Literature DB >> 10888876

Gene-expression profile of the ageing brain in mice.

C K Lee1, R Weindruch, T A Prolla.   

Abstract

Ageing of the brain leads to impairments in cognitive and motor skills, and is the major risk factor for several common neurological disorders such as Alzheimer disease (AD) and Parkinson disease (PD). Recent studies suggest that normal brain ageing is associated with subtle morphological and functional alterations in specific neuronal circuits, as opposed to large-scale neuronal loss. In fact, ageing of the central nervous system in diverse mammalian species shares many features, such as atrophy of pyramidal neurons, synaptic atrophy, decrease of striatal dopamine receptors, accumulation of fluorescent pigments, cytoskeletal abnormalities, and reactive astrocytes and microglia. To provide the first global analysis of brain ageing at the molecular level, we used oligonucleotide arrays representing 6,347 genes to determine the gene-expression profile of the ageing neocortex and cerebellum in mice. Ageing resulted in a gene-expression profile indicative of an inflammatory response, oxidative stress and reduced neurotrophic support in both brain regions. At the transcriptional level, brain ageing in mice displays parallels with human neurodegenerative disorders. Caloric restriction, which retards the ageing process in mammals, selectively attenuated the age-associated induction of genes encoding inflammatory and stress responses.

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Year:  2000        PMID: 10888876     DOI: 10.1038/77046

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  309 in total

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Authors:  H Müller; A P Bracken; R Vernell; M C Moroni; F Christians; E Grassilli; E Prosperini; E Vigo; J D Oliner; K Helin
Journal:  Genes Dev       Date:  2001-02-01       Impact factor: 11.361

2.  Influences of aging and caloric restriction on the transcriptional profile of skeletal muscle from rhesus monkeys.

Authors:  T Kayo; D B Allison; R Weindruch; T A Prolla
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-17       Impact factor: 11.205

3.  Genome-wide study of aging and oxidative stress response in Drosophila melanogaster.

Authors:  S Zou; S Meadows; L Sharp; L Y Jan; Y N Jan
Journal:  Proc Natl Acad Sci U S A       Date:  2000-12-05       Impact factor: 11.205

4.  A new approach for filtering noise from high-density oligonucleotide microarray datasets.

Authors:  J C Mills; J I Gordon
Journal:  Nucleic Acids Res       Date:  2001-08-01       Impact factor: 16.971

5.  Transcriptional analysis in the brain: trophin-induced hippocampal synaptic plasticity.

Authors:  Janet Alder; Smita Thakker-Varia; Ira B Black
Journal:  Neurochem Res       Date:  2002-10       Impact factor: 3.996

Review 6.  Functional genomics and psychiatric illness.

Authors:  Wendy Hasenkamp; Scott E Hemby
Journal:  Prog Brain Res       Date:  2002       Impact factor: 2.453

7.  Specificity assessment from fractionation experiments (SAFE): a novel method to evaluate microarray probe specificity based on hybridisation stringencies.

Authors:  Alexei L Drobyshev; Christine Machka; Marion Horsch; Matthias Seltmann; Volkmar Liebscher; Martin Hrabé de Angelis; Johannes Beckers
Journal:  Nucleic Acids Res       Date:  2003-01-15       Impact factor: 16.971

8.  Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

Authors:  Paul Pavlidis; Jie Qin; Victoria Arango; John J Mann; Etienne Sibille
Journal:  Neurochem Res       Date:  2004-06       Impact factor: 3.996

Review 9.  Caloric restriction and aging: studies in mice and monkeys.

Authors:  Rozalyn M Anderson; Dhanansayan Shanmuganayagam; Richard Weindruch
Journal:  Toxicol Pathol       Date:  2008-12-15       Impact factor: 1.902

10.  Jmjd3 is essential for the epigenetic modulation of microglia phenotypes in the immune pathogenesis of Parkinson's disease.

Authors:  Y Tang; T Li; J Li; J Yang; H Liu; X J Zhang; W Le
Journal:  Cell Death Differ       Date:  2013-11-08       Impact factor: 15.828

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