The Gene Coexpression Analysis Identifies Functional Modules Dynamically Changed After Traumatic Brain Injury.
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ABSTRACT:
SUBMITTER: Zhao ZJ
PROVIDER: S-EPMC8068551 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Genetic mechanisms of atrial fibrillation (AF) remain incompletely understood. Previous differential expression studies in AF were limited by small sample size and provided limited understanding of global gene networks, prompting the need for larger-scale, network-based analyses.Left atrial tissues from Cleveland Clinic patients who underwent cardiac surgery were assayed using Illumina Human HT-12 mRNA microarrays. The data set included 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without coronary artery disease (n=64), coronary artery disease without MV disease (n=57), and lone AF (n=35). Weighted gene coexpression network analysis was performed in the MV group to detect modules of correlated genes. Module preservation was assessed in the other 2 groups. Module eigengenes were regressed on AF severity or atrial rhythm at surgery. Modules whose eigengenes correlated with either AF phenotype were analyzed for gene content. A total of 14 modules were detected in the MV group; all were preserved in the other 2 groups. One module (124 genes) was associated with AF severity and atrial rhythm across all groups. Its top hub gene, RCAN1, is implicated in calcineurin-dependent signaling and cardiac hypertrophy. Another module (679 genes) was associated with atrial rhythm in the MV and coronary artery disease groups. It was enriched with cell signaling genes and contained cardiovascular developmental genes including TBX5.Our network-based approach found 2 modules strongly associated with AF. Further analysis of these modules may yield insight into AF pathogenesis by providing novel targets for functional studies.
| S-EPMC3955718 | biostudies-other
Project description:BackgroundComputational approaches toward gene annotation are a formidable challenge, now that many genome sequences have been determined. Each gene has its own function, but complicated cellular functions are achieved by sets of genes. Therefore, sets of genes with strong functional relationships must be identified. For this purpose, the similarities of gene expression patterns and gene sequences have been separately utilized, although the combined information will provide a better solution.Result & discussionWe propose a new method to find functional modules, by comparing gene coexpression profiles among species. A coexpression pattern is represented as a list of coexpressed genes with each guide gene. We compared two coexpression lists, one from a human guide gene and the other from a homologous mouse gene, and defined a measure to evaluate the similarity between the lists. Based on this coexpression similarity, we detected the highly conserved genes, and constructed human gene networks with conserved coexpression between human and mouse. Some of the tightly coupled genes (modules) showed clear functional enrichment, such as immune system and cell cycle, indicating that our method could identify functionally related genes without any prior knowledge. We also found a few functional modules without any annotations, which may be good candidates for novel functional modules. All of the comparisons are available at the http://v1.coxsimdb.info web database.
| S-EPMC4493118 | biostudies-literature
Project description:Purpose:Despite advances in characterizing the neurobiology of emotional disorders, there is still a significant lack of scientific understanding of the pathophysiological mechanisms governing major depressive disorder (MDD). This study attempted to elucidate the molecular circuitry of MDD and to identify more potential genes associated with the pathogenesis of the disease. Patients and Methods:Microarray data from the GSE98793 dataset were downloaded from the NCBI Gene Expression Omnibus (GEO) database, including 128 patients with MDD and 64 healthy controls. Weighted gene coexpression network analysis (WGCNA) was performed to find modules of differentially expressed genes (DEGs) with high correlations followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to obtain further biological insight into the top three key modules. The protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed, as well. Results:We filtered 3276 genes that were considered significant DEGs for further WGCNA analysis. By performing WGCNA, we found that the turquoise, blue and brown functional modules were all strongly correlated with MDD development, including immune response, neutrophil degranulation, ribosome biogenesis, T cell activation, glycosaminoglycan biosynthetic process, and protein serine/threonine kinase activator activity. Hub genes were identified in the key functional modules that might have a role in the progression of MDD. Functional annotation showed that these modules primarily enriched such KEGG pathways as the TNF signaling pathway, T cell receptor signaling pathway, primary immunodeficiency, Th1, Th2 and Th17 cell differentiation, autophagy and RNA degradation and oxidative phosphorylation. These results suggest that these genes are closely related to autophagy and cellular immune function. Conclusion:The results of this study may help to elucidate the pathophysiology of MDD development at the molecular level and explore the potential molecular mechanisms for new interventional strategies.
