Novel trends in celiac disease

Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach

BACKGROUND AND OBJECTIVES

Celiac disease is an autoimmune disease occurring in about 1 in 100 people worldwide. Early diagnosis and efficient treatment are crucial in mitigating the complications that are associated with untreated celiac disease, such as intestinal lymphoma and malignancy, and the subsequent high morbidity. The current diagnostic methods using small intestinal biopsy histopathology, endoscopy, and video capsule endoscopy (VCE) involve manual interpretation of photomicrographs or images, which can be time-consuming and difficult, with inter-observer variability. In this paper, a machine learning technique was developed for the automation of biopsy image analysis to detect and classify villous atrophy based on modified Marsh scores. This is one of the first studies to employ conventional machine learning to automate the use of biopsy images for celiac disease detection and classification.

METHODS

The Steerable Pyramid Transform (SPT) method was used to obtain sub bands from which various types of entropy and nonlinear features were computed. All extracted features were automatically classified into two-class and multi-class, using six classifiers.

RESULTS

An accuracy of 88.89%, was achieved for the classification of two-class villous abnormalities based on analysis of Hematoxylin and Eosin (H&E) stained biopsy images. Similarly, an accuracy of 82.92% was achieved for the two-class classification of red-green-blue (RGB) biopsy images. Also, an accuracy of 72% was achieved in the classification of multi-class biopsy images.

CONCLUSION

The results obtained are promising, and demonstrate the possibility of automating biopsy image interpretation using machine learning. This can assist pathologists in accelerating the diagnostic process without bias, resulting in greater accuracy, and ultimately, earlier access to treatment.

Electrochemical DNA Biosensor That Detects Early Celiac Disease Autoantibodies

Although it is estimated that more than one million Americans have celiac disease (CD), it remains challenging to diagnose. CD, an autoimmune and inflammatory response following the ingestion of gluten-containing foods, has symptoms overlapping with other diseases and requires invasive diagnostics. The gold standard for CD diagnosis involves serologic blood tests followed by invasive confirmatory biopsies. Here, we propose a less invasive method using an electrochemical DNA (E-DNA) biosensor for CD-specific autoantibodies (AABs) circulating in blood. In our approach, CD-specific AABs bind a synthetic neoepitope, causing a conformational change in the biosensor, as well as a change in the environment of an attached redox reporter, producing a measurable current reduction. We assessed the biosensor’s ability to detect CD-specific patient-derived AABs in physiological buffer as well as buffer supplemented with bovine serum. Our biosensor was able to detect AABs in a dose-dependent manner; increased signal change correlated with increased AAB concentration with an apparent dissociation constant of 0.09 ± 0.03 units/mL of AABs. Furthermore, we found our biosensor to be target-specific, with minimal off-target binding of multiple unrelated biomarkers. Future efforts aimed at increasing sensitivity in complex media may build upon the biosensor design presented here to further improve CD AAB detection and CD diagnostic tools.

Physicochemical, microstructural and digestibility analysis of gluten-free spaghetti of whole unripe plantain flour

Plantain is a climacteric fruit having economic relevance in several tropical regions. Unripe plantain is an alternative source of indigestible carbohydrates (dietary fibre) and undigestible starch fraction. Unripe plantain flour was explored in this work as an alternative ingredient (whole and pulp) in spaghetti formulations. Chemical composition, cooking quality, texture analysis, and microstructure of spaghetti formulations were analyzed. The microstructure results showed that the presence of fiber in the food matrix helped the reduction of the starch granule swelling in the cooking process. Spaghetti made with whole plantain flour exhibited lower rapidly starch fraction, with increased resistant starch fractions. Overall, the whole unripe plantain flour exhibited good potential for gluten-free spaghetti having highest content of fiber and lower starch digestion rates.

Serologic Diagnosis of Celiac Disease: New Biomarkers

Most patients affected by celiac disease (CD) are asymptomatic or hyposymptomatic and undiagnosed, and are at risk of preventable complications. Therefore, early diagnosis is highly recommended. Multiple diagnostic antibodies are available; the most frequently used is IgA to tissue transglutaminase (IgA-tTg). It may yield false results and, alone, does not address IgA deficiency. Recently, a new generation of anti-neo-epitope tTg check (IgG + IgA) has become available. It is highly sensitive and specific, covers IgA-deficient patients with CD, reflects intestinal damage, and has predictive potential in the diagnosis of CD.

