Reorganization of functional networks in mild cognitive impairment

Whether the balance between integration and segregation of information in the brain is damaged in Mild Cognitive Impairment (MCI) subjects is still a matter of debate. Here we characterize the functional network architecture of MCI subjects by means of complex networks analysis. Magnetoencephalograms (MEG) time series obtained during a memory task were evaluated by synchronization likelihood (SL), to quantify the statistical dependence between MEG signals and to obtain the functional networks. Graphs from MCI subjects show an enhancement of the strength of connections, together with an increase in the outreach parameter, suggesting that memory processing in MCI subjects is associated with higher energy expenditure and a tendency toward random structure, which breaks the balance between integration and segregation. All features are reproduced by an evolutionary network model that simulates the degenerative process of a healthy functional network to that associated with MCI. Due to the high rate of conversion from MCI to Alzheimer Disease (AD), these results show that the analysis of functional networks could be an appropriate tool for the early detection of both MCI and AD.     

Effect of acupuncture in mild cognitive impairment and Alzheimer disease: a functional MRI study

We aim to clarify the mechanisms of acupuncture in treating mild cognitive impairment (MCI) and Alzheimer disease (AD) by using functional magnetic resonance imaging (fMRI). Thirty-six right-handed subjects (8 MCI patients, 14 AD patients, and 14 healthy elders) participated in this study. Clinical and neuropsychological examinations were performed on all the subjects. MRI data acquisition was performed on a SIEMENS verio 3-Tesla scanner. The fMRI study used a single block experimental design. We first acquired the baseline resting state data in the initial 3 minutes; we then acquired the fMRI data during the procession of acupuncture stimulation on the acupoints of Tai chong and Hegu for the following 3 minutes. Last, we acquired fMRI data for another 10 minutes after the needle was withdrawn. The preprocessing and data analysis were performed using the statistical parametric mapping (SPM8) software. Then the two-sample t-tests were performed between each two groups of different states. We found that during the resting state, brain activities in AD and MCI patients were different from those of control subjects. During the acupuncture and the second resting state after acupuncture, when comparing to resting state, there are several regions showing increased or decreased activities in MCI, AD subjects compared to normal subjects. Most of the regions were involved in the temporal lobe and the frontal lobe, which were closely related to the memory and cognition. In conclusion, we investigated the effect of acupuncture in AD and MCI patients by combing fMRI and traditional acupuncture. Our fMRI study confirmed that acupuncture at Tai chong (Liv3) and He gu (LI4) can activate certain cognitive-related regions in AD and MCI patients.     

Processing of the Platelet Amyloid Precursor Protein in the Mild Cognitive Impairment (MCI)

It has been suggested that mild cognitive impairment (MCI) patients deteriorate faster than the healthy elderly population and have an increased risk of developing dementia. Certain blood molecular biomarkers have been identified as prognostic markers in Alzheimer’s disease (AD). The present study was aimed to assess the status of the platelet amyloid precursor protein (APP) metabolism in MCI and AD subjects and establish to what extent any variation could have a prognostic value suggestive of predictive AD in MCI patients. Thirty-four subjects diagnosed with MCI and 45 subjects with AD were compared to 28 healthy elderly individuals for assessing for protein levels of APP, β-APP cleaving enzyme 1 (BACE1), presenilin 1 (PS1) and a disintegrin and metalloproteinase-10 (ADAM-10) by western blot, and for the enzyme activities of BACE1 and γ-secretase by using specific fluorogenic substrates, in samples of platelets. A similar pattern in the healthy elderly and MCI patients was found for BACE1 and PS1 levels. A reduction of APP levels in MCI and AD patients compared with healthy elderly individuals was found. Augmented levels of ADAM-10 in both MCI and AD were displayed in comparison with age-matched control subjects. The ratio ADAM-10/BACE1 was higher for the MCI group versus AD group. Whereas BACE1 and PS1 levels were only increased in AD regarding to controls, BACE1 and γ-secretase activities augmented significantly in both MCI and AD groups. Finally, differences and similarities between MCI and AD patients were observed in several markers of platelet APP processing. Larger sample sets from diverse populations need to be analyzed to define a signature for the presence of MCI or AD pathology and to early detect AD at the MCI stage.     

