Celiac Disease

A Highly Sensitive Method for the Detection of Hydrolyzed Gluten in Beer Samples Using LFIA

Most gluten analysis methods have been developed to detect intact gluten, but they have shown limitations in certain foods and beverages in which gluten proteins are hydrolyzed. Methods based on G12/A1 moAbs detect the sequences of gluten immunogenic peptides (GIP), which are the main contributors to the immune response of celiac disease (CD). Immunogenic sequences with tandem epitopes for G12/A1 have been found in beers with <20 mg/kg gluten, which could be consumed by CD patients according to the Codex Alimentarius. Therefore, an accurate method for the estimation of the immunogenicity of a beer is to use two moAbs that can recognize celiac T cell epitopes comprising most of the immunogenic response. Here, a specific and sensitive method based on G12/A1 LFIA was developed to detect GIP in beers labeled gluten-free or with low gluten content, with an LOD of 0.5 mg/kg. A total of 107 beers were analyzed, of those 6.5% showed levels higher than 20 mg/kg gluten and 29% showed levels above the LOD. In addition, G12/A1 LFIA detected gluten in 15 more beer samples than competitive ELISA with another antibody. Despite their labeling, these beers contained GIP which may cause symptoms and/or intestinal damage in CD patients.

Challenges of Monitoring the Gluten-Free Diet Adherence in the Management and Follow-Up of Patients with Celiac Disease

Celiac disease (CD) is a chronic gluten-responsive immune mediated enteropathy and is treated with a gluten-free diet (GFD). However, a strict diet for life is not easy due to the ubiquitous nature of gluten. This review aims at examining available evidence on the degree of adherence to a GFD, the methods to assess it, and the barriers to its implementation. The methods for monitoring the adherence to a GFD are comprised of a dietary questionnaire, celiac serology, or clinical symptoms; however, none of these methods generate either a direct or an accurate measure of dietary adherence. A promising advancement is the development of tests that measure gluten immunogenic peptides in stools and urine. Causes of adherence/non-adherence to a GFD are numerous and multifactorial. Inadvertent dietary non-adherence is more frequent than intentional non-adherence. Cross-contamination of gluten-free products with gluten is a major cause of inadvertent non-adherence, while the limited availability, high costs, and poor quality of certified gluten-free products are responsible for intentionally breaking a GFD. Therefore, several studies in the last decade have indicated that many patients with CD who follow a GFD still have difficulty controlling their diet and, therefore, regularly consume enough gluten to trigger symptoms and damage the small intestine.

Large-Scale Screening in General Population Children for Celiac Disease with a Multiplex Electrochemiluminescence (ECL) Assay

Background

Autoimmunity Screening for Kids (ASK) study was launched to screen general population children for type 1 diabetes (T1D) and celiac disease (CD).

Methods

A total of 23,319 children from general population were screened. A high throughput multiplex electrochemiluminescence (ECL) assay to screen multiautoantibodies in a single well was applied, parallel with a standard radiobinding assay (RBA). All children with any positive autoantibodies in screening were revisited within one month for confirmation and followed every 6 months.

Results

Among 23,319 children, 2.6% (606/23,319) of children were tested positive for TGA. Multiplex ECL assay detected more TGA (584/23,319) in the initial screening than RBA (490/23,319, p = 0.004) and was able to detect TGA earlier than RBA in a subset of children by 0.8 to 34.8 months. Prevalence of TGA by either ECL or RBA in children with islet autoantibodies was found significantly higher than overall prevalence in general population screened.

Conclusions

A multiplex ECL assay was more sensitive than standard RBA by identifying more TGA positivity and detecting TGA earlier in general population screening. It also provides a high efficient tool with its unique advantage of multiplexing measurements to screen for multiple autoimmune diseases simultaneously in general population.

Beneficial Effects of a Low-Nickel Diet on Relapsing IBS-Like and Extraintestinal Symptoms of Celiac Patients during a Proper Gluten-Free Diet: Nickel Allergic Contact Mucositis in Suspected Non-Responsive Celiac Disease

Background and Aim: Nickel (Ni)-rich foods can induce allergic contact mucositis (ACM) with irritable bowel syndrome (IBS)-like symptoms in predisposed subjects. Ni ACM has a high prevalence (>30%) in the general population and can be diagnosed by a Ni oral mucosa patch test (omPT). Many celiac disease (CD) patients on a gluten-free diet (GFD) often show a recrudescence of gastrointestinal and extraintestinal symptoms, although serological and histological remission has been achieved. Since a GFD often results in higher loads of ingested alimentary Ni (e.g., corn), we hypothesized that it would lead to a consequent intestinal sensitization to Ni in predisposed subjects. We wanted to (1) study Ni ACM prevalence in still symptomatic CD patients on a GFD and (2) study the effects of a low-Ni diet (LNiD) on their recurrent symptoms. Material and Methods: We recruited 102 consecutive CD patients (74 female, 28 male; age range 18–65 years, mean age 42.3 ± 7.4) on a GFD since at least 12 months, in current serological and histological remission (Marsh–Oberhuber type 0–I) who complained of relapsing gastrointestinal and/or extraintestinal symptoms. Inclusion criteria: presence of at least three gastrointestinal symptoms with a score ≥5 on the modified Gastrointestinal Symptom Rating Scale (GSRS) questionnaire. Exclusion criteria: IgE-mediated food allergy; history of past or current cancer; inflammatory bowel diseases; infectious diseases including Helicobacter pylori; lactose intolerance. All patients enrolled underwent Ni omPT and followed a LNiD for 3 months. A 24 symptoms questionnaire (GSRS modified according to the Salerno Experts’ Criteria, with 15 gastrointestinal and 9 extraintestinal symptoms) was administered at T0 (free diet), T1 (GFD, CD remission), T2 (recurrence of symptoms despite GFD), and T3 (GFD + LNiD) for comparisons. Comparisons were performed using Wilcoxon signed-rank test. RESULTS: Twenty patients (all female, age range 23–65 years, mean age 39.1 ± 2.9) out of 102 (19.6%) were finally included. All 20 patients enrolled (100%) showed positive Ni omPT, confirming an Ni ACM diagnosis. A correct GFD (T0 vs. T1) induced the improvement of 19 out of the total 24 (79.2%) symptoms, and 14 out of 24 (58.3%) were statistically significant (p-value < 0.0083 according to Bonferroni correction). Prolonged GFD (T1 vs. T2) revealed the worsening of 20 out of the total 24 (83.3%) symptoms, and 10 out of 24 (41.7%) were statistically significant. LNiD (T2 vs. T3) determined an improvement of 20 out of the total 24 (83.4%) symptoms, and in 10 out of 24 (41.7%) symptoms the improvement was statistically significant. Conclusions: Our data suggest that the recrudescence of gastrointestinal and extraintestinal symptoms observed in CD subjects during GFD may be due to the increase in alimentary Ni intake, once gluten contamination and persisting villous atrophy are excluded. Ni overload can induce Ni ACM, which can be diagnosed by a specific Ni omPT. Improvement of symptoms occurs after a proper LNiD. These encouraging data should be confirmed with larger studies.

Increased Prevalence of Celiac Disease in School-age Children in Italy

BACKGROUND & AIMS

Celiac disease is one of the most common diseases worldwide, with an apparent trend of increasing prevalence. We investigated the prevalence of celiac disease in children in Italy in 2015-2016 and compared that with data from 25 years ago.

METHODS

We screened 4570 children (5-11 years old, 80.1% of the eligible population) from metropolitan areas of Ancona and Verona for HLA genes associated with increased risk of celiac disease, and for total serum levels of IgA and IgA class anti-tissue transglutaminase in HLA positives. Diagnoses of celiac disease were confirmed by detection of anti-endomysial antibody and analysis of intestinal biopsies. The prevalence of celiac autoimmunity and celiac disease were calculated and compared with values from the same geographical area during the years 1993-1995, after adjustment for the different diagnostic algorithm.

RESULTS

We identified 1960 children with celiac disease-associated haplotypes (43% of children screened; 95% CI, 40.8%-45.2%). The prevalence of celiac disease autoimmunity in the HLA-positive subjects was 96/1706 (5.62%; 95% CI, 4.53%-6.71%) and 54 of these children satisfied the diagnostic criteria for celiac disease. In the eligible population there were other 23 known cases of celiac disease. The overall estimated prevalence of celiac disease was 1.58% (95% CI, 1.26%-1.90%); this value is significantly higher than the 1993-1995 adjusted prevalence (0.88%; 95% CI, 0.74%-1.02%).

CONCLUSIONS

We found the prevalence of celiac disease in children in Italy to be greater than 1.5%; this value has increased significantly over the past 25 years. Studies are needed to determine the causes of this large increase.

Automatic classification of IgA endomysial antibody test for celiac disease: a new method deploying machine learning

Widespread use of endomysial autoantibody (EmA) test in diagnostics of celiac disease is limited due to its subjectivity and its requirement of an expert evaluator. The study aimed to determine whether machine learning can be applied to create a new observer-independent method of automatic assessment and classification of the EmA test for celiac disease. The study material comprised of 2597 high-quality IgA-class EmA images collected in 2017–2018. According to standard procedure, highly-experienced professional classified samples into the following four classes: I - positive, II - negative, III - IgA deficient, and IV - equivocal. Machine learning was deployed to create a classification model. The sensitivity and specificity of the model were 82.84% and 99.40%, respectively. The accuracy was 96.80%. The classification error was 3.20%. The area under the curve was 99.67%, 99.61%, 100%, and 99.89%, for I, II, III, and IV class, respectively. The mean assessment time per image was 16.11 seconds. This is the first study deploying machine learning for the automatic classification of IgA-class EmA test for celiac disease. The results indicate that using machine learning enables quick and precise EmA test analysis that can be further developed to simplify EmA analysis.