Disease phenotype and genotype are associated with shifts in intestinal-associated microbiota in inflammatory bowel diseases

Abstract

Background: Abnormal host-microbe interactions are implicated in the pathogenesis of inflammatory bowel diseases. Previous 16S rRNA sequence analysis of intestinal tissues demonstrated that a subset of Crohn's disease (CD) and ulcerative colitis (UC) samples exhibited altered intestinal-associated microbial compositions characterized by depletion of Bacteroidetes and Firmicutes (particularly Clostridium taxa). We hypothesize that NOD2 and ATG16L1 risk alleles may be associated with these alterations.

Methods: To test this hypothesis, we genotyped 178 specimens collected from 35 CD, 35 UC, and 54 control patients for the three major NOD2 risk alleles (Leu 1007fs, R702W, and G908R) and the ATG16L1T300A risk allele, that had undergone previous 16S rRNA sequence analysis. Our statistical models incorporated the following independent variables: 1) disease phenotype (CD, UC, non-IBD control); 2) NOD2 composite genotype (NOD2(R) = at least one risk allele, NOD2(NR) = no risk alleles); 3) ATG16L1T300A genotype (ATG16L1(R/R), ATG16L1(R/NR), ATG16L1(NR/NR)); 4) patient age at time of surgery and all first-order interactions. The dependent variable(s) were the relative frequencies of bacterial taxa classified by applying the RDP 2.1 classifier to previously reported 16S rRNA sequence data.

Results: Disease phenotype, NOD2 composite genotype and ATG16L1 genotype were significantly associated with shifts in microbial compositions by nonparametric multivariate analysis of covariance (MANCOVA). Shifts in the relative frequencies of Faecalibacterium and Escherichia taxa were significantly associated with disease phenotype by nonparametric ANCOVA.

Conclusions: These results support the concept that disease phenotype and genotype are associated with compositional changes in intestinal-associated microbiota.

FIGURE 1

UniFrac analysis of CD risk alleles and enteric microbiota. The images show the results of UPGMA clustering of environments (A). ATG16L1 genotype in IBD patients (B). NOD2 genotype in IBD patients (C). ATG16L1 genotype in IBD and non-IBD control patients (D). NOD2 genotype in IBD and non-IBD control patients based on the UniFrac metric.24 Jackknife resampling (100 replicates) was performed to assess the statistical support for the topology of each tree. Nodes with high support are indicated by the fraction of trees in which the nodes were recovered (>50%: >50% to <70%; >70%: >70% to <90%; >90%: >90% to 100%).