Amnestic Mild Cognitive Impairment Subjects Research Articles

Manual Motor Function as a Classifier for Alzheimer’s Disease

AbstractBackgroundIn contrast to numerous reports of gross motor problems in Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD), fine motor function has been relatively understudied. We examined if performance on manual motor tasks can distinguish between cognitively normal (CN) subjects, and individuals with MCI or AD, and which fine motor features are most informative.Method47 CN, 25 MCI, and 16 AD participants completed computerized tests of unimanual (dominant and non‐dominant hand) tapping, synchronous bimanual tapping, and alternate bimanual tapping. Outcome measures included initial reaction time, tapping speed, and variance. We used imbalanced random forest learning for classification modeling. The model was trained on 70% of the data and tested on the remaining 30% using 5‐fold cross‐validation. To investigate the contribution of individual variables to the classification model, we conducted permutation feature importance analysis.ResultThe overall classification accuracy of the training data was 56%, while the overall classification accuracy of the test data was 70%. The group‐specific accuracy, defined as the proportion of subjects predicted to belong to a certain group who are truly a member of that group, was 76% for CN, 33% of amnestic MCI, and 86% for AD. In 50% of the cases amnestic MCI subjects were classified as control subjects, and in 17% of the cases as AD subjects. The group‐specific precision, defined as the proportion of subjects who received a certain group label who truly belonged to that group (i.e., ‘true positives’) was 76% for controls, 100% for amnestic MCI, and 45% for AD. The three most important features that were used for classification of the test hold‐out data were 1) variance in tapping speed during dominant hand finger tapping; 2) the number of dual tapping trials without gaps or onset delays; and 3) initial reaction time for non‐dominant hand finger tapping.ConclusionSupervised machine learning can discriminate CN and AD subjects based on finger tapping performance features, but is less effective for distinguishing MCI subjects from CN and AD subjects. Finger tapping performance could be a cost‐effective tool for augmenting existing AD biomarkers.

Objective sleep hypoxia measures are associated with subjective quality of life ratings in amnestic MCI subjects

AbstractBackgroundSleep disturbances are common in individuals with Mild Cognitive Impairment (MCI); and sleep disturbances increase the risk of Alzheimer’s disease (AD). Lower ratings of quality of life (QoL) are also found in MCI. We examined the association between sleep disturbances and QoL ratings among participants with MCI.MethodsBaseline in‐home sleep assessments using the WatchPAT (Itamar Medical) and the QoL in AD questionnaire were collected from amnestic MCI (aMCI) participants from the diet intervention trial, Brain Energy for Amyloid Transformation in Alzheimer’s Disease (BEAT‐AD) at the Wake Forest ADRC. The WatchPAT assessed sleep time, efficiency, and sleep‐related hypoxemia measures including the apnea‐hypopnea index (AHI), oxygen desaturation index (ODI) and respiratory disturbance index (RDI), where higher values indicate greater disturbances in sleep. The QoL in AD scale ranged from 13–52 with lower scores indicating poorer QoL ratings. We assessed the association between total sleep time and sleep efficiency with QoL. Pearson correlations and regression models measured the association of sleep metrics with QoL scores.ResultsForty‐two aMCI participants (mean age =69.0 ± 7.4 years; N=23 female; mean BMI =27.6) were studied. Disturbed sleep indicated by the average number of apneas and hypopneas (AHI, mean = 18.6 ± 14.6) and respiratory events or related arousals (RDI, mean = 20.7 ± 14.2) was negatively associated with lower subjective measures of QoL. Higher AHI and RDI scores, indicating greater intermittent hypoxia and respiratory burden, were associated with lower QoL (AHI: r= ‐0.359, p=0.027; RDI: r= ‐0.340, p=0.037). There was a trend toward a negative association of ODI and QoL scores (r= ‐0.309, p=0.059). Regression models including age, sex, and BMI did not significantly predict QoL scores with AHI (F(4,35)=1.95, p>.1) or RDI (F(4,34)=1.76, p>.15), however, AHI and RDI individually added significantly to the prediction of QoL scores (AHI: B=‐.136, t=‐2.4,P<.05; RDI: B=‐.162, t=‐2.4, p<.05).ConclusionsGreater sleep disturbances related to hypoxic and respiratory events were associated with lower self‐ratings of QoL in MCI participants. Further research will increase the sample, investigate the impact of hypoxic and respiratory events on brain function, and whether longitudinal changes in diet influence the relationship of sleep‐related hypoxemia and QoL.