Physician Review of a Celiac Disease Risk Estimation and Decision-Making Expert System

Objective: Celiac disease is a genetic disease affecting people of all ages, resulting in small intestine enteropathy. It is considered to be a clinical chameleon. Average prevalence of celiac disease is 1 out of 100 people with data indicating the risk may be as high as 22% for those with first-degree relatives with the disease. Eighty-three percent of people with celiac disease may be undiagnosed. Average duration to diagnosis is 10 years. Data indicate that there is a lack of consensus regarding diagnostics and symptomatology.Method: A clinical decision support system (CDSS) was developed using Exsys Corvid for expert analysis (CD-CDSS). The CD-CDSS was divided into symptoms and manifestations with 80 points of navigation, and a serology section, and was validated by 13 experts in the field of celiac disease using a 10-statement 5-point Likert scale.Results: This scale was analyzed using Cronbach's alpha reliability coefficient, which was calculated using SPSS and revealed good internal consistency and reliability with a result of 0.813. One hundred percent of experts agreed that the CD-CDSS is capable of guiding a health care professional through the diagnostic process, contains an accurate list of symptoms based on the clinical literature, and can foster improved awareness and education about celiac disease and that there is a need for this system.Conclusions: A celiac disease risk estimation and decision-making expert system was successfully developed and evaluated by medical professionals, with 100% agreeing that this CD-CDSS is medically accurate and can guide health care professionals through the diagnostic process.

Synthetic Neoepitopes of the Transglutaminase-Deamidated Gliadin Complex as Biomarkers for Diagnosing and Monitoring Celiac Disease

BACKGROUND & AIMS

Celiac disease (CeD) has characteristics of an autoimmune disease, such as increased antibody levels to tissue transglutaminase (tTG). However, assays to measure these biomarkers in blood samples do not identify patients with sufficient accuracy for diagnosis or monitoring of CeD. We aimed to discover biomarkers of CeD derived from neoepitopes of deamidated gliadin peptides (DGP) and tTG fragments and to determine if immune reactivity against these epitopes can identify patients with CeD with mucosal healing.

METHODS

We analyzed serum samples from 90 patients with biopsy-proven CeD and 79 healthy individuals (controls) for immune reactivity against the tTG-DGP complex (discovery cohort). A fluorescent peptide microarray platform was used to estimate the antibody-binding intensity of each synthesized tTG-DGP epitope. We validated our findings in 82 patients with newly diagnosed CeD and 217 controls. We tested the ability of our peptide panel to identify patients with mucosal healing (based on the histologic analysis) using serum samples from patients with treated and healed CeD (n = 85), patients with treated but unhealed CeD (n = 81; villous atrophy despite a adhering a gluten-free diet), patients with untreated CeD (n = 82) and disease controls (n = 27), villous atrophy without CeD), and healthy controls (n = 217). Data were analyzed using principal component analysis followed by machine learning and support vector machine modeling.

RESULTS

We identified 172 immunogenic epitopes of the tTG-DGP complex. We found significantly increased immune reactivity against these epitopes vs controls. In the both cohort, the set of neoepitopes derived from the tTG-DGP complex identified patients with CeD with 99% sensitivity and 100% specificity. Serum samples from patients with untreated CeD had the greatest mean antibody-binding intensity against the tTG-DGP complex (32.5 ± 16.4). The average antibody-binding intensity was significantly higher in serum from patients with treated but unhealed CeD mucosa (15.1 ± 7.5) than in patients with treated and healed CeD mucosa (5.5 ± 3.4) (P < .001). The assay identified patients with mucosa healing status with 84% sensitivity and 95% specificity.

CONCLUSIONS

We identified immunogenic epitopes of the tTG-DGP complex, and found that an assay to measure the immune response to epitopes accurately identified patients with CeD, as well as patients with mucosal healing. This biomarker assay might be used in detection and monitoring of patients with CeD.