Sparse learning and stability selection for predicting MCI to AD conversion using baseline ADNI data

ABSTRACT: BACKGROUND: Patients with Mild Cognitive Impairment (MCI) are at high risk of progression to Alzheimer's dementia. Identifying MCI individuals with high likelihood of conversion to dementia and the associated biosignatures has recently received increasing attention in AD research. Different biosignatures for AD (neuroimaging, demographic, genetic and cognitive measures) may contain complementary information for diagnosis and prognosis of AD. METHODS: We have conducted a comprehensive study using a large number of samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to test the power of integrating various baseline data for predicting the conversion from MCI to probable AD and identifying a small subset of biosignatures for the prediction and assess the relative importance of different modalities in predicting MCI to AD conversion. We have employed sparse logistic regression with stability selection for the integration and selection of potential predictors. Our study differs from many of the other ones in three important respects: (1) we use a large cohort of MCI samples that are unbiased with respect to age or education status between case and controls (2) we integrate and test various types of baseline data available in ADNI including MRI, demographic, genetic and cognitive measures and (3) we apply sparse logistic regression with stability selection to ADNI data for robust feature selection. RESULTS: We have used 319 MCI subjects from ADNI that had MRI measurements at the baseline and passed quality control, including 177 MCI Non-converters and 142 MCI Converters. Conversion was considered over the course of a 4-year follow-up period. A combination of 15 features (predictors) including those from MRI scans, APOE genotyping, and cognitive measures achieves the best prediction with an AUC score of 0.8587. These results also demonstrate the effectiveness of stability selection for feature selection in the context of sparse logistic regression.     

Loss of 'small-world' networks in Alzheimer's disease: graph analysis of FMRI resting-state functional connectivity

Background

Local network connectivity disruptions in Alzheimer''s disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data.

Methodology/Principal Findings

18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions.

Conclusions/Significance

We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease.     

Directed Network Motifs in Alzheimer’s Disease and Mild Cognitive Impairment

Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains. We show that frequencies of specific directed network motifs can be used to distinguish between patients with Alzheimer’s disease (AD) and normal control (NC) subjects. Especially interesting from a clinical standpoint, these motif frequencies can also distinguish between subjects with mild cognitive impairment who remained stable over three years (MCI) and those who converted to AD (CONV). Furthermore, we find that the entropy of the distribution of directed network motifs increased from MCI to CONV to AD, implying that the distribution of pathology is more structured in MCI but becomes less so as it progresses to CONV and further to AD. Thus, directed network motifs frequencies and distributional properties provide new insights into the progression of Alzheimer’s disease as well as new imaging markers for distinguishing between normal controls, stable mild cognitive impairment, MCI converters and Alzheimer’s disease.     

Peripheral levels of glutathione and protein oxidation as markers in the development of Alzheimer's disease from Mild Cognitive Impairment

There is a great interest in the relationship between Mild Cognitive Impairment (MCI) and the progression to Alzheimer's disease (AD). Several studies show the importance of oxidative stress in the pathogenesis of AD. The purpose of this study was the link between oxidative damage, MCI and AD. It analysed protein carbonyls and erythrocyte glutathione system plasma levels of 34 subjects with MCI, 45 subjects with AD and 28 age-matched control subjects. The results showed an increase in protein modification, a decrease in GSH levels and GSH/GSSG ratio in AD and MCI patients compared to age-matched control subjects (p<0.05). The present study shows that some peripheral markers of oxidative stress appear in MCI with a similar pattern to that observed in AD, which suggests that oxidative stress might represent a signal of the AD pathology. AD and MCI are biochemically equivalent. MCI does not necessarily need to progress to AD on a biochemical level.     

