Acitretin reverses early functional network degradation in a mouse model of familial Alzheimer’s disease

Abstract Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer’s disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early function...

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Autores principales: Eduardo Rosales Jubal, Miriam Schwalm, Malena dos Santos Guilherme, Florian Schuck, Sven Reinhardt, Amanda Tose, Zeke Barger, Mona K. Roesler, Nicolas Ruffini, Anna Wierczeiko, Michael J. Schmeisser, Ulrich Schmitt, Kristina Endres, Albrecht Stroh
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/5f4ceae1b11d437c87d1b329fa7fb0a8
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Sumario:Abstract Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer’s disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early functional effects of AD on cortical microcircuits remain unresolved. Using two-photon calcium imaging, we found altered temporal distributions (burstiness) in the spontaneous activity of layer II/III visual cortex neurons, in a mouse model of familial Alzheimer’s disease (5xFAD), before plaque formation. Graph theory (GT) measures revealed a distinct network topology of 5xFAD microcircuits, as compared to healthy controls, suggesting degradation of parameters related to network robustness. After treatment with acitretin, we observed a re-balancing of those network measures in 5xFAD mice; particularly in the mean degree distribution, related to network development and resilience, and post-treatment values resembled those of age-matched controls. Further, behavioral deficits, and the increase of excitatory synapse numbers in layer II/III were reversed after treatment. GT is widely applied for whole-brain network analysis in human neuroimaging, we here demonstrate the translational value of GT as a multi-level tool, to probe networks at different levels in order to assess treatments, explore mechanisms, and contribute to early diagnosis.