Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease
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{"title"=>"Network topology analysis of post-mortem brain microarrays identifies more Alzheimer's related genes and microRNAs and points to novel Routes for fighting with the disease", "type"=>"journal", "authors"=>[{"first_name"=>"Sreedevi", "last_name"=>"Chandrasekaran", "scopus_author_id"=>"56201073000"}, {"first_name"=>"Danail", "last_name"=>"Bonchev", "scopus_author_id"=>"7004739529"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "doi"=>"10.1371/journal.pone.0144052", "sgr"=>"84958206472", "scopus"=>"2-s2.0-84958206472", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"26784894", "pui"=>"608240650"}, "id"=>"5ddcaba5-dcf0-393c-8e4f-bd23d894df97", "abstract"=>"Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer's disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer's disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies.", "link"=>"http://www.mendeley.com/research/network-topology-analysis-postmortem-brain-microarrays-identifies-more-alzheimers-related-genes-micr", "reader_count"=>30, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Researcher"=>11, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Other"=>3, "Student > Master"=>5, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Researcher"=>11, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Other"=>3, "Student > Master"=>5, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>4, "Biochemistry, Genetics and Molecular Biology"=>7, "Agricultural and Biological Sciences"=>6, "Medicine and Dentistry"=>3, "Neuroscience"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>4, "Chemistry"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Neuroscience"=>{"Neuroscience"=>2}, "Chemistry"=>{"Chemistry"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Unspecified"=>{"Unspecified"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>4}}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2630014"], "description"=>"<p>The genes/proteins implicated in AD pathology are highlighted in green and red. The genes/proteins of potential interest are highlighted in blue and orange. (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144052#pone.0144052.t001\" target=\"_blank\">Table 1</a> for gene highlighting details).</p>", "links"=>[], "tags"=>["drug targets", "dcn", "network topology descriptors", "KEGG pathways", "gene expression", "GSE 4757", "IL 8 extracellular ligands", "alzheimer", "approach", "disease initiation process", "Bayes method", "interaction", "IPA enrichment analysis", "Novel Routes", "limma Bioconductor package", "oxidative stress", "brain gene microarrays", "expression datasets", "brain sections", "network Topology Analysis", "Pathway Studio analysis", "Pathway Studio software package", "study offer information"], "article_id"=>1639379, "categories"=>["Biological Sciences"], "users"=>["Sreedevi Chandrasekaran", "Danail Bonchev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144052.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alzheimer_s_disease_compact_shortest_path_network_/1639379", "title"=>"Alzheimer’s disease <i>compact</i> shortest path network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:10"}
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  • {"files"=>["https://ndownloader.figshare.com/files/2630022"], "description"=>"<p>The 37 genes/proteins found in common in all 12 enriched KEGG pathways are regulated by 22 microRNAs. Genes/proteins implicated in AD pathology are highlighted in green/red and the genes/proteins of potential interest are highlighted in blue/orange (See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144052#pone.0144052.t001\" target=\"_blank\">Table 1</a>) for details. Genes/proteins causing neuronal loss are highlighted in purple and those that help in neuronal survival are in yellow.</p>", "links"=>[], "tags"=>["drug targets", "dcn", "network topology descriptors", "KEGG pathways", "gene expression", "GSE 4757", "IL 8 extracellular ligands", "alzheimer", "approach", "disease initiation process", "Bayes method", "interaction", "IPA enrichment analysis", "Novel Routes", "limma Bioconductor package", "oxidative stress", "brain gene microarrays", "expression datasets", "brain sections", "network Topology Analysis", "Pathway Studio analysis", "Pathway Studio software package", "study offer information"], "article_id"=>1639387, "categories"=>["Biological Sciences"], "users"=>["Sreedevi Chandrasekaran", "Danail Bonchev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144052.g005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MicroRNA_incorporated_integrated_Alzheimer_s_disease_mechanism_/1639387", "title"=>"MicroRNA incorporated <i>integrated</i> Alzheimer’s disease mechanism.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:58:13"}
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  • {"files"=>["https://ndownloader.figshare.com/files/2630008"], "description"=>"<p>The 15 genes/proteins implicated in AD pathology are highlighted in green and the two genes/proteins of potential interest for that disease are highlighted in blue.</p>", "links"=>[], "tags"=>["drug targets", "dcn", "network topology descriptors", "KEGG pathways", "gene expression", "GSE 4757", "IL 8 extracellular ligands", "alzheimer", "approach", "disease initiation process", "Bayes method", "interaction", "IPA enrichment analysis", "Novel Routes", "limma Bioconductor package", "oxidative stress", "brain gene microarrays", "expression datasets", "brain sections", "network Topology Analysis", "Pathway Studio analysis", "Pathway Studio software package", "study offer information"], "article_id"=>1639373, "categories"=>["Biological Sciences"], "users"=>["Sreedevi Chandrasekaran", "Danail Bonchev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144052.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alzheimer_s_disease_direct_interaction_network_/1639373", "title"=>"Alzheimer’s disease <i>direct interaction</i> network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/2630028"], "description"=>"<p>The genes/proteins and miRNAs implicated in AD pathology are highlighted in green and the genes/proteins of potential interest are highlighted in blue. Genes/proteins that code for transcription factors (TFs) are highlighted in yellow.</p>", "links"=>[], "tags"=>["drug targets", "dcn", "network topology descriptors", "KEGG pathways", "gene expression", "GSE 4757", "IL 8 extracellular ligands", "alzheimer", "approach", "disease initiation process", "Bayes method", "interaction", "IPA enrichment analysis", "Novel Routes", "limma Bioconductor package", "oxidative stress", "brain gene microarrays", "expression datasets", "brain sections", "network Topology Analysis", "Pathway Studio analysis", "Pathway Studio software package", "study offer information"], "article_id"=>1639390, "categories"=>["Biological Sciences"], "users"=>["Sreedevi Chandrasekaran", "Danail Bonchev"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144052.g006", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alzheimer_s_disease_miRNA_regulatory_network_/1639390", "title"=>"Alzheimer’s disease <i>miRNA</i> regulatory network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-28 12:38:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/2630029", "https://ndownloader.figshare.com/files/2630030"], "description"=>"<div><p>Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer’s disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer’s disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies.</p></div>", "links"=>[], "tags"=>["drug targets", "dcn", "network topology descriptors", "KEGG pathways", "gene expression", "GSE 4757", "IL 8 extracellular ligands", "alzheimer", "approach", "disease initiation process", "Bayes method", "interaction", "IPA enrichment analysis", "Novel Routes", "limma Bioconductor package", "oxidative stress", "brain gene microarrays", "expression datasets", "brain sections", "network Topology Analysis", "Pathway Studio analysis", "Pathway Studio software package", "study offer information"], "article_id"=>1639391, "categories"=>["Biological Sciences"], "users"=>["Sreedevi Chandrasekaran", "Danail Bonchev"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0144052.s001", "https://dx.doi.org/10.1371/journal.pone.0144052.s002"], "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_Topology_Analysis_of_Post_Mortem_Brain_Microarrays_Identifies_More_Alzheimer_8217_s_Related_Genes_and_MicroRNAs_and_Points_to_Novel_Routes_for_Fighting_with_the_Disease_/1639391", "title"=>"Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2016-01-28 12:58:16"}

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Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
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