Current Alzheimer Research - Volume 18, Issue 7, 2021
Volume 18, Issue 7, 2021
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Non-Ceruloplasmin Copper as a Stratification Biomarker of Alzheimer’s Disease Patients: How to Measure and Use It
Alzheimer’s Disease (AD) is a type of dementia very common in the elderly. A growing body of recent evidence has linked AD pathogenesis to Copper (Cu) dysmetabolism in the body. In fact, a subset of patients affected either by AD or by its prodromal form known as Mild Cognitive Impairment (MCI) have been observed to be unable to maintain a proper balance of Cu metabolism and distribution and are characterized by the presence in their serum of increased levels of Cu not bound to ceruloplasmin (non-ceruloplasmin Cu). Since serum non-ceruloplasmin Cu is a biomarker of Wilson's Disease (WD), a well-known condition of Cu-driven toxicosis, in this review, we propose that in close analogy with WD, the assessment of non-ceruloplasmin Cu levels can be exploited as a cost-effective stratification and susceptibility/risk biomarker for the identification of some AD/MCI individuals. The approach can also be used as an eligibility criterion for clinical trials aiming at investigating Cu-related interventions against AD/MCI.
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Exendin-4 Improves Cognitive Function of Diabetic Mice via Increasing Brain Insulin Synthesis
Authors: Xuemin Peng, Xiaoli Shi, Jiaojiao Huang, Shujun Zhang, Yongli Yan, Delin Ma, Weijie Xu, Weijie Xu, Kun Dong, Jing Tao, Mengni Li and Yan YangBackground and Objective: Type 2 Diabetes (T2D) patients are more prone to develop Alzheimer’s Disease (AD). We have previously shown that Glucagon-like peptide-1 receptor agonist exendin-4 (Ex-4) reduces tau hyperphosphorylation in T2D animals through upregulating insulin signaling, and peripheral injected Ex-4 increases insulin levels in the T2D brain. This study aims to further clarify whether the elevated insulin in the brain is produced by nerve cells under the action of Ex-4. Methods: The neuronal cell line-HT22 was treated with Ex-4 under high glucose or normal cultivation, and the number of insulin-positive cells as well as the expression levels of insulin synthesis-related genes were examined. The db/db mice were treated with the peripheral injection of Ex-4 and/or IntraCerebroVentricular (ICV) injection of siRNA to inhibit the expression of insulin synthesis- related genes and the behavior tests were carried on. Finally, plasma glucose, Cerebrospinal Fluid (CSF) glucose, CSF insulin, phosphorylation of tau, phosphorylation of AKT and GSK-3β of db/db mice were detected. Results: We found that Ex-4 promoted the expression of insulin synthesis-related genes and induced an obvious increase of insulin-positive HT-22 neuronal cells in a high glucose environment. Peripheral injection of Ex-4 improved the cognitive function of db/db mice and increased brain insulin levels which activated brain insulin signaling and subsequently alleviated tau hyperphosphorylation. However, when siRNA-neurod1 was injected to block insulin synthesis, the cognitive function of db/db mice was not improved under the action of Ex-4 anymore. Moreover, the brain insulin levels dropped to an extremely low level, and the phosphorylation level of tau increased significantly. Conclusion: This study demonstrated that Ex-4 improved cognition function by promoting brain insulin synthesis followed by the activation of brain insulin signaling and alleviation of tau hyperphosphorylation.
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A Novel Probiotic Formula, BIOCG, Protects Against Alzheimer’s-Related Cognitive Deficits via Regulation of Dendritic Spine Dynamics
Authors: Miao Sun, Wenchenyang Bao, Chengyu Huang, Ziyue Xia, Changliang Zhang, Guangxian Wang, Runxin Wang, Jiangyu Li, Shaun Roux, Qian Li, Dongmei Zou, Kai Ma and Xiaofeng BaoBackground: The brain-gut-microbiome axis has emerged as an important pathway through which perturbations in the gut and/or microbial microenvironment can impact neurological function. Such alterations have been implicated in a variety of neuropsychiatric disorders, including depression, anxiety, and Alzheimer’s Disease (AD) and the use of probiotics as therapy for these diseases remains promising. However, the mechanisms underlying the gut microenvironment’s influence on disease pathogenesis and therapy remain unclear. Objective: The objective of this study is to investigate the effect of a novel probiotic formula, BIOCG, on cognitive function and pathobiological mechanisms, including amyloid processing and dendritic spine dynamics, in a mouse model of AD. Methods: BIOCG was administered for 3 months to 3xTg or 3xTg; Thy1-YFP AD mice and functional outcomes were assessed via behavioral testing and electrophysiology. Mechanisms relevant to AD pathogenesis including dendritic spine morphology and turnover, Amyloid Precursor Protein (APP) processing and microglial phenotype were also evaluated. Finally, we sequenced fecal samples following probiotic treatment to assess the impact on gut microbial composition and correlate the changes with the above described measures. Results: Mice treated with BIOCG demonstrated preserved cognitive abilities and stronger Long- Term Potentiation (LTP), spontaneous Excitatory Postsynaptic Currents (sEPSC), and glutamate-induced LTPs, indicative of functional and electrophysiological effects. Moreover, we observed attenuated AD pathogenesis, including reduced Amyloid Beta (Aβ) burden, as well as more mature dendritic spines in the BIOCG-treated. Our finding of changes in microglial number and phenotype in the treatment group suggests that this formulation may mediate its effects via attenuation of neuroinflammation. Sequencing data confirmed that the gut microbiome in treated mice was more varied and harbored a greater proportion of “beneficial” bacteria. Conclusion: Overall, our results indicate that treatment with BIOCG enhances microbial diversity and, through gut-brain axis interactions, attenuates neuroinflammation to produce histologic and functional improvement in AD pathogenesis.
