Microarray analysis of the astrocyte transcriptome in the aging brain: relationship to Alzheimer's pathology and APOE genotype

Simpson, Julie E.; Ince, Paul G.; Shaw, Pamela J.; Heath, Paul R.; Raman, Rohini; Garwood, Claire J.; Gelsthorpe, Catherine; Baxter, Lynne; Forster, G.; Matthews, Fiona E.; Brayne, Carol; Wharton, Stephen B.

doi:10.1016/j.neurobiolaging.2011.04.013

Cited by 174 publications

(146 citation statements)

References 91 publications

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“…Microarray analyses of isolated astrocytes have identified particular transcription profiles in AD and related animal models [141,142].…”

Section: Astrocytopathymentioning

confidence: 99%

Astrogliopathy in Tauopathies

Ferrer

2018

Neuroglia

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Astrocytes are involved in many diseases of the central nervous system, not only as reactive cells to neuronal damage but also as primary actors in the pathological process. Astrogliopathy is a term used to designate the involvement of astrocytes as key elements in the pathogenesis and pathology of diseases and injuries of the central nervous system. Astrocytopathy is utilized to name non-reactive astrogliosis covering hypertrophy, atrophy and astroglial degeneration with loss of function in astrocytes and pathological remodeling, as well as senescent changes. Astrogliopathy and astrocytopathy are hallmarks of tauopathies-neurodegenerative diseases with abnormal hyper-phosphorylated tau aggregates in neurons and glial cells. The involvement of astrocytes covers different disease-specific types such as tufted astrocytes, astrocytic plaques, thorn-shaped astrocytes, granular/fuzzy astrocytes, ramified astrocytes and astrocytes with globular inclusions, as well as others which are unnamed but not uncommon in familial frontotemporal degeneration linked to mutations in the tau gene. Knowledge of molecular differences among tau-containing astrocytes is only beginning, and their distinct functional implications remain rather poorly understood. However, tau-containing astrocytes in certain conditions have deleterious effects on neuronal function and nervous system integrity. Moreover, recent studies have shown that tau-containing astrocytes obtained from human brain tauopathies have a capacity for abnormal tau seeding and spreading in wild type mice. Inclusive conceptions include a complex scenario involving neurons, glial cells and local environmental factors that potentiate each other and promote disease progression in tauopathies.

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“…Microarray analyses of isolated astrocytes have identified particular transcription profiles in AD and related animal models [141,142].…”

Section: Astrocytopathymentioning

confidence: 99%

Astrogliopathy in Tauopathies

Ferrer

2018

Neuroglia

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“…Simpson et al (25) expression profiled GFAP (glial fibrillary acidic protein) positive astrocytes microdissected from the temporal cortex of elderly subjects and identified differentially expressed genes with respect to Braak stage and APOE (apolipoprotein) ε4 carrier status. In a separate study, cortical astrocytes were collected from young and old mice and expression profiled to reveal altered expression of key genes involved in neuronal signaling (30).…”

Section: Introductionmentioning

confidence: 99%

Alzheimer's disease is associated with altered expression of genes involved in immune response and mitochondrial processes in astrocytes

Sekar

McDonald

Cuyugan

et al. 2015

Neurobiology of Aging

177

129

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Alzheimer’s disease (AD) is characterized by deficits in cerebral metabolic rates of glucose in the posterior cingulate (PC) and precuneus in AD subjects, and in APOEε4 carriers, decades prior to the onset of measureable cognitive deficits. However, the cellular and molecular basis of this phenotype remains to be clarified. Given the roles of astrocytes in energy storage and brain immunity, we sought to characterize the transcriptome of AD PC astrocytes. Cells were laser capture microdissected from AD (n=10) and healthy elderly control (n=10) subjects for RNA sequencing. We generated >5.22 billion reads and compared sequencing data between controls and AD patients. We identified differentially expressed mitochondria-related genes including TRMT61B, FASTKD2, and NDUFA4L2, and using pathway and weighted gene co-expression analyses, we identified differentially expressed immune response genes. A number of these genes, including CLU, C3, and CD74, have been implicated in Abeta generation or clearance. This data provides key insights into astrocyte-specific contributions to AD and we present this data set as a publicly available resource.

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“…We denote this brain agingrelated "ground truth" set as BrainExpression2004Age. [46] predicted 1,541 genes from StatNetExpression as aging-related, as their expressions significantly changed between different stages of Alzheimer's disease (AD). We denote this ADrelated "ground truth" set ADExpressionAge.…”

Section: Materials and Methods 21 Datamentioning

confidence: 99%

Improving identification of key players in aging via network de-noising

Yoo

Chen

Faisal

et al. 2014

Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

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Since human aging is hard to study experimentally due to long lifespan and ethical constraints, current "ground truth" knowledge about human aging has mostly been predicted computationally or statistically by transferring the knowledge from well-studied model species via sequence homology or by studying human gene expression data. Since genes, i.e., their protein products, function by interacting with each other, analysis of protein-protein interaction (PPI) network data in the context of aging is promising. Existing studies of aging from PPI networks have typically relied on static network representations. But because cellular functioning is dynamic, and because different biological data types capture complementary slices of the cell, we recently integrated the static human PPI network with aging-related gene expression data to form dynamic, age-specific networks. Then, we predicted as key players in aging those proteins whose network topologies significantly changed with age.Since current PPI networks are noisy, here, we apply stateof-the-art link prediction methods to the human PPI network to de-noise it. After we show that de-noising improves biological quality of the network, we integrate the de-noised network with the aging-related expression data to construct de-noised age-specific networks and predict novel (hopefully improved) key players in aging from the de-noised data. Indeed, PPI network de-noising improves the quality of the predictions: it results in more significant overlap between the predicted aging-related data and the "ground truth"aging-related data. Yet, we obtain many novel predictions. Thus, we produce new knowledge about human aging from de-noised dynamic networks encompassing multiple biological data types, complementing in this way the existing knowledge obtained from sequence or expression data.

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Microarray analysis of the astrocyte transcriptome in the aging brain: relationship to Alzheimer's pathology and APOE genotype

Cited by 174 publications

References 91 publications

Astrogliopathy in Tauopathies

Astrogliopathy in Tauopathies

Alzheimer's disease is associated with altered expression of genes involved in immune response and mitochondrial processes in astrocytes

Improving identification of key players in aging via network de-noising

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