The neurobiology of aging and <scp>A</scp>lzheimer's disease: walking down the same road?
Notice bibliographique
Résumé
The cognitive impairments associated with aging and age-related diseases are a major socio-economic concern for the world's rapidly growing older population. As we get older, subtle changes in nervous system biology manifest as altered sleeping patterns, impaired sensory–motor coordination, mood changes, and impairments in learning and memory. Although, in most people, these deteriorations do not reach the level of incapacitating impairments, they impact the life of a large proportion of aging people. Aging-related changes in neural function can occur at dramatically different rates across individuals and populations, and there is evidence for the involvement of both genetic and environmental risk factors. However, the neurobiological mechanisms affected at the network, cellular and molecular levels are only slowly becoming clearer. Alzheimer's disease (AD) is among the most prevalent of aging-related brain diseases, and it represents the most common form of senile dementia. AD-type dementia is characterized by a markedly accelerating decline in cognitive abilities that dramatically worsens the quality of life of patients as well as of their relatives who are often their primary caregivers. Although there have been glimpses into the molecular mechanisms of AD in recent years, it is still unclear what triggers this devastating disease and how exactly it leads to cognitive decline. Does AD hijack ‘normal’ aging-associated mechanisms of cognitive decline? Does it activate completely independent pathological neurobiological mechanisms? Is it a combination of both? Aging and AD might be walking down the same road, but when and where do they part? The inspiration for this Special Issue was the 34th Annual International Symposium of the Université de Montréal's CNS Research Group (Groupe de recherche sur le système nerveux central), held on May 7–8, 2012 (http://www.grsnc.umontreal.ca/34s/home.html). Organized by Drs Jannic Boehm, Karl Fernandes, Nicole Leclerc and Richard Robitaille, this year's symposium focused on the Neurobiology of Aging and Alzheimer's Disease. It was spearheaded by the idea that understanding normal and pathological aging will benefit from considering multiple levels of analysis, ranging from complex neuronal circuits to the molecular mechanisms. Reflecting this view, this Special Issue is organized around four themes, with a panel of international experts discussing the following themes: (i) global perturbation of neuronal circuits and networks, (ii) mechanisms of altered cell–cell communication, (iii) intracellular signaling mediating neural degeneration, and (iv) birth in death – saving neurons and rejuvenating the brain. The overall goal of this discussion has been to arrive at a clearer understanding of the mechanistic similarities and differences between normal and AD-type cognitive aging. Neuronal circuits in the cortex and hippocampus are of primary importance for higher cognitive functions, and are affected during both aging and AD. Yves Joanette reviews changing patterns of neurofunctional reorganization observed during aging, adaptations that are related to the preservation of communication abilities. Carol Barnes discusses changes in cognitive functions during ‘normal’ aging, and the alterations in hippocampal and prefrontal networks that may underlie them. Two contributors then present new primary data showing that changes in the electrophysiological connectivity between brain regions may be an early occurrence during AD. Sylvain Williams examines hippocampal output in the subiculum and shows that TgCRND8 mice begin developing alterations in gamma–theta oscillations and cross-coupling (believed to be important for memory consolidation and executive functioning) between 2 and 4 weeks of age. In humans, Jong-Min Lee reports changes in the resting state default mode network (a measure of functional connectivity) in patients with AD and amnesic mild cognitive impairment (an early stage of AD) compared with unaffected individuals. Efficient communication between neural cells is critical for network function and cognition, and changes in inter-cellular communication appear to be involved in the cognitive deficits associated with both aging and AD, as well as in pathology propagation through the AD brain. One synaptic feature of aging is deficits in long-term potentiation, a process centrally involving N-methyl-D-aspartate receptors. Jean-Marie Billard reviews the data that the amino acid D-serine is an endogenous extracellular co-agonist for N-methyl-D-aspartate receptors, and that age-related impairment of the enzyme serine racemase by oxidative stress causes a reduction in D-serine levels. Jannic Boehm discusses recent data suggesting that, in AD, extracellular amyloid-beta acts on the N-methyl-D-aspartate receptor to modify intracellular Tau. Nicole Leclerc then examines the idea that prion-like inter-cellular transmission