Identification and characterization of differentially expressed genes in Type 2 Diabetes using in silico approach

Inflammation and immunological disarrays are associated with acute exercise in type 2 diabetes

Objective

Type 2 diabetes (T2D) is the most common metabolic disorder that is associated with insulin resistance. The aim of the present study is to discover details of the molecular mechanism of exercise on control or progress of diabetic condition in patients via network analysis.

Methods

Gene expression profiles of patients with T2D before and after doing exercise are retrieved from Gene Expression Omnibus (GEO) and are pre-evaluated by the GEO2R program. Data are studied based on expression values, regulatory relationships between the differentially expressed genes (DEGs), gene ontology analyses, and protein-protein interaction PPI network analysis.

Results

A number of 118 significant DEGs were identified and classified based on fold change (FC) values as most dysregulated genes and dysregulated individuals. Action map analysis revealed that 18 DEGs appeared as the critical genes. Gene ontology analysis showed that 24 DEGs are connected to at least four pathways. JUN, IL6, IL1B, PTGS2, FOS, MYC, ATF3, CXCL8, EGR1, EGR2, NR4A1, PLK3, TTN, and UCP3 were identified as central DEGs.

Conclusion

Finally; JUN, IL6, IL1B, PTGS2, FOS, ATF3, CXCL8, EGR1, and EGR2 were introduced as the critical targeted genes by exercise. Since the critical genes after exercise are upregulated and mostly are known as the risk factors of T2D, it can be concluded that unsuitable exercise can develop diabetic conditions in patients. Acute exercise-induced inflammation and immune disturbances seem to be associated with the development of T2D in patients.

Unraveling the impact of miR-21 on apoptosis regulation in glioblastoma

Glioblastoma is a prevalent form of carcinoma that exhibits a greater incidence rate across diverse demographics globally. Despite extensive global efforts, GBM continues to be a highly lethal disease that is characterized by a grim prognosis. There is a wealth of evidence suggesting that the pathophysiology of GBM is associated with the dysregulation of numerous cellular and molecular processes. The etiology of GBM may involve various cellular and molecular pathways, including EGFR, PDCD4, NF-κB, MAPK, matrix metalloproteinases, STAT, and Akt. MicroRNAs, short non-coding RNA molecules, regulate gene expression and mRNA translation after transcription but before translation to exert control over a wide range of biological functions. Extensive research has consistently demonstrated the upregulation of miRNA-21 in glioma, indicating its involvement in diverse biological pathways that facilitate tumor cell survival. By explaining the intricate interplay between miR-21 and the regulation of apoptosis in GBM, this review has the potential to significantly enhance our comprehension of the illness and provide potential targets for therapeutic intervention.

In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

Next-generation development and application of codon model in evolution

To date, numerous nucleotide, amino acid, and codon substitution models have been developed to estimate the evolutionary history of any sequence/organism in a more comprehensive way. Out of these three, the codon substitution model is the most powerful. These models have been utilized extensively to detect selective pressure on a protein, codon usage bias, ancestral reconstruction and phylogenetic reconstruction. However, due to more computational demanding, in comparison to nucleotide and amino acid substitution models, only a few studies have employed the codon substitution model to understand the heterogeneity of the evolutionary process in a genome-scale analysis. Hence, there is always a question of how to develop more robust but less computationally demanding codon substitution models to get more accurate results. In this review article, the authors attempted to understand the basis of the development of different types of codon-substitution models and how this information can be utilized to develop more robust but less computationally demanding codon substitution models. The codon substitution model enables to detect selection regime under which any gene or gene region is evolving, codon usage bias in any organism or tissue-specific region and phylogenetic relationship between different lineages more accurately than nucleotide and amino acid substitution models. Thus, in the near future, these codon models can be utilized in the field of conservation, breeding and medicine.

In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population

Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease’s pathophysiology.

Novel Molecular Networks and Regulatory MicroRNAs in Type 2 Diabetes Mellitus: Multiomics Integration and Interactomics Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a metabolic disorder with severe comorbidities. A multiomics approach can facilitate the identification of novel therapeutic targets and biomarkers with proper validation of potential microRNA (miRNA) interactions.

OBJECTIVE

The aim of this study was to identify significant differentially expressed common target genes in various tissues and their regulating miRNAs from publicly available Gene Expression Omnibus (GEO) data sets of patients with T2DM using in silico analysis.

