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      Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease

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          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.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database.

            The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.
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              Network pharmacology.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                16 July 2012
                : 7
                : 7
                : e40498
                Affiliations
                [1 ]CAS key laboratory of genome sciences and information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
                [2 ]Graduate University, Chinese Academy of Sciences, Beijing, China
                [3 ]UC Davis Genome Center and Department of Biomedical Engineering, University of California Davis, Davis, California, United States of America
                Hospital for Sick Children, Canada
                Author notes

                Conceived and designed the experiments: DL HL. Performed the experiments: DL HL XF JS. Analyzed the data: DL HL XF JS GH. Contributed reagents/materials/analysis tools: DL. Wrote the paper: DL HL YD.

                Article
                PONE-D-11-13418
                10.1371/journal.pone.0040498
                3398025
                22815752
                fc9f72aa-f459-4d4c-9493-90c394f55577
                Liang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 13 July 2011
                : 11 June 2012
                Page count
                Pages: 17
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Functional Genomics
                Genome Expression Analysis
                Microarrays
                Systems Biology
                Genetics
                Genetics of Disease
                Genome-Wide Association Studies
                Neuroscience
                Neurobiology of Disease and Regeneration
                Systems Biology

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                Uncategorized

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