of Tau along synaptically connected circuits may mediate the propagation of Tau pathology during AD. Although significant neuronal loss does not appear to occur until very late stages of the ‘normal’ aging process, it is a prominent feature of AD. Three studies are presented that are aimed at better understanding the molecular pathways leading to neurodegeneration in AD. Ralph Nixon revisits the hotly debated topic of autophagy, a lysosome-mediated process for degrading and recycling waste intracellular constituents that is disrupted in multiple autophagy–lysosomal degradation diseases, controversially including AD. Nixon presents new data supporting lysosomal pH being increased in cellular models of Presenilin deficiency and in human cells carrying AD-causing Presenilin mutations, and he goes on to provide a technical report on the suitability of pH quantification methods for measuring lysosomal pH. Weihong Song and colleagues then present two studies focusing on the amyloid precursor protein (APP)-processing enzymes BACE1 and BACE2. In one study, Song shows that the amyloid-beta-generating BACE1 enzyme normally cleaves at a non-amyloidogenic site of APP, and that this shifts to an amyloidogenic site in response to either BACE1 overexpression or to the familial AD Swedish mutation of APP. In their second study, Song presents evidence that BACE2 (which prevents amyloid-beta overproduction by cleaving APP within the amyloid-beta domain) is normally degraded via the macrophagy–lysosome pathway (autophagy), and that inhibition of this process increases BACE2 cleavage of APP. Neuron numbers may be compromised through multiple mechanisms during aging and/or AD, including the decreasing production of new neurons (adult neurogenesis) and increasing loss of pre-existing neurons. Neurogenesis is a relatively late entrant to the field of potential causes for cognitive decline in aging and AD. Although the numbers of adult-born neurons is likely to be modest in humans, interest in this process has been fuelled by recent insights into its significant roles in the maintenance of forebrain neural populations and hippocampal-dependent processes such as learning, memory, mood and stress regulation. Karl Fernandes and colleagues review the literature to untangle what we have learned about when, how and why forebrain neurogenesis decreases with age, whereas Grigori Enikolopov and colleagues present data that certain aspects of the decrease in neurogenesis during aging can be positively influenced by caloric restriction. Changes in the central nervous system vasculature are also linked to cognitive performance; JoAnne McLaurin and colleagues review what has been learned about vascular dysfunction in animal models of AD and amyloid angiopathy, and consider the possibilities for targeting cerebrovascular amyloid and function to promote cognitive recovery. Finally, Andrea LeBlanc discusses evidence supporting the idea that the protease Caspase-6 is in the right place at the right time to be involved in the progression of AD, and may therefore represent a novel therapeutic target to inhibit neurodegeneration. At the end of the day, the question of the mechanistic links between normal and AD-type cognitive aging remains unanswered. But what have we learned? First, it has become evident that a much clearer understanding of the neurobiology of the aging process is required before we can reliably define its relationship with AD. Although we are starting to better understand the effects of aging on the brain, the cellular and molecular basis of these aging-associated changes remains only vaguely understood. Indeed, even the biological definition of aging remains ambiguous. Second, although some of the macroscopic effects of normal cognitive aging appear at an accelerated rate in AD, there is little solid evidence that this occurs via an enhancement of normal aging mechanisms. Moreover, as AD-associated cognitive changes can begin to be observed at juvenile ages in animal models and at mid-adulthood in familial AD, being old does not appear to even be a prerequisite for AD, although it remains the largest risk factor for the onset of AD. Thus, it is possible that AD induces similar types of cognitive deficits as the normal aging process, but does so via distinct pathological processes. We thank the Groupe de recherche sur le système nerveux central for its technical and financial support. In particular, we thank Ms Manon Dumas for all the organisational support, Mr Claude Gauthier for the graphical designs and Mr René Albert as webmaster. We also acknowledge the significant financial support of the Canadian Institutes of Health Research, The Fonds de Recherche du Quebec-Santé, The Quebec Network for Research in Aging, The Faculté de Médecine of the Université de Montréal and the Vice-Rector Research of Université de Montréal. Finally, we thank the editorial team of EJN for their support in organizing and publishing this Special Issue.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».