DOP30 Identifying dietary factors and metabolites that may promote healthier Crohn Disease microbiome and mucosal transcriptomics signals as future targets using Diet-Omics. (30th January 2023)

• Record Type: Journal Article
• Authors: Haberman Ziv, Y; Braun, T; Amir, A; Levhar, N; Toren, I; Malik, A; Neuman, S; Hadar, R; Efroni, G; Ben-Horin, S
• Is Part Of: Journal of Crohn's and colitis. Volume 17(2023)Supplement 1
• Page Start: i94
• Page End: i96
• Publication Date: 2023-01-30
• Subjects: Inflammatory bowel diseases -- Periodicals; 616.344005
• DOI: 10.1093/ecco-jcc/jjac190.0070
• Languages: English
• ISSNs: 1873-9946

Abstract

Abstract: Background: The increase in prevalence of Crohn Disease (CD) worldwide together with suboptimal results with current therapies mandate identification of new targets. We aimed to identify dietary components and metabolites linked with host and microbial factors to support targeting beneficial exposures. Methods: Analyses of the SOURCE Israeli sub-cohort included clinical, biomarkers, computerized food frequency questionnaire (FFQ), fecal metabolomics, mucosal terminal ileum (TI) transcriptomics, and microbiome. Results: 25 newly-diagnosed CD and 32 controls (median age 28 years, 53% males) were studied. MaAsLin multivariate analyses identified 13 increased and 74 decreased fecal metabolite in CD after controlling for age and gender (FDR<0.25) including the induction of N-Acetyl-putrescine, Cholate, and Tyramine, and reduction in Melatonin, Cytosine, Lipoic and Linolenic acid (Fig. 1). Using weighted gene co-expression network analysis together with functional annotation enrichments of the TI transcriptomics, we identified 7 gene co-expression modules that were significantly linked with CD. These modules showed no significant association with gender, age, BMI, or smoking but had strong associations with CRP and calprotectin (Fig. 2). Using a predefined gut microbial health index to summarize the microbial signals along the health-disease scale, we noted negative associations specifically with transcriptomics modules enriched for immune genes and functions. We then explored the directionality of the relationship with dietary and metabolomic features, which can rationalize decreasing their exposure if they correlate with disease, or increasing it if they correlate with control signals. Consumption of sugar, saturated fat, iodine, and selenium showed similar directionality as seen with disease; sugar and fat showed strongest associations with the epithelial innate defense module including DUOX2 and CEACAM5, and iodine and selenium were linked with the immune module that included OSM and CXCL8/9. In contrast, manganese and vitamin D consumption positively correlated with modules associated with controls and enriched in epithelial lipid processing and mitochondrial functions. Associations between fecal metabolites and host transcriptomics showed a robust signal identifying 237 significant associations (FDR<0.25). Most showed correlation with control-associated signals and an opposite direction to that seen with disease, which may justify testing them as beneficial interventions. Conclusion: Detailed Diet-Omics dataset can quantify dietary constituents and fecal metabolites directional impact on host TI transcriptome and on the microbiome, which can prioritize interventions for testing in preclinical models