS, Hylemon PB, et al. Gut microbiota alterations can predict hospitalizations in cirrhosis independent of diabetes mellitus. Sci Rep 2015;5:18559.
47. Chen Y, Guo J, Qian G, et al. Gut dysbiosis in acute-on-chronic liver failure and its predictive value for mortality. J Gastroenterol Hepatol 2015;30:1429–37.
48. Bajaj JS, Fagan A, Sikaroodi M, et al. Liver transplant modulates gut microbial dysbiosis and cognitive function in cirrhosis. Liver Transpl 2017;23:907–14.
49. Bajaj JS, Vargas HE, Reddy KR, et al. Association between intestinal microbiota collected at hospital admission and outcomes of patients with cirrhosis. Clin Gastroenterol Hepatol 2018. [Epub ahead of print July 20, 2018.]
Supplemental Digital Content
© The American College of Gastroenterology 2019. All Rights Reserved.