Prodromal Stage Of Alzheimer Research Articles

Cognitive indicators of transition to preclinical and prodromal stages of Alzheimer's disease in Down syndrome.

IntroductionThere is a critical need to identify measures of cognitive functioning sensitive to early Alzheimer's disease (AD) pathophysiology in Down syndrome to advance clinical trial research in this at‐risk population. The objective of the study was to longitudinally track performance on cognitive measures in relation to neocortical and striatal amyloid beta (Aβ) in non‐demented Down syndrome.MethodsThe study included 118 non‐demented adults with Down syndrome who participated in two to five points of data collection, spanning 1.5 to 8 years. Episodic memory, visual attention and executive functioning, and motor planning and coordination were assessed. Aβ was measured via [C‐11] Pittsburgh Compound‐B (PiB) PET.ResultsPiB was associated with level and rate of decline in cognitive performance in episodic memory, visual attention, executive functioning, and visuospatial ability in models controlling for chronological age.DiscussionThe Cued Recall Test emerged as a promising indicator of transition from preclinical to prodromal AD.

Digital Biomarkers Based Individualized Prognosis for People at Risk of Dementia: the AltoidaML Multi-site External Validation Study.

Research investigating treatments and interventions for cognitive decline and Alzheimer's disease (AD) suffer due to difficulties in accurately identifying individuals at risk of AD in the pre-symptomatic stages of the disease. There is an urgent need for better identification of such individuals in order to enable earlier treatment and to properly stage and stratify participants for clinical trials and intervention studies. Although some biological measures (biomarkers) can identify Alzheimer's-related changes before significant changes in cognitive function occur, such biomarkers are not ideal as they are only able to place individuals in rudimentary stages of the disease/cognitive decline (Tarnanas et al., Alzheimers Dement (Amst) 1(4):521-532, 2015) and sometimes mistakenly diagnose individuals (Edmonds et al. 2015). Two tests, based on real-world functioning, which have been used to screen for pre-symptomatic AD are (i) dual-task walking tests (Belghali et al. 2017) and (ii) day-out tasks (Tarnanas et al. 2013). A novel digital biomarker, the Altoida ADPS app, which implements gamified versions of these tests has been shown to accurately discriminate between healthy controls and individuals in prodromal stages of Alzheimer's disease (Tarnanas et al. 2013) and can differentiate between people with mild cognitive impairment who convert to Alzheimer's disease and those who don't (Tarnanas et al. 2015b). The aim of this study is the validation of a novel digital biomarker of cognitive decline.

The Effect of Baseline Performance and Age on Cognitive Training Improvements in Older Adults: A Qualitative Review.

Findings that the brain is capable of plasticity up until old age have led to interest in the use of cognitive training as a potential intervention to delay the onset of dementia. However, individuals participating in training regimens differ greatly with respect to their outcomes, demonstrating the importance of considering individual differences, in particular age and baseline performance in a cognitive domain, when evaluating the effectiveness of cognitive training. In this review, we summarize existing literature on cognitive training in adults across the domains of episodic memory, working memory and the task-switching component of executive functioning to clarify the picture on the impact of age and baseline performance on cognitive training-related improvements. Studies targeting episodic memory induced greater improvements in younger adults with more intact cognitive abilities, explained in part by factors specific to episodic memory training. By contrast, older, lower baseline performance adults improved most in several studies targeting working memory in older individuals as well as in the majority of studies targeting executive functioning, suggesting the preservation of neural plasticity in these domains until very old age. Our findings can have important implications for informing the design of future interventions for enhancing cognitive functions in individuals at the prodromal stage of Alzheimer's Disease and potentially delaying the clinical onset of Alzheimer's Disease. Future research should more clearly stratify individuals according to their baseline cognitive abilities and assign specialized, skill-specific cognitive training regimens in order to directly answer the question of how individual differences impact training effectiveness.