Attentional network changes in subjective cognitive decline.

Subjective cognitive decline (SCD) is known as the intermediate stage between normal cognitive aging and mild cognitive impairment (MCI). Although elderly with SCD usually perform close to normal in standardized tests, the detailed function of attention networks in this group has not been studied yet. The purpose of this study was to investigate the performance of attention networks, as a possible indicator of cognitive disorder, in older individuals with subjective memory complaint and MCI. The attention network test (ANT) was used to examine and compare the performance of three attention networks of alerting, orientation, and executive control in 17 elderly with SCD, 30 multiple domain amnestic MCI subjects, and 15 healthy controls. Although the orienting network had almost the same performance in all groups (p = 0.25), the performance of alerting (p = 0.01) and executive control networks (p = 0.02) were significantly different among the three groups: the SCD group performed poorly in both networks compared with the controls and did not differ significantly from the MCI group (p ≥ 0.05). However, controlling for general age-related slowing abolished the group difference in executive control index. More importantly, our results showed that alerting network that was affected in SCD group had high sensitivity in differentiating this group from controls (0.94%). Our data suggest that despite normal performance in neuropsychological tests, the SCD elderly may face significant degrees of attention processing problems, especially in maintaining alerting to external stimuli which might be helpful in diagnosing individuals at risk and designing proper attention-based interventions.

Regional cerebral perfusion in patients with amnestic mild cognitive impairment: effect of cerebral small vessel disease.

To explore the effort of cerebral small vessel disease (CSVD) on regional cerebral perfusion in patients with mild cognitive impairment (MCI) using NeuroGam™ software and evaluate the capability of brain perfusion single photon emission computed tomography (SPECT) in distinguishing MCI with and without CSVD. 34 amnestic MCI subjects entered this study, conducting neuropsychological tests, MRI and 99mTechnetium ethyl cystine dimer brain perfusion SPECT imaging. All subjects were divided into those with CSVD and those without CSVD. Perfusion value was measured with Brodmann area (BA) mapping in these two groups. Automated software (NeuroGam™) was used for semi-quantitative analyses of perfusion value and comparison with normal database. Compared with normal database, perfusion levels in BAs 23-left, 28 and 36-left of MCI without CSVD group had great deviations, while perfusion levels in BAs 21, 23, 24, 25, 28, 36, 38 and 47-left of MCI with CSVD group had great deviations. Furthermore, compared with CSVD group, there was significantly lower perfusion value in BA 7-left (P < 0.001) in MCI without CSVD group. CSVD could interact with pathological changes related to AD, exacerbating hypoperfusion in BAs 21, 23, 28, 36, 38 while compensating for cerebral blood perfusion disorder in BA 7-left in MCI patients. Meanwhile, MCI patients with CSVD shared similar hypoperfusion with vascular cognitive impairment (VCI) in BAs 24, 25 and 47L. Brain perfusion SPECT may help improve our ability to differentiate MCI with and without CSVD.

Executive function deficits in mild cognitive impairment: evidence from saccade tasks

Objectives: Early detection of mild cognitive impairment (MCI) is necessary to prevent irreversible brain damage caused by incipient Alzheimer’s disease. It has been showing that amnestic MCI (a-MCI) subjects exhibit subtle deficits in executive function that can be tested using saccade eye movements. Eye-tracking technology is a sensitive method to measure cognitive impairments in dementia and MCI. Methods In this study, we used eye-tracking technology to explore saccade impairments to distinguish between a-MCI and the variants of reference controls. 21 patients with AD, 40 patients with a-MCI, and 59 normal participants were recruited in current study. We measured saccade reaction time, saccade errors, saccade omission, and uncorrected saccades using anti-saccade and pro-saccade tasks with ‘gap’ and ‘overlap’ procedures. These parameters were used as markers of executive function and visual attention deficits.Results: The findings revealed that more errors, more omissions, and fewer corrections characterized the saccade behavior of the a-MCI group compared to the reference group. These eye-tracking characteristics can be considered as inhibitory control and working memory deficits in a-MCI subjects. Our results thus demonstrate the applicability of the anti-saccade task as a cognitive marker in a-MCI. Conclusion The work provides further support for eye-tracking as a useful diagnostic biomarker in the assessment of executive function in aging with cognitive impairments.

