Conserved brain myelination networks are altered in Alzheimer's and other neurodegenerative diseases

Allen, Mariet; Wang, Xue; Burgess, Jeremy D.; Watzlawik, Jens O.; Serie, Daniel J.; Younkin, Curtis S.; Nguyen, Thuy; Malphrus, Kimberly G.; Lincoln, Sarah; Carrasquillo, Minerva M.; Ho, Charlotte C.G.; Chakrabarty, Paramita; Strickland, Samantha L.; Murray, Melissa E.; Swarup, Vivek; Geschwind, Daniel H.; Seyfried, Nicholas T.; Dammer, Eric B.; Lah, James J.; Levey, Aĺlan I.; Golde, Todd E.; Funk, Cory C.; Li, Hongdong; Price, Nathan D.; Petersen, Ronald C.; Graff‐Radford, Neill R.; Younkin, Steven G.; Dickson, Dennis W.; Crook, J.Robert; Asmann, Yan W.; Ertekin-Taner, Nilüfer

doi:10.1016/j.jalz.2017.09.012

Cited by 123 publications

(210 citation statements)

References 46 publications

(85 reference statements)

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“…This finding is consistent with our prior proteomic studies in DLPFC 23,24,61 . A previous study investigating the relationship of a similar myelin/oligodendrocyte mRNA brain co-expression module to AD found that expression of this module decreased in both AD and PSP in temporal cortex, with stronger changes in PSP 76 . Another mRNA network study observed downregulation of oligodendrocyte module hubs in AD 77 .…”

Section: Discussionmentioning

confidence: 93%

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Johnson

Dammer

Duong

et al. 2019

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Our understanding of the biological changes in the brain associated with Alzheimer's disease (AD) pathology and cognitive impairment remains incomplete. To increase our understanding of these changes, we analyzed dorsolateral prefrontal cortex of control, asymptomatic AD, and AD brains from four different centers by label-free quantitative mass spectrometry and weighted protein co-expression analysis to obtain a consensus protein co-expression network of AD brain.This network consisted of 13 protein co-expression modules. Six of these modules correlated with amyloid-β plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community-based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module, which was enriched in AD genetic risk factors and correlated with APOE genetic risk. This module was also highly enriched in microglia and astrocyte protein markers associated with an antiinflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from this module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network. In this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease. IntroductionAlzheimer's disease (AD) is a leading cause of death worldwide, with increasing prevalence as global life expectancy increases 1 . Although AD is currently defined on the basis of amyloid-β plaque and tau neurofibrillary tangle deposition within the neocortex 2 , the biochemical and cellular changes in the brain that characterize the disease beyond amyloid-β and tau deposition remain incompletely understood. The genetic architecture of late-onset AD has been extensively studied, and the results of these studies implicate multiple biological pathways that contribute to development of the disease, including immune function, endocytic vesicle trafficking, and lipid homeostasis, among others 3-5 . In addition to genetic studies, transcriptomic studies on postmortem AD brain tissue have identified changes in mRNA co-expression that correlate with disease traits and cognitive decline 6,7 . However, given that mRNA levels correlate only modestly to protein le...

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Section: Discussionmentioning

confidence: 93%

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Johnson

Dammer

Duong

et al. 2019

Preprint

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“…With the recent technology advancement in single-cell gene expression analysis, including single-nucleus RNA-seq (snRNA-seq), it is now possible to study diseased tissues at the single-cell level 72 . We compared our bulk-tissue derived gene profiles with a recent snRNA-seq analysis of dorsolateral prefrontal cortex (DLPFC) region of 27 LOAD patients and controls 28 and found significant preservations of our gene signatures in the snRNA-seq DEGs with the same direction of change ( Fig. S4), despite different brain regions analyzed.…”

Section: Discussionmentioning

confidence: 95%

“…This is consistent with our previous pan-cortical transcriptomic analysis of LOAD brains (which were independent of the dataset described herein) in which BM36-PHG was the most impacted region in LOAD at the gene expression level 8 . Our DEG signatures were preserved (adjusted Fisher's exact test (FET) P value up to 1.0E-100) in ten publicly available AD transcriptomic studies 7,12,[20][21][22][23][24][25][26][27] (Fig. S3).…”

Section: Identifying Gene Expression Signatures and Pathways Of Loadmentioning

confidence: 99%

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

Wang

Sekiya

et al. 2019

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To study the molecular mechanisms driving the pathogenesis and identify novel therapeutic targets of late onset Alzheimer's Disease (LOAD), we performed an integrative network analysis of whole-genome DNA and RNA sequencing profiling of four cortical areas, including the parahippocampal gyrus, across 364 donors spanning the full spectrum of LOAD-related cognitive and neuropathological disease severities. Our analyses revealed thousands of molecular changes and uncovered for the first-time multiple neuron specific gene subnetworks most dysregulated in LOAD. ATP6V1A, a critical subunit of vacuolar-type H + -ATPase (v-ATPase), was predicted to be a key regulator of one neuronal subnetwork and its role in disease-related processes was evaluated through CRISPR-based manipulation of human induced pluripotent stem cell derived neurons and RNAi-based knockdown in transgenic Drosophila models. This study advances our understanding of LOAD pathogenesis by providing the global landscape and detailed circuits of complex molecular interactions and regulations in several key brain regions affected by LOAD and the resulting network models provide a blueprint for developing next generation therapeutics against LOAD.

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“…We generated eQTL from the publicly available AMP-AD (ROSMAP 26,27,34 (Data Citation 1), Mayo RNAseq 28,36,37 (Data Citation 2)) and CMC (MSSM-Penn-Pitt 24 (Data Citation 3), HBCC (Data Citation 4)) cohorts with available genotypes and RNA-seq data, using a common analysis pipeline ( Supplementary Table 1) (https://www.synapse.org/#!Synapse:syn17015233). Analyses proceeded separately by cohort.…”

Section: Resultsmentioning

confidence: 99%

Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions

Sieberts

Perumal

Carrasquillo

et al. 2019

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words maximum)The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer's Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes), and provide the results as a community resource. We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. In addition, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a common resource for use across the community in research programs. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia SKS, SM, MP, PLDJ, NET, LMM, the AMP-AD Consortium, and the CMC Consortium contributed to the design and generation of the study data.

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Conserved brain myelination networks are altered in Alzheimer's and other neurodegenerative diseases

Abstract: Downregulation of myelination networks may underlie both PSP and AD pathophysiology, but may be more pronounced in PSP. These data also highlight conservation of transcriptional networks across brain regions and the influence of cell type changes on these networks.

Cited by 123 publications

References 46 publications

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions

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