A Novel Microbial Dysbiosis Index and Intestinal Microbiota-Associated Markers as Tools of Precision Medicine in Inflammatory Bowel Disease Paediatric Patients

Abstract

Recent evidence indicates that the gut microbiota (GM) has a significant impact on the inflammatory bowel disease (IBD) progression. Our aim was to investigate the GM profiles, the Microbial Dysbiosis Index (MDI) and the intestinal microbiota-associated markers in relation to IBD clinical characteristics and disease state. We performed 16S rRNA metataxonomy on both stools and ileal biopsies, metabolic dysbiosis tests on urine and intestinal permeability and mucosal immunity activation tests on the stools of 35 IBD paediatric patients. On the GM profile, we assigned the MDI to each patient. In the statistical analyses, the MDI was correlated with clinical parameters and intestinal microbial-associated markers. In IBD patients with high MDI, Gemellaceae and Enterobacteriaceae were increased in stools, and Fusobacterium, Haemophilus and Veillonella were increased in ileal biopsies. Ruminococcaceae and WAL_1855D were enriched in active disease condition; the last one was also positively correlated to MDI. Furthermore, the MDI results correlated with PUCAI and Matts scores in ulcerative colitis patients (UC). Finally, in our patients, we detected metabolic dysbiosis, intestinal permeability and mucosal immunity activation. In conclusion, the MDI showed a strong association with both severity and activity of IBD and a positive correlation with clinical scores, especially in UC. Thus, this evidence could be a useful tool for the diagnosis and prognosis of IBD.

Keywords: biomarkers; disease severity; gut microbiota; inflammatory bowel disease (IBD); intestinal permeability; metabolic dysbiosis; microbial dysbiosis index (MDI); mucosal immunity activation.

Figure 1

Faecal microbiota fingerprint of 35 IBD patients stratified based on MDI (mild = 8, moderate = 19, high = 8). (A) Principal component analysis (PCA) plot for multivariate unsupervised analysis. (B) Linear discriminant analysis (LDA) plot on linear discriminant analysis effect size (LEfSe) univariate analysis.

Figure 2

Gut MDI as a function of disease characteristics. (A) Histogram of MDI in patients grouped for disease localisation. Kruskal–Wallis p-value > 0.05. (B) LDA plot on LEfSe univariate analysis applied to GM profiles of patients stratified for disease localisation. (C) Histogram of MDI in patients grouped for disease activity status. Mann–Whitney test p-value > 0.05. (D) LDA plot on LEfSe univariate analysis applied to GM profiles of patients stratified for disease activity status.

Figure 3

GM profiles associated with UC and CD. (A) PCA plot of UC and CD microbiota profiles. (B) LDA plot of LEfSe univariate analysis for the comparison between UC and CD microbiota profiles. (C) Box plot of intestinal MDI of CD compared with UC. (D) LDA plot of LEfSe univariate analysis of microbiota profiles for the comparison of UC patients stratified for disease activity. (E) Box plot of the gut MDI of UC patients stratified for disease activity. (Mann–Whitney test p-value = 0.1). (F) Fitted line plot of intestinal MDI and PUCAI (Paediatric Ulcerative Colitis Activity Index). The regression analysis revealed the presence of correlation between these two variables (R2-value = 0.71; p-value = 0.004). Each sample is represented by a dot. (G) LDA plot of LEfSe univariate analysis of microbiota profiles for the comparison of CD patients stratified for disease activity. (H) Box plot of the gut MDI of CD patients stratified for disease activity (Kruskal–Wallis test p-value 0.36). (I) Fitted line plot of intestinal MDI and PCDAI (Paediatric Crohn’s Disease Activity Index). The regression analysis revealed the absence of correlation between these two variables (R2-value = 0.11; p-value = 0.65). Each sample is represented by a dot.

Figure 4

PICRUSt2 functional prediction using the KEGG pathway database. Metabolic biomarkers associated with mild dysbiosis in IBD. LEfSe analysis was performed (LDA score > 3.3).

Figure 5

Principal component analysis (PCA) plot for multivariate unsupervised analysis for ileal IBD microbiota profile. (A) Ileal microbiota stratified for dysbiosis degree. (B) Ileal microbiota in CD and in UC.

Figure 6

Spearman’s correlation analysis between genus level in faecal microbiota and ileal microbiota. Each node refers to faecal bacteria (orange circles) and ileal bacteria (blue circles). Green and red edges indicate positive and negative correlation values, respectively (filtered to p-value < 0.05).

Figure 7

Metabolic dysbiosis, intestinal permeability and mucosal immune activation. Box plots of indican, Zpn and IgA levels measured in the IBD cohort (green for normal levels, yellow for subnormal levels and red for elevated levels). Each sample is represented by a dot.