201 Figure 5 | Fibrostenotic CD and TNF-α-antagonist usage significantly alter mucosal host–microbe interactions in the context of IBD. CentrLCC-network analyses were performed to characterize altered mucosal host–microbe interactions between different patient phenotypes. Overall, fibrostenotic CD (Montreal B2 vs. non-stricturing, non-penetrating CD, i.e. Montreal B1) and use of TNF-α-antagonists (vs. nonusers) demonstrated significant modulation of observed mucosal host–microbe associations. a, Network graphs showing microbiota–gene association networks in patients with non-stricturing, non-penetrating CD (Montreal B1) (left) and patients with fibrostenotic CD (Montreal B2) (right). When comparing these patient groups, 5 bacterial taxa and 2,639 host genes were significantly different (FDR<0.05). Four of the five bacterial taxa were significantly altered in fibrostenotic CD vs. non-stricturing, non-penetrating CD, and Lachnoclostridium was the top bacteria involved (covering 63% of total associations in non-stricturing, nonpenetrating CD and decreasing to 27% in fibrostenotic CD). In general, patients with fibrostenotic CD were characterized by a loss of Lachnoclostridium–gene interactions. Red dots indicate gut microbiota. Blue dots indicate hub genes. Gray fields indicate the main pathways represented by the associated genes. Yellow lines indicate positive associations between gene expression and bacterial abundances. Light blue lines indicate negative associations. b, Key examples of Lachnoclostridium–gene interactions that were significantly altered in patients with fibrostenotic CD compared to patients with non-stricturing, non-penetrating CD, including genes involved in immunoregulatory interactions between lymphoid and non-lymphoid cells and tyrosine kinase signaling (CD8A and CXCR5). c, Network graphs showing microbiota–gene interaction networks in patients not using TNF-α-antagonists (left) vs. patients using TNF-α-antagonists (right). When comparing both groups, 3 bacterial groups and 513 genes were differentially abundant (FDR<0.05). Among these, a single bacterial group, represented by Ruminococcaceae_UCG_002, was altered in interactions with host genes in patients using TNF-α-antagonists. d, Key examples of Ruminococcaceae–UCG_002–gene interactions significantly altered in TNF-α-antagonists users vs. non-users. These genes were involved in general biological processes such as the cell cycle but also included genes involved in fatty acid metabolism (PDK4 and ACAA1). Mucosal host–microbe interactions depend on individual dysbiotic status As patients with IBD have microbial dysbiosis compared to healthy individuals, we hypothesized that the strength and/or direction of the individual gene–bacteria interactions may depend on the microbial community (eubiosis vs dysbiosis). We therefore performed PCA on the microbiota data and calculated dysbiosis scores for all patients and controls, as represented by the median Aitchison’s distances to non-IBD controls (Figure 6A). Patients with IBD demonstrated higher dysbiosis scores compared to controls (CD vs. non-IBD: P=5.1x10-8, UC vs. non-IBD: P=0.0015), but there was no clear difference between patients with CD and UC (Figure 6B). When comparing patients with IBD above and below the 90th percentile of dysbiosis scores,13 204 individual gene–bacteria interactions showed significant dependence on microbial dysbiosis (Figure 6C, Supplementary Table S24) (FDR<0.05). We also performed permutation tests, which confirmed that the significant interactions were not observed by chance (Methods, FDR<0.05). In one example of these interactions, expression of the PLAUR gene encoding for the urokinase plasminogen activator surface receptor was positively associated with Lachnospiraceae abundance, but this shifted to an inverse association when only considering individuals with a Mucosal host-microbe interactions in IBD
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