Structural, Genetic, and Functional Signatures of Disordered Neuro-Immunological Development in Autism Spectrum Disorder
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{"title"=>"Structural, Genetic, and Functional Signatures of Disordered Neuro-Immunological Development in Autism Spectrum Disorder", "type"=>"journal", "authors"=>[{"first_name"=>"Vishal", "last_name"=>"Saxena", "scopus_author_id"=>"7103293119"}, {"first_name"=>"Shweta", "last_name"=>"Ramdas", "scopus_author_id"=>"6602138268"}, {"first_name"=>"Courtney Rothrock", "last_name"=>"Ochoa", "scopus_author_id"=>"55514931300"}, {"first_name"=>"David", "last_name"=>"Wallace", "scopus_author_id"=>"57199423697"}, {"first_name"=>"Pradeep", "last_name"=>"Bhide", "scopus_author_id"=>"7003969279"}, {"first_name"=>"Isaac", "last_name"=>"Kohane", "scopus_author_id"=>"35264289500"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84870761625", "pui"=>"366222113", "doi"=>"10.1371/journal.pone.0048835", "isbn"=>"1932-6203 (Electronic) 1932-6203 (Linking)", "sgr"=>"84870761625", "pmid"=>"23239965"}, "id"=>"76e74a1e-5e3f-3cd1-9001-24ad54542c36", "abstract"=>"BACKGROUND: Numerous linkage studies have been performed in pedigrees of Autism Spectrum Disorders, and these studies point to diverse loci and etiologies of autism in different pedigrees. The underlying pattern may be identified by an integrative approach, especially since ASD is a complex disorder manifested through many loci.\\n\\nMETHOD: Autism spectrum disorder (ASD) was studied through two different and independent genome-scale measurement modalities. We analyzed the results of copy number variation in autism and triangulated these with linkage studies.\\n\\nRESULTS: Consistently across both genome-scale measurements, the same two molecular themes emerged: immune/chemokine pathways and developmental pathways.\\n\\nCONCLUSION: Linkage studies in aggregate do indeed share a thematic consistency, one which structural analyses recapitulate with high significance. These results also show for the first time that genomic profiling of pathways using a recombination distance metric can capture pathways that are consistent with those obtained from copy number variations (CNV).", "link"=>"http://www.mendeley.com/research/structural-genetic-functional-signatures-disordered-neuroimmunological-development-autism-spectrum-d", "reader_count"=>33, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Researcher"=>6, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3, "Professor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Researcher"=>6, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>9, "Medicine and Dentistry"=>10, "Arts and Humanities"=>1, "Neuroscience"=>2, "Psychology"=>4, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>10}, "Neuroscience"=>{"Neuroscience"=>2}, "Social Sciences"=>{"Social Sciences"=>1}, "Psychology"=>{"Psychology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"United States"=>2, "Brazil"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/530960"], "description"=>"<p>All genes within CNVs were used to find the top ranked pathways in the CNVs (A) and these new pathways along with other a priori created pathways were tested using LoGS (B).</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "developmental biology", "neurological disorders", "Biochemistry"], "article_id"=>201452, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overall_analysis_scheme_/201452", "title"=>"Overall analysis scheme.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:24:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/531310"], "description"=>"<p>A. Far away genes can be influenced by genes closer to a marker. Thus, we can't just use the closest genes to the marker. B. Since our real locus could be anywhere within the 30 cM window, any of the genes within the window could be the closest gene, and since our best location for the marker is the center of the window, we simply rank the genes from this point to take into account the fact that any of the genes within the window could be the gene closest to some ‘real’ marker. C. The low density of markers means that many genes are ‘covered’ by each marker. The gene of interest may be far from the marker and may not necessarily be the closest gene from the marker.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "developmental biology", "neurological disorders", "Biochemistry"], "article_id"=>201800, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Why_the_closest_gene_is_not_necessarily_the_best_gene_/201800", "title"=>"Why the closest gene is not necessarily the best gene.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:30:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/531055"], "description"=>"<p>We pick markers on various chromosome implicated in autism. We then find genes within 50 cM of each marker. Next we ‘align’ each marker to have the same or common origin and then rank genes from this common origin.</p>", "links"=>[], "tags"=>["overview"], "article_id"=>201557, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_General_overview_of_LoGS_/201557", "title"=>"General overview of LoGS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:25:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/531480"], "description"=>"<p>Gene sets that begin with ‘c’ are further tested in EASE for their top categories. BP = biological process; CC = cellular component; MF = molecular function. V = enrichment score for a pathway. P = P value via permutation test.</p>", "links"=>[], "tags"=>["autism", "shown", "20"], "article_id"=>201972, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.t002", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_LoGS_on_autism_loci_Shown_are_the_top_20_pathways_/201972", "title"=>"LoGS on autism loci. Shown are the top 20 pathways.