Beneficial effect of computer-based multidomain cognitive training in patients with mild cognitive impairment

The purpose of the present study was to explore the effects of computer-based multidomain cognitive training program on Greek patients with Mild Cognitive Impairment (MCI). Forty-six patients with MCI were randomly divided into two groups; (a) the training group, which received a computer-based multidomain cognitive training program with the use of the RehaCom software and (b) the control group, which underwent standard-clinical care. The duration of the computer-based training program was 15 weeks, administered twice a week for approximately one hour per session. Analysis of the baseline versus endpoint performance of each group demonstrated that in the control group delayed memory and executive function had deteriorated over the observation period of 15 weeks, while improvement was observed in the training group’s performance on delayed memory, word recognition, Boston Naming Test (BNT), Clock Drawing Test (CDT), Semantic Fluency (SF), Trail Making Test-A (TMT-A) and Trail Making Test-B (TMT-B). Comparison between the two groups presented asignificant effect of the intervention for most cognitive domains. These findings are promising for the development of training methods designed to delay cognitive decline in patients with MCI, which is considered to be the prodromal stage of Alzheimer’s Disease (AD).

A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging

BackgroundDiagnosis of early mild cognitive impairment (EMCI) as a prodromal stage of Alzheimer’s disease (AD) with its delineation from the cognitively normal (CN) group remains a challenging but essential step for the planning of early treatment. Although several studies have focused on the MCI diagnosis, this study introduces the early stage of MCI to assess more thoroughly the earliest signs of disease manifestation and progression. New methodWe used random forest feature selection model with a Gaussian-based algorithm to perform method evaluation. This integrated method serves to define multivariate normal distributions in order to classify different stages of AD, with the focus placed on detecting EMCI subjects in the most challenging classification of CN vs. EMCI. ResultsUsing 896 participants classified into the four categories of CN, EMCI, late mild cognitive impairment (LMCI) and AD, the results show that the EMCI group can be delineated from the CN group with a relatively high accuracy of 78.8% and sensitivity of 81.3%. Comparison with existing method(s)The feature selection model and classifier are compared with some other prominent algorithms. Although higher accuracy has been achieved using the Gaussian process (GP) model (78.8%) over the SVM classifier (75.6%) for CN vs. EMCI classification, with 0.05 being the cutoff for significance, and based on student’s t-test, it was determined that the differences for accuracy, sensitivity, specificity between the GP method and support vector machine (SVM) are not statistically significant. ConclusionAddressing the challenging classification of CN vs. EMCI provides useful information to help clinicians and researchers determine essential measures that can help in the early detection of AD.

Functional Network Alterations in Patients With Amnestic Mild Cognitive Impairment Characterized Using Functional Near-Infrared Spectroscopy.

Amnestic mild cognitive impairment (aMCI) is conceptualized as a cognitive disorder characterized by memory deficits. Patients with aMCI are treated as prodromal stage of Alzheimer's disease (AD) and have an increased likelihood of developing into AD. The investigation of aMCI is therefore fundamental to the early detection and intervention of AD. Growing evidence has shown that functional network alterations induced by cognition impairment can be captured by advanced neuroimaging techniques. In this study, functional near-infrared spectroscopy (fNIRS), an affordable, robust and portable neuroimaging modality, was employed to characterize the functional network in aMCI patients. FNIRS data were collected from 16 healthy controls and 16 aMCI patients using a digits verbal span task. Functional networks were constructed from temporal hemodynamic response signals. Graph-based indices were then calculated from the constructed brain networks to assess global and regional differences between the groups. Results suggested that brain networks in aMCI patients were characterized with higher integration as well as higher segregation compared to healthy controls. In addition, major regions of interest (ROIs) within frontal, temporal, precentral and parietal areas were identified to be associated with cognition impairment. Our findings validate the feasibility of utilizing fNIRS as a portable and reliable tool for the investigation of abnormal network alterations in patients with cognition decline.

Plasma A\u03b242/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study

BackgroundTo facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer’s disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers.MethodsWe included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification.ResultsEighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779–0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden’s cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913–0.100).ConclusionsPlasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer’s disease.

A Multicenter Study on the Diagnosis and Intervention of New Biomarkers on the Prodromal Stage of Alzheimer's Disease

A Multicenter Study on the Diagnosis and Intervention of New Biomarkers on the Prodromal Stage of Alzheimer's Disease

Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION): study design, cohort description, and preliminary data

ABSTRACTObjectives: Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION) is a longitudinal ongoing study initiated in 2018 that takes place in the Cognitive Disorders Clinic of Aiginition Hospital of the National and Kapodistrian University of Athens. Its aim is to address several research questions concerning the preclinical and prodromal stage of Alzheimer’s disease and explore potential markers for early detection, prediction, and primary prevention of dementia.Methods: We here present the design and the preliminary baseline characteristics of ALBION. The sample of our study consists of people aged over 50 who are concerned about their memory but are cognitively normal (CN) or have mild cognitive deficits. Each participant undergoes an extensive assessment including several demographic, medical, social, environmental, clinical, nutritional, neuropsychological determinants and lifestyle activities. Furthermore, we are collecting data from portable devices, neuroimaging techniques and biological samples (blood, stools, CSF). All participants are assessed annually for a period of 10 years.Results: In total, 47 participants have completed the initial evaluation up to date and are divided in two groups, CN individuals (N = 26) and MCI patients (N = 21), based on their cognitive status. The participants are, on average, 64 years old, 46.3% of the sample is male with an average of 12.73 years of education. MCI patients report more comorbidities and have a lower score in the MMSE test. Regarding APOE status, 2 participants are ε4 homozygotes and 10 ε4 heterozygotes. CSF analyses (Aβ42, Τ-tau, P-tau) revealed no differences between the two groups.Conclusion: The ALBION study offers an opportunity to explore preclinical dementia and identify new and tailored markers, particularly relating to lifestyle. Further investigation of these populations may provide a wider profile of the changes taking place in the preclinical phase of dementia, leading to potentially effective therapeutic and preventive strategies.

Verubecestat fails to slow progression of disease in prodromal Alzheimer's

Verubecestat reduces amyloid‐beta levels in the brain in healthy individuals and in patients with Alzheimer's disease, but a placebo‐controlled trial has found that the drug did not slow progression of dementia in patients who were at a prodromal stage of Alzheimer's disease. The research team terminated the trial for futility after finding more adverse outcomes in the medication group than in the placebo group. Study results were published April 11 in The New England Journal of Medicine.

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

BackgroundAlthough amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer’s disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory.MethodsWe retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB.ResultsTrajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group.ConclusionsOur data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis.

Financial Management Skills in Aging, MCI and Dementia: Cross Sectional Relationship to 18F-Florbetapir PET Cortical β-amyloid Deposition.

There is a need to more fully characterize financial capacity losses in the preclinical and prodromal stages of Alzheimer's disease (AD) and their pathological substrates. To test the association between financial skills and cortical β-amyloid deposition in aging and subjects at risk for AD. Cross-sectional analyses of data from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3) study conducted across 50 plus sites in the US and Canada. Multicenter biomarker study. 243 subjects (144 cognitively normal, 79 mild cognitive impairment [MCI], 20 mild AD). 18F-Florbetapir brain PET scans to measure global cortical β-amyloid deposition (SUVr) and the Financial Capacity Instrument Short Form (FCI-SF) to evaluate an individual's financial skills in monetary calculation, financial concepts, checkbook/register usage, and bank statement usage. There are five sub scores and a total score (range of 0-74) with higher scores indicating better financial skill. FCI-SF total score was significantly worse in MCI [Cohen's d= 0.9 (95%CI: 0.6-1.2)] and AD subjects [Cohen's d=3.1(CI: 2.5-3.7)] compared to normals. Domain scores and completion times also showed significant difference. Across all subjects, higher cortical β-amyloid SUVr was significantly associated with worse FCI-SF total score after co-varying for age, education, and cognitive score [Cohen's f2=0.751(CI: 0.5-1.1)]. In cognitively normal subjects, after covarying for age, gender, and education, higher β -amyloid PET SUVr was associated with longer task completion time [Cohen's f2=0.198(CI: 0.06-0.37)]. Using a multicenter study sample, we document that financial capacity is impaired in the prodromal and mild stages of AD and that such impairments are, in part, associated with the extent of cortical β-amyloid deposition. In normal aging, β-amyloid deposition is associated with slowing of financial tasks. These data confirm and extend prior research highlighting the utility of financial capacity assessments in at risk samples.

