DOP30 Cross-ethnic microbiome analyses identify shared and specific signals for Northern Indian IBD patients

Abstract

Abstract Background Clinical manifestation of the inflammatory bowel disease (IBD) shows considerable variation across the world. We hypothesized these differences may be influenced by geographical differences in gut microbiome. To test this, we investigated the correlation between gut microbiota and the disease phenotypes of IBD in a cohort form the Northern part of India. Methods Stool samples and clinical metadata were collected from 226 IBD patients (198 ulcerative colitis and 28 Crohn’s disease) and 66 controls from a population cohort from the Northern India. We used metagenomic shotgun sequencing to determine diversity, composition and function of the gut microbiota of the participants. Microbiome was then associated to IBD and its subtypes and clinical metadata (e.g. medication use, drug response, and disease activity). We replicated our results in 436 IBD patients and 903 population controls from the Netherlands analyzed using an identical workflow and used machine learning to assess how well do the Indian IBD signals generalize to Dutch IBD. Results We identified reduction in microbiome diversity and changes in beta diversity in Indian IBD patients (FDR < 0.05, replicated in Dutch population) and identified that 319 taxa and 71 biochemical pathways are altered in Indian patients (FDR < 0.05). Of note, 39% of these signals were replicated in the Dutch cohort (at FDR < 0.05 level). We identified strong dysbiosis shared across Indian and Dutch IBD patients, characterized by expansion of opportunistic pathogens (e.g. Genera Clostridium, Streptococcus and Lactobacilli) and oral bacteria (e.g. Streptococcus oralis and Bifidobacterium dentium) as well as reduction in butyrate producers such as Faecalibacterium prausnitzii, Roseburia hominis and Blautia massiliensis. In addition, we found novel pathobionts specific to the Indian cohort (including oral bacteria from Genus Scardovia and Oribacterium; Actinomyces dentalis and Klebsiella pneumoniae). Machine-learning models trained on the Indian cohort were highly predictive in the Indian test set (Sensitivity 0.84, Specificity 0.95) and generalized to Dutch cohort (Sensitivity 0.77, Specificity 0.69). In addition to IBD-associated dysbiosis, we identified links between medication use and gut microbiota independent of the disease activity: use of Tofacitinib (used by 26 UC patients) was linked to decrease in Lactobacilliales and increase in Clostridia, while Prednisolone and Azathioprine associated to reduction in Roseburia and increase in Streptococcus and Granulicatella. Conclusion The IBD patients from Northern India show gut dysbiosis similar to European patients, but also show enrichment in India-specific pathobionts. The microbiome-based diagnostic models generalize across these populations.