A Multi-network Approach Identifies Protein-Specific Co-expression in Asymptomatic and Symptomatic Alzheimer's Disease.

Here, we report proteomic analyses of 129 human cortical tissues to define changes associated with the asymptomatic and symptomatic stages of Alzheimer's disease (AD). Network analysis revealed 16 modules of co-expressed proteins, 10 of which correlated with AD phenotypes. A subset of modules overlapped with RNA co-expression networks, including those associated with neurons and astroglial cell types, showing altered expression in AD, even in the asymptomatic stages. Overlap of RNA and protein networks was otherwise modest, with many modules specific to the proteome, including those linked to microtubule function and inflammation. Proteomic modules were validated in an independent cohort, demonstrating some module expression changes unique to AD and several observed in other neurodegenerative diseases. AD genetic risk loci were concentrated in glial-related modules in the proteome and transcriptome, consistent with their causal role in AD. This multi-network analysis reveals protein- and disease-specific pathways involved in the etiology, initiation, and progression of AD.

[1]  Ira Driscoll,et al.  Impact of Alzheimer's pathology on cognitive trajectories in nondemented elderly , 2006, Annals of neurology.

[2]  S. Gilman,et al.  Diagnostic criteria for Parkinson disease. , 1999, Archives of neurology.

[3]  C Hulette,et al.  The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) , 1995, Neurology.

[4]  Jie Ma,et al.  Improving X!Tandem on Peptide Identification from Mass Spectrometry by Self-Boosted Percolator , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[5]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[6]  K. Muramoto,et al.  Localization of Microtubule-Associated Protein (MAP) 1B in the Postsynaptic Densities of the Rat Cerebral Cortex , 2003, Cellular and Molecular Neurobiology.

[7]  Tomaž Curk,et al.  Analysis of alternative splicing associated with aging and neurodegeneration in the human brain. , 2011, Genome research.

[8]  Chadwick M. Hales,et al.  U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease , 2013, Proceedings of the National Academy of Sciences.

[9]  J. Ryu,et al.  A leaky blood–brain barrier, fibrinogen infiltration and microglial reactivity in inflamed Alzheimer’s disease brain , 2008, Journal of cellular and molecular medicine.

[10]  M. Mann,et al.  Quantitative proteomics reveals subset-specific viral recognition in dendritic cells. , 2010, Immunity.

[11]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[12]  Xia Yang,et al.  A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease , 2013, Arteriosclerosis, thrombosis, and vascular biology.

[13]  Noah W. Gray,et al.  Dynamin 3 Is a Component of the Postsynapse, Where it Interacts with mGluR5 and Homer , 2003, Current Biology.

[14]  Neil Buckholtz,et al.  Accelerating Medicines Partnership: Alzheimer’s Disease (AMP-AD) Knowledge Portal Aids Alzheimer’s Drug Discovery through Open Data Sharing , 2016, Expert opinion on therapeutic targets.

[15]  S. Horvath,et al.  Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology , 2011, Nature.

[16]  Hollis G. Potter,et al.  Author Manuscript , 2013 .

[17]  Rebecca F. Halperin,et al.  A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. , 2007, The Journal of clinical psychiatry.

[18]  G. Alexander,et al.  Longitudinal PET Evaluation of Cerebral Metabolic Decline in Dementia: A Potential Outcome Measure in Alzheimer's Disease Treatment Studies. , 2002, The American journal of psychiatry.

[19]  M. Weiner,et al.  Increased metabolic vulnerability in early-onset Alzheimer's disease is not related to amyloid burden. , 2010, Brain : a journal of neurology.

[20]  Satoru Miyano,et al.  Open source clustering software , 2004 .

[21]  Rui Luo,et al.  Is My Network Module Preserved and Reproducible? , 2011, PLoS Comput. Biol..

[22]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..

[23]  Jeffrey R. Whiteaker,et al.  Proteogenomic characterization of human colon and rectal cancer , 2014, Nature.

[24]  J. Lowe,et al.  Amyotrophic lateral sclerosis: current issues in classification, pathogenesis and molecular pathology. , 1998, Neuropathology and applied neurobiology.

[25]  S. Horvath,et al.  Functional organization of the transcriptome in human brain , 2008, Nature Neuroscience.

[26]  Alok J. Saldanha,et al.  Java Treeview - extensible visualization of microarray data , 2004, Bioinform..