Multivariable Analysis of Gluten-Free Pasta Elaborated with Non-Conventional Flours Based on the Phenolic Profile, Antioxidant Capacity and Color

The phenolic compounds, color and antioxidant capacity of gluten-free pasta prepared with non-conventional flours such as chickpea (CHF), unripe plantain (UPF), white maize (WMF) and blue maize (BMF) were analyzed. Fifteen phenolic compounds (five anthocyanins, five hydroxybenzoic acids, three hydroxycinnamic acids, one hydroxyphenylacetic acid and one flavonol) were identified in pasta prepared with blue maize, and 10 compounds were identified for samples prepared with white maize. The principal component analysis (PCA) led to results describing 98% of the total variance establishing a clear separation for each pasta. Both the proportion (25, 50 and 75%) and type of maize flour (white and blue) affected the color parameters (L*, C _ab *, h _ab and ΔE* _ab ) and antioxidant properties (DPPH, ABTS and FRAP methods) of samples, thus producing gluten-free products with potential health benefits intended for general consumers (including the population with celiac disease).

Celiac disease: From pathophysiology to treatment

Celiac disease, also known as "celiac sprue", is a chronic inflammatory disorder of the small intestine, produced by the ingestion of dietary gluten products in susceptible people. It is a multifactorial disease, including genetic and environmental factors. Environmental trigger is represented by gluten while the genetic predisposition has been identified in the major histocompatibility complex region. Celiac disease is not a rare disorder like previously thought, with a global prevalence around 1%. The reason of its under-recognition is mainly referable to the fact that about half of affected people do not have the classic gastrointestinal symptoms, but they present nonspecific manifestations of nutritional deficiency or have no symptoms at all. Here we review the most recent data concerning epidemiology, pathogenesis, clinical presentation, available diagnostic tests and therapeutic management of celiac disease.

Celiac disease-related hepatic injury: Insights into associated conditions and underlying pathomechanisms

BACKGROUND

Celiac disease (CD) is the most common autoimmune enteropathy. Clinical manifestations may range from a typical malabsorption syndrome to several apparently unrelated extra-intestinal symptoms.

AIM

Here we specifically focus on the spectrum of CD-related liver disorders and the underlying pathomechanisms.

METHODS

A computer-based search up to August 2015 was completed using appropriate keywords. References from selected papers were also reviewed and used if relevant.

RESULTS

An unexplained hypertransaminasemia with nonspecific histologic hepatic changes is the most common hepatic presentation. CD however can coexist with a number of liver disorders such as Autoimmune Hepatitis, Autoimmune Cholangitis, Primary Biliary Cirrhosis and Primary Sclerosing Cholangitis requiring a specific treatment in addition to gluten-free diet. CD has also been associated with Viral Hepatitis, Fatty Liver, Non-Alcoholic Steatohepatitis and some severe cryptogenic hepatopaties in the liver transplantation list. Pathomechanisms underlying hepatic injury in CD are multiple, appear still not completely defined and may probably co-occur.

CONCLUSIONS

An ever-increasing number of CD-related liver injuries exist, probably representing a continuum of a same disorder where genetic predisposition, timing, and duration of previous gluten exposure might influence the reversibility of liver damage. Evidences, although not conclusive, support therefore testing for CD also in cryptogenic hepatobiliary conditions where the relationship with CD has not yet been fully investigated.

Antibodies against neo-epitope tTg complexed to gliadin are different and more reliable then anti-tTg for the diagnosis of pediatric celiac disease

The neo-epitope tTg (tTg-neo) autoantibody, never challenged the anti-tissue transglutaminase (tTg) premiership, recommended by ESPGHAN, for celiac disease (CD) diagnosis. Pediatric CD (PCD), abdominal pains and normal children, normal adults, and rheumatoid arthritis patients, were tested using the following ELISAs detecting IgA, IgG or both IgA and IgG (check): AESKULISA® tTg (tTg; RUO) and AESKULISA® tTg-neo. Higher OD activity was detected for tTg-neo IgA, IgG and IgA+IgG than for tTg. tTg-neo IgA, IgG correlated better with intestinal damage than tTg. The tTg-neo combined IgA+IgG ELISA kit had higher sensitivity and a comparable specificity for the diagnosis of PCD. The drop in the % competition was much higher with the tTg-neo then the tTg antibodies. The false positivity of the tTg was significantly higher than the tTg-neo one. Serological diagnostic performances, reflection of intestinal damage, diverse epitopes and false positivity were better with the tTg-neo.