Association of Cerebrospinal Fluid Adiponectin Levels With Cerebral Glucose Metabolism In Mild Cognitive Impairment: A Pilot Study.

Adiponectin has been implicated in the pathophysiology of dementia, especially Alzheimer's disease. However, the association between cerebrospinal fluid (CSF) adiponectin levels and positron emission tomography (PET) imaging remains unclear. To explore whether CSF adiponectin levels are associated with 11C-Pittsburgh compound B (PiB) or 18F-fluorodeoxyglucose (FDG) uptake in amnestic mild cognitive impairment (MCI) subjects. Thirty-four amnestic MCI subjects underwent PiB-PET, FDG-PET, and CSF analysis. The CSF adiponectin levels were measured using the Bio-Plex 200 suspension array system. PET uptake was assessed for the frontal and temporoparietal lobes and posterior cingulate gyrus, referenced against the cerebellar cortex. The increased brain amyloid burden was defined as a mean uptake value ratio greater than 1.4. Spearman's rank correlation analysis and a multiple regression model were used to examine the association between CSF adiponectin levels and PiB or FDG uptake. The mean age was 76.3 years; 38.2% were men, and 61.8% were women. A high amyloid burden was identified in 18 (52.9%) subjects. CSF adiponectin levels positively correlated with global FDG uptake (β = 0.45; 95% confidence interval (CI), 0.13 to 0.76, p < 0.01), especially in the parietotemporal lobe and posterior cingulate gyrus (β = 0.70; 95% CI, 0.41 to 0.99, p<0.01, β = 0.33; 95% CI, 0.03 to 0.63, p = 0.03, respectively) after adjusting for covariates, including age, sex, education years, body mass index, vascular risk factors, ApoEε4 status, and PiB status in all amnestic MCI subjects. CSF adiponectin levels were associated with cortical glucose metabolism, particularly in the specific regions that connect with the medial temporal, but not brain amyloid burden in amnestic MCI subjects.

Predictors of rate of cognitive decline in patients with amnestic mild cognitive impairment

Objective Amnestic mild cognitive impairment (MCI) is a known risk factor for conversion to Alzheimer’s disease (AD). Although substantial research has been conducted on the general profile of amnestic MCI subjects and predictors of conversion to AD, research on predictors of rate of decline has been considerably less extensive. The present study sought to more systematically and comprehensively examine predictors of rate of cognitive decline in a longitudinal sample of individuals with MCI, including age, genetic vulnerability, baseline cognitive performance, and baseline neuropsychiatric severity. Method Participants with single or multi-domain amnestic MCI (N = 151) were assessed at baseline and for a mean of 1.32 follow-up visits (mean interval from baseline to last follow-up = 1.61 years). Results Results showed that carriers of the ApoE ε4 allele declined more quickly on all three dementia severity measures compared to non-carriers. Older individuals did not decline more rapidly in dementia severity. Participants with lower executive functions composite scores and greater memory impairment severity at baseline predicted faster decline on dementia severity measures. Contrary to hypotheses, those with lower levels of depression at baseline declined more rapidly on dementia severity measures compared to those with higher levels of depression. Conclusion Identifying potential predictors of rate of decline from amnestic MCI to AD could be clinically meaningful for prognostic purposes, understanding risk and protective factors, as well as guiding future treatments and clinical trials that could aim to target and delay progression among those patients who are vulnerable to more quickly convert to AD.

A longitudinal study of polysomnographic variables in patients with mild cognitive impairment converting to Alzheimer's disease.