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Cerebrospinal Fluid Biomarker Levels as Markers for Nursing Home Placement and Survival Time in Alzheimer’s Disease
Authors: Carina Wattmo, Kaj Blennow and Oskar HanssonBackground: Cerebrospinal Fluid (CSF) biomarkers are associated with conversion from mild cognitive impairment to Alzheimer’s Disease (AD), but their predictive value for later end-points has been less evaluated with inconsistent results. Objective: We investigated potential relationships between CSF amyloid-β1-42 (Aβ42), Phosphorylated tau (P-tau), and Total tau (T-tau) with time to Nursing Home Placement (NHP) and life expectancy after diagnosis. Methods: This prospective observational study included 129 outpatients clinically diagnosed with mild-to-moderate AD who underwent a lumbar puncture. The CSF biomarkers were analysed with xMAP technology. Dates of institutionalisation and death were recorded. Results: After 20 years of follow-up, 123 patients (95%) were deceased. The participants with abnormal P-tau and T-tau (A+ T+ (N)+) died earlier than those with normal P-tau/abnormal T-tau (A+ T- (N)+) (mean, 80.5 vs. 85.4 years). Linear associations were demonstrated between lower Aβ42 and shorter time to NHP (p = 0.017), and higher P-tau and younger age at death (p = 0.016). No correlations were detected between survival after AD diagnosis and CSF biomarkers. In sexand- age-adjusted Cox regression models, higher P-tau and T-tau were independent predictors of shorter lifespan after diagnosis. In multivariate Cox models, older age and lower baseline cognitive status, but not elevated tau, significantly precipitated both institutionalisation and death. Conclusion: These findings suggest that CSF biomarker levels plateau in the dementia phase of AD, which may limit their possible relationships with clinical end-points, such as NHP and survival time. However, the biomarkers reflect the central pathophysiologies of AD. In particular, pathologic tau is associated with more advanced disease, younger age at onset, and earlier death.
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Association of the MAOB rs1799836 Single Nucleotide Polymorphism and APOE ε4 Allele in Alzheimer’s Disease
Background: The dopaminergic system is functionally compromised in Alzheimer’s Disease (AD). The activity of Monoamine Oxidase B (MAOB), the enzyme involved in the degradation of dopamine, is increased during AD. Also, increased expression of MAOB occurs in the postmortem hippocampus and neocortex of patients with AD. The MAOB rs1799836 polymorphism modulates MAOB transcription, consequently influencing protein translation and MAOB activity. We recently showed that cerebrospinal fluid levels of amyloid β1-42 are decreased in patients carrying the A allele in MAOB rs1799836 polymorphism. Objective: The present study compares MAOB rs1799836 polymorphism and APOE, the only confirmed genetic risk factor for sporadic AD. Methods: We included 253 participants, 127 of whom had AD, 57 had mild cognitive impairment, 11 were healthy controls, and 58 suffered from other primary causes of dementia. MAOB and APOE polymorphisms were determined using TaqMan SNP Genotyping Assays. Results: We observed that the frequency of APOE ε4/ε4 homozygotes and APOE ε4 carriers is significantly increased among patients carrying the AA MAOB rs1799836 genotype. Conclusion: These results indicate that the MAOB rs1799836 polymorphism is a potential genetic biomarker of AD and a potential target for the treatment of decreased dopaminergic transmission and cognitive deterioration in AD.
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Robust Discovery of Mild Cognitive Impairment Subtypes and Their Risk of Alzheimer’s Disease Conversion Using Unsupervised Machine Learning and Gaussian Mixture Modeling
Background: Alzheimer’s Disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of Alzheimer’s disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans. Objective: This study aimed to determine whether the unsupervised discovering of latent classes of subjects with Mild Cognitive Impairment (MCI) may be useful in finding different prodromal AD stages and/or subjects with a low MCI to AD conversion risk. Methods: Total 18 features relevant to the MCI to AD conversion process led to the identification of 681 subjects with early MCI. Subjects were divided into training (70%) and validation (30%) sets. Subjects from the training set were analyzed using consensus clustering, and Gaussian Mixture Models (GMM) were used to describe the latent classes. The discovered GMM predicted the latent class of the validation set. Finally, descriptive statistics, rates of conversion, and Odds Ratios (OR) were computed for each discovered class. Results: Through consensus clustering, we discovered three different clusters among MCI subjects. The three clusters were associated with low-risk (OR = 0.12, 95%CI = 0.04 to 0.3|), medium-risk (OR = 1.33, 95%CI = 0.75 to 2.37), and high-risk (OR = 3.02, 95%CI = 1.64 to 5.57) of converting from MCI to AD, with the high-risk and low-risk groups highly contrasting. Hence, prodromal AD subjects were present in only two clusters. Conclusion: We successfully discovered three different latent classes among MCI subjects with varied risks of MCI-to-AD conversion through consensus clustering. Two of the discovered classes may represent two different prodromal presentations of Alzheimer´s disease.
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Volumes & issues
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Volume 22 (2025)
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Volume 21 (2024)
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Volume 20 (2023)
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Volume 19 (2022)
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Volume 18 (2021)
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Volume 17 (2020)
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Volume 16 (2019)
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Volume 15 (2018)
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Volume 14 (2017)
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Volume 13 (2016)
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Volume 12 (2015)
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Volume 11 (2014)
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Volume 10 (2013)
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Volume 9 (2012)
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Volume 8 (2011)
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Volume 7 (2010)
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Volume 6 (2009)
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Volume 5 (2008)
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Volume 4 (2007)
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Volume 3 (2006)
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Volume 2 (2005)
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Volume 1 (2004)
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