P032 Host transcriptome signatures in human fecal-washes predict histological remission in IBD patients
Ungar, B.(1);Yavzori, M.(1);Fudim, E.(1);Picard, O.(1);Kopylov, U.(1);Eliakim, R.(1);Shouval, D.(2);Levin, Y.(3);Savidor, A.(3);Ben-Moshe, S.(4);Manco, R.(4);Dan, S.(4);Egozi, A.(4);Bahar Halpern, K.(4);Mayer, C.(5);Barshak, I.(5);Ben-Horin, S.(1);Itzkovitz, S.(4);
(1)Tel-HaShomer Sheba Medical Center, Department of Gastroenterology, Ramat Gan, Israel;(2)Schneider Children’s Medical Center, Gastroentreology- Nutrition and Liver Diseases, Petah Tikva, Israel;(3)The Nancy and Stephen Grand Israel National Center for Personalized Medicine, The De Botton Institute for Protein Profiling, Rehovot, Israel;(4)Weizmann Institute of Science- Rehovot- Israel, Molecular Cell Biology, Rehovot, Israel;(5)Sheba Medical Center Tel Hashomer, Pathology Institute, Ramat Gan, Israel;
Colonoscopy is the gold standard for evaluation of inflammation in inflammatory bowel diseases (IBD), yet entails cumbersome preparations and risks of injury. Existing non-invasive prognostic tools are limited in their diagnostic power. Moreover, transcriptomics of colonic biopsies have been inconclusive in their association with clinical features. Our aim was to assess the utility of host transcriptomics of fecal wash samples of IBD patients compared to controls.
In this prospective cohort study, we obtained biopsies and fecal-wash samples from IBD patients and controls undergoing lower endoscopy. We performed RNAseq of biopsies and matching fecal-washes, and associated them with endoscopic and histological inflammation status. We also performed fecal mass-spectrometry proteomics on a subset of samples. We inferred cell compositions using computational deconvolution and used classification algorithms to identify informative genes.
We analyzed biopsies and fecal washes from 39 patients (19 IBD, 20 controls). Host fecal-transcriptome carried information that was distinct from biopsy RNAseq and fecal proteomics. Transcriptomics of fecal washes, yet not of biopsies, from patients with histological inflammation were significantly correlated to one another (p=5.3*10-12). Fecal-transcriptome was significantly more powerful in identifying histological inflammation compared to transcriptome of intestinal biopsies (150 genes with area-under-the-curve >0.9 in fecal samples versus 10 genes in biopsy RNAseq). Fecal samples were enriched in inflammatory monocytes, regulatory T cells, natural killer-cells and innate lymphoid cells.
Figure 1 - Fecal-wash host transcriptome predicts histological inflammation. A) Study layout, B) Clustergram of fecal-wash host cell mRNA signatures, demonstrating that patients with histological inflammation (red) are clustered when measuring fecal wash transcriptome yet not biopsy transcriptomes. C-D) Principle Component Analysis demonstrating improved separation of inflamed patients based on fecal host transcriptomes. E, F) Expression of host genes in fecal washes has higher statistical power (Area under the Curve, AUC) in classifying histological inflammation compared to biopsies. D shows NFKBIA as an example, E shows the AUC of the 5% best classifying genes, F shows the overall AUC based on biopsies or washes. Gray areas have AUC>0.9. G) UMAP of cells obtained from scRNAseq of mouse small intestine fecal washes.
Fecal wash host transcriptome is a powerful biomarker reflecting histological inflammation. Furthermore, it opens the way to identifying important correlates and therapeutic targets that may be obscure using biopsy transctriptomics.