The main condition at increased risk of dementia is considered to be mild cognitive impairment. Mild cognitive impairment has been defined as a transitional state between normal aging and dementia, of which it may represent a prodrome. The aim of our study was to evaluate whether sleep variables (both conventional and microstructural ones) in subjects with mild cognitive impairment correlate with conversion to dementia. Nineteen subjects with amnestic mild cognitive impairment (mean age 68.5 ± 7.0 years) and 11 cognitively intact healthy elderly individuals (mean age 69.2 ± 12.6 years) underwent ambulatory polysomnography for the evaluation of nocturnal sleep architecture and cyclic alternating pattern parameters. Amnestic mild cognitive impairment subjects were clinically and cognitively re-evaluated after 2 years, during routine follow-up, and further classified as amnestic mild cognitive impairment converters (that is, patients developing Alzheimer's disease, N = 11) and amnestic mild cognitive impairment non-converters. Compared with healthy elderly individuals, amnestic mild cognitive impairment showed disrupted sleep with decreased rapid eye movement sleep, cyclic alternating pattern rate and cyclic alternating pattern slow-wave-related phases (A1 index). Standard sleep architecture analysis did not show significant differences between the two subgroups of amnestic mild cognitive impairment, whereas cyclic alternating pattern analysis showed that cyclic alternating pattern rate, A1 index and A3 index are significantly reduced in converters compared with non-converters. Our data confirm that in amnestic mild cognitive impairment subjects there is a sleep impairment, particularly when considering more refined sleep parameters and that sleep variables at baseline are different among converters versus non-converters at the 2-year follow-up. Specific sleep alterations might represent potential further biomarkers for the diagnosis and prognosis of early-phase cognitive impairment.

Behavioral and cognitive markers of mild cognitive impairment: diagnostic value of saccadic eye movements and Simon task.

Mild Cognitive Impairment (MCI) has been considered as a prodromal stage of Alzheimer disease (AD). Subtle changes in specific aspects of executive function like inhibitory control have been found in MCI. We examined attentional and inhibitory control with the aim to distinguish between amnestic MCI patients and healthy controls. Using neuropsychological, behavioral, and oculomotor function experiments, we examined executive function in 59 normal control, 49, multiple domain amnestic MCI (a-MCI) subjects, and 21 early stage AD patients using eye tracking and Simon task as measures of attentional control, to determine which saccade and behavioral tasks were sensitive enough to identify a-MCI. Saccades were investigated in gap and overlap pro-saccade and anti-saccade tasks. Scores on the Simon task were inversely correlated with general cognitive status and can distinguish a-MCI from controls with excellent specificity (AUC = 0.65 for reaction time and 0.59 for false responses). More importantly, our results showed that saccadic gains were affected in a-MCI and were the most sensitive measures to distinguish a-MCI from normal participants AST gap task AUC = 0.7, PST gap task AUC = 0.63, AST overlap task (AUC = 0.73). Moreover, these parameters were strongly correlated with neuropsychological measures. Using tests in parallel model, improved sensitivity up to 0.97. The present results enable us to suggest eye tracking along with behavioral data as a possible sensitive tools to detect a-MCI in preclinical stage.

ACCOUNTING FOR GENETIC CONTEXT: INCORPORATING INTERACTIONS BETWEEN POLYGENIC RISK SCORES FOR ALZHEIMER’S AND ASSOCIATED RISK FACTORS AND THEIR RELATION TO MILD COGNITIVE IMPAIRMENT

