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Gut dysbiosis is associated with poorer long-term prognosis in cirrhosis

BACKGROUND Gut dysbiosis is common in cirrhosis. AIM To study the influence of gut dysbiosis on prognosis in cirrhosis. METHODS The case-control study included 48 in-patients with cirrhosis and 21 healthy controls. Stool microbiome was assessed using 16S ribosomal ribonucleic acid gene sequencing. We used modified dysbiosis ratio (MDR): [Bacilli (%) + Proteobacteria (%)]/[Clostridia (%) + Bacteroidetes (%)]. Patients with MDR more the median made up the group with severe dysbiosis, others did the group with non-severe dysbiosis. The follow-up period was 4 years. RESULTS The mortality rate of patients with severe dysbiosis was significantly higher than that of patients with non-severe dysbiosis (54.2% vs 12.5%; P = 0.001). The presence of severe dysbiosis was independent risk factors for death [hazard ratio = 8.6 × (1.9-38.0); P = 0.005]. The abundance of Enterobacteriaceae (P = 0.002), Proteobacteria (P = 0.002), and Lactobacillaceae (P = 0.025) was increased and the abundance of Firmicutes (P = 0.025) and Clostridia (P = 0.045) was decreased in the deceased patients compared with the survivors. The deceased patients had a higher MDR value than the survivors [0.131 × (0.069-0.234) vs 0.034 × (0.009-0.096); P = 0.004]. If we applied an MDR value of 0.14 as the cutoff point, then it predicted patient death within the next year with a sensitivity of 71.4% and a specificity of 82.9% [area under the curve = 0.767 × (0.559-0.974)]. MDR was higher in patients with cirrhosis than in health controls [0.064 × (0.017-0.131) vs 0.005 × (0.002-0.007); P < 0.001], and in patients with decompensated cirrhosis than in patients with compensated cirrhosis [0.106 × (0.023-0.211) vs 0.033 × (0.012-0.074); P = 0.031]. MDR correlated negatively with prothrombin (r = -0.295; P = 0.042), cholinesterase (r = -0.466; P = 0.014) and serum albumin (r = -0.449; P = 0.001) level and positively with Child–Turcotte–Pugh scale value (r = 0.360; P = 0.012). CONCLUSION Gut dysbiosis is associated with a poorer long-term prognosis in cirrhosis.


