Targeted Analysis of the Gut Microbiome for Diagnosis, Prognosis and Treatment Individualization in Pediatric Inflammatory Bowel Disease.
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ABSTRACT:
SUBMITTER: Olbjorn C
PROVIDER: S-EPMC9319120 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Inflammatory bowel disease (IBD) is a chronic disease of unknown etiology which mostly involves the intestine and requires a personalized approach for treatment. IBD represents a heterogeneous group of patients with inherently variable disease courses. Hence, the heterogeneity of patient populations may delay the diagnosis, clinical practice and initiation of appropriate treatment. Use of biomarkers for diagnosis and management of IBD is still necessary. Descriptions of the immunological pathway abnormalities in IBD improve assessment to identify the patient's disease status, and relative risk of progression to complicated disease behaviors, and this information may ultimately influence therapeutic decisions. In this study, we try to explain the role of biomarkers in early diagnosis, estimating prognosis, and target agents for correct managements of IBD's patients. This information might be important to provide insight into emerging panels of multiple IBD biomarkers and highlighting the essential role of personalizes panel for each patient.
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Project description:Inflammatory bowel disease (IBD) is a group of chronic diseases of the digestive tract that affects millions of people worldwide. Genetic, environmental and microbial factors have been implicated in the onset and exacerbation of IBD. However, the mechanisms associating gut microbial dysbioses and aberrant immune responses remain largely unknown. The integrative Human Microbiome Project seeks to close these gaps by examining the dynamics of microbiome functionality in disease by profiling the gut microbiomes of >100 individuals sampled over a 1-year period. Here, we present the first results based on 78 paired faecal metagenomes and metatranscriptomes, and 222 additional metagenomes from 59 patients with Crohn's disease, 34 with ulcerative colitis and 24 non-IBD control patients. We demonstrate several cases in which measures of microbial gene expression in the inflamed gut can be informative relative to metagenomic profiles of functional potential. First, although many microbial organisms exhibited concordant DNA and RNA abundances, we also detected species-specific biases in transcriptional activity, revealing predominant transcription of pathways by individual microorganisms per host (for example, by Faecalibacterium prausnitzii). Thus, a loss of these organisms in disease may have more far-reaching consequences than suggested by their genomic abundances. Furthermore, we identified organisms that were metagenomically abundant but inactive or dormant in the gut with little or no expression (for example, Dialister invisus). Last, certain disease-specific microbial characteristics were more pronounced or only detectable at the transcript level, such as pathways that were predominantly expressed by different organisms in patients with IBD (for example, Bacteroides vulgatus and Alistipes putredinis). This provides potential insights into gut microbial pathway transcription that can vary over time, inducing phenotypical changes that are complementary to those linked to metagenomic abundances. The study's results highlight the strength of analysing both the activity and the presence of gut microorganisms to provide insight into the role of the microbiome in IBD.
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Project description:The inflammatory bowel diseases (IBDs), which include Crohn's disease (CD) and ulcerative colitis (UC), are multifactorial chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome-the molecular interface between host and microbiota-are less well understood. To address this gap, we performed untargeted metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n = 155) and validation (n = 65) cohorts of CD, UC and non-IBD control patients. Metabolomic and metagenomic profiles were broadly correlated with faecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While > 50% of differentially abundant metabolite features were uncharacterized, many could be assigned putative roles through metabolomic 'guilt by association' (covariation with known metabolites). Differentially abundant species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between differentially abundant species and well-characterized differentially abundant metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets.
| S-EPMC6342642 | biostudies-literature
Project description:Inflammatory bowel disease (IBD) is characterized by flares of inflammation with a periodic need for increased medication and sometimes even surgery. The aetiology of IBD is partly attributed to a deregulated immune response to gut microbiome dysbiosis. Cross-sectional studies have revealed microbial signatures for different IBD subtypes, including ulcerative colitis, colonic Crohn's disease and ileal Crohn's disease. Although IBD is dynamic, microbiome studies have primarily focused on single time points or a few individuals. Here, we dissect the long-term dynamic behaviour of the gut microbiome in IBD and differentiate this from normal variation. Microbiomes of IBD subjects fluctuate more than those of healthy individuals, based on deviation from a newly defined healthy plane (HP). Ileal Crohn's disease subjects deviated most from the HP, especially subjects with surgical resection. Intriguingly, the microbiomes of some IBD subjects periodically visited the HP then deviated away from it. Inflammation was not directly correlated with distance to the healthy plane, but there was some correlation between observed dramatic fluctuations in the gut microbiome and intensified medication due to a flare of the disease. These results will help guide therapies that will redirect the gut microbiome towards a healthy state and maintain remission in IBD.
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Project description:Patients with inflammatory bowel disease (IBD) wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiome's composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools. We collected fifteen 16S rRNA microbiome datasets (7,707 samples) from North America to benchmark combinations of gut microbiome features, data normalization and transformation methods, batch effect correction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with two binary classification metrics following leave-one-dataset-out cross (LODO) validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features processed with a compositional transformation method and batch effect correction with the naive zero-centering method attain the best classification performance. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics. These findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.
