Prominent hippocampal CA3 gene expression profile in neurocognitive aging

Haberman, Rebecca P.; Colantuoni, Carlo; Stocker, Amy M.; Schmidt, Alexandra; Pedersen, Jan T.; Gallagher, Michela

doi:10.1016/j.neurobiolaging.2009.10.005

Cited by 80 publications

(145 citation statements)

References 51 publications

(76 reference statements)

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“…The measure of age-dependent changes in gene expression correlated with memory performance [52,53] and could be partially reversed by techniques known to positively influence the process of brain ageing [51,54,55]. It should nevertheless be noted that the detected changes in gene expression could be responsible for the neuronal deficits but they could also be adaptive, helping to maintain the structural integrity of neuronal networks in the ageing environment [56]. In neurodegenerative disorders, an acceleration of expression changes is observed in genes involved in inflammatory and apoptotic processes; thus, there is partially a continuum between age-related and neuropathological expression changes.…”

Section: Functional Histological and Molecular Changes In The Ageingmentioning

confidence: 99%

The endocannabinoid system in normal and pathological brain ageing

Bilkei-Gorzó

2012

Phil. Trans. R. Soc. B

116

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The role of endocannabinoids as inhibitory retrograde transmitters is now widely known and intensively studied. However, endocannabinoids also influence neuronal activity by exerting neuroprotective effects and regulating glial responses. This review centres around this less-studied area, focusing on the cellular and molecular mechanisms underlying the protective effect of the cannabinoid system in brain ageing. The progression of ageing is largely determined by the balance between detrimental, proageing, largely stochastic processes, and the activity of the homeostatic defence system. Experimental evidence suggests that the cannabinoid system is part of the latter system. Cannabinoids as regulators of mitochondrial activity, as anti-oxidants and as modulators of clearance processes protect neurons on the molecular level. On the cellular level, the cannabinoid system regulates the expression of brainderived neurotrophic factor and neurogenesis. Neuroinflammatory processes contributing to the progression of normal brain ageing and to the pathogenesis of neurodegenerative diseases are suppressed by cannabinoids, suggesting that they may also influence the ageing process on the system level. In good agreement with the hypothesized beneficial role of cannabinoid system activity against brain ageing, it was shown that animals lacking CB1 receptors show early onset of learning deficits associated with age-related histological and molecular changes. In preclinical models of neurodegenerative disorders, cannabinoids show beneficial effects, but the clinical evidence regarding their efficacy as therapeutic tools is either inconclusive or still missing.

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Section: Functional Histological and Molecular Changes In The Ageingmentioning

confidence: 99%

The endocannabinoid system in normal and pathological brain ageing

Bilkei-Gorzó

2012

Phil. Trans. R. Soc. B

116

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“…In the context of aging, altered transcriptional regulation of genes that promote or are necessary for synaptic plasticity is associated with memory impairment in aged rodents (Blalock et al 2003;Rowe et al 2007;Haberman et al 2011). Affected genes implicated in plasticity notably include the immediate-early genes HomerI1a, and Arc (activity regulated cytoskeleton-associated protein), which are necessary for learning and memory (Penner et al 2011), as well as zif268, bdnf (brain-derived neurotrophic factor) (Hattiangady et al 2005), and reelin (Stranahan et al 2011).…”

Section: Hippocampal Gene Transcription Profiles In the Aged Brainmentioning

confidence: 99%

“…Higher resolution analysis, however, documented that methylation varied substantially across promoter CpGs on the Gabra5 gene, and reliably distinguished aged rats with memory impairment at one site. While only limited data are available pertaining to methylation changes in the aged rodent brain, a reasonable account of the observations reported by Haberman et al (2011) is that methylation of individual CpGs within a transcription factor site may be more directly relevant to key memory-related cell biological processes than average methylation levels across promoter regions. By this view, deeper mapping of CpG island methylation across the genome may be necessary to accurately characterize how the dysregulation of epigenetic chromatin modification contributes to cognitive decline with age.…”

Section: Epigenetic Signatures Of Cognitive Agingmentioning

confidence: 99%

“…Data derived from a rodent model of neurocognitive aging in which old Long-Evans rats show individual variability in cognitive outcome highlight the marked changes in hippocampal gene transcription that occur in association with age-related memory impairment, thereby distinguishing neurobiological signatures that are specifically associated with age-related memory decline from changes coupled with chronological age, unrelated to cognitive outcome. Adopting this approach, Haberman et al (2011) demonstrated that aged rats with memory impairment show a constellation of gene transcriptional changes that are positioned to influence a wide range of learning and memory-related processes in the hippocampus. Affected targets include gene expression important for synaptic plasticity and connectivity, and protein quality control, a function necessary for neuronal health and memory consolidation .…”

