Possible Neuropathology of Sleep Disturbance Linking to Alzheimer's Disease: Astrocytic and Microglial Roles.

Sleep disturbances not only deteriorate Alzheimer's disease (AD) progress by affecting cognitive states but also accelerate the neuropathological changes of AD. Astrocytes and microglia are the principal players in the regulation of both sleep and AD. We proposed that possible astrocyte-mediated and microglia-mediated neuropathological changes of sleep disturbances linked to AD, such as astrocytic adenosinergic A1, A2, and A3 regulation; astrocytic dopamine and serotonin; astrocyte-mediated proinflammatory status (TNFα); sleep disturbance-attenuated microglial CX3CR1 and P2Y12; microglial Iba-1 and astrocytic glial fibrillary acidic protein (GFAP); and microglia-mediated proinflammatory status (IL-1b, IL-6, IL-10, and TNFα). Furthermore, astrocytic and microglial amyloid beta (Aß) and tau in AD were reviewed, such as astrocytic Aß interaction in AD; astrocyte-mediated proinflammation in AD; astrocytic interaction with Aß in the central nervous system (CNS); astrocytic apolipoprotein E (ApoE)-induced Aß clearance in AD, as well as microglial Aß clearance and aggregation in AD; proinflammation-induced microglial Aß aggregation in AD; microglial-accumulated tau in AD; and microglial ApoE and TREM2 in AD. We reviewed astrocytic and microglial roles in AD and sleep, such as astrocyte/microglial-mediated proinflammation in AD and sleep; astrocytic ApoE in sleep and AD; and accumulated Aß-triggered synaptic abnormalities in sleep disturbance. This review will provide a possible astrocytic and microglial mechanism of sleep disturbance linked to AD.

Effects of Mdivi-1 on Neural Mitochondrial Dysfunction and Mitochondria-Mediated Apoptosis in Ischemia-Reperfusion Injury After Stroke: A Systematic Review of Preclinical Studies.

This systematic review sought to determine the effects of Mitochondrial division inhibitor-1 (Mdivi-1) on neural mitochondrial dysfunction and neural mitochondria-mediated apoptosis in ischemia/reperfusion (I/R) injury after ischemic stroke. Pubmed, Web of Science, and EMBASE databases were searched through July 2021. The studies published in English language that mentioned the effects of Mdivi-1 on neural mitochondrial dysfunction and neural mitochondria-mediated apoptosis in I/R-induced brain injury were included. The CAMARADES checklist (for in vivo studies) and the TOXRTOOL checklist (for in vitro studies) were used for study quality evaluation. Twelve studies were included (median CAMARADES score = 6; TOXRTOOL scores ranging from 16 to 18). All studies investigated neural mitochondrial functions, providing that Mdivi-1 attenuated the mitochondrial membrane potential dissipation, ATP depletion, and complexes I-V abnormalities; enhanced mitochondrial biogenesis, as well as inactivated mitochondrial fission and mitophagy in I/R-induced brain injury. Ten studies analyzed neural mitochondria-mediated apoptosis, showing that Mdivi-1 decreased the levels of mitochondria-mediated proapoptotic factors (AIF, Bax, cytochrome c, caspase-9, and caspase-3) and enhanced the level of antiapoptotic factor (Bcl-2) against I/R-induced brain injury. The findings suggest that Mdivi-1 can protect neural mitochondrial functions, thereby attenuating neural mitochondria-mediated apoptosis in I/R-induced brain injury. Our review supports Mdivi-1 as a potential therapeutic compound to reduce brain damage in ischemic stroke (PROSPERO protocol registration ID: CRD42020205808). Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42020205808].

Neuroprotective Effects of a Small Mitochondrially-Targeted Tetrapeptide Elamipretide in Neurodegeneration.

Neural mitochondrial dysfunction, neural oxidative stress, chronic neuroinflammation, toxic protein accumulation, and neural apoptosis are common causes of neurodegeneration. Elamipretide, a small mitochondrially-targeted tetrapeptide, exhibits therapeutic effects and safety in several mitochondria-related diseases. In neurodegeneration, extensive studies have shown that elamipretide enhanced mitochondrial respiration, activated neural mitochondrial biogenesis via mitochondrial biogenesis regulators (PCG-1α and TFAM) and the translocate factors (TOM-20), enhanced mitochondrial fusion (MNF-1, MNF-2, and OPA1), inhibited mitochondrial fission (Fis-1 and Drp-1), as well as increased mitophagy (autophagy of mitochondria). In addition, elamipretide has been shown to attenuate neural oxidative stress (hydrogen peroxide, lipid peroxidation, and ROS), neuroinflammation (TNF, IL-6, COX-2, iNOS, NLRP3, cleaved caspase-1, IL-1ß, and IL-18), and toxic protein accumulation (Aß). Consequently, elamipretide could prevent neural apoptosis (cytochrome c, Bax, caspase 9, and caspase 3) and enhance neural pro-survival (Bcl2, BDNF, and TrkB) in neurodegeneration. These findings suggest that elamipretide may prevent the progressive development of neurodegenerative diseases via enhancing mitochondrial respiration, mitochondrial biogenesis, mitochondrial fusion, and neural pro-survival pathway, as well as inhibiting mitochondrial fission, oxidative stress, neuroinflammation, toxic protein accumulation, and neural apoptosis. Elamipretide or mitochondrially-targeted peptide might be a targeted agent to attenuate neurodegenerative progression.

A Novel Metabolic Connectome Method to Predict Progression to Mild Cognitive Impairment.

OBJECTIVE: Glucose-based positron emission tomography (PET) imaging has been widely used to predict the progression of mild cognitive impairment (MCI) into Alzheimer's disease (AD) clinically. However, existing discriminant methods are unsubtle to reveal pathophysiological changes. Therefore, we present a novel metabolic connectome-based predictive modeling to predict progression from MCI to AD accurately. METHODS: In this study, we acquired fluorodeoxyglucose PET images and clinical assessments from 420 MCI patients with 36 months follow-up. Individual metabolic network based on connectome analysis was constructed, and the metabolic connectivity in this network was extracted as predictive features. Three different classification strategies were implemented to interrogate the predictive performance. To verify the effectivity of selected features, specific brain regions associated with MCI conversion were identified based on these features and compared with prior knowledge. RESULTS: As a result, 4005 connectome features were obtained, and 153 in which were selected as efficient features. Our proposed feature extraction method had achieved 85.2% accuracy for MCI conversion prediction (sensitivity: 88.1%; specificity: 81.2%; and AUC: 0.933). The discriminative brain regions associated with MCI conversion were mainly located in the precentral gyrus, precuneus, lingual, and inferior frontal gyrus. CONCLUSION: Overall, the results suggest that our proposed individual metabolic connectome method has great potential to predict whether MCI patients will progress to AD. The metabolic connectome may help to identify brain metabolic dysfunction and build a clinically applicable biomarker to predict the MCI progression.