INTRODUCTION
Microbiota are stable ecological communities of microorganisms in certain habitats [1]. Recently, the human microbiota has attracted the attention of researchers. Previous studies have shown that its composition varies in different diseases, and it has been hypothesized that the pathology of the human microbiota (dysbiosis) can participate in the pathogenesis of these diseases [2].
As the gut microbiota is the richest human microbiota, most research has been devoted to it. The gut microbiota plays an important role in human life; it digests nondigestible carbohydrates as well as generates vitamins and short-chain fatty acids (butyrate is particularly prominent), which are used as a source of energy by colonocytes. This function is performed by strict anaerobes of the main taxa of normal microbiota, which belong to the Clostridia class and Bacteroidetes phylum. Nevertheless, the gut microbiota can also play a pathogenic role because it has potential pathogenic bacteria, which belong to the Bacilli class (Streptococcaceae, Enterococcaceae) and Proteobacteria phylum (Enterobacteriaceae). In addition, facultative anaerobes of the Bacilli class and Proteobacteria phylum can enter the gut wall, mesenteric lymph nodes, portal, and systemic blood flow. This phenomenon is called bacterial translocation. The gut microbiota is also the main source of endotoxin (lipopolysaccharide), a toxic substance of gram-negative bacteria, primarily Proteobacteria [3].
To date, several articles [4][5][6] have been published that describe alterations of the gut microbiome in cirrhosis. Researchers have shown that the abundance of harmful Proteobacteria increases, whereas the abundances of useful Ruminococcaceae and Lachnospiraceae belonging to the Clostridia class decrease in the gut microbiome in cirrhosis.
Analysis of the relationship between gut dysbiosis and the course of cirrhosis is complicated by several problems. The first is the fact that the only reliable method for analyzing the gut microbiota is sequencing, which is very expensive and requires a rare bioinformatics specialist. Therefore, the study of dysbiosis has not yet transcended the walls of scientific laboratories and entered clinical medicine.
The second problem is the interpretation of obtained data. The researcher acquires a huge amount of redundant data after sequencing. A generalizing indicator should be used to simplify the analysis. Several such indicators have been proposed, including the richness and diversity of microbiota, the Firmicutes/Bacteroidetes ratio [7], and the cirrhosis dysbiosis ratio (CDR) [5]. However, these indicators have various disadvantages; first of all, many of them have a weak theoretical basis. Thus, the proliferation of harmful bacteria can lead to an increase in the richness and diversity of microbiota. However, the proliferation of beneficial bacteria can lead to similar changes; therefore, an increase or decrease in these indicators cannot be correctly interpreted. Firmicutes is too heterogeneous and represented by useful members of the Сlostridia class as well as potentially pathogenic members of the Bacilli class. In addition, the Firmicutes/Bacteroidetes ratio does not take into account Proteobacteria that are the main potentially pathogenic bacteria. Bacteroidetes has a multifaceted effect on the macroorganism and cannot be considered as only harmful bacteria. Therefore, the Firmicutes/Bacteroidetes ratio may be useful for comparing the gut microbiota between countries, between individuals on different diets, or for assessing changes in the microbiota with age, but it cannot show how much better or worse the composition of the microbiota has become.
The CDR proposed by Bajaj et al [5] is based on the ratio of "good" to "bad" bacteria. However, it also has some disadvantages. Its values decrease with an increase in the severity of dysbiosis, which can lead to misinterpretation. Bacteroidaceae were among the "bad" bacteria, but they play a rather neutral role in the gut microbiome and are widely represented in the microbiomes of healthy individuals, especially in studies from Asian countries [4]. In addition, Bacteroidaceae, being strict anaerobes, cannot be subjects of bacterial translocation [8]. At the same time, the list of "bad" bacteria did not include Bacilli, which together with Enterobacteriaceae are responsible for bacterial translocation [8] and secondary infections[3, 9,10] in cirrhosis.
Thus, the development and testing of a pathogenetically-based dysbiosis ratio remains an important task. With this ratio, it will be possible to replace expensive and inaccessible sequencing with polymerase chain reaction (PCR) for selected taxa via automatic ratio calculation, which will allow for the introduction of gut dysbiosis tests into clinical practice.
The second important task of studying gut dysbiosis in cirrhosis is to clarify whether its presence affects the prognosis of patients.
Identifying a solution to these two problems is the aim of the present research.

Theoretical substantiation of the modified dysbiosis ratio
We used the CDR as a basis but flipped the equation such that the "bad" bacteria were in the numerator and the "good" bacteria were in the denominator. Therefore, our modified dysbiosis ratio (MDR) increased with aggravation of dysbiosis, which was less confusing in its interpretation. We considered Proteobacteria and Bacilli as "bad" bacteria since they are responsible for bacterial translocation as well as the development of secondary infections[3, [8][9][10] and their contents increase in cirrhosis [4,5]. We used the dominant taxa in healthy individuals, Clostridia and Bacteroidetes, as "good" bacteria. These taxa are strict anaerobes; therefore, they do not undergo bacterial translocation and do not cause extraintestinal secondary infections in cirrhosis[3, [8][9][10]. Clostridia predominate in the American population, where the Western diet is widespread, whereas Bacteroidetes are more common in the Asian population, where the Eastern diet is widespread [4,5]. Thus, the total accounting of these taxa is also intended to reduce the effect of diet on the value of the MDR. The abundance of Clostridia has been found to decrease with the development of cirrhosis [4,5]. The changes in Bacteroidetes abundance in cirrhosis appear to vary across different studies [4][5][6]. Thus, the pathogenesis-and evidence-based MDR was calculated as follows: [Bacilli (%) + Proteobacteria (%)]/[Clostridia (%) + Bacteroidetes (%)].