Sirtuin1: A Promising Serum Protein Marker for Early Detection of Alzheimer’s Disease

Sirtuin (SIRT) pathway has a crucial role in Alzheimer’s disease (AD). The present study evaluated the alterations in serum sirtuin1 (SIRT1) concentration in healthy individuals (young and old) and patients with AD and mild cognitive impairment (MCI). Blood samples were collected from 40 AD and 9 MCI patients as cases and 22 young healthy adults and 22 healthy elderly individuals as controls. Serum SIRT1 was estimated by Surface Plasmon Resonance (SPR), Western Blot and Enzyme Linked Immunosorbent Assay (ELISA). A significant (p<0.0001) decline in SIRT1 concentration was observed in patients with AD (2.27±0.46 ng/µl) and MCI (3.64±0.15 ng/µl) compared to healthy elderly individuals (4.82±0.4 ng/µl). The serum SIRT1 concentration in healthy elderly was also significantly lower (p<0.0001) compared to young healthy controls (8.16±0.87 ng/µl). This study, first of its kind, has demonstrated, decline in serum concentration of SIRT1 in healthy individuals as they age. In patients with AD and MCI the decline was even more pronounced, which provides an opportunity to develop this protein as a predictive marker of AD in early stages with suitable cut off values.     

Interhemispheric Functional and Structural Disconnection in Alzheimer’s Disease: A Combined Resting-State fMRI and DTI Study

Neuroimaging studies have demonstrated that patients with Alzheimer’s disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI) to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI), as well as 16 cognitive normal healthy subjects (CN). The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC) method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of AD<MCI<CN. Increased VMHC was observed in MCI subjects in posterior brain regions with patterns of AD/CN < MCI (sensorimotor cortex) and AD < CN/MCI (occipital gyrus). DTI analysis showed the most significant difference among the three cohorts was the fractional anisotropy in the genu of corpus callosum, which was positively associated with the VMHC of prefrontal and subcortical regions. Across all the three cohorts, the diffusion parameters in the genu of corpus callosum and VMHC in the above brain regions had significant correlation with the cognitive performance. These results demonstrate that there are specific patterns of interhemispheric functional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.     

Bile acid quantification of 20 plasma metabolites identifies lithocholic acid as a putative biomarker in Alzheimer’s disease

Introduction

There is still a clear need for a widely available, inexpensive and reliable method to diagnose Alzheimer’s disease (AD) and monitor disease progression. Liquid chromatography–mass spectrometry (LC-MS) is a powerful analytic technique with a very high sensitivity and specificity.

Objectives

The aim of the present study is to measure concentrations of 20 bile acids using the novel Kit from Biocrates Life Sciences based on LC-MS technique.

Methods

Twenty bile acid metabolites were quantitatively measured in plasma of 30 cognitively healthy subjects, 20 patients with mild cognitive impairment (MCI) and 30 patients suffering from AD.

Results

Levels of lithocholic acid were significantly enhanced in plasma of AD patients (50?±?6 nM, p?=?0.004) compared to healthy controls (32?±?3 nM). Lithocholic acid plasma levels of MCI patients (41?±?4 nM) were not significantly different from healthy subjects or AD patients. Levels of glycochenodeoxycholic acid, glycodeoxycholic acid and glycolithocholic acid were significantly higher in AD patients compared to MCI patients (p?<?0.05). All other cholic acid metabolites were not significantly different between healthy subjects, MCI patients and AD patients. ROC analysis shows an overall accuracy of about 66%. Discriminant analysis was used to classify patients and we found that 15/23 were correctly diagnosed. We further showed that LCA levels increased by about 3.2 fold when healthy subjects converted to AD patients within a 8–9 year follow up period. Pathway analysis linked these changes to a putative toxic cholesterol pathway.

Conclusion

In conclusion, 4 bile acids may be useful to diagnose AD in plasma samples despite limitations in diagnostic accuracy.