Alzheimer's disease (AD) is under considerable genetic influence. Despite widespread interest in AD risk genes, little attention has been paid to the interactive effects of different risk genes. Polygenic risk scores (PRSs) represent a useful approach to summarize multiple small genetic effects across the genome. We previously showed that higher AD-PRSs were associated with significantly increased odds of having mild cognitive impairment (MCI) in adults who were only in their 50s (Logue et al., Mol Psychiatry, in press). Risk factors for AD such as cardiovascular disease and obesity are also under genetic influence, yet it is unknown how genetic risk for these conditions interacts with genetic risk for AD. We included 1118 cognitively normal participants, 89 amnestic MCI, and 46 non-amnestic MCI — determined by extensive neuropsychological testing in the Vietnam Era Twin Study of Aging (VETSA). Mean age=56.75 years; range=51-67. An AD-PRS was developed from the International Genomics of Alzheimer's Project database. PRSs for coronary artery disease (CAD) and BMI—known AD risk factors—were calculated for all subjects. We tested main and interaction effects of the AD-PRS and these risk factor PRSs in both MCI groups. There was a significant main effect of the AD-PRS in both MCI groups. There was an interaction between the AD-PRS and CAD-PRS in amnestic MCI subjects (p<0.05), and between the AD-PRS and BMI-PRS in non-amnestic MCI subjects (p=0.055). In both cases, the association between the AD-PRS and MCI was attenuated as scores on the risk factor PRS increased. These results indicate the importance of considering broader genetic context when examining risk for MCI or AD. When genetic risk for conditions that contribute to AD is low, an AD-PRS may be more predictive of MCI status. However, an AD-PRS may be less predictive in individuals at high risk for other conditions. These findings suggest that incorporating PRSs for other AD risk factors and their interactions may better characterize variability in the genetic etiology of AD. Further work is necessary to determine whether such interactions can identify individuals whose impairment is due to AD versus other conditions.

Brain Imaging of Alzheimer Dementia Patients and Elderly Controls with 18F-MK-6240, a PET Tracer Targeting Neurofibrillary Tangles.

18F-MK-6240 (18F-labeled 6-(fluoro)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine) is a highly selective, subnanomolar-affinity PET tracer for imaging neurofibrillary tangles (NFTs). Plasma kinetics, brain uptake, and preliminary quantitative analysis of 18F-MK-6240 in healthy elderly (HE) subjects, subjects with clinically probable Alzheimer disease (AD), and subjects with amnestic mild cognitive impairment were characterized in a study that is, to our knowledge, the first to be performed on humans. Methods: Dynamic PET scans of up to 150 min were performed on 4 cognitively normal HE subjects, 4 AD subjects, and 2 amnestic mild cognitive impairment subjects after a bolus injection of 152-169 MBq of 18F-MK-6240 to evaluate tracer kinetics and distribution in brain. Regional SUV ratio (SUVR) and distribution volume ratio were determined using the cerebellar cortex as a reference region. Total distribution volume was assessed by compartmental modeling using radiometabolite-corrected input function in a subgroup of 6 subjects. Results:18F-MK-6240 had rapid brain uptake with a peak SUV of 3-5, followed by a uniformly quick washout from all brain regions in HE subjects; slower clearance was observed in regions commonly associated with NFT deposition in AD subjects. In AD subjects, SUVR between 60 and 90 min after injection was high (approximately 2-4) in regions associated with NFT deposition, whereas in HE subjects, SUVR was approximately 1 across all brain regions, suggesting high tracer selectivity for binding NFTs in vivo. 18F-MK-6240 total distribution volume was approximately 2- to 3-fold higher in neocortical and medial temporal brain regions of AD subjects than in HE subjects and stabilized by 60 min in both groups. Distribution volume ratio estimated by the Logan reference tissue model or compartmental modeling correlated well (R2 > 0.9) to SUVR from 60 to 90 min for AD subjects. Conclusion:18F-MK-6240 exhibited favorable kinetics and high binding levels to brain regions with a plausible pattern for NFT deposition in AD subjects. In comparison, negligible tracer binding was observed in HE subjects. This pilot study suggests that simplified ratio methods such as SUVR can be used to quantify NFT binding. These results support further clinical development of 18F-MK-6240 for potential application in longitudinal studies.

