Wheat flour is one of the most important food ingredients containing several essential nutrients including proteins. Gluten is one of the major protein components of wheat consisted of glutenin (encoded on chromosome 1) and gliadin (encoded on chromosome 1 and 6) and there are around hundred genes encoding it in wheat. Gluten proteins have the ability of eliciting the pathogenic immune responses and hypersensitivity reactions in susceptible individuals called “gluten-related disorders (GRDs)”, which include celiac disease (CD), wheat allergy (WA), and non-celiac gluten sensitivity (NCGS). Currently removing gluten from the diet is the only effective treatment for mentioned GRDs and studies for the appropriate and alternative therapeutic approaches are ongoing. Accordingly, several genetic studies have focused on breeding wheat with low immunological properties through gene editing methods. The present review considers genetic characteristics of gluten protein components, focusing on their role in the incidence of gluten-related diseases, and genetic modifications conducted to produce wheat with less immunological properties.

Background. Celiac disease (CeD) is an autoimmune intestinal disorder caused by gluten protein consumption in genetically predisposed individuals. As biopsy sampling is an invasive procedure, finding novel noninvasive serological markers for screening of at‐risk CeD population is a priority. Metabolomics is helpful in monitoring metabolite changes in body fluids and tissues. In the present study, we evaluated serum metabolite levels of CeD patients relative to healthy controls with the aim of introducing new biomarkers for population screening. Method. We compared the serum metabolic profile of CeD patients (n = 42) and healthy controls (n = 22) using NMR spectroscopy and multivariate analysis. Result. 25 metabolites were identified by serum metabolic profiling. Levels of 3‐hydroxyisobutyric acid and isobutyrate showed significant differences in CeD patients’ samples compared with healthy controls (p < 0.05). According to pathway analysis, our data demonstrated that changes in nine metabolic pathways were significantly disrupted/affected in patients with CeD. These enriched pathways are involved in aminoacyl‐tRNA biosynthesis; primary bile acid biosynthesis; nitrogen metabolism; glutamine and glutamate metabolism; valine, leucine, and isoleucine biosynthesis and degradation; taurine and hypotaurine metabolism; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and arginine biosynthesis. Conclusion. In summary, our results demonstrated that changes in the serum level of 25 metabolites may be useful in distinguishing CeD patients from healthy controls, which have the potential to be considered candidate biomarkers of CeD.

Amino acids (AAs) and vitamin imbalances are observed in celiac disease (CD). This study evaluated the plasma profile of vitamin A and AAs and the expression level of IL-2, IL-4, IL-10, IL-12 and TGFβ in CD patients. A total of 60 children and adults with CD and 40 healthy controls (HCs) were included. The plasma profile of Vitamin A and AAs and the mRNA expression levels of target genes were assessed. Active adult patients exhibited a decrease in Vitamin A levels (p = 0.04) and an increase in IL-2 (p = 0.008) and IL-12 (p = 0.007) mRNA expression compared to the HCs. The treated adult patients showed elevated Serine (p = 0.003) and Glycine (p = 0.04) levels, as well as increased IL-12 (p < 0.0001) mRNA expression, and a decrease in Tryptophan (p = 0.04) levels relative to the controls. Additionally, the treated adult patients had higher plasma levels of Threonine compared to both the active (p = 0.04) and control (p = 0.02) subjects, and the increased mRNA expression of IL-4 (p = 0.01) in comparison to the active patients. In active children with CD, the IL-2 mRNA level was found to be higher than in the controls (p < 0.0001) and in the treated children (p = 0.005). The treated children with CD exhibited decreased plasma levels of Tryptophan (p = 0.01) and Isoleucine (p = 0.01) relative to the controls, and the increased mRNA expression of TGFβ (p = 0.04) relative to the active patients. Elevated levels of specific AAs (Serine, Glycine, Threonine) in the treated CD patients suggested their potential to improve intestinal damage and inflammation, while decreased levels of Tryptophan and Isoleucine highlighted the need for dietary intervention.