     

New insights into Alzheimer's disease progression: a combined TMS and structural MRI study

Background:

Combination of structural and functional data of the human brain can provide detailed information of neurodegenerative diseases and the influence of the disease on various local cortical areas.

Methodology and Principal Findings:

To examine the relationship between structure and function of the brain the cortical thickness based on structural magnetic resonance images and motor cortex excitability assessed with transcranial magnetic stimulation were correlated in Alzheimer''s disease (AD) and mild cognitive impairment (MCI) patients as well as in age-matched healthy controls. Motor cortex excitability correlated negatively with cortical thickness on the sensorimotor cortex, the precuneus and the cuneus but the strength of the correlation varied between the study groups. On the sensorimotor cortex the correlation was significant only in MCI subjects. On the precuneus and cuneus the correlation was significant both in AD and MCI subjects. In healthy controls the motor cortex excitability did not correlate with the cortical thickness.

Conclusions:

In healthy subjects the motor cortex excitability is not dependent on the cortical thickness, whereas in neurodegenerative diseases the cortical thinning is related to weaker cortical excitability, especially on the precuneus and cuneus. However, in AD subjects there seems to be a protective mechanism of hyperexcitability on the sensorimotor cortex counteracting the prominent loss of cortical volume since the motor cortex excitability did not correlate with the cortical thickness. Such protective mechanism was not found on the precuneus or cuneus nor in the MCI subjects. Therefore, our results indicate that the progression of the disease proceeds with different dynamics in the structure and function of neuronal circuits from normal conditions via MCI to AD.     

Abnormal cortical networks in mild cognitive impairment and Alzheimer's disease

Recently, many researchers have used graph theory to study the aberrant brain structures in Alzheimer's disease (AD) and have made great progress. However, the characteristics of the cortical network in Mild Cognitive Impairment (MCI) are still largely unexplored. In this study, the gray matter volumes obtained from magnetic resonance imaging (MRI) for all brain regions except the cerebellum were parcellated into 90 areas using the automated anatomical labeling (AAL) template to construct cortical networks for 98 normal controls (NCs), 113 MCIs and 91 ADs. The measurements of the network properties were calculated for each of the three groups respectively. We found that all three cortical networks exhibited small-world properties and those strong interhemispheric correlations existed between bilaterally homologous regions. Among the three cortical networks, we found the greatest clustering coefficient and the longest absolute path length in AD, which might indicate that the organization of the cortical network was the least optimal in AD. The small-world measures of the MCI network exhibited intermediate values. This finding is logical given that MCI is considered to be the transitional stage between normal aging and AD. Out of all the between-group differences in the clustering coefficient and absolute path length, only the differences between the AD and normal control groups were statistically significant. Compared with the normal controls, the MCI and AD groups retained their hub regions in the frontal lobe but showed a loss of hub regions in the temporal lobe. In addition, altered interregional correlations were detected in the parahippocampus gyrus, medial temporal lobe, cingulum, fusiform, medial frontal lobe, and orbital frontal gyrus in groups with MCI and AD. Similar to previous studies of functional connectivity, we also revealed increased interregional correlations within the local brain lobes and disrupted long distance interregional correlations in groups with MCI and AD.     

Dkk-3 is elevated in CSF and plasma of Alzheimer's disease patients

Biomarkers in CSF can offer improved diagnostic accuracy for Alzheimer's disease (AD). The present study investigated whether the glycoprotein and putative tumor suppressor Dickkopf homolog 3 (Dkk-3) is secreted into CSF and evaluated its applicability as a diagnostic marker for AD. Using our highly specific immunoenzymometric assay, Dkk-3 levels were measured in plasma and/or CSF of patients suffering from depression, mild cognitive impairment (MCI), or AD and compared with healthy subjects. Dkk-3 identity was verified by western blot and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)/MS. High concentrations of Dkk-3 were detected in CSF compared with plasma (28.2 ± 1.3 vs. 1.22 ± 0.04 nmol/L, respectively). Consistently Dkk-3 expression was demonstrated in neurons of the cortex and epithelial cells of the choroid plexus, the major source of CSF. Significantly increased Dkk-3 levels in plasma and CSF were observed for AD patients compared with healthy subjects but not patients suffering from MCI or depression. In summary, our data indicate that elevated Dkk-3 levels are specifically associated with AD and might serve as a potential non-invasive AD biomarker in plasma.     

Increased oxidative damage in nuclear and mitochondrial DNA in mild cognitive impairment

Increasing evidence suggests that oxidative damage is associated with normal aging and several neurodegenerative diseases. Mild cognitive impairment (MCI), the phase between normal aging and early dementia, is a common problem in the elderly with many subjects going on to develop Alzheimer's disease (AD). Although increased DNA oxidation is observed in the AD brain, it is unclear when the oxidative damage begins. To determine if DNA oxidation occurs in the brain of subjects with MCI, we quantified multiple oxidized bases in nuclear and mitochondrial DNA isolated from frontal, parietal and temporal lobes and cerebellum of short post-mortem interval autopsies of eight amnestic patients with MCI and six age-matched control subjects using gas chromatography/mass spectrometry with selective ion monitoring. We found statistically significant elevations (p < 0.05) of 8-hydroxyguanine, a widely studied biomarker of DNA damage, in MCI nuclear DNA from frontal and temporal lobe and in mitochondrial DNA from the temporal lobe compared with age-matched control subjects. Levels of 8-hydroxyadenine and 4,6-diamino-5-formamidopyrimidine were significantly elevated in nuclear DNA from all three neocortical regions in MCI. Statistically significant elevations of 4,6-diamino-5-formamidopyrimidine were also observed in mitochondrial DNA of MCI temporal, frontal and parietal lobes. These results suggest that oxidative damage to nuclear and mitochondrial DNA occurs in the earliest detectable phase of AD and may play a meaningful role in the pathogenesis of this disease.     

Atrophic Patterns of the Frontal-Subcortical Circuits in Patients with Mild Cognitive Impairment and Alzheimer’s Disease

Atrophy of the cortical thickness and gray matter volume are regarded as sensitive markers for the early clinical diagnosis of Alzheimer’s disease (AD). This study aimed to investigate differences in atrophy patterns in the frontal-subcortical circuits between MCI and AD, assess whether these differences were essential for the pathologic basis of cognitive impairment. A total of 131 individuals were recruited, including 45 with cognitively normal controls (CN), 46 with MCI, and 40 with AD. FreeSurfer software was used to perform volumetric measurements of the frontal-subcortical circuits from 3.0T magnetic resonance (MR) scans. Data revealed that both MCI and AD subjects had a thinner cortex in the left caudal middle frontal gyrus and the left lateral orbitofrontal gyrus compared with CN individuals. The left lateral orbitofrontal gyrus was also thinner in AD compared with MCI patients. There were no statistically significant differences in the cortical mean curvature among the three groups. Both MCI and AD subjects exhibited smaller bilateral hippocampus volumes compared with CN individuals. The volumes of the bilateral hippocampus and the right putamen were also smaller in AD compared with MCI patients. Logistic regression analyses revealed that the left lateral orbitofrontal gyrus and bilateral hippocampus were risk factors for cognitive impairment. These current results suggest that atrophy was heterogeneous in subregions of the frontal-subcortical circuits in MCI and AD patients. Among these subregions, the reduced thickness of the left lateral orbitofrontal and the smaller volume of the bilateral hippocampus seemed to be markers for predicting cognitive impairment.     

Evaluating Alzheimer’s Disease Progression Using Rate of Regional Hippocampal Atrophy

Alzheimer’s disease (AD) is characterized by neurofibrillary tangle and neuropil thread deposition, which ultimately results in neuronal loss. A large number of magnetic resonance imaging studies have reported a smaller hippocampus in AD patients as compared to healthy elderlies. Even though this difference is often interpreted as atrophy, it is only an indirect measurement. A more direct way of measuring the atrophy is to use repeated MRIs within the same individual. Even though several groups have used this appropriate approach, the pattern of hippocampal atrophy still remains unclear and difficult to relate to underlying pathophysiology. Here, in this longitudinal study, we aimed to map hippocampal atrophy rates in patients with AD, mild cognitive impairment (MCI) and elderly controls. Data consisted of two MRI scans for each subject. The symmetric deformation field between the first and the second MRI was computed and mapped onto the three-dimensional hippocampal surface. The pattern of atrophy rate was similar in all three groups, but the rate was significantly higher in patients with AD than in control subjects. We also found higher atrophy rates in progressive MCI patients as compared to stable MCI, particularly in the antero-lateral portion of the right hippocampus. Importantly, the regions showing the highest atrophy rate correspond to those that were described to have the highest burden of tau deposition. Our results show that local hippocampal atrophy rate is a reliable biomarker of disease stage and progression and could also be considered as a method to objectively evaluate treatment effects.     

Distinct transthyretin oxidation isoform profile in spinal fluid from patients with Alzheimer’s disease and mild cognitive impairment

Background

Transthyretin (TTR), an abundant protein in cerebrospinal fluid (CSF), contains a free, oxidation-prone cysteine residue that gives rise to TTR isoforms. These isoforms may reflect conditions in vivo. Since increased oxidative stress has been linked to neurodegenerative disorders such as Alzheimer’s disease (AD) it is of interest to characterize CSF-TTR isoform distribution in AD patients and controls. Here, TTR isoforms are profiled directly from CSF by an optimized immunoaffinity-mass spectrometry method in 76 samples from patients with AD (n = 37), mild cognitive impairment (MCI, n = 17)), and normal pressure hydrocephalus (NPH, n = 15), as well as healthy controls (HC, n = 7). Fractions of three specific oxidative modifications (S-cysteinylation, S-cysteinylglycinylation, and S-glutathionylation) were quantitated relative to the total TTR protein. Results were correlated with diagnostic information and with levels of CSF AD biomarkers tau, phosphorylated tau, and amyloid β_1-42 peptide.

Results

Preliminary data highlighted the high risk of artifactual TTR modification due to ex vivo oxidation and thus the samples for this study were all collected using strict and uniform guidelines. The results show that TTR is significantly more modified on Cys(10) in the AD and MCI groups than in controls (NPH and HC) (p ≤ 0.0012). Furthermore, the NPH group, while having normal TTR isoform distribution, had significantly decreased amyloid β peptide but normal tau values. No obvious correlations between levels of routine CSF biomarkers for AD and the degree of TTR modification were found.

Conclusions

AD and MCI patients display a significantly higher fraction of oxidatively modified TTR in CSF than the control groups of NPH patients and HC. Quantitation of CSF-TTR isoforms thus may provide diagnostic information in patients with dementia symptoms but this should be explored in larger studies including prospective studies of MCI patients. The development of methods for simple, robust, and reproducible inhibition of in vitro oxidation during CSF sampling and sample handling is highly warranted. In addition to the diagnostic information the possibility of using TTR as a CSF oxymeter is of potential value in studies monitoring disease activity and developing new drugs for neurodegenerative diseases.     

The Relationship between Associative Learning,Transfer Generalization,and Homocysteine Levels in Mild Cognitive Impairment

Previous studies have shown that high total homocysteine levels are associated with Alzheimer''s disease (AD) and mild cognitive impairment (MCI). In this study, we test the relationship between cognitive function and total homocysteine levels in healthy subjects (Global Dementia Rating, CDR = 0) and individuals with MCI (CDR = 0.5). We have used a cognitive task that tests learning and generalization of rules, processes that have been previously shown to rely on the integrity of the striatal and hippocampal regions, respectively. We found that total homocysteine levels are higher in MCI individuals than in healthy controls. Unlike what we expected, we found no difference between MCI subjects and healthy controls in learning and generalization. We conducted further analysis after diving MCI subjects in two groups, depending on their Global Deterioration Scale (GDS) scores: individuals with very mild cognitive decline (vMCD, GDS = 2) and mild cognitive decline (MCD, GDS = 3). There was no difference among the two MCI and healthy control groups in learning performance. However, we found that individuals with MCD make more generalization errors than healthy controls and individuals with vMCD. We found no difference in the number of generalization errors between healthy controls and MCI individuals with vMCD. In addition, interestingly, we found that total homocysteine levels correlate positively with generalization errors, but not with learning errors. Our results are in agreement with prior results showing a link between hippocampal function, generalization performance, and total homocysteine levels. Importantly, our study is perhaps among the first to test the relationship between learning (and generalization) of rules and homocysteine levels in healthy controls and individuals with MCI.     

Altered Oscillation and Synchronization of Default-Mode Network Activity in Mild Alzheimer’s Disease Compared to Mild Cognitive Impairment: An Electrophysiological Study

Some researchers have suggested that the default mode network (DMN) plays an important role in the pathological mechanisms of Alzheimer’s disease (AD). To examine whether the cortical activities in DMN regions show significant difference between mild AD from mild cognitive impairment (MCI), electrophysiological responses were analyzed from 21 mild Alzheimer’s disease (AD) and 21 mild cognitive impairment (MCI) patients during an eyes closed, resting-state condition. The spectral power and functional connectivity of the DMN were estimated using a minimum norm estimate (MNE) combined with fast Fourier transform and imaginary coherence analysis. Our results indicated that source-based EEG maps of resting-state activity showed alterations of cortical spectral power in mild AD when compared to MCI. These alterations are characteristic of attenuated alpha or beta activities in the DMN, as are enhanced delta or theta activities in the medial temporal, inferior parietal, posterior cingulate cortex and precuneus. With regard to altered synchronization in AD, altered functional interconnections were observed as specific connectivity patterns of connection hubs in the precuneus, posterior cingulate cortex, anterior cingulate cortex and medial temporal regions. Moreover, posterior theta and alpha power and altered connectivity in the medial temporal lobe correlated significantly with scores obtained on the Mini-Mental State Examination (MMSE). In conclusion, EEG is a useful tool for investigating the DMN in the brain and differentiating early stage AD and MCI patients. This is a promising finding; however, further large-scale studies are needed.     

Identification of conversion from mild cognitive impairment to Alzheimer's disease using multivariate predictors

Prediction of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of major interest in AD research. A large number of potential predictors have been proposed, with most investigations tending to examine one or a set of related predictors. In this study, we simultaneously examined multiple features from different modalities of data, including structural magnetic resonance imaging (MRI) morphometry, cerebrospinal fluid (CSF) biomarkers and neuropsychological and functional measures (NMs), to explore an optimal set of predictors of conversion from MCI to AD in an Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. After FreeSurfer-derived MRI feature extraction, CSF and NM feature collection, feature selection was employed to choose optimal subsets of features from each modality. Support vector machine (SVM) classifiers were then trained on normal control (NC) and AD participants. Testing was conducted on MCIc (MCI individuals who have converted to AD within 24 months) and MCInc (MCI individuals who have not converted to AD within 24 months) groups. Classification results demonstrated that NMs outperformed CSF and MRI features. The combination of selected NM, MRI and CSF features attained an accuracy of 67.13%, a sensitivity of 96.43%, a specificity of 48.28%, and an AUC (area under curve) of 0.796. Analysis of the predictive values of MCIc who converted at different follow-up evaluations showed that the predictive values were significantly different between individuals who converted within 12 months and after 12 months. This study establishes meaningful multivariate predictors composed of selected NM, MRI and CSF measures which may be useful and practical for clinical diagnosis.