Patients
In this case-control prospective study, 113 consecutive patients with cirrhosis were admitted to the Department of Hepatology of Clinic for Internal Diseases, Gastroen-terology and Hepatology at Sechenov University (Moscow, Russia) and screened for inclusion. The study procedures were explained to potential participants, and written informed consent was obtained before enrollment. The present study was approved by the Ethics Committee of Sechenov University in accordance with the Declaration of Helsinki (№03- 16).
The inclusion criteria were as follows: diagnosis of cirrhosis verified by histology or clinical, biochemical, and ultrasound findings; and age between 18 and 70 years. The exclusion criteria were as follows: use of lactulose, lactitol, or other prebiotics, probiotics, antibiotics, or metformin in the past 6 wk; alcohol consumption in the past 6 wk; or inflammatory bowel disease, cancer, or any other serious disease. Of the original 113 patients screened for inclusion, 48 met the criteria and were enrolled in the study while 65 were excluded (Figure 1).
A study control group consisted of 21 healthy individuals who visited the clinic for routine health examinations during the same period.
The severity of liver disease was determined using the Child-Turcotte-Pugh (CTP) scoring system [11], in which class A was defined as compensated cirrhosis and classes B and C were defined as decompensated cirrhosis.

Gut microbiome analysis
The morning after admission, a stool sample was taken into a sterile disposable container and immediately frozen at -80 °C [12].
Deoxyribonucleic acid from the stool was isolated using the MagNa Pure Compact Nucleic Acid Isolation Kit I (Roche, Basel, Switzerland) according to the manufacturer's instructions. Libraries for sequencing were prepared by two rounds of PCR amplification. In the first round, specific primers for the v3-v4 region of the 16S ribosomal ribonucleic acid (RNA) gene were used: 16S-F: TCGTCGGCA-GCGTCAG-ATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG and 16S-R: GTCTCGTGG-GCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC.
After amplification, the PCR product was purified using AMPure XP magnetic beads (Beckman Coulter, Brea, CA, United States). Then, a second round of PCR was performed to attach specific adapters and enable multiplexing of the samples. To begin, 5 μL of the first PCR product was added to the reaction after ball cleaning with primers containing Illumina indices (Nextera XT Index v2 Primers; San Diego, CA, United States) and adapter sequences as well as 2 × KAPA HiFi HotStart ReadyMix. The amplification products were also purified using AMPure XP beads (Beckman Coulter). The concentrations of the prepared libraries were then measured using a Qubit 2.0 fluorimeter (London, United Kingdom) and quantitative PCR. The quality of the libraries was assessed using the Agilent 2100 Bioanalyzer (Santa Clara, CA, United States). The libraries were mixed in equal proportions and diluted to the required concentration to be run on a MiSeq (Illumina) device. Pair-end readings of 300 + 300 nucleotides were obtained. Reads were trimmed from the 3'-tail with Trimmomatic (Illumina) and then merged into a single amplicon with the MeFiT tool [13,14]. We did not perform operational taxonomic unit picking; instead, we classified amplicon sequences with the Ribosomal Database Project (RDP) classifier and RDP database [15].

Follow-up
The patients were contacted by phone every 3 mo to confirm that they were alive. If there was no answer, we contacted the patient's relatives by phone to find out if the patient was alive or dead. If it was not possible to contact them, we studied patient electronic medical records in the United Medical Information and Analytical System of Moscow, in which death registration data are entered. The follow-up period was 4 years.

