Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Epigenetics in autoimmune diseases: Unraveling the hidden regulators of immune dysregulation

Autoimmune diseases result from complex interactions between genetic and environmental factors. Recent advances in epigenetic research shed light on the intricate regulatory mechanisms that contribute to the development and progression of such conditions. The present review aims to explore the role of epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNAs, in the context of autoimmune diseases. We discuss the current understanding of epigenetic alterations associated with various autoimmune disorders, their impact on immune cell function, and their potential as innovative therapeutic targets. Additionally, we highlight the main future directions in the field of epigenetics in autoimmunity.

The emerging role of biotechnological advances and artificial intelligence in tackling gluten sensitivity

Gluten comprises an intricate network of hundreds of related but distinct proteins, mainly "gliadins" and "glutenins," which play a vital role in determining the rheological properties of wheat dough. However, ingesting gluten can trigger severe conditions in susceptible individuals, including celiac disease, wheat allergy, or non-celiac gluten sensitivity, collectively known as gluten-related disorders. This review provides a panoramic view, delving into the various aspects of gluten-triggered disorders, including symptoms, diagnosis, mechanism, and management. Though a gluten-free diet remains the primary option to manage gluten-related disorders, the emerging microbial and plant biotechnology tools are playing a transformative role in reducing the immunotoxicity of gluten. The enzymatic hydrolysis of gluten and the development of gluten-reduced/free wheat lines using RNAi and CRISPR/Cas technology are laying the foundation for creating safer wheat products. In addition to biotechnological interventions, the emerging artificial intelligence technologies are also bringing about a paradigm shift in the diagnosis and management of gluten-related disorders. Here, we provide a comprehensive overview of the latest developments and the potential these technologies hold for tackling gluten sensitivity.

Interferon autoantibodies as signals of a sick thymus

Type I interferons (IFN-I) are key immune messenger molecules that play an important role in viral defense. They act as a bridge between microbe sensing, immune function magnitude, and adaptive immunity to fight infections, and they must therefore be tightly regulated. It has become increasingly evident that thymic irregularities and mutations in immune genes affecting thymic tolerance can lead to the production of IFN-I autoantibodies (autoAbs). Whether these biomarkers affect the immune system or tissue integrity of the host is still controversial, but new data show that IFN-I autoAbs may increase susceptibility to severe disease caused by certain viruses, including SARS-CoV-2, herpes zoster, and varicella pneumonia. In this article, we will elaborate on disorders that have been identified with IFN-I autoAbs, discuss models of how tolerance to IFN-Is is lost, and explain the consequences for the host.

Coexistence of apoptosis, pyroptosis, and necroptosis pathways in celiac disease

Usually, the massive elimination of cells under steady-state conditions occurs by apoptosis, which is also acknowledged to explain the loss of enterocytes in the small intestine of celiac disease (CD) patients. However, little is known about the role of proinflammatory cell death pathways in CD. Here, we have used confocal microscopy, western blot, and RT-qPCR analysis to assess the presence of regulated cell death pathways in the duodenum of CD patients. We found an increased number of dead (TUNEL+) cells in the lamina propria of small intestine of CD patients, most of them are plasma cells (CD138+). Many dying cells expressed FAS and were in close contact with CD3+ T cells. Caspase-8 and caspase-3 expression was increased in CD, confirming the activation of apoptosis. In parallel, caspase-1, IL-1β, and GSDMD were increased in CD samples indicating the presence of inflammasome-dependent pyroptosis. Necroptosis was also present, as shown by the increase of RIPK3 and phosphorylate MLKL. Analysis of published databases confirmed that CD has an increased expression of regulated cell death -related genes. Together, these results reveal that CD is characterized by cell death of different kinds. In particular, the presence of proinflammatory cell death pathways may contribute to mucosal damage.

Transcriptome profile and immune infiltrated landscape revealed a novel role of γδT cells in mediating pyroptosis in celiac disease

BACKGROUND

Celiac disease (CeD) is a primary malabsorption syndrome with no specific therapy, which greatly affects the quality of life. Since the pathogenesis of CeD remains riddled, based on multiple transcriptome profiles, this study aimed to establish an immune interaction network and elucidated new mechanisms involved in the pathogenesis of CeD, providing potentially new evidence for the diagnosis and treatment of CeD.

METHODS

Three microarray and three RNA sequencing datasets of human duodenal tissue with or without CeD were included in Gene Expression Omnibus and respectively merged into derivation and validation cohorts. Differential expression gene and functional enrichment analysis were developed, then pyroptosis enrichment score (PES) model was established to quantify pyroptosis levels. Immune infiltration and co-expression network were constructed based on Xcell database. Protein-protein interaction and weighted gene co-expression network analysis were determined to identify pyroptosis relative hub genes, whose predictive efficiency were tested using a least absolute shrinkage and selection operator (LASSO) regression model. CeD animal and in vitro cell line models were established to verify the occurrence of pyroptosis and molecules expression employing immunofluorescence, western blotting, cell counting kit-8 assay and enzyme-linked immunosorbent assay. Analysis of single-cell RNAseq (scRNAseq) was performed using "Seurat" R package.

RESULTS

Differentially expressed genes (DEGs) (137) were identified in derivation cohort whose function was mainly enriched in interferon response and suppression of metabolism. Since an enrichment of pyroptosis pathway in CeD was unexpectedly discovered, a PES model with high efficiency was constructed and verified with two external databases, which confirmed that pyroptosis was significantly upregulated in CeD epithelia. γδT cells exhibited high expression of IFN-γ were the most relevant cells associated with pyroptosis and occupied a greater weight in the LASSO predictive model of CeD. An accumulation of GSDMD expressed in epithelia was identified using scRNAseq, while animal model and in vitro experiments confirmed that epithelium cells were induced to become "pre-pyroptotic" status via IFN-γ/IRF1/GSDMD axis. Furthermore, gluten intake triggered pyroptosis via caspase-1/GSDMD/IL-1β pathway.

CONCLUSION

Our study demonstrated that pyroptosis was involved in the pathogenesis of CeD, and elucidated the novel role of γδT cells in mediating epithelial cell pyroptosis.

Transcriptional states of CAR-T infusion relate to neurotoxicity – lessons from high-resolution single-cell SOM expression portraying

Anti-CD19 CAR-T cell immunotherapy is a hopeful treatment option for patients with B cell lymphomas, however it copes with partly severe adverse effects like neurotoxicity. Single-cell resolved molecular data sets in combination with clinical parametrization allow for comprehensive characterization of cellular subpopulations, their transcriptomic states, and their relation to the adverse effects. We here present a re-analysis of single-cell RNA sequencing data of 24 patients comprising more than 130,000 cells with focus on cellular states and their association to immune cell related neurotoxicity. For this, we developed a single-cell data portraying workflow to disentangle the transcriptional state space with single-cell resolution and its analysis in terms of modularly-composed cellular programs. We demonstrated capabilities of single-cell data portraying to disentangle transcriptional states using intuitive visualization, functional mining, molecular cell stratification, and variability analyses. Our analysis revealed that the T cell composition of the patient’s infusion product as well as the spectrum of their transcriptional states of cells derived from patients with low ICANS grade do not markedly differ from those of cells from high ICANS patients, while the relative abundancies, particularly that of cycling cells, of LAG3-mediated exhaustion and of CAR positive cells, vary. Our study provides molecular details of the transcriptomic landscape with possible impact to overcome neurotoxicity.

Artificial Intelligence Analysis of Celiac Disease Using an Autoimmune Discovery Transcriptomic Panel Highlighted Pathogenic Genes including BTLA

Celiac disease is a common immune-related inflammatory disease of the small intestine caused by gluten in genetically predisposed individuals. This research is a proof-of-concept exercise focused on using Artificial Intelligence (AI) and an autoimmune discovery gene panel to predict and model celiac disease. Conventional bioinformatics, gene set enrichment analysis (GSEA), and several machine learning and neural network techniques were used on a publicly available dataset (GSE164883). Machine learning and deep learning included C5, logistic regression, Bayesian network, discriminant analysis, KNN algorithm, LSVM, random trees, SVM, Tree-AS, XGBoost linear, XGBoost tree, CHAID, Quest, C&R tree, random forest, and neural network (multilayer perceptron). As a result, the gene panel predicted celiac disease with high accuracy (95-100%). Several pathogenic genes were identified, some of the immune checkpoint and immuno-oncology pathways. They included CASP3, CD86, CTLA4, FASLG, GZMB, IFNG, IL15RA, ITGAX, LAG3, MMP3, MUC1, MYD88, PRDM1, RGS1, etc. Among them, B and T lymphocyte associated (BTLA, CD272) was highlighted and validated at the protein level by immunohistochemistry in an independent series of cases. Celiac disease was characterized by high BTLA, expressed by inflammatory cells of the lamina propria. In conclusion, artificial intelligence predicted celiac disease using an autoimmune discovery gene panel.

