Molecular Insights into the Pathogenesis of Alzheimer's Disease and Its Relationship to Normal Aging
Publication Date
December 28, 2011
Journal
PLOS ONE
Authors
Alexei A. Podtelezhnikov, Keith Q. Tanis, Michael Nebozhyn, William J. Ray, et al
Volume
6
Issue
12
Pages
e29610
DOI
https://dx.plos.org/10.1371/journal.pone.0029610
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0029610
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22216330
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247273
Europe PMC
http://europepmc.org/abstract/MED/22216330
Web of Science
000300676300073
Scopus
84555205301
Mendeley
http://www.mendeley.com/research/molecular-insights-pathogenesis-alzheimers-disease-relationship-normal-aging
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/698773"], "description"=>"<p>The reported values were obtained using PFC1 samples unless otherwise noted.</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "cell biology", "physiology", "neurological disorders", "Biochemistry"], "article_id"=>369157, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.t001", "stats"=>{"downloads"=>2, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Biomarker_Characteristics_/369157", "title"=>"Biomarker Characteristics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-12-28 02:32:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/698614"], "description"=>"<p>HD samples are colored in green. The reference biomarker scores corresponding to non demented individuals are represented by dashed lines.</p>", "links"=>[], "tags"=>["ndstress", "alz", "samples", "pfc2", "colored"], "article_id"=>369002, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g006", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_NdStress_and_Alz_in_AD_and_HD_AD_samples_of_PFC2_are_colored_in_red_/369002", "title"=>"Comparison of NdStress and Alz in AD and HD. AD samples of PFC2 are colored in red.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:30:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/698183"], "description"=>"<p>The box plots (A) demonstrate the distribution of BioAge in different 5-year long age segments and list the ANOVA p-values for the BioAge separation between normal and AD subjects in each chronological age segment. (B) Prediction of chronological age in the independent normal cohort using BioAge. The postmortem prefrontal cortex samples from individual of different age were profiled in an earlier study (GSE1572) <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029610#pone.0029610-Lu1\" target=\"_blank\">[3]</a>. BioAge was calculated based on average expression of several hundred genes from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029610#pone.0029610.s008\" target=\"_blank\">Table S2</a> (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029610#s2\" target=\"_blank\">Methods</a>).</p>", "links"=>[], "tags"=>["chronological"], "article_id"=>368587, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Aging_score_versus_chronological_age_in_PFC1_/368587", "title"=>"Aging score versus chronological age in PFC1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:23:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/698289"], "description"=>"<p>(A) Clustered gene-gene correlation matrix demonstrating strong mutual correlations between genes that were differentially expressed between AD and non-demented samples from PFC1. Three outlined clusters correspond to NdStress, Alz, and Inflame. The coregulation of these genes is also shown in the panel (B). Each colored line represents expression levels of individual genes in 55 PFC1 samples from non-demented and AD subjects sorted in the order of increasing BioAge. Only representative samples that scored in the top or bottom 3% for any of the biomarkers were selected for this figure to improve visualization.</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "cell biology", "physiology", "neurological disorders", "Biochemistry"], "article_id"=>368685, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Disease_specific_metagenes_/368685", "title"=>"Disease-specific metagenes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:24:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/698808"], "description"=>"<p>**Bonferroni corrected Hypergeometric p-value<0.05.</p><p>*Bonferroni corrected Hypergeometric p-value<0.1.</p>#<p>Bonferroni corrected Hypergeometric p-value<0.5.</p><p>Up- and down regulated arms of metagenes are denoted as (+) and (−). Complete analysis is shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029610#pone.0029610.s009\" target=\"_blank\">Table S3</a>.</p>", "links"=>[], "tags"=>["pathways", "enriched"], "article_id"=>369200, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.t002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Selected_pathways_that_are_enriched_in_metagenes_/369200", "title"=>"Selected pathways that are enriched in metagenes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-12-28 02:33:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/698402"], "description"=>"<p>Each biomarker is represented by its score in each sample based on the average gene expression of contributing genes (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029610#s2\" target=\"_blank\">Methods</a>). Non-demented PFC1 samples are shown by black dots. AD samples are shown by red dots. All pairwise relationships between the biomarkers and with chronological age are shown.</p>", "links"=>[], "tags"=>["matrix", "relationships", "aging", "disease-specific", "biomarkers", "chronological"], "article_id"=>368789, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Plot_matrix_of_mutual_relationships_between_key_aging_and_disease_specific_biomarkers_as_well_as_chronological_age_/368789", "title"=>"Plot matrix of mutual relationships between key aging and disease-specific biomarkers as well as chronological age.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:26:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/698689"], "description"=>"<p>The trajectories of BioAge changes as a function of time reflect the relatively constant rate of aging in non-demented subjects (black), and acceleration of the rate of aging in AD (red). The dots represent the postmortem state of the brain captured by gene expression profiling. The state transition model defines several broad categories for normal brains N0–N3 and for diseased states A1 and A2. The sequence of transitions and associated gene expression biomarkers are shown by arrows.</p>", "links"=>[], "tags"=>["progression"], "article_id"=>369079, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g007", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Disease_progression_model_/369079", "title"=>"Disease progression model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:31:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/698470"], "description"=>"<p>Each plot shows relationships between the biomarker values in PFC1 and VC1. Samples from non-demented and AD subjects are shown in black and red respectively.</p>", "links"=>[], "tags"=>["biomarker", "scores", "pfc1", "vc1"], "article_id"=>368858, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_between_biomarker_scores_in_PFC1_and_VC1_of_the_same_individuals_/368858", "title"=>"Correlation between biomarker scores in PFC1 and VC1 of the same individuals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:27:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/698082"], "description"=>"<p>The heat map shows hierarchical clustering of the 4000 most variable genes. The samples (rows) are sorted according to the values of the first principal component of the complete dataset and labeled according to diagnosis (normal samples in black, AD samples in red on the right).</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "cell biology", "physiology", "neurological disorders", "Biochemistry"], "article_id"=>368474, "categories"=>["Microbiology", "Neuroscience", "Biochemistry", "Physiology", "Biological Sciences", "Cell Biology"], "users"=>["Alexei A. Podtelezhnikov", "Keith Q. Tanis", "Michael Nebozhyn", "William J. Ray", "David J. Stone", "Andrey P. Loboda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0029610.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Gene_expression_in_PFC1_/368474", "title"=>"Gene expression in PFC1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-28 02:21:14"}

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Relative Metric

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