Statistical analysis
Statistical analysis was performed with STATISTICA 10 (StatSoft Inc., Tulsa, OK, United States) and SPSS Statistics (IBM SPSS, Armonk, NY, United States) software. The data are presented as medians (interquartile ranges). Differences between continuous variables were assessed with the Mann-Whitney test because many variables were not distributed normally. Fisher's exact test was used to assess the differences between categorical variables. Survival was assessed using the Kaplan-Meier estimator and Cox regression test. A Cox regression model was constructed to assess the influence of various factors on patient survival and hazard ratios (HRs). Correlations between variables were computed using Spearman's rank correlation. P values ≤ 0.05 were considered as statistically significant.  If we used the median MDR (0.064) as a cutoff point, then the group of patients with cirrhosis could be divided into patients with severe (n = 24) and non-severe (n = 24) dysbiosis ( Figure 1).
The abundance of useful Clostridia was reduced and that of harmful Bacilli was increased, whereas the abundance of harmful Enterobacteriaceae was not significantly changed in patients with non-severe dysbiosis compared to healthy controls. The abundance of Clostridia further decreased, the abundance of Bacilli further increased, and the abundance of Enterobacteriaceae also increased in patients with severe dysbiosis. Interestingly, an increase in the abundance of Bifidobacteriaceae considered beneficial to the gut microbiome was also observed in cirrhosis without significant differences between groups with different degrees of dysbiosis. The abundance of Bacteroidetes did not differ significantly between patients with cirrhosis and healthy individuals (Table 1).
There were no significant differences in age, body mass index, sex distribution, and etiology of cirrhosis between patients with severe and non-severe dysbiosis. Patients with severe dysbiosis had lower serum albumin and cholinesterase levels, higher CTP scale values, and higher C-reactive protein levels. Although the incidences of ascites, esophageal varices, and hepatic encephalopathy were higher in patients with severe dysbiosis than in those with non-severe dysbiosis, these differences did not reach the significance level. There were no differences between the groups of patients in red blood cell, white blood cell, and platelet counts; creatinine, sodium, potassium, and glucose levels; and aminotransferase, alkaline phosphatase, and gamma-glutamate transferase activities ( Table 2).
The  The mortality rate of patients with severe dysbiosis was significantly higher than that of patients with non-severe dysbiosis (54.2% vs 12.5%; P = 0.001). Moreover, the difference in mortality was insignificant in the first year of follow-up (20.8% vs 8.3%; P = 0.092) and significant in subsequent years of follow-up (33.4%

