Celiac disease: Epidemiology, Genetic and Clinical Behavior in Iran

Mulder, C.J.J. [Promotor]Zali, M.R. [Promotor

The Potential of Algae in Treating Celiac Disease

Compounds found in algae, such as bioactive substances, sulfated polysaccharides, and polyunsaturated fatty acids, have been found to have positive effects on the immune system. Previous research has shown that algae can also benefit digestive system disorders. They possess antioxidant and anti-inflammatory properties and can influence the balance of gut microbiota and maintain the integrity of the intestinal lining. Celiac disease (CD), a disorder caused by an abnormal immune response to gluten, results in inflammation and damage to the intestinal lining, leading to problems with nutrient absorption. Although a lifelong gluten-free diet is the only treatment option for this disease, it is challenging to adhere to. Therefore, recent studies have focused on finding supplementary or alternative therapies for celiac disease patients. Traditional medical treatments, like anti-inflammatory and biological drugs, are associated with significant side effects and are not suitable for supplementary therapy for this group of patients. Algae shows promise as a potential research area for treating CD; however, their specific effects on this condition have not been widely studied. The aim of this study was to gather current information and draw attention to the potential use of algae extracts in treating CD to encourage further research in this field

Celiac disease and hepatitis C relationships in transcriptional regulatory networks

Aim: we mainly aimed to elucidate potential comorbidities between celiac disease and hepatitis c by means of data and network analysis approaches. Background: understanding the association among the disorders evidently has important impact on the diagnosis and therapeutic approaches. Celiac disease is the most challenging, common types of autoimmune disorders. On the other hand, hepatitis c virus genome products like some proteins are supposed to be resemble to gliadin types that in turn activates gluten intolerance in people with inclined to gluten susceptibilities. Moreover, a firm support of association between chronic hepatitis and celiac disease remains largely unclear. Henceforth exploring cross-talk among these diseases will apparently lead to the promising discoveries concerning important genes and regulators. Methods: 321 and 1032 genes associated with celiac disease and hepatitis c retrieved from DisGeNET were subjected to build a gene regulatory network. Afterward a network-driven integrative analysis was performed to exploring prognosticates genes and related pathways. Results: 105 common genes between these diseases included 11 transcription factors were identified as hallmark molecules where by further screening enriched in biological GO terms and pathways chiefly in immune systems and signaling pathways such as chemokines, cytokines and interleukins. Conclusion: in silico data analysis approaches indicated that the identified selected combinations of genes covered a wide range of known functions triggering the inflammation implicated in these diseases

Celiac disease and hepatitis C relationships in transcriptional regulatory networks

Aim: we mainly aimed to elucidate potential comorbidities between celiac disease and hepatitis c by means of data and network analysis approaches. Background: understanding the association among the disorders evidently has important impact on the diagnosis and therapeutic approaches. Celiac disease is the most challenging, common types of autoimmune disorders. On the other hand, hepatitis c virus genome products like some proteins are supposed to be resemble to gliadin types that in turn activates gluten intolerance in people with inclined to gluten susceptibilities. Moreover, a firm support of association between chronic hepatitis and celiac disease remains largely unclear. Henceforth exploring cross-talk among these diseases will apparently lead to the promising discoveries concerning important genes and regulators. Methods: 321 and 1032 genes associated with celiac disease and hepatitis c retrieved from DisGeNET were subjected to build a gene regulatory network. Afterward a network-driven integrative analysis was performed to exploring prognosticates genes and related pathways. Results: 105 common genes between these diseases included 11 transcription factors were identified as hallmark molecules where by further screening enriched in biological GO terms and pathways chiefly in immune systems and signaling pathways such as chemokines, cytokines and interleukins. Conclusion: in silico data analysis approaches indicated that the identified selected combinations of genes covered a wide range of known functions triggering the inflammation implicated in these diseases

Nasopharyngeal carcinoma protein interaction mapping analysis via proteomic approaches