METHODS

Using differentially expressed genes (DEGs) identified from 5 publicly available T2DM data sets, we performed functional enrichment, coexpression, and network analyses to identify pathways, protein-protein interactions, and miRNA-mRNA interactions involved in T2DM.

RESULTS

We extracted 2852, 8631, 5501, 3662, and 3753 DEGs from the expression profiles of GEO data sets GSE38642, GSE25724, GSE20966, GSE26887, and GSE23343, respectively. DEG analysis showed that 16 common genes were enriched in insulin secretion, endocrine resistance, and other T2DM-related pathways. Four DEGs, MAML3, EEF1D, NRG1, and CDK5RAP2, were important in the cluster network regulated by commonly targeted miRNAs (hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-124-3p, hsa-mir-1-3p), which are involved in the advanced glycation end products (AGE)-receptor for advanced glycation end products (RAGE) signaling pathway, culminating in diabetic complications and endocrine resistance.

CONCLUSIONS

This study identified tissue-specific DEGs in T2DM, especially pertaining to the heart, liver, and pancreas. We identified a total of 16 common DEGs and the top four common targeting miRNAs (hsa-let-7b-5p, hsa-miR-124-3p, hsa-miR-1-3p, and has-miR-155-5p). The miRNAs identified are involved in regulating various pathways, including the phosphatidylinositol-3-kinase-protein kinase B, endocrine resistance, and AGE-RAGE signaling pathways.

Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis

For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-induced arthritis (PIA) rat model (n = 24 total) were probed on AIT’s 16k protein microarray. To investigate the analogy of underlying disease pathways, differential reactivity analysis was conducted. A total of n = 602 differentially reactive antigens (DIRAGs) at a significance cutoff of p < 0.05 were identified between seropositive and seronegative RA for the human samples. Correlation with the clinical disease activity index revealed an inverse correlation of antibodies against self-proteins found in pathways relevant for antigen presentation and immune regulation. The PIA model showed n = 1291 significant DIRAGs within acute disease. Significant DIRAGs for (I) seropositive, (II) seronegative and (III) PIA were subjected to the Reactome pathway browser which also revealed pathways relevant for antigen presentation and immune regulation; of these, seven overlapping pathways had high significance. We therefore conclude that the PIA model reflects the biological similarities of the disease pathogenesis. Our data show that protein array analysis can elucidate biological differences and pathways relevant in disease as well be a useful additional layer of omics information.

PPARɣ2, aldose reductase, and TCF7L2 gene polymorphisms: relation to diabetes mellitus

Purpose

Diabetes mellitus (DM) is a growing global health concern. Genetic factors play a pivotal role in the development of diabetes. Therefore, the present work aimed to study the relation between peroxisome proliferator-activate receptors (PPARɣ2) (rs3856806), aldose reductase (AR) (rs759853), transcription factor 7 like 2 (TCF7L2) (rs7903146) gene polymorphism with diabetes in the Egyptian population.

Methods

The study included 260 diabetics and 120 healthy subjects. Genotyping was done using polymerase chain reaction-restriction fragment length polymorphism.

Results

Regression analysis revealed that PPARɣ2 TT, TCF7L2 TT were suggested to be independent risk predictors for T1DM and TCF7L2 TC, CC genotype were suggested to be independent protective factors against T1DM development. On the other hand, PPARɣ2 TT, AR TT genotypes were suggested to be independent risk predictors for T2DM susceptibility, and PPARɣ2 CT genotypes were suggested to be independent protective factors against T2DM development.

Conclusion

The present study revealed that PPARγ2 (rs3856806), TCF7L2 (rs7903146) and AR (rs759853) gene polymorphism may play an important role in the susceptibility of diabetes. Therefore, these polymorphisms may have a prognostic value for diabetes in the Egyptian population. Further work is required to confirm the role of these polymorphisms in diabetes.

Identification of Hub Genes Associated with Diabetes Mellitus and Tuberculosis Using Bioinformatic Analysis

Purpose

To investigate the potential pathophysiological association between tuberculosis (TB) and diabetes mellitus (DM) using bioinformatic analyses.