DISCUSSION
Translating scientific developments into clinical practice is a rather difficult task. The study of the gut microbiome in various diseases is becoming mainstream in modern science, but thus far, it has no applications in clinical practice. It is hindered by the high cost of sequencing the fecal microbiome and the shortage of bioinformatics specialists.
Therefore, an important step in introducing the study of gut dysbiosis into clinical practice is to replace this expensive method with a simpler and more affordable one. PCR is an ideal candidate to determine the content of selected taxa in feces, followed by a comprehensive assessment of the state of the gut microbiome.
The idea to conduct a comprehensive assessment of the state of the gut microbiome in cirrhosis originated with Bajaj and colleagues [5]. However, their CDR can be improved, which was one of the aims of our study.
Here, we modified the CDR to improve its analytical performance and show that it can be used to predict the death of patients.
First, we inverted the CDR equation, placing the abundance of "bad" bacteria in the numerator and the abundance of "good" bacteria in the denominator. Thus, the value May 27, 2021 Volume 13 Issue 5 of our MDR increases with the aggravation of dysbiosis, which is more logical. The original CDR decreases with the aggravation of dysbiosis, which can be confusing to interpret. Our MDR is based on the data regarding the role of various taxa in the pathogenesis of cirrhosis complications and changes in their abundance in cirrhosis. We excluded Bacteroidaceae from the list of "bad" bacteria since their role in the pathogenesis of cirrhosis is not clear, and the change in their abundance in the gut microbiome in cirrhosis varies according to different researchers. According to our data, it does not change significantly, according to Chen et al [4], it decreases, and according to Bajaj et al [5], it increases in compensated cirrhosis and decreases in decompensated cirrhosis, becoming almost the same as that in healthy individuals. On the contrary, in a study by Kakiyama et al [6], the abundance of Bacteroidaceae decreased with compensated cirrhosis and increased with decompensated cirrhosis. Instead, we added Bacilli to the list of "bad" bacteria, which, like Proteobacteria/Enterobacteriaceae, are responsible for bacterial translocation and the development of extraintestinal infections in cirrhosis [8][9][10]. The abundances of both of these taxa increased with cirrhosis according to all studies [4][5][6], including ours.
As "good" bacteria, we used the higher-level taxon Clostridia, which includes all taxa accounted as "good" bacteria in the CDR. The main problem is that the abundance of these taxa is highly dependent on diet [16,17]. Among healthy individuals, it was 90% in the Russian population (our data), approximately 45% in the American population [5], and approximately 30% in the Chinese population [4]. However, if you add to them to the abundance of Bacteroidetes, which changes in the opposite direction relative to Clostridia and Firmicutes [16,17], then the differences were not so large: 95%, 80%, and 90%, respectively. This dependence of the Bacteroidetes and Clostridia abundances on diet led to the fact that the value of the CDR in our population was more than an order of magnitude higher than in the original study. Thus, the addition of Bacteroidetes to the group of "good" bacteria can neutralize the effect of diet on MDR and allow it to be used in different populations.
In our study, we were able to show that despite the change in the order of values, the CDR retained its main characteristics: it was higher in healthy individuals, lower in patients with compensated cirrhosis, and minimal in patients with decompensated cirrhosis.
Both the CDR and MDR were useful in assessing the prognosis of patients with cirrhosis, but the analytical characteristics of our modification were higher. In particular, the MDR, unlike the CDR, made it possible to assess the long-term (more 1 year) prognosis of patients.
Interestingly, the different taxa included in the MDR had different effects on prognosis. Clostridia and Bacilli mainly determined the medium-term prognosis (death within a year), and Proteobacteria and Enterobacteriaceae determined the long-term prognosis (death over the subsequent 3 years). This finding may be due to the fact that Bacilli provide a more powerful translocation of living bacteria, which leads to faster death, whereas Enterobacteriaceae act mainly by translocating their endotoxin, which leads to a more delayed death.
Thus, we were able to show that the gut microbiome in cirrhosis can be comprehensively and reliably evaluated using targeted analysis of the most significant taxa, which will allow for replacing expensive and poorly available sequencing with cheaper and more affordable PCR for four indicators (Proteobacteria, Bacilli, Clostridia, and Bacteroidetes) that does not require interpretation by rare bioinformatics specialists.
This will be a big step forward in introducing the achievements of fundamental hepatology into clinical practice, as it will give doctors an instrument for assessing the state of the gut microbiome in their patients as well as determining how it is affected by drugs that are prescribed for the correction of dysbiosis. This reality reinforces the strength of our study.
In addition, our study is the first to describe the effect of gut dysbiosis on the prognosis of patients with cirrhosis, thereby confirming existing hypotheses about the important role of the gut-liver axis in the course of cirrhosis [3,[18][19][20][21]. This is its second strong point.
The limitation of our study is its small sample size, which did not prevent us from obtaining significant results. It should also be noted that patients with severe hepatic encephalopathy (grades 2-4) are typically not admitted to our clinic, so these patients were not included in our study. The question of whether our results can be transferred to this cohort of patients remains open. Since patients with infections received antibiotics before admission, which could change the composition of the gut microbiota, we excluded them from the study. None of the included patients developed infectious complications of cirrhosis during hospitalization. Thus, patients with infectious complications of cirrhosis were not included in our study, and it is not clear whether the results can be generalized to them. A larger study involving nonincluded patient populations should be provided to confirm the findings.
New studies are needed to evaluate how various methods (e.g., probiotics, prebiotics, antibiotics, and fecal transplantation) can correct dysbiosis by analyzing the MDR and how this correction can improve the prognosis of patients with cirrhosis.

CONCLUSION
In conclusion, we were able to improve the CDR as well as show that gut dysbiosis is associated with poor prognosis in cirrhosis. Thus, we have developed a methodological apparatus and scientific basis for the correction of gut dysbiosis in such patients.