Overview of biomarkers for diagnosis and monitoring of celiac disease

Among the adverse reactions caused by wheat, celiac disease (CD) is the longest studied and best-known pathology. The more recently defined non-celiac gluten sensitivity (NCGS) presents with symptoms which are often indistinguishable from CD. Diagnosis of CD is based on serologic, molecular, and bioptic testing. The IgA anti-transglutaminase (tTG) test is considered highly important, as it shows high sensitivity and specificity and its levels correlate to the degree of intestinal damage. Small bowel biopsy can be avoided in symptomatic patients with IgA anti-tTG levels above 10× the manufacturer's cut-off. Recently, tests of anti-deamidated peptides of gliadin (DGP) have replaced classic anti-native gliadin (AGA) tests. DGP assays have a considerably higher diagnostic accuracy than AGA assays, especially in the IgG class, and can replace anti-tTG tests in patients with selective IgA deficiency. The combination of IgG anti-DGP plus IgA anti-tTG assays show greater sensitivity than a single test, with very high specificity. EMA tests have great diagnostic accuracy but are not recommended by all the latest guidelines because they are observer dependent. Biopsy must still be considered the gold standard for CD diagnosis. HLA-DQ genotyping can be used to screen asymptomatic children and in cases of histology/serology disagreement. About half of NCGS patients are DQ2 positive and have IgG AGA. To diagnose NCGS, first CD and wheat allergy must be excluded; then the wheat dependence of symptoms must be verified by a gluten-free diet and subsequent gluten challenge.

Differentiation between Celiac Disease, Nonceliac Gluten Sensitivity, and Their Overlapping with Crohn's Disease: A Case Series

Celiac disease (CD) and nonceliac gluten sensitivity (NCGS) are two distinct conditions triggered by the ingestion of gliadin. Although symptoms of nonceliac gluten sensitivity may resemble those of celiac disease, due to the lack of objective diagnostic tests, NCGS is associated with overlapping symptomatologies of autoimmunities and Crohn's disease. Furthermore, a gluten-free diet is only recommended for those who meet the criteria for a diagnosis of CD. Unfortunately, that leaves many nonceliac gluten-sensitive people suffering unnecessarily from very serious symptoms that put them at risk for complications of autoimmune disorders that might be resolved with a gluten-free diet. Thus, a new paradigm is needed for aid in diagnosing and distinguishing among various gut-related diseases, including CD, NCGS (also known as silent celiac disease), and gut-related autoimmunities. Herein, we report three different cases: the first, an elderly patient with celiac disease which was diagnosed based on signs and symptoms of malabsorption and by a proper lab test; second, a case of NCGS which was initially misdiagnosed as lupus but was detected as NCGS by a proper lab test with its associated autoimmunities, including gluten ataxia and neuromyelitis optica; third, a patient with NCGS overlapping with Crohn's disease. The symptomatologies of all three patients improved significantly after 12 months of gluten-free diet plus other modalities.

New screening tests enrich anti-transglutaminase results and support a highly sensitive two-test based strategy for celiac disease diagnosis

BACKGROUND

The identification of specific serological algorithms allowing the diagnosis of celiac disease (CD) is a new challenge for both the clinic and the laboratory. We compared the diagnostic accuracy of three new tests proposed for CD screening with that of the well established IgA tTG, and ascertained whether any combination of these tools might enhance accuracy in diagnosing CD.

METHODS

In sera from 329 CD and 374 control children, the following were assayed: IgA tTG; IgA/IgG, which identify tTG-gliadin complexes (Aeskulisa Celi Check and CeliCheck IgGA); IgA/IgG, which identify deamidated gliadin peptides and tTG (QUANTA Lite(TM) h-tTG/DGP Screen).

RESULTS

When specificity was set at 100%, the most sensitive index of CD was IgA tTG (75.7%, cut-off=100U), followed by QUANTA Lite(TM) h-tTG/DGP Screen (65.3%, cut-off 145U), Aeskulisa Celi Check (62.6%, cut-off 909U/mL) and CeliCheck IgGA (59.6%, cut-off 977U/mL). Three algorithms were obtained by combining IgA tTG with each of the new tests. The algorithm obtained by measuring IgA tTG and QUANTA Lite(TM) h-tTG/DGP Screen allowed the correct identification of CD in 78.7% of cases (negative predictive value=97.3%).

CONCLUSIONS

The two-test based strategy could be used for the cost effective diagnosis of CD.