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confidence: 99%

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Epigenetic contributions to cognitive aging: disentangling mindspan and lifespan

2014

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Epigenetic modifications of chromatin structure provide a mechanistic interface for gene-environment interactions that impact the individualization of health trajectories across the lifespan. A growing body of research indicates that dysfunctional epigenetic regulation contributes to poor cognitive outcomes among aged populations. Here we review neuroepigenetic research as it relates to cognitive aging, focusing specifically on memory function mediated by the hippocampal system. Recent work that differentiates epigenetic contributions to chronological aging from influences on mindspan, or the preservation of normal cognitive abilities across the lifespan, is also highlighted. Together, current evidence indicates that while age-related memory impairment is associated with dysfunction in the coordinated regulation of chromatin modification, animal models that show individual differences in cognitive outcome underscore the enormous mechanistic complexity that surrounds epigenetic dynamics in the aged hippocampus.Cognitive decline, especially memory loss, is one of the most prevalent and feared consequences of growing older. In the United States it is expected that by 2050, 12% of people over the age of 65 will suffer from moderate-to-severe memory impairment (Federal Interagency Forum on Aging-Related Statistics: Older Americans Update 2004). Understanding the neural basis of cognitive decline is all the more pressing in light of national demographic trends highlighting the rapidly expanding elderly population, with the number of people aged 65 and older projected to increase from 43 million to more than 83 million over the next four decades (Ortman et al. 2014). Alongside a focus on negative outcomes, there is increasing recognition that memory decline is not an inevitable consequence of aging as some older adults maintain normal memory abilities across the lifespan. Identifying the neurobiological mechanisms that impact differential cognitive outcomes with age is critical. In this context, research exploring the biological substrates that drive individual healthspan trajectories from early development through old age can provide valuable insight into the brain mechanisms that influence mindspan.A life course perspective emphasizes that environmental and experiential factors operate throughout life to potently influence the biological mechanisms that dictate the arc of an individual's health trajectory (for review, see Halfon et al. 2014). An emerging theme is that age alone is only a coarse predictor of health outcome, and current efforts are focused on disentangling chronological age effects from other determinants of functional outcomes in the elderly. Epigenetic modifications of the genome have gained attention in this context since they allow for genomic plasticity in post-mitotic cells and provide a means by which environment and experience interface with gene transcription to impact biological functions across the lifespan. This plasticity is crucial for adaptation and resilience in the face of environmenta...

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“…we have used subset of gene expression data of Rattus norvegicus (Rat) of hippocampal region for CA1 region of Gene expression profiling in differential cognitive outcomes in aging: CA1 from GEO database with geo_accession id GSE14723 [18].…”

Section: Data Set and Implementationmentioning

confidence: 99%

Two Phase Integrated Rule based Model (TPC-IRBM) for Clustering of Gene Expression Data of CA1 Region of Rat Hippocampus

Tripathi¹,

Mishra²

2013

IJCA

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This paper propose a semi supervised clustering model TPC-IRBM(Two phase clustering-Integrated rule based model) for clustering large data set such as gene expression data. TPC-IRBM works in two phases to cluster the gene expression data set. The proposed model is based on rule based models CRT,C5,CHAID and QUEST. In the first phase of the model 30 % data(which may vary) is extracted to prepare training, testing and validation data (TTV data)using suitable heuristic or neural network based clustering techniques. The output of first phase is used as build the models and generate the rule base fitting to TTV data using aforesaid models. The proposed model is then constructed by selecting and integrating the quality rules of various models using qualifying criteria corresponding to every cluster.The number of quality rules in proposed model is much more compared to that of CRT,C5,CHAID and QUEST.The performance in terms of accuracy is better compared to the models. Although in some cases Neural Network based models performance is slightly better but a very high cost of complexity for very large data set. KeywordsGene expression clustering,semi supervised clustering, integrated rule based model, two phase clustering,CA1 region gene expression clustering of rat hippocampus.

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Prominent hippocampal CA3 gene expression profile in neurocognitive aging

Cited by 80 publications

References 51 publications

The endocannabinoid system in normal and pathological brain ageing

The endocannabinoid system in normal and pathological brain ageing

Epigenetic contributions to cognitive aging: disentangling mindspan and lifespan

Two Phase Integrated Rule based Model (TPC-IRBM) for Clustering of Gene Expression Data of CA1 Region of Rat Hippocampus

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