| S-EPMC8895431 | biostudies-literature
Project description:ObjectivesInflammatory bowel diseases (IBD), comprised of Crohn's disease (CD) and ulcerative colitis (UC), are characterized by a complex pathophysiology that is thought to result from an aberrant immune response to a dysbiotic luminal microbiota in genetically susceptible individuals. New technologies support the joint assessment of host-microbiome interaction.MethodsUsing whole genome sequencing and shotgun metagenomics, we studied the clinical features, host genome, and stool microbial metagenome of 85 IBD patients, and compared the results to 146 control individuals. Genetic risk scores, computed on 159 single nucleotide variants, and human leukocyte antigen (HLA) types differentiated IBD patients from healthy controls.ResultsGenetic risk was associated with the need for use of biologics in IBD and, modestly, with the composition of the gut microbiome. As compared with healthy controls, IBD patients had hallmarks of stool microbiome dysbiosis, with loss of a diversified core microbiome, enrichment and depletion of specific bacteria, and enrichment of bacterial virulence factors.ConclusionsWe show that genetic risk may have a role in early risk stratification in the care of IBD patients and propose that expression of virulence factors in a dysbiotic microbiome may contribute to pathogenesis in IBD.
| S-EPMC5795019 | biostudies-literature
Project description:In view of the increasing evidence that commonly prescribed, non-antibiotic drugs interact with the gut microbiome, we re-examined the microbiota variance in inflammatory bowel disease (IBD) to determine the degree to which medication and supplement intake might account for compositional differences between disease subtypes and geographic location. We assessed the confounding effects of various treatments on the faecal microbiota composition (16S rRNA gene sequencing) in persons with Crohn's disease (CD; n = 188) or ulcerative colitis (UC; n = 161) from either Cork (Ireland) or Manitoba (Canada) sampled at three time points. The medication profiles between persons with UC and CD and from different countries varied in number and type of drugs taken. Among Canadian participants with CD, surgical resection and overall medication and supplement usage is significantly more common than for their Irish counterparts. Treatments explained more microbiota variance (3.5%) than all other factors combined (2.4%) and 40 of the 78 tested medications and supplements showed significant associations with at least one taxon in the gut microbiota. However, while treatments accounted for a relatively small proportion of the geographic contribution to microbiome variance between Irish and Canadian participants, additive effects from multiple medications contributed significantly to microbiome differences between UC and CD.
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Project description:The human microbiome is of considerable interest to pediatric inflammatory bowel disease (PIBD) researchers with 1 potential mechanism for disease development being aberrant immune handling of the intestinal bacteria. This study analyses the fecal microbiome through treatment in newly diagnosed PIBD patients and compares to cohabiting siblings where possible. Patients were recruited on clinical suspicion of PIBD before diagnosis. Treatment-naïve fecal samples were collected, with further samples at 2 and 6 weeks into treatment. Samples underwent 16S ribosomal ribonucleic acid (RNA) gene sequencing and short-chain fatty acids (SCFAs) analysis, results were analyzed using quantitative-insights-into-microbial-ecology. Six PIBD patients were included in the cohort: 4 Crohn disease (CD), 1 ulcerative colitis (UC), 1 inflammatory bowel disease (IBD) unclassified, and median age 12.6 (range 10-15.1 years); 3 patients had an unaffected healthy sibling recruited. Microbial diversity (observed species/Chao1/Shannon diversity) was reduced in treatment-naïve patients compared to siblings and patients in remission. Principal coordinate analysis using Bray-Curtis dissimilarity and UniFrac revealed microbial shifts in CD over the treatment course. In treatment-naïve PIBD, there was reduction in functional ability for amino acid metabolism and carbohydrate handling compared to controls (P?=?.038) and patients in remission (P?=?.027). Metabolic function returned to normal after remission was achieved. SCFA revealed consistent detection of lactate in treatment-naïve samples. This study adds in-depth 16S rRNA sequencing analysis on a small longitudinal cohort to the literature and includes sibling controls and patients with UC/IBD unclassified. It highlights the initial dysbiosis, reduced diversity, altered functional potential, and subsequent shifts in bacteria from diagnosis over time to remission.
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Project description:Changes in the gut microbiome have been associated with inflammatory bowel disease. A protective role of short chain fatty acids produced by the gut microbiota has been suggested as a causal mechanism. Nevertheless, multi-omic analyses have failed to identify a clear link between changes in specific taxa and disease states. Recently, metagenomic analyses unveiled that gut bacterial species have a previously unappreciated genomic diversity, implying that a geno-centric approach may be better suited to identifying the mechanisms involved. Here, we quantify the abundance of terminal genes in propionate-producing fermentative pathways in the microbiome of a large cohort of healthy subjects and patients with inflammatory bowel disease. The results show that propionate kinases responsible for propionate production in the gut are depleted in patients with Crohn's disease. Our results also indicate that changes in overall species abundances do not necessarily correlate with changes in the abundances of metabolic genes, suggesting that these genes are not part of the core genome. This, in turn, suggests that changes in strain composition may be as important as changes in species abundance in alterations of the gut microbiome associated with pathological conditions.
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Project description:Crohn’s disease (CD) and ulcerative colitis are chronic inflammatory bowel diseases (IBD) of which the etiology and pathogenesis are not completely understood. In paediatric patients, the disease tends to be more severe and aggressive then in adults. Here, we perform a proteomic approach on ascending colon biopsies from 119 pediatric patients to characterize disease pathogenesis and the impacts of treatment. Consistent with previous findings, we report an altered proteome in IBD patients that indicates impaired mitochondrial function. Gene ontology revealed that proteins downregulated in inflammation are associated with metabolism, whereas upregulated proteins contribute to protein processing. A comparison of proteomes from CD patients before and after therapeutic intervention identified over 100 proteins that are significantly different between patients that responded and those that did not respond to therapy; creatine kinase B was elevated before treatment in patients with mucosal healing after treatment, whereas basigin increased after treatment in responsive patients.
2021-08-26 | PXD024229 | Pride