IBD metabonomics predicts phenotype, disease course, and treatment response.
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ABSTRACT:
SUBMITTER: Bjerrum JT
PROVIDER: S-EPMC8379620 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Incidence of IBD is rising in parallel with overweight and obesity. Contrary to conventional belief, about 15-40% of patients with IBD are obese, which might contribute to the development of IBD. Findings from cross-sectional and retrospective cohort studies are conflicting on the effect of obesity on natural history and course of IBD. Most studies are limited by small sample size, low event rates, non-validated assessment of disease activity and lack robust longitudinal follow-up and have incomplete adjustment for confounding factors. The effect of obesity on the efficacy of IBD-related therapy remains to be studied, though data from other autoimmune diseases suggests that obesity results in suboptimal response to therapy, potentially by promoting rapid clearance of biologic agents leading to low trough concentrations. These data provide a rationale for using weight loss interventions as adjunctive therapy in patients with IBD who are obese. Obesity also makes colorectal surgery technically challenging and might increase the risk of perioperative complications. In this Review, we highlight the existing literature on the epidemiology of obesity in IBD, discuss its plausible role in disease pathogenesis and effect on disease course and treatment response, and identify high-priority areas of future research.
| S-EPMC5550405 | biostudies-other
Project description:PPAR? is a nuclear receptor that regulates numerous pathways including cytokine expression and immune responses and plays an important role in controlling colon inflammation. We aimed at determining the occurring PPAR? SNPs, at predicting the haplotypes, and at determining the frequency outcome in inflammatory bowel disease (IBD) patients in comparison with healthy controls. We determined genetic variants in the coding exons and flanking intronic sequences of the NR1C3 gene in 284 IBD patients and 194 controls and predicted NR1C3 haplotypes via bioinformatic analysis. We investigated whether certain NR1C3 variants are associated with susceptibility to IBD or its disease course. None of the detected 22 NR1C3 variants were associated with IBD. Two variants with allelic frequencies over 1% were included in haplotype/diplotype analyses. None of the NR3C1 haplotypes showed association with IBD development or disease course. We conclude that NR1C3 haplotypes are not related to IBD susceptibility or IBD disease activity.
| S-EPMC3289871 | biostudies-literature
Project description:Circulating tumor cells (CTCs) are putative markers of tumor prognosis and may serve to evaluate patient's response to chemotherapy. CTCs are often detected as single cells but infrequently as clusters and are indicative of worse prognosis. In this study, we developed a short-term culture of nucleated blood cells which was applied to blood samples from breast, lung, esophageal and bladder cancer patients. Clusters of different degrees of compactness, classified as very tight, tight and loose were observed across various cancer types. These clusters show variable expression of cytokeratins. Cluster formation from blood samples obtained during the course of chemotherapy was found to be associated with disease progression and shorter overall survival. The short-term cultures offer a robust and highly reliable method for early prediction of treatment response in different cancer types.
| S-EPMC6538674 | biostudies-other
Project description:ObjectiveDetermine whether a treatment effect of ibudilast on brain atrophy rate differs between participants with primary (PPMS) and secondary (SPMS) progressive multiple sclerosis.BackgroundProgressive forms of MS are both associated with continuous disability progression. Whether PPMS and SPMS differ in treatment response remains unknown.Design/methodsSPRINT-MS was a randomized, placebo-controlled 96-week phase 2 trial in both PPMS (n = 134) and SPMS (n = 121) patients. The effect of PPMS and SPMS phenotype on the rate of change of brain atrophy measured by brain parenchymal fraction (BPF) was examined by fitting a three-way interaction linear-mixed model. Adjustment for differences in baseline demographics, disease measures, and brain size was explored.ResultsAnalysis showed that there was a three-way interaction between the time, treatment effect, and disease phenotype (P < 0.06). After further inspection, the overall treatment effect was primarily driven by patients with PPMS (P < 0.01), and not by patients with SPMS (P = 0.97). This difference may have been due to faster brain atrophy progression seen in the PPMS placebo group compared to SPMS placebo (P < 0.02). Although backward selection (P < 0.05) retained age, T2 lesion volume, RNFL, and longitudinal diffusivity as significant baseline covariates in the linear-mixed model, the adjusted overall treatment effect was still driven by PPMS (P < 0.01).InterpretationThe previously reported overall treatment effect of ibudilast on worsening of brain atrophy in progressive MS appears to be driven by patients with PPMS that may be, in part, because of the faster atrophy progression rates seen in the placebo-treated group.
