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The study of Alzheimer's disease (AD) pathogenesis requires the use of animal models that develop some amount of amyloid pathology in the brain. Aged canines (beagles) naturally accumulate human-type amyloid-beta peptide (Abeta) and develop parallel declines in cognitive function. However, the type and quantity of biochemically extracted Abeta in brain and cerebrospinal fluid (CSF), its link to aging, and similarity to human aging has not been examined systematically. Thirty beagles, aged 4.5-15.7 years, were studied. Abeta40 and Abeta42 were measured in CSF by ELISA, and from SDS and formic acid extracted prefrontal cortex. A sample of the contralateral hemisphere, used to assess immunohistochemical amyloid load, was used for comparison. In the brain, increases in Abeta42 were detected at a younger age, prior to increases in Abeta40, and were correlated with an increased amyloid load. In the CSF, Abeta42 decreased with age while Abeta40 levels remained constant. The CSF Abeta42/40 ratio was also a good predictor of the amount of Abeta in the brain. The amount of soluble oligomers in CSF was inversely related to brain extractable Abeta, whereas oligomers in the brain were correlated with SDS soluble Abeta42. These findings indicate that the Abeta in the brain of the aged canine exhibits patterns that mirror Abeta deposited in the human brain. These parallels support the idea that the aged canine is a useful intermediate between transgenic mice and humans for studying the development of amyloid pathology and is a potentially useful model for the refinement of therapeutic interventions.

β-Amyloid (Aβ), a small, fibrillogenic peptide, is known to play an important role in the pathogenesis of Alzheimer’s disease (AD) in the brain. In addition, Aβ accumulates in skeletal muscle cells in individuals with sporadic inclusion body myositis (sIBM), an age-related muscle disease. Because of the socioeconomic burden associated with age-related diseases, particularly AD, there has been considerable emphasis on studying potential therapeutic strategies. The high fat, low carbohydrate ketogenic diet has been used extensively to treat refractory childhood epilepsy and has been studied as a potential treatment for other neurological diseases, including Parkinson’s disease and AD. In this study, we fed young APP/PS1 knock-in mice, which have a whole body knock-in of AD-related genes, a ketogenic diet and determined the effect on Aβ levels in the brain and skeletal muscle, as well motor performance and oxidative stress. Aβ and its precursor, the β-C-terminal fragment of amyloid precursor protein (CTFβ), were unchanged overall in both the brain and quadriceps after 1 month on the ketogenic diet, and there was no effect on nitrotyrosine, a product of oxidative stress. The ketogenic diet improved performance on the Rota-rod apparatus (p=0.007), however. These data indicate that the ketogenic diet may have some efficacy in the treatment of both neurologic and muscle diseases though the underlying mechanisms do not involve amelioration of Aβ pathology.

Abbreviation used: AD, Alzheimer's disease; APP · PS1, amyloid precursor protein and presenilin-1 knock-in mice; APP, amyloid precursor protein; Ab, amyloid-b; DEA, diethylamine; HNE, 4-hydroxynonenal; PS, presenilin-1; SDS, sodium dodecyl sulfate; WD, Western diet; WT, wild type. AbstractA chronic high fat Western diet (WD) promotes a variety of morbidity factors although experimental evidence for shortterm WD mediating brain dysfunction remains to be elucidated. The amyloid precursor protein and presenilin-1 (APP · PS1) knock-in mouse model has been demonstrated to recapitulate some key features of Alzheimer's disease pathology, including amyloid-b (Ab) pathogenesis. In this study, we placed 1-month-old APP · PS1 mice and nontransgenic littermates on a WD for 4 weeks. The WD resulted in a significant elevation in protein oxidation and lipid peroxidation in the brain of APP · PS1 mice relative to non-transgenic littermates, which occurred in the absence of increased Ab levels. Altered adipokine levels were also observed in APP · PS1 mice placed on a short-term WD, relative to nontransgenic littermates. Taken together, these data indicate that short-term WD is sufficient to selectively promote cerebral oxidative stress and metabolic disturbances in APP · PS1 knock-in mice, with increased oxidative stress preceding alterations in Ab. These data have important implications for understanding how WD may potentially contribute to brain dysfunction and the development of neurodegenerative disorders such as Alzheimer's disease.

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Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute’s “Brain-CODE” is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care.

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