NGF-Dependent Changes in Ubiquitin Homeostasis Trigger Early Cholinergic Degeneration in Cellular and Animal AD-Model.

Basal forebrain cholinergic neurons (BFCNs) depend on nerve growth factor (NGF) for their survival/differentiation and innervate cortical and hippocampal regions involved in memory/learning processes. Cholinergic hypofunction and/or degeneration early occurs at prodromal stages of Alzheimer’s disease (AD) neuropathology in correlation with synaptic damages, cognitive decline and behavioral disability. Alteration(s) in ubiquitin-proteasome system (UPS) is also a pivotal AD hallmark but whether it plays a causative, or only a secondary role, in early synaptic failure associated with disease onset remains unclear. We previously reported that impairment of NGF/TrkA signaling pathway in cholinergic-enriched septo-hippocampal primary neurons triggers “dying-back” degenerative processes which occur prior to cell death in concomitance with loss of specific vesicle trafficking proteins, including synapsin I, SNAP-25 and α-synuclein, and with deficit in presynaptic excitatory neurotransmission. Here, we show that in this in vitro neuronal model: (i) UPS stimulation early occurs following neurotrophin starvation (-1 h up to -6 h); (ii) NGF controls the steady-state levels of these three presynaptic proteins by acting on coordinate mechanism(s) of dynamic ubiquitin-C-terminal hydrolase 1 (UCHL-1)-dependent (mono)ubiquitin turnover and UPS-mediated protein degradation. Importantly, changes in miniature excitatory post-synaptic currents (mEPSCs) frequency detected in -6 h NGF-deprived primary neurons are strongly reverted by acute inhibition of UPS and UCHL-1, indicating that NGF tightly controls in vitro the presynaptic efficacy via ubiquitination-mediated pathway(s). Finally, changes in synaptic ubiquitin and selective reduction of presynaptic markers are also found in vivo in cholinergic nerve terminals from hippocampi of transgenic Tg2576 AD mice, even from presymptomatic stages of neuropathology (1-month-old). By demonstrating a crucial role of UPS in the dysregulation of NGF/TrkA signaling on properties of cholinergic synapses, these findings from two well-established cellular and animal AD models provide novel therapeutic targets to contrast early cognitive and synaptic dysfunction associated to selective degeneration of BFCNs occurring in incipient early/middle-stage of disease.

Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by β-Amyloid Positivity.

The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS). Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [18F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images. One hundred sixteen participants (Aβ- cognitively normal [CN], n = 35; Aβ- aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ- aMCI showed somewhat uniform disruption when compared to CN. Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.

Task-enhanced arterial spin labeled perfusion MRI predicts longitudinal neurodegeneration in mild cognitive impairment.

Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease (AD), but is also recognized to be a heterogeneous condition. Biomarkers that predict AD progression in MCI are of clinical significance because they can be used to better identify appropriate candidates for therapeutic intervention studies. It has been hypothesized that comparing to structural measurements, functional ones may be more sensitive to early disease abnormalities and the sensitivity could be further enhanced when combined with cognitive task, a "brain stress test." In this study, we investigated the value of regional cerebral blood flow (CBF), measured by arterial spin labeled perfusion MRI (ASL MRI) during a memory-encoding task, in predicting the estimated rate of hippocampal atrophy, an established marker of AD progression. Thirty-one amnestic MCI patients (20 male and 11 female; age: 70.9 ± 6.5 years, range from 56 to 83 years; mini mental status examination: 27.8 ± 1.8) and 42 normal control subjects (13 male and 29 female; age: 70.6 ± 8.8 years, range from 55 to 88 years; mini mental status examination: 29.1 ± 1.2) were included in this study. We compared the predictive value of CBF during task to CBF during rest and structural volumetry. Both region-of-interest and voxelwise analyses showed that baseline CBF measurements during task (strongest effect in fusiform gyrus, region-of-interest analysis statistics: r = 0.56, p = .003), but not resting ASL MRI or structural volumetry, were correlated with the estimated rate of hippocampal atrophy in amnestic MCI patients. Further, stepwise linear regression demonstrated that resting ASL MRI and volumetry did not provide complementary information in prediction. These results support the notion that physiologic measures during a cognitive challenge may increase the ability to detect subtle functional changes that predict progression. As such, ASL MRI could have important utility in stratifying candidates for AD treatment trials.

Convolutional Neural Networks-Based MRI Image Analysis for the Alzheimer's Disease Prediction From Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the prodromal stage of Alzheimer’s disease (AD). Identifying MCI subjects who are at high risk of converting to AD is crucial for effective treatments. In this study, a deep learning approach based on convolutional neural networks (CNN), is designed to accurately predict MCI-to-AD conversion with magnetic resonance imaging (MRI) data. First, MRI images are prepared with age-correction and other processing. Second, local patches, which are assembled into 2.5 dimensions, are extracted from these images. Then, the patches from AD and normal controls (NC) are used to train a CNN to identify deep learning features of MCI subjects. After that, structural brain image features are mined with FreeSurfer to assist CNN. Finally, both types of features are fed into an extreme learning machine classifier to predict the AD conversion. The proposed approach is validated on the standardized MRI datasets from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. This approach achieves an accuracy of 79.9% and an area under the receiver operating characteristic curve (AUC) of 86.1% in leave-one-out cross validations. Compared with other state-of-the-art methods, the proposed one outperforms others with higher accuracy and AUC, while keeping a good balance between the sensitivity and specificity. Results demonstrate great potentials of the proposed CNN-based approach for the prediction of MCI-to-AD conversion with solely MRI data. Age correction and assisted structural brain image features can boost the prediction performance of CNN.

Serum ischaemia-modified albumin might be a potential biomarker for oxidative stress in amnestic mild cognitive impairment.

Amnestic mild cognitive impairment (aMCI) is considered to be a prodromal stage of Alzheimer's disease. The clinical role of ischaemia-modified albumin (IMA) and the association between IMA and oxidative stress in aMCI have not been investigated. The aim of the study was to explore this relationship and to generate new ideas for controlling Alzheimer's disease. This community-based case-control study included 113 patients with aMCI and 832 cognitively normal controls. Serum levels of albumin and IMA, diacron-reactive oxygen metabolite, and biological anti-oxidant potential, were measured. The IMA/albumin ratio and the biological anti-oxidant potential/diacron-reactive oxygen metabolite ratio were calculated. In univariate analysis, the serum IMA level and the IMA/albumin ratio were higher in the aMCI patients than in the controls (P < 0.001, P < 0.001, respectively). In multivariate analysis, a serum IMA level ≥476.4 ng/mL and an IMA/albumin ratio ≥9.4 were separately associated with the development of aMCI (odds ratio = 3.56, 95% confidence interval: 2.33-5.46; odds ratio = 3.43, 95% confidence interval: 2.25-5.27, respectively). There was a linear correlation between serum IMA level and several oxidative stress markers (biological anti-oxidant potential/diacron-reactive oxygen metabolite ratio: r = -0.585, P < 0.001; diacron-reactive oxygen metabolite: r = 0.549, P < 0.001; biological anti-oxidant potential: r = -0.293, P < 0.001). Serum IMA might be a potential biomarker for oxidative stress in aMCI.

Somatostatin and Neuropeptide Y in Cerebrospinal Fluid: Correlations With Amyloid Peptides Aβ1-42 and Tau Proteins in Elderly Patients With Mild Cognitive Impairment.