Background: Non-celiac wheat sensitivity (NCWS) is a poorly understood gluten-related disorder (GRD) and its prominent symptoms can be ameliorated by gluten avoidance. This study aimed to determine the effectiveness of a probiotic mixture in hydrolyzing gliadin peptides (toxic components of gluten) and suppressing gliadin-induced inflammatory responses in Caco-2 cells. Methods: Wheat dough was fermented with a probiotic mix for 0, 2, 4, and 6 h. The effect of the probiotic mix on gliadin degradation was monitored by SDS-PAGE. The expression levels of IL-6, IL-17A, INF-γ, IL-10, and TGF-β were evaluated using ELISA and qRT-PCR methods. Results: According to our findings, fermenting wheat dough with a mix of B. longum, L. acidophilus, and L. plantarum for 6 h was effective in gliadin degradation. This process also reduced levels of IL-6 (p = 0.004), IL-17A (p = 0.004), and IFN-γ (p = 0.01) mRNA, as well as decreased IL-6 (p = 0.006) and IFN-γ (p = 0.0009) protein secretion. 4 h fermentation led to a significant decrease in IL-17A (p = 0.001) and IFN-γ (p = 0.003) mRNA, as well as reduced levels of IL-6 (p = 0.002) and IFN-γ (p < 0.0001) protein secretion. This process was also observed to increase the expression levels of IL-10 (p < 0.0001) and TGF-β (p < 0.0001) mRNA. Conclusions: 4 h fermentation of wheat flour with the proposed probiotic mix might be a good strategy to develop an affordable gluten-free wheat dough for NCWS and probably other GRD patients.

Context: In recent decades, adverse reactions to gluten have increased, collectively known as gluten-related disorders (GRDs). The most prominent GRD is celiac disease (CD), a T-cell-mediated autoimmune-like disorder of the small intestine triggered by the ingestion of gluten proteins in genetically predisposed individuals. Celiac disease is often associated with various autoimmune and idiopathic conditions, including autoimmune thyroid disorders (AITDs). Autoimmune thyroid disorders result from immune system dysregulation and lead to an assault on the thyroid gland. This study aims to examine the potential effect of gluten consumption on the development of AITDs. Evidence Acquisition: A narrative literature review was conducted using the Google Scholar, Scopus, and PubMed electronic databases to identify studies investigating the role of gluten in the development of AITDs. Keywords such as "Gluten," "Autoimmune thyroid disease," and "Gluten-free diet" were used. Results: The involvement of gluten in the pathogenesis of autoimmune diseases is mediated through various mechanisms. Gluten may contribute to the expansion and progression of AITDs through mechanisms such as dysbiosis, leaky gut, and cross-reactivity. There is evidence that adherence to a gluten-free diet (GFD) may positively impact patients with AITDs, supporting the importance of personalized dietary strategies to mitigate risks associated with gluten intake. Conclusions: The findings suggest that dietary management, particularly strict adherence to a GFD, may be beneficial for individuals with both CD and AITDs. Emerging evidence highlights the importance of personalized dietary strategies to mitigate the risks associated with gluten intake. A deeper understanding of the gut-thyroid axis could lead to the development of innovative approaches in the management of autoimmune disorders.

This paper focuses on celiac disease (CD), an autoimmune disorder characterized by small intestinal enteropathy and gastrointestinal symptoms. The prevalence of CD is rising, and there is a need for prompt and accurate diagnosis. The paper discusses the challenges in classifying CD and the consequences of delayed diagnosis, including increased morbidity and mortality rates. It also highlights the Marsh classification, which categorizes CD based on histological characteristics. However, this classification has limitations, which can lead to misdiagnosis. The emergence of multiomics data and artificial intelligence (AI) is presented as a potential solution to improve CD diagnosis and management. Multiomics data integration enables a more precise diagnosis, while AI and machine learning (ML) techniques facilitate the identification of clinically relevant patterns and the development of diagnostic models. According to the findings, the integration of AI and multiomics data holds transformative potential for the diagnosis and management of CD, facilitating early diagnosis and personalized treatment strategies. AI‐assisted methods, including video capsule endoscopy (VCE) analysis, have shown sensitivities exceeding 90%, enhancing diagnostic accuracy while reducing invasiveness. As novel biomarkers are identified, individualized management approaches can evolve, leading to improved patient outcomes, though further efforts are needed to standardize these technologies in clinical practice.