Amnestic mild cognitive impairment individuals with dissimilar pathologic origins show common regional vulnerability in the default mode network

IntroductionAlzheimer's and Parkinson's disease (AD and PD) are distinct disorders but share similar biomarker profiles. The regions of the default mode network are implicated in these diseases and are associated with amnestic symptoms. The role of apolipoprotein-ε4 (APOE-ε4), which is associated with cognitive function, is unclear in PD. MethodsIn this work, we evaluated cortical thickness of default mode network regions that are likely affected in both early AD and PD individuals, that is, with amnestic mild cognitive impairment. We identified the prevalence of APOE-ε4 and evaluated its association with cortical atrophy. ResultsWe observed significant parahippocampal atrophy and hippocampal atrophy rates in amnestic mild cognitive impairment subjects, regardless of disease origins (AD or PD). Similarly, mild cognitive impairment ε4 carriers showed significant precuneal atrophy compared with noncarriers. DiscussionThis work supports that converging changes to default mode network regions, especially the temporal lobe and precuneus, are shared in AD and PD.

A Permutation Disalignment Index-Based Complex Network Approach to Evaluate Longitudinal Changes in Brain-Electrical Connectivity

In the study of neurological disorders, Electroencephalographic (EEG) signal processing can provide valuable information because abnormalities in the interaction between neuron circuits may reflect on macroscopic abnormalities in the electrical potentials that can be detected on the scalp. A Mild Cognitive Impairment (MCI) condition, when caused by a disorder degenerating into dementia, affects the brain connectivity. Motivated by the promising results achieved through the recently developed descriptor of coupling strength between EEG signals, the Permutation Disalignment Index (PDI), the present paper introduces a novel PDI-based complex network model to evaluate the longitudinal variations in brain-electrical connectivity. A group of 33 amnestic MCI subjects was enrolled and followed-up with over four months. The results were compared to MoCA (Montreal Cognitive Assessment) tests, which scores the cognitive abilities of the patient. A significant negative correlation could be observed between MoCA variation and the characteristic path length ( λ ) variation ( r = - 0 . 56 , p = 0 . 0006 ), whereas a significant positive correlation could be observed between MoCA variation and the variation of clustering coefficient (CC, r = 0 . 58 , p = 0 . 0004 ), global efficiency (GE, r = 0 . 57 , p = 0 . 0005 ) and small worldness (SW, r = 0 . 57 , p = 0 . 0005 ). Cognitive decline thus seems to reflect an underlying cortical “disconnection” phenomenon: worsened subjects indeed showed an increased λ and decreased CC, GE and SW. The PDI-based connectivity model, proposed in the present work, could be a novel tool for the objective quantification of longitudinal brain-electrical connectivity changes in MCI subjects.

Differential Phenotypes of Myeloid-Derived Suppressor and T Regulatory Cells and Cytokine Levels in Amnestic Mild Cognitive Impairment Subjects Compared to Mild Alzheimer Diseased Patients.

Alzheimer disease (AD) is the most prevalent form of dementia although the underlying cause(s) remains unknown at this time. However, neuroinflammation is believed to play an important role and suspected contributing immune parameters can be revealed in studies comparing patients at the stage of amnestic mild cognitive impairment (aMCI) to healthy age-matched individuals. A network of immune regulatory cells including regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) maintains immune homeostasis but there are very few data on the role of these cells in AD. Here, we investigated the presence of these cells in the blood of subjects with aMCI and mild AD (mAD) in comparison with healthy age-matched controls. We also quantitated several pro- and anti-inflammatory cytokines in sera which can influence the development and activation of these cells. We found significantly higher levels of MDSCs and Tregs in aMCI but not in mAD patients, as well as higher serum IL-1β levels. Stratifying the subjects based on CMV serostatus that is known to influence multiple immune parameters showed an absence of differences between aMCI subjects compared to mAD patients and healthy controls. We suggest that the increase in MDSCs and Tregs number in aMCI subjects may have a beneficial role in modulating inflammatory processes. However, this protective mechanism may have failed in mAD patients, allowing progression of the disease. This working hypothesis obviously requires testing in future studies.

The evaluation of brain perfusion SPECT using an easy Z-score imaging system in the mild cognitive impairment subjects with brain amyloid-β deposition

ObjectiveThe analysis of 99mTc-ECD single-photon emission computed tomography (SPECT) images using the easy Z-score imaging system (eZIS) program is useful for the diagnosis of early AD in daily medical practice. However, it remains unclear whether eZIS analysis can identify the amnestic mild cognitive impairment (MCI) subjects with brain amyloid-β deposition. The aim of this study was to evaluate the usefulness of an eZIS analysis for predicting amnestic MCI subjects with brain amyloid β deposition. Patients and methodsTwenty-three subjects with MCI (10 men and 13 women, mean age; 74.2 years) underwent brain perfusion SPECT and 11C-Pittsburgh Compound B positron emission tomography (PiB-PET). MCI subjects were divided into PiB-positive and PiB-negative subgroups. SPECT data was analyzed using the Specific Volume of interest Analysis of the eZIS program. Three indicators (severity, extent, and ratio) were calculated automatically and compared between the two subgroups. ResultsFive of 12 (41.7%) subjects in the PiB-positive subgroup and three of 11 (27.3%) subjects in the PiB-negative subgroup showed the abnormal value for each indicator. The frequency of subjects with abnormal ratio values was significantly higher in the PiB-positive subgroup compared to the PiB-negative subgroup (p=0.02), whereas that of subjects with abnormal values in severity and extent did not differ among the two subgroups. In particular, all subjects in the PiB-negative subgroup showed normal ratio values. Moreover, the subjects with abnormal values on two indicators, including ratio, or on all three indicators, showed PiB-positive. ConclusionThe analysis of brain perfusion SPECT using an eZIS program cannot identify the amnestic MCI subjects with brain amyloid-β deposition. However, abnormal three indicators or normal ratio values may be helpful SPECT findings for predicting the results of PiB-PET in the amnestic MCI subjects.

ALZHEIMER’S DISEASE PATIENTS WITH HIGHER COGNITIVE RESERVE PRESENT MORE EFFICIENT NETWORK TOPOLOGY

AD is the most common form of dementia worldwide, and yet there is still no means of curing or even preventing the disease. It may be possible, however, to delay the onset of AD by reducing some modifiable factors. In this context, innumerable epidemiological studies report that greater cognitive reserve (CR) may postpone the clinical expression of AD. In the present study we sought to investigate: a) the relationship between education and resting-state fMRI graph metrics in healthy controls, amnestic mild cognitive impairment subjects (aMCI) and mild Alzheimer's disease (AD) patients; b) the relationship between cerebrospinal fluid (CSF) biomarkers’ levels and graph metrics in aMCI and mild AD patients; c) the relationship between CSF biomarkers’ levels and education in aMCI and mild AD patients. 14 mild AD patients, 31 aMCI, and 28 controls were scanned on a 3.0T MR scanner, and CSF samples were obtained from aMCI and AD patients. Education was used as a measure of cognitive reserve. We used the UF2C toolbox to construct functional connectivity matrices based on 70 functional regions. Graph metrics were computed with the GraphVar toolbox, network-based statistics corrected for multiplicity. The relationship between CSF and education was assessed with multiple regression models. Education positively correlated to measures of centrality (betweenness centrality – Bc and eigenvector centrality - v), segregation (clustering coefficient - C), and integration (efficiency - E) in several regions in controls, aMCI and mild AD patients. CSF abnormal levels of proteins (beta amyloid, total-tau and phospho-tau) significantly related to disruption in network topology in aMCI and mild AD patients. No relationship was found between CSF biomarkers and education. Although cognitive reserve may not be protective against the development of AD pathophysiology, it does seem that individuals with higher cognitive reserve present a more efficient network topology. Whereas healthy individuals with more years of education presented increased network efficiency, AD patients more educated might be better able to recruit compensatory mechanisms to maintain cognitive function.

State-based functional connectivity changes associate with cognitive decline in amnestic mild cognitive impairment subjects

Episodic memory (EM) dysfunction is a central characteristic of amnestic mild cognitive impairment (aMCI) subjects, and has a high risk of converting to Alzheimer's disease (AD). However, it is unknown how the EM network is modulated when a situation is switched. Twenty-six aMCI and twenty-two cognitively normal (CN) subjects were enrolled in this study. All of the subjects completed multi-dimensional neuropsychological tests and underwent functional magnetic resonance imaging scans during a resting-state and an episodic memory retrieval task state. The EM network was constructed using a seed-based functional connectivity (FC) approach. AMCI subjects showed poorer cognitive performances in the episodic memory and executive function. We demonstrated that connectivity of the left posterior parahippocampal gyrus (LpPHG) connected to the left ventral medial prefrontal cortex and the right postcentral gyrus (RPCG) was significantly decreased in aMCI subjects compared to CN subjects. Meanwhile, there was increased connectivity of the LpPHG to the right dorsal medial prefrontal cortex (RDMPFC), RPCG, left inferior parietal cortex, and bilateral superior parietal lobe in all of the subjects that changed from a resting-state to a task-state. Interestingly, the changed LpPHG-RDMPFC connectivity strength was significantly correlated with EM scores and executive function in the aMCI subjects. As a result, general brain regions are functionally organized and integrated into the EM network, and this strongly suggests that more cognitive resources are mobilized to meet the challenge of cognitive demand in the task state. These findings extend our understanding of the underlying mechanisms of EM deficits in aMCI subjects.

Copper subtype of Alzheimer's disease (AD): Meta-analyses, genetic studies and predictive value of non-ceruloplasmim copper in mild cognitive impairment conversion to full AD

Alzheimer's disease (AD) is the most common form of dementia. A myriad of complex factors contribute to AD, promoting the deposition in plaques of amyloid-beta (Aβ), which is the main constituent of this pathognomonic sign of AD at autopsy brain inspection. Aβ toxicity is related to oxidative stress, which results in synaptic loss in specific brain areas, eventually leading to cognitive decline. Metal, and especially copper, dyshomeostasis is a key factor in these processes. Recent studies have demonstrated that the serum fraction of copper that is not bound to ceruloplasmin (Non-Cp copper, also known as ‘free’ or labile copper) increases in a percentage of AD patients and mild cognitive impairment (MCI) subjects; this is considered a precursor of AD. Non-Cp copper is the exchangeable fraction of low molecular weight copper in serum. It is distinguished from the copper structurally bound to the ceruloplasmin protein, a master protein of iron metabolism. Non-Cp copper levels are higher than normal reference values (range 0–1.6μmol/L) in about 50% of amnestic MCI subjects and 60% of AD patients, typifying them in a subset of AD. Meta-analyses, genetic studies and a prognostic study evaluating the predictive value of Non-Cp copper in MCI conversion to full AD demonstrate the existence of this copper phenotype of AD.

CEREBRAL MICROBLEEDS ARE ASSOCIATED WITH CEREBRAL BLOOD FLOW AND METABOLISM BUT NOT AMYLOID BURDEN OR BRAIN ATROPHY IN COGNITIVELY NORMAL ELDERLY

in AD, as well as the connectivity of the DMN. In this study, we aimed to analyze the extent in which damage in the DMN white matter influences in cognitive function in MCI and AD patients compared to healthy elderly. Methods:We studied 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls). MRI data were acquired on a 3.0T MRI Philips Achieva scanner. Tensor calculation and tractographywere performed with ExploreDTI software, and axial diffusivity, radial diffusivity, fractional anisotropy, mean diffusivity and streamline count were calculated. Participants also underwent a full range neuropsychological testing. For differences between groups, we performed ANOVA with Tukey posthoc test (adjusting for multiple comparisons). In order to verify if there was any association between cognition and DTI parameters, we performed a multiple stepwise regression, adjusted for multiple comparisons. For streamline count, we used white matter total volume as a covariate.Results: AD patients showed lower values of fractional anisotropy and radial diffusivity in the cingulum (P1⁄4.010 and .012, respectively), and lower radial diffusivity in the parahippocampal bundle (P1⁄4.013) compared to controls. R egression models revealed that cognitive performance is accounted for by 30% of white matter microstructural values, together with years of education. Conclusions: Only AD patients differed from controls in terms of DTI values between DMN nodes. DTI measures have a relative strong predicting power in cognitive performance, together with years of education.

Structural connectivity of the default mode network and cognition in Alzheimer׳s disease

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.