A combination of low cerebrospinal fluid (CSF) Amyloid β1–42 (Aβ1–42) and high Total-Tau (T-Tau) and Phosphorylated-Tau (P-Tau) occurs at a prodromal stage of Alzheimer’s disease (AD) and recent findings suggest that network abnormalities and interneurons dysfunction contribute to cognitive deficits. Somatostatin (SOM) and Neuropeptide Y (NPY) are two neuropeptides which are expressed in GABAergic interneurons with different fates in AD the former only being markedly affected. The aim of this study was to analyze CSF SOM, NPY and CSF Aβ1–42; T-Tau, P-Tau relationships in 43 elderly mild cognitively impairment (MCI) participants from the Biomarker of AmyLoïd pepTide and AlZheimer’s disease Risk (BALTAZAR) cohort. In these samples, CSF SOM and CSF Aβ1–42 on the one hand, and CSF NPY and CSF T-Tau and P-Tau on the other hand are positively correlated. CSF SOM and NPY concentrations should be further investigated to determine if they can stand for early AD biomarkers.Clinical Trial Registration: www.ClinicalTrials.gov, identifier #NCT01315639.

Up-regulation of DMN Connectivity in Mild Cognitive Impairment Via Network-based Cognitive Training.

Background: Previous work designed a network-based protocol of cognitive training. This programme exploits a mechanism of induced task-oriented co-activation of multiple regions that are part of the default mode network (DMN), to induce functional rewiring and increased functional connectivity within this network.Objective: In this study, the programme was administered to patients with a diagnosis of mild cognitive impairment to test its effects in a clinical sample.Method: Twenty-three patients with mild cognitive impairment (mean age: 73.74 years, standard deviation 5.13, female/male ratio 13/10) allocated to the experimental condition, underwent one month of computerised training, while fourteen patients (mean age: 73.14 years, standard deviation 6.16, female/male ratio 7/7) assigned to the control condition underwent a regime of intense social engagement. Patients were in the prodromal stage of Alzheimer’s disease (AD) as confirmed by clinical follow ups for at least two years. The DMN was computed at baseline and retest, together with other, control patterns of connectivity, grey matter maps and neuropsychological profiles.Results: A condition-by-timepoint interaction indicating increased connectivity triggered by the programme was found in left parietal DMN regions. No decreases as well as no changes in the other networks or morphology were found. Although between-condition cognitive changes did not reach statistical significance, they correlated positively with changes in DMN connectivity in the left parietal region, supporting the hypothesis that parietal changes were beneficial.Conclusion: This programme of cognitive training up-regulates a pattern of connectivity which is pathologically down-regulated in AD. We argue that, when cognitive interventions are conceptualised as tools to induce co-activation repeatedly, they can lead to clinically relevant improvements in brain functioning, and can be of aid in support of pharmacological and other interventions in the earliest stages of AD.

Tau Depletion in APP Transgenic Mice Attenuates Task-Related Hyperactivation of the Hippocampus and Differentially Influences Locomotor Activity and Spatial Memory.

Hippocampal hyperactivity, ascribed to amyloid β (Aβ)-induced imbalances in neural excitation and inhibition, is found in patients with mild cognitive impairment, a prodromal stage of Alzheimer's disease (AD). To better understand the relationship between hippocampal hyperactivity and the molecular triggers of behavioral impairments in AD, we used Mn-enhanced MRI (MEMRI) to assess neuronal activity after subjecting mice to a task requiring spatial learning and memory. Depletion of endogenous tau in an amyloid precursor protein (APP) transgenic (J20) mouse line was shown to ameliorate hippocampal hyperactivity in J20 animals, tau depletion failed to reverse memory deficits associated with APP/Aβ overproduction. On the other hand, deletion of tau alleviated the hyperlocomotion displayed by APP transgenics, suggesting that the functional effects of Aβ-tau interactions reflect the temporal appearance of these molecules in individual brain areas.