Gene Expression Signatures Reveal Common Virus Infection Pathways in Target Tissues of Type 1 Diabetes, Hashimoto's Thyroiditis, and Celiac Disease

Type 1 diabetes (T1D) patients are at heightened risk for other autoimmune disorders, particularly Hashimoto's thyroiditis (HT) and celiac disease (CD). Recent evidence suggests that target tissues of autoimmune diseases engage in a harmful dialogue with the immune system. However, it is unclear whether shared mechanisms drive similar molecular signatures at the target tissues among T1D, HT, and CD. In our current study, microarray datasets were obtained and mined to identify gene signatures from disease-specific targeted tissues including the pancreas, thyroid, and intestine from individuals with T1D, HT, and CD, as well as their matched controls. Further, the threshold-free algorithm rank-rank hypergeometric overlap analysis (RRHO) was used to compare the genomic signatures of the target tissues of the three autoimmune diseases. Next, promising drugs that could potentially reverse the observed signatures in patients with two or more autoimmune disorders were identified using the cloud-based CLUE software platform. Finally, microarray data of auto-antibody positive individuals but not diagnosed with T1D and single cell sequencing data of patients with T1D and HT were used to validate the shared transcriptomic fingerprint. Our findings revealed significant common gene expression changes in target tissues of the three autoimmune diseases studied, many of which are associated with virus infections, including influenza A, human T-lymphotropic virus type 1, and herpes simplex infection. These findings support the importance of common environmental factors in the pathogenesis of T1D, HT, and CD.

Celiac disease: From genetics to epigenetics

Celiac disease (CeD) is a multifactorial autoimmune disorder spread worldwide. The exposure to gluten, a protein found in cereals like wheat, barley and rye, is the main environmental factor involved in its pathogenesis. Even if the genetic predisposition represented by HLA-DQ2 or HLA-DQ8 haplotypes is widely recognised as mandatory for CeD development, it is not enough to explain the total predisposition for the disease. Furthermore, the onset of CeD comprehend a wide spectrum of symptoms, that often leads to a delay in CeD diagnosis. To overcome this deficiency and help detecting people with increased risk for CeD, also clarifying CeD traits linked to disease familiarity, different studies have tried to make light on other predisposing elements. These were in many cases genetic variants shared with other autoimmune diseases. Since inherited traits can be regulated by epigenetic modifications, also induced by environmental factors, the most recent studies focused on the potential involvement of epigenetics in CeD. Epigenetic factors can in fact modulate gene expression with many mechanisms, generating more or less stable changes in gene expression without affecting the DNA sequence. Here we analyze the different epigenetic modifications in CeD, in particular DNA methylation, histone modifications, non-coding RNAs and RNA methylation. Special attention is dedicated to the additional predispositions to CeD, the involvement of epigenetics in developing CeD complications, the pathogenic pathways modulated by epigenetic factors such as microRNAs and the potential use of epigenetic profiling as biomarker to discriminate different classes of patients.

Single-cell approaches to dissect adaptive immune responses involved in autoimmunity: the case of celiac disease

Single-cell analysis is a powerful technology that has found widespread use in recent years. For diseases with involvement of adaptive immunity, single-cell analysis of antigen-specific T cells and B cells is particularly informative. In autoimmune diseases, the adaptive immune system is obviously at play, yet the ability to identify the culprit T and B cells recognizing disease-relevant antigen can be difficult. Celiac disease, a widespread disorder with autoimmune components, is unique in that disease-relevant antigens for both T cells and B cells are well defined. Furthermore, the celiac disease gut lesion is readily accessible allowing for sampling of tissue-resident cells. Thus, disease-relevant T cells and B cells from the gut and blood can be studied at the level of single cells. Here we review single-cell studies providing information on such adaptive immune cells and outline some future perspectives in the area of single-cell analysis in autoimmune diseases.

Insights from tissue "omics" analysis on intestinal remodeling in celiac disease

Celiac disease (CeD) is a prevalent intestinal disorder that only develops in genetically susceptible individuals when they mount a harmful CD4+ T-cell response towards gluten peptides. Intake of gluten leads to inflammation and remodeling of the small intestine with symptoms such as nausea and diarrhea. The only current treatment is a lifelong gluten free diet. The immunological basis for CeD is well characterized but the mechanisms that drive intestinal remodeling are still poorly understood. Transcriptome or proteome analysis of intestinal biopsies gives a global snapshot of all processes that occur in the tissue, including alterations in the epithelial cell layer. This paper will introduce concepts of intestinal remodeling, recapitulate the current understanding of CeD pathogenesis and discuss findings from relevant tissue "omics" studies. On the basis of this review, I give perspectives on what tissue "omics" studies can tell us about disease pathogenesis with a particular focus on the gluten induced intestinal remodeling.