| S-EPMC7818089 | biostudies-literature
Project description:Backgrounds:Endoscopic stricturotomy (ESt) has been shown to be effective in treating inflammatory bowel disease (IBD)-associated anastomotic strictures. However, the outcome of ESt in benign, non-IBD conditions has not been described. The aim of this study was to evaluate the outcome of ESt in the management of IBD and non-IBD-associated strictures. Methods:Data of all consecutive IBD and non-IBD patients with benign anastomotic strictures treated with ESt from 2009 to 2016 were extracted. The primary outcomes were surgery-free survival and procedure-related complications. Results:A total of 49 IBD and 15 non-IBD patients were included in this study. The IBD group included 25 patients with Crohn's disease and 24 with ulcerative colitis and ileal pouches. Underlying diseases in the non-IBD group included colorectal cancer (n?=?7), diverticulitis (n?=?5), large bowel prolapse (n?=?2), and constipation (n?=?1). Immediate technical success was achieved in all patients in both groups. Bleeding complications occurred on five occasions (4.7% per procedure) in the IBD group, while no complication occurred in the non-IBD group (P?=?0.20). Stricture improvement on follow-up endoscopy was found in 10 (20.4%) and 5 (33.3%) patients in the IBD and non-IBD groups, respectively (P?=?0.32). Six (12.2%) patients in the IBD group and four (26.7%) patients in the non-IBD group eventually required stricture-related surgery (P?=?0.23). IBD patients appeared to have a higher tendency for maintaining surgery-free after the procedure than non-IBD patients (P?=?0.08). Conclusions:Endoscopic stricturotomy was shown to have comparable outcomes, though non-IBD patients seem to have a higher need for subsequent surgery but a lower complication rate than IBD patients.
| S-EPMC7136702 | biostudies-literature
Project description:INTRODUCTION:Inflammatory bowel diseases (IBDs) are chronic diseases of unknown cause characterised by a progressive and unpredictable disease course. In the last decade, biological treatment has become a cornerstone in the treatment of IBD. However, one-in-three-to-four patients do not respond to first-line biological agents and another third of patients see their response diminish over time. This highlights an unmet need for optimising the use of biologicals and the prediction of treatment response. Considering the multifaceted nature of IBD, we hypothesise that multiomics profiling of sequential samples from single patients could facilitate the discovery of predictive biomarkers of response to biological therapy and disease course. METHODS:This is a multicentre prospective cohort study which will enrol 840 biological-naïve patients with IBD who initiate biological therapy in a 3-year period. Primary outcomes are the occurrence of primary non-response (evaluated at weeks 14-16) and loss of response (evaluated during entire follow-up in patients who obtain partial or full response after induction period). Each patient will be followed up for their clinical data for at least 1?year or till the end of study period (up to 4?years). Blood and stool samples will be collected sequentially during the first year of biological treatment. Intestinal tissue will be sampled after 1?year of treatment and whenever an endoscopy is performed. Samples will undergo transcriptomic, proteomic and microbial DNA analyses. Omics data will be integrated with clinical data to identify a panel of predictive biomarkers of response to biological therapy and disease behaviour in patients with IBD. ETHICS AND DISSEMINATION:Ethical approval has been obtained from the Danish Ethics Committee (H-18064178). Inclusion is ongoing at three study centres and will be initiated in two additional centres. Both positive and negative study results will be disseminated through peer-reviewed journals according to Strengthening the Reporting of Observational Studies in Epidemiology guidelines, as well as presented at international conferences.
| S-EPMC7045223 | biostudies-literature
Project description:BackgroundSuccess in personalized medicine in complex disease is critically dependent on biomarker discovery. We profiled serum proteins using a novel proximity extension assay [PEA] to identify diagnostic and prognostic biomarkers in inflammatory bowel disease [IBD].MethodsWe conducted a prospective case-control study in an inception cohort of 552 patients [328 IBD, 224 non-IBD], profiling proteins recruited across six centres. Treatment escalation was characterized by the need for biological agents or surgery after initial disease remission. Nested leave-one-out cross-validation was used to examine the performance of diagnostic and prognostic proteins.ResultsA total of 66 serum proteins differentiated IBD from symptomatic non-IBD controls, including matrix metallopeptidase-12 [MMP-12; Holm-adjusted p = 4.1 × 10-23] and oncostatin-M [OSM; p = 3.7 × 10-16]. Nine of these proteins are associated with cis-germline variation [59 independent single nucleotide polymorphisms]. Fifteen proteins, all members of tumour necrosis factor-independent pathways including interleukin-1 (IL-1) and OSM, predicted escalation, over a median follow-up of 518 [interquartile range 224-756] days. Nested cross-validation of the entire data set allowed characterization of five-protein models [96% comprising five core proteins ITGAV, EpCAM, IL18, SLAMF7 and IL8], which define a high-risk subgroup in IBD [hazard ratio 3.90, confidence interval: 2.43-6.26], or allowed distinct two- and three-protein models for ulcerative colitis and Crohn's disease respectively.ConclusionWe have characterized a simple oligo-protein panel that has the potential to identify IBD from symptomatic controls and to predict future disease course. Further prospective work is required to validate our findings.
