Dataset Information

Using Serum IgE Antibodies to Predict Esophageal Eosinophilia in Children.

ABSTRACT: OBJECTIVES:Symptoms of eosinophilic esophagitis are variable and can be nonspecific. Food-specific serum immunoglobulin E (IgE) antibodies are frequently found in patients with eosinophilic esophagitis and are obtained using a widely available blood test. Our objective was to evaluate the ability of food-specific IgE antibodies to predict the presence of esophageal eosinophilia. METHODS:We reviewed 144 medical records for pediatric patients having esophageal biopsy and serum analysis for IgE antibodies to food (exploratory group). We performed logistic regression using sex and number of positive food-specific IgE tests to develop a model that predicts ?15 eosinophils/high-power field (hpf) in the esophagus. We tested the model using 142 additional patients (validation group). RESULTS:The probability of having ?15 eosinophils/hpf in the esophagus was higher in boys and increased with the number of positive food-specific IgE tests from 12% (95% confidence interval 4.8-26) in girls with 0 foods positive to 86% (95% confidence interval 71-94) for boys with 4 or 5 foods positive. The statistical model using sex and number of positive IgE tests to predict patients having ?15 eosinophils/hpf showed acceptable discriminative ability (area under the receiver operating characteristic curve 0.80). The performance metrics for the model to predict ?15 eosinophils/hpf in the validation group were similar (area under the receiver operating characteristic curve 0.75). CONCLUSIONS:Requiring only a blood test and a simple algorithm, analysis for IgE antibodies to food may expedite an esophagogastroduodenoscopy and decrease delays in the diagnosis and treatment of patients with nonspecific gastrointestinal symptoms who have increased eosinophils in the esophagus.

SUBMITTER: Erwin EA

PROVIDER: S-EPMC5665571 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using Serum IgE Antibodies to Predict Esophageal Eosinophilia in Children.

Erwin Elizabeth A EA Rhoda Dale A DA Redmond Margaret M Ly Jean B JB Russo John M JM Hill Ivor D ID Platts-Mills Thomas A E TAE

Journal of pediatric gastroenterology and nutrition 20171101 5

<h4>Objectives</h4>Symptoms of eosinophilic esophagitis are variable and can be nonspecific. Food-specific serum immunoglobulin E (IgE) antibodies are frequently found in patients with eosinophilic esophagitis and are obtained using a widely available blood test. Our objective was to evaluate the ability of food-specific IgE antibodies to predict the presence of esophageal eosinophilia.<h4>Methods</h4>We reviewed 144 medical records for pediatric patients having esophageal biopsy and serum analy ...[more]

PMID: 28981449

Similar Datasets

Project description:ObjectiveBesides reducing gastric acid secretion, proton pump inhibitors (PPIs) suppress Th2-cytokine-stimulated expression of an eosinophil chemoattractant (eotaxin-3) by esophageal epithelial cells through acid-independent, anti-inflammatory mechanisms. To explore acid-inhibitory and acid-independent, anti-inflammatory PPI effects in reducing esophageal eosinophilia, we studied eotaxin-3 expression by the proximal and distal esophagus of children with esophageal eosinophilia before and after PPI therapy. In vitro, we studied acid and bile salt effects on IL-13-stimulated eotaxin-3 expression by esophageal epithelial cells.DesignAmong 264 children with esophageal eosinophilia seen at a tertiary pediatric hospital from 2008 through 2012, we identified 10 with esophageal biopsies before and after PPI treatment alone. We correlated epithelial cell eotaxin-3 immunostaining with eosinophil numbers in those biopsies. In vitro, we measured eotaxin-3 protein secretion by esophageal squamous cells stimulated with IL-13 and exposed to acid and/or bile salt media, with or without omeprazole.ResultsThere was strong correlation between peak eosinophil numbers and peak eotaxin-3-positive epithelial cell numbers in esophageal biopsies. Eotaxin-3 expression decreased significantly with PPIs only in the proximal esophagus. In esophageal cells, exposure to acid-bile salt medium significantly suppressed IL-13-induced eotaxin-3 secretion; omeprazole added to the acid-bile salt medium further suppressed that eotaxin-3 secretion, but not as profoundly as at pH-neutral conditions.ConclusionIn children with esophageal eosinophilia, PPIs significantly decrease eotaxin-3 expression in the proximal but not the distal esophagus. In esophageal squamous cells, acid and bile salts decrease Th2 cytokine-stimulated eotaxin-3 secretion profoundly, possibly explaining the disparate PPI effects on the proximal and distal esophagus. In the distal esophagus, where acid reflux is greatest, a PPI-induced reduction in acid reflux (an effect that could increase eotaxin-3 secretion induced by Th2 cytokines) might mask the acid-independent, anti-inflammatory PPI effect of decreasing cytokine-stimulated eotaxin-3 secretion.

Project description:Background: Neutralizing anti-drug antibodies (ADA) can greatly reduce the efficacy of biopharmaceuticals used to treat patients with multiple sclerosis (MS). However, the biological factors pre-disposing an individual to develop ADA are poorly characterized. Thus, there is an unmet clinical need for biomarkers to predict the development of immunogenicity, and subsequent treatment failure. Up to 35% of MS patients treated with beta interferons (IFNβ) develop ADA. Here we use machine learning to predict immunogenicity against IFNβ utilizing serum metabolomics data. Methods: Serum samples were collected from 89 MS patients as part of the ABIRISK consortium-a multi-center prospective study of ADA development. Metabolites and ADA were quantified prior to and after IFNβ treatment. Thirty patients became ADA positive during the first year of treatment (ADA+). We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions. Results: We were able to predict future immunogenicity from baseline metabolomics data. Lasso logistic regression with/without interactions and support vector machines were the most successful at identifying ADA+ or ADA- cases, respectively. Furthermore, patients who become ADA+ had a distinct metabolic response to IFNβ in the first 3 months, with 29 differentially regulated metabolites. Machine learning algorithms could also predict ADA status based on metabolite concentrations at 3 months. Lasso logistic regressions had the greatest proportion of correct classifications [F1 score (accuracy measure) = 0.808, specificity = 0.913]. Finally, we hypothesized that serum lipids could contribute to ADA development by altering immune-cell lipid rafts. This was supported by experimental evidence demonstrating that, prior to IFNβ exposure, lipid raft-associated lipids were differentially expressed between MS patients who became ADA+ or remained ADA-. Conclusion: Serum metabolites are a promising biomarker for prediction of ADA development in MS patients treated with IFNβ, and could provide novel insight into mechanisms of immunogenicity.

Dataset Information

Using Serum IgE Antibodies to Predict Esophageal Eosinophilia in Children.

Publications

Using Serum IgE Antibodies to Predict Esophageal Eosinophilia in Children.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets