189 Patients with CD N = 181 696 intestinal biopsies Clinical records Clinical characteristics Host gene expression Cell type deconvolution Mucosal microbiota Bulk mRNA sequencing 16S sequencing Inflammation status Montreal classification Dysbiosis status Condition 1 Condition 2 Condition 1 Condition 2 Context-specific host-microbiota networks Context-specific host-microbiota individual associations Treatment Non-IBD controls N = 16 Patients with UC N = 156 Figure 1 | Methodological workflow of the study. The study cohort consisted of 337 patients with IBD (CD: n=181, UC: n=156) and 16 non-IBD controls, from whom 696 intestinal biopsies were collected (IBD: n=640, controls: n=56) and processed to perform bulk mucosal mRNA-sequencing and 16S rRNA gene sequencing. Detailed phenotypic data were extracted from clinical records for all study participants. In total, 251 ileal biopsies (CD: n=186, UC: n=56, controls: n=9) and 445 colonic biopsies (CD: n=165, UC: n=233, controls: n=47) were included: 212 biopsies derived from inflamed regions and 484 from non-inflamed regions. Mucosal gene expression and bacterial abundances were systematically analyzed in relation to different (clinical) phenotypes: presence of tissue inflammation, Montreal disease classification, medication use (e.g. TNF-α-antagonists) and dysbiotic status. Pathway-based clustering and network analysis (Sparse-CCA and centrLCC analysis) and individual pairwise gene–taxa associations were investigated to identify host– microbiota interactions in different contexts. We then analyzed the degree to which mucosal microbiota could explain the variation in intestinal cell type–enrichment (estimated by deconvolution of bulk RNAseq data). To confirm our main findings, we used publicly available mucosal 16S and RNA-seq datasets for external validation.13 Mucosal host-microbe interactions in IBD
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