12,739 research outputs found

    Expression-Based Network Biology Identifies Alteration in Key Regulatory Pathways of Type 2 Diabetes and Associated Risk/Complications

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    Type 2 diabetes mellitus (T2D) is a multifactorial and genetically heterogeneous disease which leads to impaired glucose homeostasis and insulin resistance. The advanced form of disease causes acute cardiovascular, renal, neurological and microvascular complications. Thus there is a constant need to discover new and efficient treatment against the disease by seeking to uncover various novel alternate signalling mechanisms that can lead to diabetes and its associated complications. The present study allows detection of molecular targets by unravelling their role in altered biological pathways during diabetes and its associated risk factors and complications. We have used an integrated functional networks concept by merging co-expression network and interaction network to detect the transcriptionally altered pathways and regulations involved in the disease. Our analysis reports four novel significant networks which could lead to the development of diabetes and other associated dysfunctions. (a) The first network illustrates the up regulation of TGFBRII facilitating oxidative stress and causing the expression of early transcription genes via MAPK pathway leading to cardiovascular and kidney related complications. (b) The second network demonstrates novel interactions between GAPDH and inflammatory and proliferation candidate genes i.e., SUMO4 and EGFR indicating a new link between obesity and diabetes. (c) The third network portrays unique interactions PTPN1 with EGFR and CAV1 which could lead to an impaired vascular function in diabetic nephropathy condition. (d) Lastly, from our fourth network we have inferred that the interaction of β-catenin with CDH5 and TGFBR1 through Smad molecules could contribute to endothelial dysfunction. A probability of emergence of kidney complication might be suggested in T2D condition. An experimental investigation on this aspect may further provide more decisive observation in drug target identification and better understanding of the pathophysiology of T2D and its complications

    Topological Analysis of Biological Pathways: Genes, MicroRNAs and Pathways Involved in Hepatocellular Carcinoma

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    abstract: Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of miRNAs on the topology of biological pathways between controls and cases. In the dissertation, it is discussed that how rewired biological pathways (Chapter 1) and/or rewired miRNA-mRNA interactions (Chapter 2) aberrantly influence the activity of biological pathways and their association with disease. This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.Dissertation/ThesisDoctoral Dissertation Molecular and Cellular Biology 201

    Gene regulatory network reveals oxidative stress as the underlying molecular mechanism of type 2 diabetes and hypertension

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    <p>Abstract</p> <p>Background</p> <p>The prevalence of diabetes is increasing worldwide. It has been long known that increased rates of inflammatory diseases, such as obesity (OBS), hypertension (HT) and cardiovascular diseases (CVD) are highly associated with type 2 diabetes (T2D). T2D and/or OBS can develop independently, due to genetic, behavioral or lifestyle-related variables but both lead to oxidative stress generation. The underlying mechanisms by which theses complications arise and manifest together remain poorly understood. Protein-protein interactions regulate nearly every living process. Availability of high-throughput genomic data has enabled unprecedented views of gene and protein co-expression, co-regulations and interactions in cellular systems.</p> <p>Methods</p> <p>The present work, applied a systems biology approach to develop gene interaction network models, comprised of high throughput genomic and PPI data for T2D. The genes differentially regulated through T2D were 'mined' and their 'wirings' were studied to get a more complete understanding of the overall gene network topology and their role in disease progression.</p> <p>Results</p> <p>By analyzing the genes related to T2D, HT and OBS, a highly regulated gene-disease integrated network model has been developed that provides useful functional linkages among groups of genes and thus addressing how different inflammatory diseases are connected and propagated at genetic level. Based on the investigations around the 'hubs' that provided more meaningful insights about the cross-talk within gene-disease networks in terms of disease phenotype association with oxidative stress and inflammation, a hypothetical co-regulation disease mechanism model been proposed. The results from this study revealed that the oxidative stress mediated regulation cascade is the common mechanistic link among the pathogenesis of T2D, HT and other inflammatory diseases such as OBS.</p> <p>Conclusion</p> <p>The findings provide a novel comprehensive approach for understanding the pathogenesis of various co-associated chronic inflammatory diseases by combining the power of pathway analysis with gene regulatory network evaluation.</p

    Diabetes and associated cardiovascular complications: The role of microRNAs

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    Diabetes mellitus (DM) refers to a complex cluster of metabolic disorders characterized by hyperglycemia caused by inadequate insulin secretion, insulin resistance, or excessive glucagon secretion. If not correctly treated, the prolonged effects of DM-associated metabolic perturbations lead to systemic vascular complications and cardiovascular disease (CVD), the principal cause of mortality among patients with DM. Given the increase in the global prevalence of diabetes, novel diagnostic and therapeutic procedures are necessary for its effective identification and treatment. Recent findings point to an important role of microRNA (miRNAs) in DM initiation and progression, as well as the occurrence of associated cardiovascular complications. miRNAs are short, highly conserved, single-stranded, non-coding RNAs that contribute to the maintenance of physiological homeostasis through the regulation of crucial processes such as metabolism, cell proliferation, and apoptosis. The increased availability of high-throughput methodologies for identifying and characterizing non-coding RNAs has led to considerable interest in miRNAs as potential biomarkers and therapeutic agents for DM. In this review, we first comprehensively detail the regulatory miRNAs involved in the pathophysiology of DM and diabetic cardiomyopathy (DCMP). Subsequently, we summarize findings regarding the utility of several of these miRNAs as potential prognostic and diagnostic biomarkers for DM and DM-associated CVD. Finally, we evaluate the potential of miRNA-based therapeutic approaches for treating DM and DCMP in the clinical setting

    Integrated datasets of proteomic and metabolomic biomarkers to predict its impacts on comorbidities of type 2 diabetes mellitus

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    © 2020 Cheema et al. Objective: The objective of the current study is to accomplish a relative exploration of the biological roles of differentially dysregulated genes (DRGs) in type 2 diabetes mellitus (T2DM). The study aimed to determine the impact of these DRGs on the biological pathways and networks that are related to the associated disorders and complications in T2DM and to predict its role as prospective biomarkers. Methods: Datasets obtained from metabolomic and proteomic profiling were used for investigation of the differential expression of the genes. A subset of DRGs was integrated into IPA software to explore its biological pathways, related diseases, and their regulation in T2DM. Upon entry into the IPA, only 94 of the DRGs were recognizable, mapped, and matched within the database. Results: The study identified networks that explore the dysregulation of several functions; cell components such as degranulation of cells; molecular transport process and metabolism of cellular proteins; and inflammatory responses. Top disorders associated with DRGs in T2DM are related to organ injuries such as renal damage, connective tissue disorders, and acute inflammatory disorders. Upstream regulator analysis predicted the role of several transcription factors of interest, such as STAT3 and HIF alpha, as well as many kinases such as JAK kinases, which affects the gene expression of the dataset in T2DM. Interleukin 6 (IL6) is the top regulator of the DRGs, followed by leptin (LEP). Monitoring the dysregulation of the coupled expression of the following biomarkers (TNF, IL6, LEP, AGT, APOE, F2, SPP1, and INS) highlights that they could be used as potential prognostic biomarkers. Conclusion: The integration of data obtained by advanced metabolomic and proteomic technologies has made it probable to advantage in understanding the role of these biomarkers in the identification of significant biological processes, pathways, and regulators that are associated with T2DM and its comorbidities

    A lesson for cancer research : placental microarray gene analysis in preeclampsia

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    Tumor progression and pregnancy share many common features, such as immune tolerance and invasion. The invasion of trophoblasts in the placenta into the uterine wall is essential for fetal development, and is thus precisely regulated. Its deregulation has been implicated in preeclampsia, a leading cause for maternal and perinatal mortality and morbidity. Pathogenesis of preeclampsia remains to be defined. Microarray-based gene profiling has been widely used for identifying genes responsible for preeclampsia. In this review, we have summarized the recent data from the microarray studies with preeclamptic placentas. Despite the complex of gene signatures, suggestive of the heterogeneity of preeclampsia, these studies identified a number of differentially expressed genes associated with preeclampsia. Interestingly, most of them have been reported to be tightly involved in tumor progression. We have discussed these interesting genes and analyzed their potential molecular functions in preeclampsia, compared with their roles in malignancy development. Further investigations are warranted to explore the involvement in molecular network of each identified gene, which may provide not only novel strategies for prevention and therapy for preeclampsia but also a better understanding of cancer cells. The trophoblastic cells, with their capacity for proliferation and differentiation, apoptosis and survival, migration, angiogenesis and immune modulation by exploiting similar molecular pathways, make them a compelling model for cancer research
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