The prevalence and transcriptional activity of the mucosal microbiota of ulcerative colitis patients

Active microbes likely have larger impact on gut health status compared to inactive or dormant microbes. We investigate the composition of active and total mucosal microbiota of treatment-naïve ulcerative colitis (UC) patients to determine the microbial picture at the start-up phase of disease, using both a 16S rRNA transcript and gene amplicon sequencing. DNA and RNA were isolated from the same mucosal colonic biopsies. Our aim was to identify active microbial members of the microbiota in early stages of disease and reveal which members are present, but do not act as major players. We demonstrated differences in active and total microbiota of UC patients when comparing inflamed to non-inflamed tissue. Several taxa, among them the Proteobacteria phyla and families therein, revealed lower transcriptional activity despite a high presence. The Bifidobacteriaceae family of the Actinobacteria phylum showed lower abundance in the active microbiota, although no difference in presence was detected. The most abundant microbiota members of the inflamed tissue in UC patients were not the most active. Knowledge of active members of microbiota in UC patients could enhance our understanding of disease etiology. The active microbial community composition did not deviate from the total when comparing UC patients to non-IBD controls

Multiple Polymorphisms Affect Expression and Function of the Neuropeptide S Receptor (NPSR1)

Peer reviewe

Integrative epigenome-wide analysis demonstrates that DNA methylation may mediate genetic risk in inflammatory bowel disease

Epigenetic alterations may provide important insights into gene-environment interaction in inflammatory bowel disease (IBD). Here we observe epigenome-wide DNA methylation differences in 240 newly-diagnosed IBD cases and 190 controls. These include 439 differentially methylated positions (DMPs) and 5 differentially methylated regions (DMRs), which we study in detail using whole genome bisulphite sequencing. We replicate the top DMP (RPS6KA2) and DMRs (VMP1, ITGB2 and TXK) in an independent cohort. Using paired genetic and epigenetic data, we delineate methylation quantitative trait loci; VMP1/microRNA-21 methylation associates with two polymorphisms in linkage disequilibrium with a known IBD susceptibility variant. Separated cell data shows that IBD-associated hypermethylation within the TXK promoter region negatively correlates with gene expression in whole-blood and CD8+ T cells, but not other cell types. Thus, site-specific DNA methylation changes in IBD relate to underlying genotype and associate with cell-specific alteration in gene expression

Deep Resequencing of GWAS Loci Identifies Rare Variants in <i>CARD9</i>, <i>IL23R</i> and <i>RNF186</i> That Are Associated with Ulcerative Colitis

Genome-wide association studies and follow-up meta-analyses in Crohn's disease (CD) and ulcerative colitis (UC) have recently identified 163 disease-associated loci that meet genome-wide significance for these two inflammatory bowel diseases (IBD). These discoveries have already had a tremendous impact on our understanding of the genetic architecture of these diseases and have directed functional studies that have revealed some of the biological functions that are important to IBD (e.g. autophagy). Nonetheless, these loci can only explain a small proportion of disease variance (~14% in CD and 7.5% in UC), suggesting that not only are additional loci to be found but that the known loci may contain high effect rare risk variants that have gone undetected by GWAS. To test this, we have used a targeted sequencing approach in 200 UC cases and 150 healthy controls (HC), all of French Canadian descent, to study 55 genes in regions associated with UC. We performed follow-up genotyping of 42 rare non-synonymous variants in independent case-control cohorts (totaling 14,435 UC cases and 20,204 HC). Our results confirmed significant association to rare non-synonymous coding variants in both IL23R and CARD9, previously identified from sequencing of CD loci, as well as identified a novel association in RNF186. With the exception of CARD9 (OR = 0.39), the rare non-synonymous variants identified were of moderate effect (OR = 1.49 for RNF186 and OR = 0.79 for IL23R). RNF186 encodes a protein with a RING domain having predicted E3 ubiquitin-protein ligase activity and two transmembrane domains. Importantly, the disease-coding variant is located in the ubiquitin ligase domain. Finally, our results suggest that rare variants in genes identified by genome-wide association in UC are unlikely to contribute significantly to the overall variance for the disease. Rather, these are expected to help focus functional studies of the corresponding disease loci. © 2013 Beaudoin et al

Contribution of the NOD1/CARD4 insertion/deletion polymorphism +32656 to inflammatory bowel disease in northern Europe

Background: NOD1/CARD4 and NOD2/CARD15 are both intracellular pattern-recognition receptors. The NOD1/CARD4 gene lies within a previously described inflammatory bowel disease (IBD) locus (7p14). An association has been suggested between the NOD1/CARD4+32656 deletion*1 variant of a complex deletion*1/insertion*2 polymorphism and IBD in 1 recent study in Europe. Our aim was to assess the influence of NOD1/CARD4+32656 on disease susceptibility and phenotype in the Scottish and Swedish IBD populations. Methods: A total of 3,962 individuals (1,791 IBD patients, 522 parents, 1,649 healthy controls) from 2 independent populations (Scotland and Sweden) were genotyped for NOD1/CARD4+32656 A/C by TaqMan and direct sequencing. Case-control, Transmission Disequilibrium Testing (TDT) and detailed genotype–phenotype (Montreal) analyses were performed. The case-control analysis had 80% power to detect an effect size of odds ratio (OR) 1.21 for IBD. Results: In case-control analyses in Scottish and Swedish patients, none of the genotypes studied in IBD, Crohn's disease (CD) or ulcerative colitis (UC), differed significantly from controls (deletion*1 allelic frequency 73.9%, 73.6%, 73.9%, and 73.6%, respectively: all P > 0.8). No epistatic interaction with NOD2/CARD15 was seen for CD susceptibility. TDT analysis in our Scottish early onset cohort was negative. Conclusions: This variant allele of NOD1/CARD4+32656 is not associated with a strong effect on susceptibility to IBD in children and adults in Northern Europe. A gene-wide haplotype-based approach may be preferable to analysis of individual variants to assess the contribution of the NOD1/CARD4 gene to IBD. </p

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers