Mild cognitive impairment (MCI) is a syndrome thought to be a prodrome of dementia for some patients. One subtype, amnestic MCI, may be specifically predispose patients to develop Alzheimer’s Dementia (AD). Since dementia has been associated with a range of neuropsychiatric symptoms (NPS), we sought to examine the prevalence of NPS in MCI and its subtypes.
1779 participants in the National Alzheimer Coordinating Center (NACC) with MCI were included in this study. All participants were evaluated systematically with a thorough cognitive battery, clinical interview, and consensus diagnoses, and subtyped as: 1) amnestic (aMCI) (single- or multiple-domain) vs. non-amnestic (non-aMCI); 2) executive dysfunction-MCI (exMCI) (single- or multiple-domain) vs. no executive dysfunction-MCI (non-exMCI); 3) both aMCI and exMCI; 4) and neither aMCI nor exMCI. Additionally , aMCI vs. nonaMCI and exMCI vs. non-exMCI dichotomies were explored. NPS were assessed with the Neuropsychiatric Inventory (NPI-Q) and Geriatric Depression Scale (GDS).
1379 participants (77.5%) met criteria for aMCI and 616 (34.6%) for exMCI. No differences were observed in the prevalence of NPS between aMCI vs. non-aMCI. However, exMCI was associated with greater severity of depression, anxiety, agitation, disinhibition, irritability, and sleep problems, although these differences do not persist after adjustment for several variables. .
While there were few associations between aMCI and NPS, the presence of executive dysfunction in MCI was associated with greater severity of symptoms and specifically with depression (evidenced by GDS score) and anxiety. These findings may have implications for MCI prognosis and need to be explored in longitudinal studies.
Mild Cognitive Impairment; Depression; Executive Dysfunction; Neuropsychiatric symptoms
Decline in episodic memory is one of the hallmark features of Alzheimer's disease (AD) and is also a defining feature of amnestic Mild Cognitive Impairment (MCI), which is posited as a potential prodrome of AD. While deficits in episodic memory are well documented in MCI, the nature of this impairment remains relatively under-researched, particularly for those domains with direct relevance and meaning for the patient's daily life. In order to fully explore the impact of disruption to the episodic memory system on everyday memory in MCI, we examined participants' episodic memory capacity using a battery of experimental tasks with real-world relevance. We investigated episodic acquisition and delayed recall (story-memory), associative memory (face-name pairings), spatial memory (route learning and recall), and memory for everyday mundane events in 16 amnestic MCI and 18 control participants. Furthermore, we followed MCI participants longitudinally to gain preliminary evidence regarding the possible predictive efficacy of these real-world episodic memory tasks for subsequent conversion to AD.
The most discriminating tests at baseline were measures of acquisition, delayed recall, and associative memory, followed by everyday memory, and spatial memory tasks, with MCI patients scoring significantly lower than controls. At follow-up (mean time elapsed: 22.4 months), 6 MCI cases had progressed to clinically probable AD. Exploratory logistic regression analyses revealed that delayed associative memory performance at baseline was a potential predictor of subsequent conversion to AD.
As a preliminary study, our findings suggest that simple associative memory paradigms with real-world relevance represent an important line of enquiry in future longitudinal studies charting MCI progression over time.
Amnestic mild cognitive impairment (aMCI) represents a prodromal stage of Alzheimer`s disease (AD), especially when additional cognitive domains are affected (Petersen et al., 2009). Thus, single-domain amnestic MCI (sdaMCI) and multiple-domain-amnestic MCI (mdaMCI) biomarkers are important for enabling early interventions to help slow down progression of the disease. Recording event-related potentials (ERPs) is a non-invasive and inexpensive measure of brain activity associated with cognitive processes, and it is of interest from a clinical point of view. The ERP technique may also be useful for obtaining early sdaMCI and mdaMCI biomarkers because ERPs are sensitive to impairment in processes that are not manifested at behavioral or clinical levels. In the present study, EEG activity was recorded in 25 healthy participants and 30 amnestic MCI patients (17 sdaMCI and 13 mdaMCI) while they performed a Simon task. The ERPs associated with visuospatial (N2 posterior-contralateral – N2pc -) and motor (lateralized readiness potential – LRP –) processes were examined. The N2pc amplitude was smaller in participants with mdaMCI than in healthy participants, which indicated a decline in the correlates of allocation of attentional resources to the target stimulus. In addition, N2pc amplitude proved to be a moderately good biomarker of mdaMCI subtype (0.77 sensitivity, 0.76 specificity). However, the LRP amplitude was smaller in the two MCI groups (sdaMCI and mdaMCI) than in healthy participants, revealing a reduction in the motor resources available to execute the response in sdaMCI and mdaMCI patients. Furthermore, the LRP amplitude proved to be a valid biomarker (0.80 sensitivity, 0.92 specificity) of both amnestic MCI subtypes.
Compared to cognitively healthy ageing (CH), intra-individual variability in reaction time (IIVRT), a behavioural marker of neurological integrity, is commonly reported to increase in both Alzheimer’s disease (AD) and mild cognitive impairment (MCI). It varies in MCI with respect to whether it represents the pro-dromal stages of dementia or not; being greatest in those most likely to convert. Abnormal IIVRT in MCI therefore represents a potential measure of underlying functional integrity that may serve to differentiate MCI from CH and to help identify those patients for whom MCI is the result of a progressive pathological process. As the clinical approach to MCI is increasingly stratified with respect to gender, we investigated whether this factor could influence study outcome. The influence of RTSPEED and processing load upon IIVRT was also examined. Under low processing load conditions, IIVRT was significantly increased in both MCI and AD compared to CH. However, correcting for an individual’s processing speed abolished this effect in MCI but not in AD, indicating that the increased IIVRT in MCI and AD may result from different factors. In MCI but not in CH, IIVRT was significantly greater for females. Increasing task processing load by adding distracting information, although increasing overall IIVRT, failed to improve the differentiation between CH and both MCI and AD, and in MCI resulted in a reduction in the influence of gender upon study outcome. The outcome of studies investigating IIVRT in MCI and AD compared to CH therefore appear influenced by the gender of the participants, by task-related processing load and processing speed.
Patients with mild cognitive impairment are at an increased risk of progression to Alzheimer's disease. However, not all patients with mild cognitive impairment progress, and it is difficult to accurately identify those patients who are in the prodromal stage of Alzheimer's disease. In a recent paper, Koivunen and colleagues report that Pittsburgh compound-B, an amyloid-beta positron emission tomography ligand, predicts the progression of patients with mild cognitive impairment to Alzheimer's disease. Of 29 subjects with mild cognitive impairment, 21 (72%) had a positive Pittsburgh compound-B positron emission tomography baseline scan. In their study, 15 of these 21 (71%) patients progressed to Alzheimer's disease, whilst only 1 out of 8 (12.5%) Pittsburgh compound-B-negative patients with mild cognitive impairment did so. Moreover, in these mild cognitive impairment patients, the overall amyloid burden increased approximately 2.5% during the follow-up period. This is consistent with other longitudinal amyloid imaging studies that found a similar increase in amyloid deposition over time in patients with mild cognitive impairment. These studies together challenge current theories that propose a flattening of the increase of brain amyloid deposition already in the preclinical stage of Alzheimer's disease. These findings may have important implications for the design of future clinical trials aimed at preventing progression to Alzheimer's disease by lowering the brain amyloid-beta burden in patients with mild cognitive impairment.
We report evidence that computer-based high-dimensional pattern classification of MRI detects patterns of brain structure characterizing mild cognitive impairment (MCI), often a prodromal phase of Alzheimer's Disease (AD). 90% diagnostic accuracy was achieved, using cross-validation, for 30 participants in the Baltimore Longitudinal Study of Aging. Retrospective evaluation of serial scans obtained during prior years revealed gradual increases in structural abnormality for the MCI group, often before clinical symptoms, but slower increase for individuals remaining cognitively normal. Detecting complex patterns of brain abnormality in very early stages of cognitive impairment has pivotal importance for the detection and management of AD.
Prodromal Alzheimer's Disease; MCI; Pattern Recognition; MRI
Differences in brain metabolism as measured by FDG-PET in prodromal and early Alzheimer's disease (AD) have been consistently observed, with a characteristic parietotemporal hypometabolic pattern. However, exploration of brain metabolic correlates of more nuanced measures of cognitive function has been rare, particularly in larger samples. We analyzed the relationship between resting brain metabolism and memory and executive functioning within diagnostic group on a voxel-wise basis in 86 people with AD, 185 people with mild cognitive impairment (MCI), and 86 healthy controls (HC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found positive associations within AD and MCI but not in HC. For MCI and AD, impaired executive functioning was associated with reduced parietotemporal metabolism, suggesting a pattern consistent with known AD-related hypometabolism. These associations suggest that decreased metabolic activity in the parietal and temporal lobes may underlie the executive function deficits in AD and MCI. For memory, hypometabolism in similar regions of the parietal and temporal lobes were significantly associated with reduced performance in the MCI group. However, for the AD group, memory performance was significantly associated with metabolism in frontal and orbitofrontal areas, suggesting the possibility of compensatory metabolic activity in these areas. Overall, the associations between brain metabolism and cognition in this study suggest the importance of parietal and temporal lobar regions in memory and executive function in the early stages of disease and an increased importance of frontal regions for memory with increasing impairment.
mild cognitive impairment (MCI); Alzheimer's disease (AD); FDG PET; memory; executive function
Awareness of cognitive dysfunction shown by individuals with Mild Cognitive Impairment (MCI), a condition conferring risk for Alzheimer’s disease (AD), is variable. Anosognosia, or unawareness of loss of function, is beginning to be recognized as an important clinical symptom of MCI. However, little is known about the brain substrates underlying this symptom. We hypothesized that MCI participants’ activation of cortical midline structures (CMS) during self-appraisal would covary with level of insight into cognitive difficulties (indexed by a discrepancy score between patient and informant ratings of cognitive decline in each MCI participant). To address this hypothesis, we first compared 16 MCI participants and 16 age-matched controls, examining brain regions showing conjoint or differential BOLD response during self-appraisal. Second, we used regression to investigate the relationship between awareness of deficit in MCI and BOLD activity during self-appraisal, controlling for extent of memory impairment. Between-group comparisons indicated that MCI participants show subtly attenuated CMS activity during self-appraisal. Regression analysis revealed a highly-significant relationship between BOLD response during self-appraisal and self-awareness of deficit in MCI. This finding highlights the level of anosognosia in MCI as an important predictor of response to self-appraisal in cortical midline structures, brain regions vulnerable to changes in early AD.
Magnetic Resonance Imaging; Self Assessment (Psychology); Agnosia; Alzheimer disease; Neocortex; Aging
A challenge in developing informative neuroimaging biomarkers for early diagnosis of Alzheimer's disease is the need to identify biomarkers that are evident before the onset of clinical symptoms, and which have sufficient sensitivity and specificity on an individual patient basis. Recent literature suggests that spatial patterns of brain atrophy discriminate amongst Alzheimer's disease, mild cognitive impairment (MCI) and cognitively normal (CN) older adults with high accuracy on an individual basis, thereby offering promise that subtle brain changes can be detected during prodromal Alzheimer's disease stages. Here, we investigate whether these spatial patterns of brain atrophy can be detected in CN and MCI individuals and whether they are associated with cognitive decline. Images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to construct a pattern classifier that recognizes spatial patterns of brain atrophy which best distinguish Alzheimer's disease patients from CN on an individual person basis. This classifier was subsequently applied to longitudinal magnetic resonance imaging scans of CN and MCI participants in the Baltimore Longitudinal Study of Aging (BLSA) neuroimaging study. The degree to which Alzheimer's disease-like patterns were present in CN and MCI subjects was evaluated longitudinally in relation to cognitive performance. The oldest BLSA CN individuals showed progressively increasing Alzheimer's disease-like patterns of atrophy, and individuals with these patterns had reduced cognitive performance. MCI was associated with steeper longitudinal increases of Alzheimer's disease-like patterns of atrophy, which separated them from CN (receiver operating characteristic area under the curve equal to 0.89). Our results suggest that imaging-based spatial patterns of brain atrophy of Alzheimer's disease, evaluated with sophisticated pattern analysis and recognition methods, may be useful in discriminating among CN individuals who are likely to be stable versus those who will show cognitive decline. Future prospective studies will elucidate the temporal dynamics of spatial atrophy patterns and the emergence of clinical symptoms.
early Alzheimer's disease; mild cognitive impairment; neuroimaging; ageing; SPARE-AD
In addition to amyloid beta (Aβ) and tau, α-synuclein, best known for its role in Parkinson’s disease (PD), has been suggested to be involved in cognition and pathogenesis of Alzheimer’s disease (AD). We investigate the potential of α-synuclein in cerebrospinal fluid (CSF) as a biomarker of cognitive decline in AD, and its prodromal phase, mild cognitive impairment (MCI). Using an established, sensitive Luminex assay, we measured α-synuclein levels in the CSF of a cohort of close to 400 healthy control, MCI and AD subjects obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and factored in APOE genotype in data analysis. CSF α-synuclein levels were significantly higher in the MCI (P = 0.005) and AD (P < 0.001) groups, compared to controls. However, receiver operating characteristic (ROC) curve analysis suggests that CSF α-synuclein level on its own only offered modest sensitivity (65 %) and specificity (74 %) as a diagnostic marker of AD, with an area under the curve (AUC) value of 0.719 for AD vs controls. The effect of APOE genotype, if any, was quite subtle. However, there was a significant correlation between α-synuclein and cognition (P = 0.001), with increased α-synuclein levels associated with decreased MMSE scores. Our results support a role for α-synuclein even in MCI, the early phase of AD, in addition to being a potential contributor in MCI and AD diagnosis or monitoring of disease progression.
alpha-synuclein; Alzheimer’s disease; Mild cognitive impairment; biomarkers; cerebrospinal fluid
We evaluated the association between hippocampal atrophy and increase of the EEG markers alpha3/alpha2 relative power ratio in mild cognitive impairment (MCI) and Alzheimer's disease patients. Seventy-nine subjects with MCI and 11 patients with AD underwent EEG recording and MRI scan. The MCI group was subdivided in three subgroups according to growing hippocampal atrophy. The groups were characterized by alpha3/alpha2 relative power ratio. In AD patients group mapped hippocampal regions were computed and related with alpha3/alpha2 power ratio. Results show that the increase of alpha3/alpha2 power ratio is correlated with atrophy of hippocampus both in MCI and in Alzheimer's disease patients. This finding confirms the possible diagnostic role of EEG markers as diagnostic and prognostic factors in patient with prodromal and declared Alzheimer's disease.
Low cerebrospinal fluid (CSF) amyloid-β1-42 concentration and high total-tau/Aβ1-42 ratio have been recommended to support the diagnosis of prodromal Alzheimer’s disease (AD) in patients with amnestic mild cognitive impairment (aMCI) and also to select patients for clinical trials.
We tested this recommendation with clinical trials simulations using patients from the Alzheimer Disease Neuroimaging Initiative who fulfilled the following entry criteria: (1) aMCI, (2) aMCI with CSF Aβ1-42 ≤192 mg/mL, (3) and aMCI with total-tau/Aβ1-42 >.0.39. For each criterion, we randomly resampled the database obtaining samples for 1000 trials for each trial scenario, planning for 1 or 2 year trials with samples from 50 to 400 patients per treatment or placebo group, with up to 40% dropouts, outcomes after using the AD assessment scale-cognitive subscale and clinical dementia rating scale with effect sizes ranging from 0.15 to 0.75, and calculated statistical power.
Approximately 70% to 74% of aMCI patients with CSF measures met biomarker criteria. The addition of the low Aβ1-42 or high tau/Aβ1-42 requirement resulted in minimal or no increase in the power of the trials compared with enrolling aMCI without requiring the biomarker criteria. Slightly larger mean differences between the placebo and treatment groups fulfilling biomarker criteria were offset by increased outcome variability within the groups.
Although patients with aMCI or patients with prodromal AD meeting CSF biomarkers criteria were slightly more cognitively impaired and showed greater decline than patients with aMCI diagnosed without considering the biomarkers, the requirement of biomarker-positive patients would most likely not result in more efficient clinical trials, and trials would take longer because fewer patients would be available. A CSF Aβ1-42 marker, however, could be useful as an explanatory variable or covariate when warranted by the action of a drug.
Alzheimer disease; Mild cognitive impairment; Biomarkers; Clinical trials; Simulations; Amyloid-beta protein; Alzheimer’s disease neuroimaging initiative (ADNI); Alzheimer’s disease assessment scale; Clinical dementia rating
Sensitive cognitive global scores are beneficial in screening and monitoring for prodromal Alzheimer's disease (AD). Early cortical changes provide a novel opportunity for validating established cognitive total scores against the biological disease markers.
We examined how two different total scores of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery and the Mini-Mental State Examination (MMSE) are associated with cortical thickness (CTH) in mild cognitive impairment (MCI) and prodromal AD. Cognitive and magnetic resonance imaging (MRI) data of 22 progressive MCI, 78 stable MCI, and 98 control subjects, and MRI data of 103 AD patients of the prospective multicenter study were analyzed.
CERAD total scores correlated with mean CTH more strongly (r = 0.34-0.38, p < 0.001) than did MMSE (r = 0.19, p = 0.01). Of those vertex clusters that showed thinning in progressive MCI, 60-75% related to the CERAD total scores and 3% to the MMSE.
CERAD total scores are sensitive to the CTH signature of prodromal AD, which supports their biological validity in detecting early disease-related cognitive changes.
Alzheimer's disease; Cognition; Cortical thickness; Magnetic resonance imaging;
Memory; Neuropsychology; Mild cognitive impairment; AddNeuroMed study
Although a majority of patients with amnestic mild cognitive impairment (aMCI) progress to Alzheimer disease, the natural history of nonamnestic MCI (naMCI) is less clear. Noninvasive imaging surrogates for underlying pathological findings in MCI would be clinically useful for identifying patients who may benefit from disease-specific treatments at the prodromal stage of dementia.
To determine the characteristic magnetic resonance imaging (MRI) and proton MR spectroscopy (1H MRS) profiles of MCI subtypes.
Community-based sample at a tertiary referral center.
Ninety-one patients with single-domain aMCI, 32 patients with multiple-domain aMCI, 20 patients with single- or multiple-domain naMCI, and 100 cognitively normal elderly subjects frequency-matched by age and sex.
Main Outcome Measures
Posterior cingulate gyrus 1H MRS metabolite ratios, hippocampal volumes, and cerebrovascular disease on MRI.
Patients with single-domain aMCI were characterized by small hippocampal volumes and elevated ratios of myo-inositol to creatine levels. Patients with naMCI on average had normal hippocampal volumes and 1H MRS metabolite ratios, but a greater proportion (3 of 20 patients [15%]) had cortical infarctions compared with patients with single-domain aMCI (6 of 91 [7%]). For characterization of MCI subtypes, 1H MRS and structural MRI findings were complementary.
The MRI and 1H MRS findings in singledomain aMCI are consistent with a pattern similar to that of Alzheimer disease. Absence of this pattern on average in patients with naMCI suggests that cerebrovascular disease and other neurodegenerative diseases may be contributing to the cognitive impairment in many individuals with naMCI.
Mild cognitive impairment (MCI) was proposed as a nosological entity referring to elderly people with mild cognitive deficit but no dementia. MCI is a heterogeneous clinical entity with multiple sources of heterogeneity. The concept of MCI was reviewed and a diagnostic procedure with three different stages was proposed by the European Consortium on Alzheimer's Disease Working Group on MCI. Firstly, MCI should correspond to cognitive complaints coming from the patients or their families; the reporting of a relative decline in cognitive functioning during the past year by a patient or informant; cognitive disorders as evidenced by clinical evaluation; absence of major repercussions on daily life; and absence of dementia. These criteria, similar to those defined during an international workshop in Stockholm, make it possible to identify an MCI syndrome, which is the first stage of the diagnostic procedure. Secondly, subtypes of MCI had to be recognised. Finally, the aetiopathogenic subtype could be identified. Identifying patients at a high risk for progression to dementia and establishing more specific and adapted therapeutic strategies at an early stage, together with more structured overall management, is made possible by the diagnostic procedure proposed.
Mild cognitive impairment (MCI) is regarded as a prodromal phase of late onset Alzheimer's disease (LOAD). It has been proposed that oxidative stress (OxS) might be implicated in the pathogenesis of LOAD. The aim of this study was to investigate whether a redox imbalance measured as serum level of hydroperoxides (i.e., by-products of lipid peroxidation) and/or serum antioxidant capacity might be predictive of the clinical progression of MCI to LOAD. The levels of these two markers were measured in 111 patients with MCI (follow-up: 2.0 ± 0.6 years), 105 patients with LOAD, and 118 nondemented healthy controls. Multivariate analysis adjusted for potential confounding factors, including age, gender, smoking, and comorbidities, showed a significant increase (P < 0.05) in baseline levels of OxS in MCI and LOAD as compared to cognitive healthy controls. No differences in either of OxS markers were found by comparing MCI patients who converted (n = 29) or not converted (n = 82) to LOAD. Overall, these results suggest that systemic OxS might be a precocious feature of MCI and LOAD. However, the role of OxS as an early prognostic marker of progression to LOAD needs further investigations.
Mild cognitive impairment (MCI) is a heterogeneous clinical entity that comprises the prodromal phase of Alzheimer's disease (Pr-AD). New biomarkers are useful in detecting Pr-AD, but they are not universally available. We aimed to investigate baseline clinical and neuropsychological variables that might predict progression from MCI to AD dementia.
All patients underwent a complete clinical and neuropsychological evaluation at baseline and every 6 months during a two-year follow-up period, with 54 out of 109 MCI patients progressing to dementia (50 of them progressed to AD dementia), and 55 remaining as stable MCI (S-MCI).
A combination of MMSE and California Verbal Learning Test Long Delayed Total Recall (CVLT-LDTR) constituted the best predictive model: subjects scoring above 26/30 on MMSE and 4/16 on CVLT-LDTR had a negative predictive value of 93.93% at 2 years, whereas those subjects scoring below both of these cut-off scores had a positive predictive value of 80.95%.
Pr-AD might be distinguished from S-MCI at baseline using the combination of MMSE and CVLT-LDTR. These two neuropsychological predictors are relatively brief and may be readily completed in non-specialist clinical settings.
Alzheimer's disease (AD) is associated with abnormal functioning of the default mode network (DMN). Functional connectivity (FC) changes to the DMN have been found in patients with amnestic mild cognitive impairment (aMCI), which is the prodromal stage of AD. However, whether or not aMCI also alters the effective connectivity (EC) of the DMN remains unknown. We employed a combined group independent component analysis (ICA) and Bayesian network (BN) learning approach to resting-state functional MRI (fMRI) data from 17 aMCI patients and 17 controls, in order to establish the EC pattern of DMN, and to evaluate changes occurring in aMCI. BN analysis demonstrated heterogeneous regional convergence degree across DMN regions, which were organized into two closely interacting subsystems. Compared to controls, the aMCI group showed altered directed connectivity weights between DMN regions in the fronto-parietal, temporo-frontal, and temporo-parietal pathways. The aMCI group also exhibited altered regional convergence degree in the right inferior parietal lobule. Moreover, we found EC changes in DMN regions in aMCI were correlated with regional FC levels, and the connectivity metrics were associated with patients' cognitive performance. This study provides novel sights into our understanding of the functional architecture of the DMN and adds to a growing body of work demonstrating the importance of the DMN as a mechanism of aMCI.
Activated microglia may play a role in the pathogenesis of Alzheimer disease (AD) as they cluster around beta-amyloid (Aβ) plaques. They are, therefore, a potential therapeutic target in both AD and its prodrome amnestic mild cognitive impairment (MCI).
To characterize in vivo with 11C-(R)-PK11195 and 11C-PIB PET the distribution of microglial activation and amyloid deposition in patients with amnestic MCI.
Fourteen subjects with MCI had 11C-(R)-PK11195 and 11C-PIB PET with psychometric tests.
Seven out of 14 (50%) patients with MCI had increased cortical 11C-PIB retention (p < 0.001) while 5 out of 13 (38%) subjects with MCI showed increased 11C-(R)-PK11195 uptake. The MCI subgroup with increased 11C-PIB retention also showed increased cortical 11C-(R)-PK11195 binding (p < 0.036) though this increase only remained significant in frontal cortex after a correction for multiple comparisons. There was no correlation between regional levels of 11C-(R)-PK11195 and 11C-PIB binding in individual patients with MCI: only three of the five MCI cases with increased 11C-(R)-PK11195 binding had increased levels of 11C-PIB retention.
Our findings indicate that, while amyloid deposition and microglial activation can be detected in vivo in around 50% of patients with mild cognitive impairment (MCI), these pathologies can occur independently. The detection of microglial activation in patients with MCI suggests that anti-inflammatory therapies may be relevant to the prevention of AD.
= Alzheimer disease;
= binding potential;
= mild cognitive impairment;
= Mini-Mental State Examination;
= peripheral benzodiazepine binding site;
= region of interest;
= standard deviation;
= simplified reference tissue model.
Sleep is important for declarative memory consolidation in healthy adults. Sleep disruptions are typical in Alzheimer’s disease, but whether they contribute to memory impairment is unknown. Sleep has not been formally examined in amnestic mild cognitive impairment (aMCI), which is characterized by declarative-memory deficits without dementia and can signify prodromal Alzheimer’s disease. We studied 10 aMCI patients and 10 controls over 2 weeks using daily sleep surveys, wrist-worn activity sensors, and daily recognition tests. Recognition was impaired and more variable in aMCI patients, whereas sleep was similar across groups. However, lower recognition of items learned the previous day was associated with lower subjective sleep quality in aMCI patients. This correlation was not present for information learned the same day, thus did not reflect nonspecific effects of poor sleep on memory. These results indicate that inadequate memory consolidation in aMCI patients is related to declines in subjective sleep indices. Furthermore, participants with greater across-night sleep variability exhibited lower scores on a standardized recall test taken prior to the 2-week protocol, suggesting that consistent sleep across nights also contributes to successful memory. Physiological analyses are needed to further specify which aspects of sleep in neurological disorders impact memory function and consolidation.
declarative memory; sleep; amnestic mild cognitive impairment; memory consolidation
In recent studies of Alzheimer’s disease (AD), it has increasing attentions in identifying mild cognitive impairment (MCI) converters (MCI-C) from MCI non-converters (MCI-NC). Note that MCI is a prodromal stage of AD, with possibility to convert to AD. Most traditional methods for MCI conversion prediction learn information only from MCI subjects (including MCI-C and MCI-NC), not from other related subjects, e.g., AD and normal controls (NC), which can actually aid the classification between MCI-C and MCI-NC. In this paper, we propose a novel domain-transfer learning method for MCI conversion prediction. Different from most existing methods, we classify MCI-C and MCI-NC with aid from the domain knowledge learned with AD and NC subjects as auxiliary domain to further improve the classification performance. Our method contains two key components: (1) the cross-domain kernel learning for transferring auxiliary domain knowledge, and (2) the adapted support vector machine (SVM) decision function construction for cross-domain and auxiliary domain knowledge fusion. Experimental results on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database show that the proposed method can significantly improve the classification performance between MCI-C and MCI-NC, with aid of domain knowledge learned from AD and NC subjects.
This work builds upon previous studies that reported high sensitivity and specificity in classifying individuals with mild cognitive impairment (MCI), which is often a prodromal phase of Alzheimer's Disease (AD), via pattern classification of MRI scans. The current study integrates MRI and PET 15O water scans from 30 participants in the Baltimore Longitudinal Study of Aging, and tests the hypothesis that joint evaluation of structure and function can yield higher classification accuracy than either alone. Classification rates of up to 100% accuracy were achieved via leave-one-out cross validation, whereas conservative estimates of generalization performance in new scans, evaluated via bagging cross-validation, yielded an area under the receiver operating characteristic (ROC) curve equal to 0.978 (97.8%), indicating excellent diagnostic accuracy. Spatial maps of regions determined to contribute the most to the classification implicated many temporal, prefrontal, orbitofrontal, and parietal regions. Detecting complex patterns of brain abnormality in early stages of cognitive impairment has pivotal importance for the detection and management of AD.
Alzheimer's Disease; MCI; high-dimensional Pattern Classification; MRI; PET; voxel-based analysis; diagnosis of AD
Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. Most previous work in this area has centred around the same automated techniques used to diagnose AD patients from healthy controls, by coupling high dimensional brain image data or other relevant biomarker data to modern machine learning techniques. Such studies can now distinguish between AD patients and controls as accurately as an experienced clinician. Models trained on patients with AD and control subjects can also distinguish between MCI patients that will convert to AD within a given timeframe (MCI-c) and those that remain stable (MCI-s), although differences between these groups are smaller and thus, the corresponding accuracy is lower. The most common type of classifier used in these studies is the support vector machine, which gives categorical class decisions. In this paper, we introduce Gaussian process (GP) classification to the problem. This fully Bayesian method produces naturally probabilistic predictions, which we show correlate well with the actual chances of converting to AD within 3 years in a population of 96 MCI-s and 47 MCI-c subjects. Furthermore, we show that GPs can integrate multimodal data (in this study volumetric MRI, FDG-PET, cerebrospinal fluid, and APOE genotype with the classification process through the use of a mixed kernel). The GP approach aids combination of different data sources by learning parameters automatically from training data via type-II maximum likelihood, which we compare to a more conventional method based on cross validation and an SVM classifier. When the resulting probabilities from the GP are dichotomised to produce a binary classification, the results for predicting MCI conversion based on the combination of all three types of data show a balanced accuracy of 74%. This is a substantially higher accuracy than could be obtained using any individual modality or using a multikernel SVM, and is competitive with the highest accuracy yet achieved for predicting conversion within three years on the widely used ADNI dataset.
•Prediction of MCI to AD conversion using ADNI data and Gaussian processes.•74% accuracy, 0.795 area under ROC curve for predicting conversion within 3 years.•Gaussian processes allow automatic parameter tuning including multimodal weights.•Statistically significant improvement for multimodal vs best unimodal prediction.•Probabilistic interpretation of results to better reflect continuum of disease.
Alzheimer's disease; Mild cognitive impairment; Gaussian process; Support vector machine; Multimodality; Probabilistic classification; Risk scores
Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) can both denote prodromal Alzheimer's disease. While the two concepts share common clinical features, differential diagnosis between them is crucial. The objective of this pilot study was to explore differences in terms of the hippocampal (HC) and entorhinal cortex (EC) volume reduction between LLD and aMCI patients with (aMCI/D+ group) or without (aMCI group) depressive symptoms. Six LLD, 6 aMCI, and 6 aMCI/D+ participants were assessed using a structural magnetic resonance imaging protocol. Manual segmentation of HC and EC was carried out. The results of volumetric comparisons suggest that the HC was larger in aMCI/D+ and LLD subjects compared to aMCI participants. The left EC mean volume was slightly lower in aMCI/D+ subjects. Power analyses revealed that 36 participants per group would suffice to confirm these findings. Overall, these pilot findings suggest that aMCI can be distinguished from LLD based on cerebral atrophy measures, and that HC and EC atrophy in aMCI varies according to the presence or absence of depressive symptoms.
Aging; Alzheimer's disease; Depression; Entorhinal cortex; Hippocampus; Mild cognitive impairment; Prodromal phase; Magnetic resonance imaging; Medial temporal lobe
Mild cognitive impairment (MCI) is a frequent clinical entity, considered today to be a prodromal stage of Alzheimer's dementia, but not having until now a standardized pharmacological treatment. The aim of this study is to follow the outcome of the patients diagnosed with MCI non treated and treated with nootropics, alternative herbal agents, and cholinesterase inhibitors.
The study comprises a number of 200 patients (over 60 years) diagnosed with MCI. The patients were evaluated using MMSE (Mini Mental State Evaluation) at the inclusion into the study and after 1 year of treatment. The patients were divided in four different groups: Group A - 50 patients diagnosed with MCI treated with Piracetamum 1600mg/day, Group B - 50 patients diagnosed with MCI treated with Rhodiola rosea, 2 capsules/day, Group C - 50 patients diagnosed with MCI treated with Galantamine (16mg/day), Group D - 50 patients diagnosed with MCI non treated
The average of MMSE scores at screening was 23.96 points for group A, 24.16 points for group B, 23.96 for group C and 24.5 points for group D. After 1 year of treatment, cognitive performance improves with 2.12 points for Group A, 1.97 points for Group B, 2.04 points for Group C and without any improvement for Group D.
Comparing the outcome of treated and non-treated groups, we observed that the early treatment of mild cognitive impairment delay the transition to dementia. The outcome of the treated groups after 1 year of pharmacological treatment was approximately the same. This study proves the necessity of early treatment and of the enlargement of therapies in mild cognitive impairment. The acceptance of nonconventional therapies can change the relationships between physicians and well educated patients who more frequently advocate for a broad range of treatment choices.