| S-EPMC7079285 | biostudies-literature
Project description:ObjectivesResearch suggests that the majority of mild traumatic brain injury (mTBI) patients exhibit both cognitive and emotional dysfunction within the first weeks of injury, followed by symptom resolution 3-6 months postinjury. The neuronal correlates of said dysfunction are difficult to detect with standard clinical neuroimaging, complicating differential diagnosis and early identification of patients who may not recover. This study examined whether resting state functional magnetic resonance imaging (fMRI) provides objective markers of injury and predicts cognitive, emotional, and somatic complaints in mTBI patients semiacutely (<3 weeks postinjury) and in late recovery (3-5 month) phases.MethodsTwenty-seven semiacute mTBI patients and 26 gender, age, and education-matched controls were studied. Fifteen of 27 patients returned for a follow-up visit 3-5 months postinjury. The main dependent variables were spontaneous fluctuations (temporal correlation) in the default-mode (DMN) and fronto-parietal task-related networks as measured by fMRI.ResultsSignificant differences in self-reported cognitive, emotional, and somatic complaints were observed (all P < 0.05), despite normal clinical (T1 and T2) imaging and neuropsychological testing results. Mild TBI patients demonstrated decreased functional connectivity within the DMN and hyper-connectivity between the DMN and lateral prefrontal cortex. Measures of functional connectivity exhibited high levels of sensitivity and specificity for patient classification and predicted cognitive complaints in the semi-acute injury stage. However, no changes in functional connectivity were observed across a 4-month recovery period.ConclusionsAbnormal connectivity between the DMN and frontal cortex may provide objective biomarkers of mTBI and underlie cognitive impairment.
| S-EPMC3204375 | biostudies-literature
Project description:BackgroundWhen plants are subjected to cold stress, they undergo a series of molecular and physiological changes to protect themselves from injury. Indica cultivars can usually withstand only mild cold stress in a relatively short period. Hormone-mediated defence response plays an important role in cold stress. Weighted gene co-expression network analysis (WGCNA) is a very useful tool for studying the correlation between genes, identifying modules with high phenotype correlation, and identifying Hub genes in different modules. Many studies have elucidated the molecular mechanisms of cold tolerance in different plants, but little information about the recovery process after cold stress is available.ResultsTo understand the molecular mechanism of cold tolerance in rice, we performed comprehensive transcriptome analyses during cold treatment and recovery stage in two cultivars of near-isogenic lines (9311 and DC907). Twelve transcriptomes in two rice cultivars were determined. A total of 2509 new genes were predicted by fragment splicing and assembly, and 7506 differentially expressed genes were identified by pairwise comparison. A total of 26 modules were obtained by expression-network analysis, 12 of which were highly correlated with cold stress or recovery treatment. We further identified candidate Hub genes associated with specific modules and analysed their regulatory relationships based on coexpression data. Results showed that various plant-hormone regulatory genes acted together to protect plants from physiological damage under short-term low-temperature stress. We speculated that this may be common in rice. Under long-term cold stress, rice improved the tolerance to low-temperature stress by promoting autophagy, sugar synthesis, and metabolism.ConclusionThrough WGCNA analysis at the transcriptome level, we provided a potential regulatory mechanism for the cold stress and recovery of rice cultivars and identified candidate central genes. Our findings provided an important reference for the future cultivation of rice strains with good tolerance.
| S-EPMC8974213 | biostudies-literature
Project description:Time dependent-profiles in the gene expression level following lateral moderate fluid percussion injury in the rat brain We used microarray to elucidate relationship between the alteration of gene expression levels and the progression of brain damages following traumatic brain injury. To examine the levels of gene expression in the early phase of traumatic brain injury, we analyzed the gene expression at 3, 6, 12, and 48 h after trauma using the lateral moderate fluid percussion TBI model. The ratios of the gene expression level were compared between chips corresponding to the 3, 6 and 12 h fluid percussion groups and the sham group chips. On the other hand, the rations of gene expression level after 48 h FPI were compared with 48 h sham chip, because the gene expression levels of 48 h sham chip were distinct from sham group chips (3, 6 and 12 h) in the cluster and principal components analyses.
2010-12-07 | E-GEOD-24047 | biostudies-arrayexpress
Project description:Background: Traumatic brain injury (TBI) is a brain function change caused by external forces, which is one of the main causes of death and disability worldwide. The aim of this study was to identify early diagnostic markers and potential therapeutic targets for TBI. Methods: Differences between TBI and controls in GSE89866 and GSE104687 were analyzed. The two groups of differentially expressed genes (DEGs) were combined for coexpression analysis, and the modules of interest were performed using enrichment analysis. Hub genes were identified by calculating area under curve (AUC) values of module genes, PPI network analysis, and functional similarity. Finally, the difference in immune cell infiltration between TBI and control was calculated by ssGSEA. Results: A total of 4,817 DEGs were identified in GSE89866 and 1,329 DEGs in GSE104687. They were clustered into nine modules. The genes of modules 1, 4, and 7 had the most crosstalk and were identified as important modules. Enrichment analysis revealed that they were mainly associated with neurodevelopment and immune inflammation. In the PPI network constructed by genes with top 50 AUC values in module genes, we identified the top 10 genes with the greatest connectivity. Among them, down-regulated RPL27, RPS4X, RPL23A, RPS15A, and RPL7A had similar functions and were identified as hub genes. In addition, DC and Tem were significantly up-regulated and down-regulated between TBI and control, respectively. Conclusion: We found that hub genes may have a diagnostic role for TBI. Molecular dysregulation mechanisms of TBI are associated with neurological and immune inflammation. These results may provide new ideas for the diagnosis and treatment of TBI.
