Effect of Artificial Liver Support Systems on Gut Microbiota in Patients with HBV-Related Acute-on-Chronic Liver Failure

Abstract

Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a rare and severe form of end-stage liver disease with high mortality; gut microbes are strongly associated with the development of this severe liver disease but the exact association is unclear. Artificial liver support systems (ALSS) are clinically important in prolonging the waiting time for liver transplantation and in aiding drug therapy to achieve remission. The aim of this study was to investigate the effect of ALSS on the abundance and diversity of microorganisms in the gut of HBV-ACLF patients. In this study, 109 stool samples were collected from patients with hepatitis B virus-associated acute chronic liver failure (HBV-ACLF) for 16S rRNA sequencing. Among them, 44 samples were from patients treated with ALSS therapy as an adjunct to standard medical treatment (SMT) and 65 were from patients receiving SMT only. Analysis of the sequencing results suggested that there were significant differences in the abundance and diversity of gut microbiota between the with-ALSS and without-ALSS groups (p < 0.05). The operational taxonomic units and Shannon indexes indicated that the diversity and abundance of the gut microbiome, while decreasing after the first ALSS treatment, gradually increased after an increase in the number of ALSS therapies. The overall proportion of HBV-ACLF patients with coinfection was 27.59%; the coinfection can reduce the abundance of the Bacteroidetes phylum in the microbiome significantly whereas Proteobacteria were highly enriched. After ALSS therapy, HBV-ACLF patients had a decrease in potentially harmful bacteria, an increase in potentially beneficial bacteria, an increase in the diversity of the intestinal microbiota, and the intestinal microecological disorders were corrected to a certain extent. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBIL) levels, as well as the international normalized ratio (INR), showed a decreasing trend whereas plasminogen activity (PTA) increased and the condition of patients with HBV-ACLF progressed in a favorable direction. In addition, the abundance of Blautia and Coprococcus was negatively correlated with TBIL and INR, positively correlated with PTA, and positively correlated with disease recovery. Our study shows that ALSS can alter the composition of the gut microbiota and have an ameliorating effect on the gut microecological imbalance in HBV-ACLF patients. It is worth mentioning that Blautia and Coprococcus may have great potential as biomarkers.

Keywords: acute-on-chronic liver failure; artificial liver support system; blood biochemical indicators; gut microbiota; hepatitis B virus.

Figure 1

Changes in blood biochemical indicators in 15 patients with HBV-ACLF before and after artificial liver support therapy. Pre (before ALSS, green bar chart), post (after ALSS, blue bar chart), and the letters a–o represent each of these 15 HBV-ACLF patients. (A) ALT: alanine aminotransferase. (B) AST: aspartate aminotransferase. (C) ALB: albumin. (D) TBIL: total bilirubin. (E) PTA: prothrombin activity. (F) INR: international normalized ratio. (G) WBC: white blood cell. (H) NEUT: neutrophil.

Figure 2

Distribution of gut microbiota in the with-ALSS and without-ALSS groups. Different colours in A and B represent different phyla or genera of gut microbes, and different colours in C and D represent different subgroups. (A) Relative abundance of gut microbiota at the phylum level in the with-ALSS and without-ALSS groups. (B) Relative abundance of gut microbiota at the genus level in the with-ALSS and without-ALSS groups. (C) Simpson, Shannon, chao1, and otus diversity index of the with-ALSS and without-ALSS groups. (D) PCoA plot based on the weighted unifrac distance of the with-ALSS and without-ALSS groups.

Figure 3

Distribution of gut microbiota in the pre- and post-groups. Different colours in A and B represent different phyla or genera of gut microbes, and different colours in C and D represent different subgroups. (A) Relative abundance of gut microbiota at the phylum level in the pre- and post-groups. (B) Relative abundance of gut microbiota at the genus level in the pre- and post-groups. (C) Shannon index (p = 0.037) and otus index (p = 0.028) of the pre- and post-groups (p < 0.05 from t-test). (D) PCoA plot based on the weighted unifrac distance of the pre- and post-groups.

Figure 4

Distribution of gut microbiota in T0, T1, T2, and T3 groups. Different colours in A and B represent different phyla or genera of gut microbes, and different colours in C and D represent different subgroups. (A) Relative abundance of gut microbiota at the phylum level in T0, T1, T2, and T3 groups. (B) Relative abundance of gut microbiota at the genus level in T0, T1, T2, and T3 groups. (C) Chao1 index of T0, T1, T2, and T3 groups (p = 0.035 from t-test). (D) PCoA plot based on the weighted unifrac distance of T0, T1, T2, and T3 groups (p < 0.05, permutation test).

Figure 5

Distribution of gut microbiota in the infected and uninfected groups. Different colours in A and B represent different phyla or genera of gut microbes, and different colours in C and D represent different subgroups. (A) Relative abundance of gut microbiota at the phylum level in the infected and uninfected groups. (B) Relative abundance of gut microbiota at the genus level in the infected and uninfected groups. (C) Simpson and Shannon index of T0, T1, T2, and T3 groups. (D) PCoA plot based on the weighted unifrac distance of the infected and uninfected groups.

Figure 6

Correlation analysis of genus abundance with patient’s blood biochemical indicators (plus and asterisk both mean p < 0.05). * denotes statistical significance, + denotes more significant statistical significance.