Dataset Information

Concerted perturbation observed in a hub network in Alzheimer's disease.

ABSTRACT: Alzheimer's disease (AD) is a progressive neurodegenerative disease involving the alteration of gene expression at the whole genome level. Genome-wide transcriptional profiling of AD has been conducted by many groups on several relevant brain regions. However, identifying the most critical dys-regulated genes has been challenging. In this work, we addressed this issue by deriving critical genes from perturbed subnetworks. Using a recent microarray dataset on six brain regions, we applied a heaviest induced subgraph algorithm with a modular scoring function to reveal the significantly perturbed subnetwork in each brain region. These perturbed subnetworks were found to be significantly overlapped with each other. Furthermore, the hub genes from these perturbed subnetworks formed a connected hub network consisting of 136 genes. Comparison between AD and several related diseases demonstrated that the hub network was robustly and specifically perturbed in AD. In addition, strong correlation between the expression level of these hub genes and indicators of AD severity suggested that this hub network can partially reflect AD progression. More importantly, this hub network reflected the adaptation of neurons to the AD-specific microenvironment through a variety of adjustments, including reduction of neuronal and synaptic activities and alteration of survival signaling. Therefore, it is potentially useful for the development of biomarkers and network medicine for AD.

SUBMITTER: Liang D

PROVIDER: S-EPMC3398025 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Concerted perturbation observed in a hub network in Alzheimer's disease.

Liang Dapeng D Han Guangchun G Feng Xuemei X Sun Jiya J Duan Yong Y Lei Hongxing H

PloS one 20120716 7

Alzheimer's disease (AD) is a progressive neurodegenerative disease involving the alteration of gene expression at the whole genome level. Genome-wide transcriptional profiling of AD has been conducted by many groups on several relevant brain regions. However, identifying the most critical dys-regulated genes has been challenging. In this work, we addressed this issue by deriving critical genes from perturbed subnetworks. Using a recent microarray dataset on six brain regions, we applied a heavi ...[more]

PMID: 22815752

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Project description:ObjectiveTo investigate the differential expression gene modules and hub genes associated with Alzheimer's disease (AD) by weighted gene co-expression network analysis (WGCNA) and annotate the biological functions of these modules.MethodsWe downloaded transcriptome sequencing data from the GEO database, and according to the correlation of the genes, a gene co-expression network was constructed with the parameter setting of β=8 and a correlation coefficient threshold of 0.85. Pearson correlation test was used to calculate the correlation between the module genes and clinical traits to screen the gene modules significantly associated with AD and identify the hub genes according to the connectivity within modules. GO functional enrichment analysis and KEGG pathway analysis were used to annotate the functions of the modules. A cell model of AD was established in SH-SY5Y cells by Aβ1-42 treatment, and the mRNA expression levels of the hub genes were compared between the Aβ1-42-treated cells and the control cells.ResultsTen gene co-expression modules were constructed based on the correlations of gene expression, in which the brown (r=0.66, P < 0.001) and turquoise modules (r=-0.68, P < 0.001) were significantly correlated with the AD group. Forty-eight genes were identified as the hub genes in the co-expression network. Function annotation revealed that the genes in both modules were mainly enriched in DNA damage and repair pathways and metabolism-related pathways. Differential expression analysis of the genes revealed that the genes DNASE1, TEKT2 and MTSS1L were highly expressed while ACP2, LANCL2 and GMPR2 were lowly expressed in AD group. The results of cell experiment confirmed the up-regulation of DNASE1, TEKT2 and MTSS1L genes and the down-regulation of ACP2, LANCL2, and GMPR2 in Aβ1-42-treated SH-SY5Y cells (P < 0.01).ConclusionThe brown and turquoise modules are closely correlated with AD. The hub genes including MTSS1L, GMPR2, ACP2, ACTG1 and LANCL2 selected from the modules may participate in AD pathogenesis by regulating DNA damage and repair.

Project description:Brain connectivity studies have revealed that highly connected 'hub' regions are particularly vulnerable to Alzheimer pathology: they show marked amyloid-β deposition at an early stage. Recently, excessive local neuronal activity has been shown to increase amyloid deposition. In this study we use a computational model to test the hypothesis that hub regions possess the highest level of activity and that hub vulnerability in Alzheimer's disease is due to this feature. Cortical brain regions were modeled as neural masses, each describing the average activity (spike density and spectral power) of a large number of interconnected excitatory and inhibitory neurons. The large-scale network consisted of 78 neural masses, connected according to a human DTI-based cortical topology. Spike density and spectral power were positively correlated with structural and functional node degrees, confirming the high activity of hub regions, also offering a possible explanation for high resting state Default Mode Network activity. 'Activity dependent degeneration' (ADD) was simulated by lowering synaptic strength as a function of the spike density of the main excitatory neurons, and compared to random degeneration. Resulting structural and functional network changes were assessed with graph theoretical analysis. Effects of ADD included oscillatory slowing, loss of spectral power and long-range synchronization, hub vulnerability, and disrupted functional network topology. Observed transient increases in spike density and functional connectivity match reports in Mild Cognitive Impairment (MCI) patients, and may not be compensatory but pathological. In conclusion, the assumption of excessive neuronal activity leading to degeneration provides a possible explanation for hub vulnerability in Alzheimer's disease, supported by the observed relation between connectivity and activity and the reproduction of several neurophysiologic hallmarks. The insight that neuronal activity might play a causal role in Alzheimer's disease can have implications for early detection and interventional strategies.

Project description:Language impairment and behavioral symptoms are both common phenomena in dementia patients. In this study, we investigated the behavioral symptoms in dementia patients with different language backgrounds. Through this, we aimed to propose a possible connection between language and delusion.We recruited 21 patients with Alzheimer's disease (AD), according to the DSM-IV and NINCDS-ADRDA criteria, from the memory clinic of the Cardinal Tien Hospital in Taipei, Taiwan. They were classified into two groups: 11 multilinguals who could speak Japanese, Taiwanese and Mandarin Chinese, and 10 bilinguals who only spoke Taiwanese and Mandarin Chinese. There were no differences between age, education, disease duration, disease severity, environment and medical care between these two groups. Comprehensive neuropsychological examinations, including Clinical Dementia Rating (CDR), Mini-Mental Status Examination (MMSE), Cognitive Abilities Screening Instrument (CASI), Verbal fluency, Chinese version of the Boston naming test (BNT) and the Behavioral Pathology in Alzheimer's Disease Rating Scale (BEHAVE-AD), were administered.The multilingual group showed worse results on the Boston naming test. Other neuropsychological tests, including the MMSE, CASI and Verbal fluency, were not significantly different. More delusions were noted in the multilingual group. Three pairs of subjects were identified for further examination of their differences. These three cases presented the typical scenario of how language misunderstanding may cause delusions in multilingual dementia patients. Consequently, more emotion and distorted ideas may be induced in the multilinguals compared with the MMSE-matched controls.Inappropriate mixing of language or conflict between cognition and emotion may cause more delusions in these multilingual patients. This reminds us that delusion is not a pure biological outcome of brain degeneration. Although the cognitive performance was not significantly different between our groups, language may still affect their delusion.

Project description:Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer's disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer's disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer's pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer's disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure--analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity 'overload' that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both.

Dataset Information

Concerted perturbation observed in a hub network in Alzheimer's disease.

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Concerted perturbation observed in a hub network in Alzheimer's disease.

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