| S-EPMC8042258 | biostudies-literature
Project description:Mild traumatic brain injury (mTBI) is one of the most common neurological disorders for which a subset of patients develops persistent postconcussive symptoms. Previous studies discovered abnormalities and disruptions in the brain functional networks of mTBI patients principally using static functional connectivity measures which assume that neural communication across the brain is static during resting state conditions. In this study, we examine the differences in dynamic neural communication between mTBI and control participants through the application of a combination of dynamic functional analysis and graph theoretic algorithms. Resting state functional magnetic resonance imaging data was obtained on 47 mTBI patients at the acute stage of injury and 30 demographically matched healthy control participants. Results show unique alterations in both the static and dynamic functional connectivity at the acute stage in mTBI patients who suffer persistent symptoms (≥6 months after injury). In addition, mTBI patients with postconcussion syndrome demonstrated a unique allocation of time in various brain states compared to both control participants and mTBI patients with favorable outcomes. These findings suggest that global damage to the overall communication across the brain in the acute stage may contribute to chronic mTBI symptoms. Dynamic functional analysis is a powerful tool that provides insights into the brain states and the innovative analysis methodology utilized may hold the potential to delineate patients predisposed to poor outcomes upon early presentation following injury.
| S-EPMC6648233 | biostudies-literature
Project description:Brain-derived neurotrophic factor (BDNF), a key player in regulating synaptic strength and learning, is dysregulated following traumatic brain injury (TBI), suggesting that stimulation of BDNF signaling pathways may facilitate functional recovery. This study investigates whether CN2097, a peptidomimetic ligand which targets the synaptic scaffold protein, postsynaptic density protein 95, to enhance downstream signaling of tropomyosin-related kinase B, a receptor for BDNF, can improve neurological function after TBI. Moderate to severe TBI elicits neuroinflammation and c-Jun-N-terminal kinase (JNK) activation, which is associated with memory deficits. Here we demonstrate that CN2097 significantly reduces the post-traumatic synthesis of proinflammatory mediators and inhibits the post-traumatic activation of JNK in a rodent model of TBI. The recordings of field excitatory post-synaptic potentials in the hippocampal CA1 subfield demonstrate that TBI inhibits the expression of long-term potentiation (LTP) evoked by high-frequency stimulation of Schaffer collaterals, and that CN2097 attenuates this LTP impairment. Lastly, we demonstrate that CN2097 significantly improves the complex auditory processing deficits, which are impaired after injury. The multifunctionality of CN2097 strongly suggests that CN2097 could be highly efficacious in targeting complex secondary injury processes resulting from neurotrauma.
| S-EPMC5591207 | biostudies-literature
Project description:BackgroundUlcerative colitis is a type of inflammatory bowel disease posing a great threat to the public health worldwide. Previously, gene expression studies of mucosal colonic biopsies have provided some insight into the pathophysiological mechanisms in ulcerative colitis; however, the exact pathogenesis is unclear. The purpose of this study is to identify the most related genes and pathways of UC by bioinformatics, so as to reveal the core of the pathogenesis.MethodsGenome-wide gene expression datasets involving ulcerative colitis patients were collected from gene expression omnibus database. To identify most close genes, an integrated analysis of gene expression signature was performed by employing robust rank aggregation method. We used weighted gene co-expression network analysis to explore the functional modules involved in ulcerative colitis pathogenesis. Besides, biological process and pathways analysis of co-expression modules were figured out by gene ontology enrichment analysis using Metascape.ResultsA total of 328 ulcerative colitis patients and 138 healthy controls were from 14 datasets. The 150 most significant differentially expressed genes are likely to include causative genes of disease, and further studies are needed to demonstrate this. Seven main functional modules were identified, which pathway enrichment analysis indicated were associated with many biological processes. Pathways such as 'extracellular matrix, immune inflammatory response, cell cycle, material metabolism' are consistent with the core mechanism of ulcerative colitis. However, 'defense response to virus' and 'herpes simplex infection' suggest that viral infection is one of the aetiological agents. Besides, 'Signaling by Receptor Tyrosine Kinases' and 'pathway in cancer' provide new clues for the study of the risk and process of ulcerative colitis cancerization.
| S-EPMC6858811 | biostudies-literature