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-04 00:32:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/285573", "https://ndownloader.figshare.com/files/285636", "https://ndownloader.figshare.com/files/285684", "https://ndownloader.figshare.com/files/285726", "https://ndownloader.figshare.com/files/285776", "https://ndownloader.figshare.com/files/285820", "https://ndownloader.figshare.com/files/285891", "https://ndownloader.figshare.com/files/285938"], "description"=>"<div><h3>Background</h3><p>Numerous linkage studies have been performed in pedigrees of Autism Spectrum Disorders, and these studies point to diverse loci and etiologies of autism in different pedigrees. The underlying pattern may be identified by an integrative approach, especially since ASD is a complex disorder manifested through many loci.</p> <h3>Method</h3><p>Autism spectrum disorder (ASD) was studied through two different and independent genome-scale measurement modalities. We analyzed the results of copy number variation in autism and triangulated these with linkage studies.</p> <h3>Results</h3><p>Consistently across both genome-scale measurements, the same two molecular themes emerged: immune/chemokine pathways and developmental pathways.</p> <h3>Conclusion</h3><p>Linkage studies in aggregate do indeed share a thematic consistency, one which structural analyses recapitulate with high significance. These results also show for the first time that genomic profiling of pathways using a recombination distance metric can capture pathways that are consistent with those obtained from copy number variations (CNV).</p> </div>", "links"=>[], "tags"=>["signatures", "disordered", "neuro-immunological", "autism", "disorder"], "article_id"=>116290, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048835.s001", "https://dx.doi.org/10.1371/journal.pone.0048835.s002", "https://dx.doi.org/10.1371/journal.pone.0048835.s003", "https://dx.doi.org/10.1371/journal.pone.0048835.s004", "https://dx.doi.org/10.1371/journal.pone.0048835.s005", "https://dx.doi.org/10.1371/journal.pone.0048835.s006", "https://dx.doi.org/10.1371/journal.pone.0048835.s007", "https://dx.doi.org/10.1371/journal.pone.0048835.s008"], "stats"=>{"downloads"=>3, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Structural_Genetic_and_Functional_Signatures_of_Disordered_Neuro_Immunological_Development_in_Autism_Spectrum_Disorder__/116290", "title"=>"Structural, Genetic, and Functional Signatures of Disordered Neuro-Immunological Development in Autism Spectrum Disorder", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-12-04 01:44:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/530845"], "description"=>"<p>Each affected individual from different pedigrees captures a different part of the same pathway. The same will be true of different CNVs in different autistic individuals.</p>", "links"=>[], "tags"=>["conceptual"], "article_id"=>201341, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_conceptual_picture_of_our_overall_analysis_/201341", "title"=>"A conceptual picture of our overall analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:22:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/531212"], "description"=>"<p>Here we show how left ranked genes and right ranked genes are placed together in the same ranking.</p>", "links"=>[], "tags"=>["treated", "overview"], "article_id"=>201706, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g004", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genes_to_the_left_and_right_of_the_marker_are_treated_equally_LoGS_overview_continued_/201706", "title"=>"Genes to the left and right of the marker are treated equally (LoGS overview continued).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:28:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/531445"], "description"=>"<p>Copy number gain or loss in the iCNV-5 genes.</p>", "links"=>[], "tags"=>["icnv-5"], "article_id"=>201941, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Copy_number_gain_or_loss_in_the_iCNV_5_genes_/201941", "title"=>"Copy number gain or loss in the iCNV-5 genes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-04 00:32:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/531385"], "description"=>"<p>In this figure, we use two loci to illustrate how LoGS works. Say Chromosome 21 has two loci that were implicated in ASD while chromosome 9 has just one locus. We then locate all the genes on chromosomes 1 and 9 and then rank them by their genetic distance from the closest locus on that chromosome (for example the gene between loci 1p21.1 and 1q23.3 is closer to 1q23.3 and thus its distance from 1q23.3 is used). This ranking for all chromosomes (in this example chromosomes 1 and 9) is then collected and we run gene set enrichment analysis as explained in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048835#s4\" target=\"_blank\">methods</a> section. The black boxes are markers and the dashed lines represent genes.</p>", "links"=>[], "tags"=>["rationale"], "article_id"=>201889, "categories"=>["Biological Sciences", "Biochemistry", "Genetics", "Developmental Biology", "Neuroscience"], "users"=>["Vishal Saxena", "Shweta Ramdas", "Courtney Rothrock Ochoa", "David Wallace", "Pradeep Bhide", "Isaac Kohane"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048835.g006", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_rationale_behind_LoGS_/201889", "title"=>"The rationale behind LoGS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-04 00:31:29"}

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Relative Metric

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