Patients and Methods

Gene expression datasets for healthy controls (HCs), TB patients, DM patients, TB+DM patients (GSE114192), and metformin-treated cells (GSE102677) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified from pairwise dataset comparisons TB vs HCs and DM vs HCs. DEGs were verified by comparing them to DEGs for TB+DM vs HCs. Enrichment analysis of DEGs common to all three dataset comparisons was conducted using DAVID. The protein–protein interaction (PPI) network was established via STRING and visualised in Cytoscape. Hub genes were identified using the Cytoscape plug-in cytoHubba and then were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. Targeted miRNA prediction analysis identified metformin treatment-induced gene expression changes in peripheral blood mononuclear cells.

Results

A total of 422 DEGs were common to all three dataset comparisons. Functional enrichment analysis revealed these DEGs were enriched for functional terms of type I interferon signaling pathway, innate immune response, inflammatory response, and infectious diseases. Ten hub genes identified using PPI network analysis were screened for interactions with metformin target gene INS using cytoHubba based on maximal clique centrality (MCC) score. Subsequently, five hub genes were predicted to functionally interact with INS, including STAT1, IFIT3, RSAD2, IFI44L, and XAF1, as verified by RT-qPCR. Meanwhile, seven miRNAs (miR-3680-3p, miR-3059-5p, miR-629-3p, miR-29b-2-5p, miR-514b-5p, miR-4755-5p, miR-4691-3p) were associated with regulation of hub genes. Notably, six hub genes (STAT1, IFIT3, RSAD2, ISG15, IFI44, IFI6) were down-regulated in cells exposed to both metformin and Mycobacterium tuberculosis antigens.

Conclusion

Network hub genes hold promise as disease status biomarkers and as metformin treatment targets for alleviating TB and DM. This study describes a strategy for exploring pathogenic mechanisms of diseases such as TB and DM.

Transcriptome analysis of islets from diabetes-resistant and diabetes-prone obese mice reveals novel gene regulatory networks involved in beta-cell compensation and failure

The mechanisms underpinning beta-cell compensation for obesity-associated insulin resistance and beta-cell failure in type 2 diabetes remain poorly understood. We used a large-scale strategy to determine the time-dependent transcriptomic changes in islets of diabetes-prone db/db and diabetes-resistant ob/ob mice at 6 and 16 weeks of age. Differentially expressed genes were subjected to cluster, gene ontology, pathway and gene set enrichment analyses. A distinctive gene expression pattern was observed in 16 week db/db islets in comparison to the other groups with alterations in transcriptional regulators of islet cell identity, upregulation of glucose/lipid metabolism, and various stress response genes, and downregulation of specific amino acid transport and metabolism genes. In contrast, ob/ob islets displayed a coordinated downregulation of metabolic and stress response genes at 6 weeks of age, suggestive of a preemptive reconfiguration in these islets to lower the threshold of metabolic activation in response to increased insulin demand thereby preserving beta-cell function and preventing cellular stress. In addition, amino acid transport and metabolism genes were upregulated in ob/ob islets, suggesting an important role of glutamate metabolism in beta-cell compensation. Gene set enrichment analysis of differentially expressed genes identified the enrichment of binding motifs for transcription factors, FOXO4, NFATC1, and MAZ. siRNA-mediated knockdown of these genes in MIN6 cells altered cell death, insulin secretion, and stress gene expression. In conclusion, these data revealed novel gene regulatory networks involved in beta-cell compensation and failure. Preemptive metabolic reconfiguration in diabetes-resistant islets may dampen metabolic activation and cellular stress during obesity.

Increased expression of anion transporter SLC26A9 delays diabetes onset in cystic fibrosis

Diabetes is a common complication of cystic fibrosis (CF) that affects approximately 20% of adolescents and 40%-50% of adults with CF. The age at onset of CF-related diabetes (CFRD) (marked by clinical diagnosis and treatment initiation) is an important measure of the disease process. DNA variants associated with age at onset of CFRD reside in and near SLC26A9. Deep sequencing of the SLC26A9 gene in 762 individuals with CF revealed that 2 common DNA haplotypes formed by the risk variants account for the association with diabetes. Single-cell RNA sequencing (scRNA-Seq) indicated that SLC26A9 is predominantly expressed in pancreatic ductal cells and frequently coexpressed with CF transmembrane conductance regulator (CFTR) along with transcription factors that have binding sites 5' of SLC26A9. These findings were replicated upon reanalysis of scRNA-Seq data from 4 independent studies. DNA fragments derived from the 5' region of SLC26A9-bearing variants from the low-risk haplotype generated 12%-20% higher levels of expression in PANC-1 and CFPAC-1 cells compared with the high- risk haplotype. Taken together, our findings indicate that an increase in SLC26A9 expression in ductal cells of the pancreas delays the age at onset of diabetes, suggesting a CFTR-agnostic treatment for a major complication of CF.