Nasopharyngeal carcinoma (NPC), although not very common in many parts of the world, is a major concern in some countries, including Iran. Molecular studies are very helpful to provide essential information regarding underlying carcinogenetic mechanisms. Here, considering NPC proteomic approaches, established biomarkers were designated for protein-protein interaction network construction and analysis with corresponding plug-ins. A network of reported protein markers was constructed and topological and biological process features were investigated. Centrality analysis showed that JUN, CALM1, HSB1, and SOD1 are more important than other differentially expressed proteins in an interacting pattern. What is more, by extending the network, Tp53, PRDM10, AKT1, ALB, HSP90AA1, and EGFR achieved the highest values for NPC network strength. It can be concluded that these proteins as well as their contributing processes, particularly in a second network, may be important for NPC onset and development. Targeting these candidate proteins may allow novel treatment approaches following appropriate validation. © Asian Pacific Journal of Cancer Prevention, 2017

The Main Targets of Okadaic Acid Toxin in Human Intestinal Caco-2 Cells: An Investigation of Biological Systems

Background: Okadaic acid (OA) is a toxin of polluted shellfish. Consuming the contaminated shellfish is accompanied by diarrhea and paralytic and amnesic disorders. There is a correlation between diarrhea and the consumed OA. Determining the critical targeted genes by OA was the aim of this study. Methods: The transcriptomic data about the effect of OA on human intestinal caco-2 cells were extracted from gene expression omnibus (GEO) and evaluated via the GEO2R program. The significant differentially expressed genes (DEGs) were included in a protein-protein interaction (PPI) network and the central nodes were enriched via gene ontology to find the crucial affected biological terms. Results: Among the 178 significant DEGs plus 50 added first neighbors, four hub-bottleneck genes (ALB, FOS, JUN, and MYC) were determined. Twenty-eight critical biological terms were identified as the dysregulated individuals in response to the presence of OA. “ERK1/2-activator protein-1 (AP-1) complex binds KDM6B promoter” was highlighted as the major class of biological terms. Conclusion: It can be concluded that down-regulation of ALB as a potent central gene leads to impairment of blood homeostasis in the presence of OA. Up-regulation of the other three central genes (JUN, FOS, and MYC) grossly affects the vital pathways in the human body

Nasopharyngeal carcinoma protein interaction mapping analysis via proteomic approaches

Nasopharyngeal carcinoma (NPC), although not very common in many parts of the world, is a major concern in some countries, including Iran. Molecular studies are very helpful to provide essential information regarding underlying carcinogenetic mechanisms. Here, considering NPC proteomic approaches, established biomarkers were designated for protein-protein interaction network construction and analysis with corresponding plug-ins. A network of reported protein markers was constructed and topological and biological process features were investigated. Centrality analysis showed that JUN, CALM1, HSB1, and SOD1 are more important than other differentially expressed proteins in an interacting pattern. What is more, by extending the network, Tp53, PRDM10, AKT1, ALB, HSP90AA1, and EGFR achieved the highest values for NPC network strength. It can be concluded that these proteins as well as their contributing processes, particularly in a second network, may be important for NPC onset and development. Targeting these candidate proteins may allow novel treatment approaches following appropriate validation. © Asian Pacific Journal of Cancer Prevention, 2017

Protein-protein interaction network analysis for a biomarker panel related to human esophageal adenocarcinoma

Background: Esophageal adenocarcinoma (EAC) is one of the mostlethal cancers in the world with a very poor prognosis. Identification of molecular diagnostic methods is an important goal. Since protein-protein interaction (PPI) network analysis is a suitable method for molecular assessment, in the present research a PPI network related to EAC was targeted. Material and Method: Cytoscape software and its applications including STRING DB, Cluster ONE and ClueGO were applied to analyze the PPI network. Result: Among 182 EAC-related proteins which were identified, 129 were included in a main connected component. Proteins based on centrality analysis of characteristics such as degree, betweenness, closeness and stress were screened and key nodes were introduced. Two clusters were determined of which only one was significant statistically. Gene ontology revealed 50 terms in three groups associated with EAC. Conclusion: The findings indicate nine crucial proteins could form a candidate biomarker panel for EAC. Furthermore, an important cluster with 27 proteins related to the disease was identified. Gene ontology analysis of this cluster showed main related terms to closely correspond with those for colorectal cancer