[27]  S. Horvath,et al.  Genes and pathways underlying regional and cell type changes in Alzheimer's disease , 2013, Genome Medicine.

[28]  Richard D. Smith,et al.  Normalization and missing value imputation for label-free LC-MS analysis , 2012, BMC Bioinformatics.

[29]  Léon Personnaz,et al.  Enrichment or depletion of a GO category within a class of genes: which test? , 2007, Bioinform..

[30]  M. Mann,et al.  Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.

[31]  Tao Xie,et al.  Inferring causal genomic alterations in breast cancer using gene expression data , 2011, BMC Systems Biology.

[32]  Daniel H. Geschwind,et al.  Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders , 2015, Nature Reviews Genetics.

[33]  D. Geschwind,et al.  A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging , 2008, The Journal of Neuroscience.

[34]  H. Braak,et al.  Neuropathological stageing of Alzheimer-related changes , 2004, Acta Neuropathologica.

[35]  Matthias Mann,et al.  Cell type– and brain region–resolved mouse brain proteome , 2015, Nature Neuroscience.

[36]  Edward L. Huttlin,et al.  Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses. , 2012, Analytical chemistry.

[37]  E. Marcotte,et al.  Global signatures of protein and mRNA expression levelsw , 2009 .

[38]  M. Oldham.  Transcriptomics: From Differential Expression to Coexpression , 2013 .

[39]  D. Salmon,et al.  Physical basis of cognitive alterations in alzheimer's disease: Synapse loss is the major correlate of cognitive impairment , 1991, Annals of neurology.

[40]  L. Tran,et al.  Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease , 2013, Cell.

[41]  A. Levey,et al.  Aggregation Properties of the Small Nuclear Ribonucleoprotein U1-70K in Alzheimer Disease* , 2014, The Journal of Biological Chemistry.

[42]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[43]  Daniel S. Himmelstein,et al.  Understanding multicellular function and disease with human tissue-specific networks , 2015, Nature Genetics.

[44]  T. Maniatis,et al.  An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex , 2014, The Journal of Neuroscience.

[45]  J. Hardy,et al.  The amyloid hypothesis of Alzheimer's disease at 25 years , 2016, EMBO molecular medicine.

[46]  E. Wang,et al.  Circulatory miR-34a as an RNA-based, noninvasive biomarker for brain aging , 2011, Aging.

[47]  Seth Love,et al.  Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease , 2010, PloS one.

[48]  Leslie Wilson,et al.  Inability of tau to properly regulate neuronal microtubule dynamics: a loss-of-function mechanism by which tau might mediate neuronal cell death. , 2005, Biochimica et biophysica acta.

[49]  Michael A. Beer,et al.  Transactivation of miR-34a by p53 broadly influences gene expression and promotes apoptosis. , 2007, Molecular cell.

[50]  Sara G. Murray,et al.  Blood coagulation protein fibrinogen promotes autoimmunity and demyelination via chemokine release and antigen presentation , 2015, Nature Communications.

[51]  C. Sander,et al.  Automated Network Analysis Identifies Core Pathways in Glioblastoma , 2010, PloS one.

[52]  Patrick F Sullivan,et al.  The Psychiatric GWAS Consortium: Big Science Comes to Psychiatry , 2010, Neuron.

[53]  Brendan MacLean,et al.  Bioinformatics Applications Note Gene Expression Skyline: an Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments , 2022 .

[54]  B. Zlokovic.  The Blood-Brain Barrier in Health and Chronic Neurodegenerative Disorders , 2008, Neuron.

[55]  Marco Y. Hein,et al.  Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * , 2014, Molecular & Cellular Proteomics.

[56]  Xia Yang,et al.  Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases , 2014 .

[57]  M. Mosesson.  Fibrinogen and fibrin structure and functions , 2005, Journal of thrombosis and haemostasis : JTH.

[58]  Chris T. A. Evelo,et al.  Bioinformatics Applications Note Databases and Ontologies Go-elite: a Flexible Solution for Pathway and Ontology Over-representation , 2022 .

[59]  Nick C Fox,et al.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease , 2013, Nature Genetics.

[60]  L. Ferrucci,et al.  Neuropathologic studies of the Baltimore Longitudinal Study of Aging (BLSA). , 2009, Journal of Alzheimer's disease : JAD.

[61]  Ru-jing Ren,et al.  The endosomal-lysosomal system: from acidification and cargo sorting to neurodegeneration , 2015, Translational Neurodegeneration.