Neuroblastoma: An Updated Review on Biology and Treatment

BACKGROUND

Neuroblastoma (NB) is the second leading extracranial solid tumors of early childhood and clinically characterized by the presence of round, small, monomorphic cells with excess nuclear pigmentation (hyperchromasia).Owing to a lack of definitive treatment against NB and less survival rate in high-risk patients, there is an urgent requirement to understand molecular mechanisms associated with NB in a better way, which in turn can be utilized for developing drugs towards the treatment of NB in human.

OBJECTIVES

In this review, an approach was adopted to understand major risk factors, pathophysiology, the molecular mechanism associated with NB, and various therapeutic agents that can serve as drugs towards the treatment of NB in humans.

CONCLUSION

Numerous genetic (e.g., MYCN amplification), perinatal, and gestational factors are responsible for developing NB. However, no definite environmental or parental exposures responsible for causing NB have been confirmed to date. Though intensive multimodal treatment approaches, namely, chemotherapy, surgery & radiation, may help in improving the survival rate in children, these approaches have several side effects and do not work efficiently in high-risk patients. However, recent studies suggested that numerous phytochemicals, namely, vincristine, and matrine have a minimal side effect in the human body and may serve as a therapeutic drug during the treatment of NB. Most of these phytochemicals work in a dose-dependent manner and hence must be prescribed very cautiously. The information discussed in the present review will be useful in the drug discovery process as well as treatment and prevention on NB in humans.

Curcumin - A Novel Therapeutic Agent in the Prevention of Colorectal Cancer

Background:

Colorectal cancer is the third important cause of cancer-associated deaths across the world. Hence, there is an urgent need for understanding the complete mechanism associated with colorectal cancer, which in turn can be utilized toward early detection as well as the treatment of colorectal cancer in humans. Though colorectal cancer is a complex process and chemotherapy is the first step toward the treatment of colorectal cancer, recently several studies suggested that dietary phytochemicals may also aid significantly in reducing colorectal cancer risk in human. However, only few phytochemicals, specifically curcumin derived from the rhizomes of Curcuma longa, have better chemotherapeutic property, which might be because of its ability to regulate the activity of key factors associated with the initiation, promotion, as well as progression of tumors.

Objectives:

In the present review, the authors made an attempt to summarize the physiochemical properties of curcumin, which in turn prevent colorectal cancer via regulating numerous cell signaling as well as genetic pathways.

Conclusions:

Accumulated evidence suggested that curcumin suppresses tumour/colon cancer in various ways, (a) restricting cell cycle progression, or stimulating apoptosis, (b) restricting angiogenesis, anti-apoptotic proteins expression, cell survival signaling pathways & their cross-communication and (c) regulating immune responses. The information discussed in the present review will be useful in the drug discovery process as well as the treatment and prevention of colorectal cancer in humans.

Gene surgery: Potential applications for human diseases

Gene therapy became in last decade a new emerging therapeutic era showing promising results against different diseases such as cancer, cardiovascular diseases, diabetes, and neurological disorders. Recently, the genome editing technique for eukaryotic cells called CRISPR-Cas (Clustered Regulatory Interspaced Short Palindromic Repeats) has enriched the field of gene surgery with enhanced applications. In the present review, we summarized the different applications of gene surgery for treating human diseases such as cancer, diabetes, nervous, and cardiovascular diseases, besides the molecular mechanisms involved in these important effects. Several studies support the important therapeutic applications of gene surgery in a large number of health disorders and diseases including β-thalassemia, cancer, immunodeficiencies, diabetes, and neurological disorders. In diabetes, gene surgery was shown to be effective in type 1 diabetes by triggering different signaling pathways. Furthermore, gene surgery, especially that using CRISPR-Cas possessed important application on diagnosis, screening and treatment of several cancers such as lung, liver, pancreatic and colorectal cancer. Nevertheless, gene surgery still presents some limitations such as the design difficulties and costs regarding ZFNs (Zinc Finger Nucleases) and TALENs (Transcription Activator-Like Effector Nucleases) use, off-target effects, low transfection efficiency, in vivo delivery-safety and ethical issues.