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Project description:Inflammatory bowel diseases (IBDs) are highly heterogeneous in disease phenotype, behavior, and response to therapy. Diagnostic and therapeutic decisions in IBD are based primarily on clinical and endoscopic severity and histopathologic analysis of intestinal biopsies. With this approach, however, only a minority of patients experience durable remission. This may be due to substantial heterogeneity in disease pathogenicity that is not accounted for by current classification systems. Patients can present with similar clinical and endoscopic severity and receive similar therapy but show divergent response ranging from mucosal/transmural healing to nonresponse. Using mucosal biopsy samples that are already obtained as part of the clinical practice to support the diagnosis and state-of-the-art high throughput sequencing approaches can detect the widest range in host gene expression in the actual lining of the affected gut. These analyses can better dissect disease heterogeneity and guide potential treatment response. Here we review studies that use gut tissue-based gene expression profiles to predict disease outcome in IBD.
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Project description:The deleterious amino acid substitution mutations in IL-10 receptor alpha gene are most frequently reported in several autoimmune diseases including early onset-inflammatory bowel disease (IBD). Despite the important role of IL-10 RA in maintaining immune homeostasis, the specific structural and functional implications of these mutations on protein phenotype, stability, ligand binding and post translational characteristics is not well explored. Therefore, this study performed the multidimensional computational analysis of IL10RA missense variations causative to pediatric or early onset inflammatory bowel disease (<5 years of age). Our computational algorithmic screening identified the deleterious nature of p. W45G, p. Y57C, p. W69G, p.T84I, p.Y91C, p.R101W, p.R117C, and p.R117H, IBD causative IL10-RA mutations. The sensitivity and specificity analysis of different computational methods showed that CADD outperform SIFT, PolyPhen 2.0, FATHMM, LRT, MetaLR, MetaSVM, PROVEAN and Condel in predicting the pathogenicity of IL10RA mutations. Our three-dimensional protein modeling assays showed that the point mutations cause major drifts in the structural plasticity of IL10 RA molecule and negatively influence its stability. Findings from molecular docking analysis have shown that these point mutations decrease the binding affinity of IL10RA toward IL10 and may likely to disturb the IL10 signaling pathway. This study provides an easy frame work for phenotypic characterization of mutant IL10RA molecule in terms of structure, flexibility and stability aspects. Our approach may also add a new dimension to conventional functional biology assays in quickly studying IL10 RA mutations and also for designing and developing inhibitors for mutant IL10RA molecule.
| S-EPMC5934427 | biostudies-literature
Project description:The rate of disability accumulation varies across multiple sclerosis (MS) patients. Machine learning techniques may offer more powerful means to predict disease course in MS patients. In our study, 724 patients from the Comprehensive Longitudinal Investigation in MS at Brigham and Women's Hospital (CLIMB study) and 400 patients from the EPIC dataset, University of California, San Francisco, were included in the analysis. The primary outcome was an increase in Expanded Disability Status Scale (EDSS) ≥ 1.5 (worsening) or not (non-worsening) at up to 5 years after the baseline visit. Classification models were built using the CLIMB dataset with patients' clinical and MRI longitudinal observations in first 2 years, and further validated using the EPIC dataset. We compared the performance of three popular machine learning algorithms (SVM, Logistic Regression, and Random Forest) and three ensemble learning approaches (XGBoost, LightGBM, and a Meta-learner L). A "threshold" was established to trade-off the performance between the two classes. Predictive features were identified and compared among different models. Machine learning models achieved 0.79 and 0.83 AUC scores for the CLIMB and EPIC datasets, respectively, shortly after disease onset. Ensemble learning methods were more effective and robust compared to standalone algorithms. Two ensemble models, XGBoost and LightGBM were superior to the other four models evaluated in our study. Of variables evaluated, EDSS, Pyramidal Function, and Ambulatory Index were the top common predictors in forecasting the MS disease course. Machine learning techniques, in particular ensemble methods offer increased accuracy for the prediction of MS disease course.
| S-EPMC7567781 | biostudies-literature