Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Hubs of belief networks across sociodemographic and ideological groups

Beliefs are essential components of the human mind, as they define personal identity, integration and adaptation to social groups. Most theoretical studies suggest that beliefs are organized as structured networks: the so-called belief system. According to these studies and their empirical implementation using graph-theoretical approaches, a belief is any proposition considered as true by the respondent. In a recent contribution, we introduced a novel operationalization: a proposition is a belief if (1) it is taken to be true; and (2) the subject declares to be willing to hold it even if irrefutable evidence were hypothetically argued against it. Here, we implement this operationalization using a graph theory approach to investigate the network organization of the belief system in a sample of 108 participants, as well as the differences between key ideological (left- vs. right-wingers) and sociodemographic features (younger vs. older, female vs. male). We identified a well-coordinated network of interlocked spiritual, prosocial and nature-related beliefs, which displays a dense core of 10 hub nodes. Moreover, we observed how specific social liberalist beliefs and transcendental or individualistic/prosocial viewpoints are articulated within left- and right-wingers networks or younger and older participants. Interestingly, we observed that females tend to engage in denser belief networks than male respondents. In conclusion, our research expands tangible scientific evidence of the belief system of humans through the network study of belief reports, which in turn opens innovative ways to study belief systems in social and clinical samples

Memory decline evolves independently of disease activity in MS

The natural history of cognitive impairment in multiple sclerosis (MS) and its relationship with disease activity is not well known. In this study, we evaluate a prospective cohort of 44 MS patients who were followed every 3 months for 2 years. Cognitive evaluation was done at baseline and by the end of the study using the Brief Repeatable Battery-Neuropsychology. Clinical evaluation included assessment of new relapses and changes in disability (Extended Disability Status Scale (EDSS)) confirmed at 6 months. RESULTS: We found that verbal memory performance deteriorates after 2 years in patients with MS. These changes were observed in stable and active patients both in terms of relapses and disability progression, even at the beginning of the disease, and in patients with or without cognitive impairment at study entry. Attention and executive functions measured with the symbol digit modality test (SDMT) declined after 2 years in patients with confirmed disability progression. Furthermore, SDMT performance correlated with the EDSS change. CONCLUSIONS: Our findings indicate that verbal memory steadily declines in patients with MS from the beginning of the disease and independently of other parameters of disease activity

A computational analysis of protein-protein interaction networks in neurodegenerative diseases

<p>Abstract</p> <p>Background</p> <p>Recent developments have meant that network theory is making an important contribution to the topological study of biological networks, such as protein-protein interaction (PPI) networks. The identification of differentially expressed genes in DNA array experiments is a source of information regarding the molecular pathways involved in disease. Thus, considering PPI analysis and gene expression studies together may provide a better understanding of multifactorial neurodegenerative diseases such as Multiple Sclerosis (MS) and Alzheimer disease (AD). The aim of this study was to assess whether the parameters of degree and betweenness, two fundamental measures in network theory, are properties that differentiate between implicated (seed-proteins) and non-implicated nodes (neighbors) in MS and AD. We used experimentally validated PPI information to obtain the neighbors for each seed group and we studied these parameters in four networks: MS-blood network; MS-brain network; AD-blood network; and AD-brain network.</p> <p>Results</p> <p>Specific features of seed-proteins were revealed, whereby they displayed a lower average degree in both diseases and tissues, and a higher betweenness in AD-brain and MS-blood networks. Additionally, the heterogeneity of the processes involved indicate that these findings are not pathway specific but rather that they are spread over different pathways.</p> <p>Conclusion</p> <p>Our findings show differential centrality properties of proteins whose gene expression is impaired in neurodegenerative diseases.</p

Fractal dimension analysis of grey matter in multiple sclerosis

The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of a complex object. Among other applications, FD has been used to identify abnormalities of the human brain in conventional magnetic resonance imaging (MRI), including white matter abnormalities in patients with Multiple Sclerosis (MS). Extensive grey matter (GM) pathology has been recently identified in MS and it appears to be a key factor in long-term disability. The aim of the present work was to assess whether FD measurement of GM in T1 MRI sequences can identify GM abnormalities in patients with MS in the early phase of the disease. A voxel-based morphometry approach optimized for MS was used to obtain the segmented brain, where we later calculated the three-dimensional FD of the GM in MS patients and healthy controls.We found that patients with MS had a significant increase in the FD of the GM compared to controls. Such differences were present even in patients with short disease durations, including patients with first attacks of MS. In addition, the FD of the GM correlated with T1 and T2 lesion load, but not with GM atrophy or disability. The FD abnormalities of the GM here detected differed from the previously published FD of the white matter in MS, suggesting that different pathological processes were taking place in each structure. These results indicate that GM morphology is abnormal in patients with MS and that this alteration appears early in the course of the disease

In vivo staging of regional amyloid deposition

Objectives: To estimate a regional progression pattern of amyloid deposition from cross-sectional amyloid-sensitive PET data and evaluate its potential for in vivo staging of an individual's amyloid pathology. Methods: Multiregional analysis of florbetapir (18F-AV45)–PET data was used to determine individual amyloid distribution profiles in a sample of 667 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including cognitively normal older individuals (CN) as well as patients with mild cognitive impairment and Alzheimer disease (AD) dementia. The frequency of regional amyloid positivity across CN individuals was used to construct a 4-stage model of progressing amyloid pathology, and individual distribution profiles were used to evaluate the consistency of this hierarchical stage model across the full cohort. Results: According to a 4-stage model, amyloid deposition begins in temporobasal and frontomedial areas, and successively affects the remaining associative neocortex, primary sensory-motor areas and the medial temporal lobe, and finally the striatum. Amyloid deposition in these brain regions showed a highly consistent hierarchical nesting across participants, where only 2% exhibited distribution profiles that deviated from the staging scheme. The earliest in vivo amyloid stages were mostly missed by conventional dichotomous classification approaches based on global florbetapir-PET signal, but were associated with significantly reduced CSF Aβ42 levels. Advanced in vivo amyloid stages were most frequent in patients with AD and correlated with cognitive impairment in individuals without dementia. Conclusions: The highly consistent regional hierarchy of PET-evidenced amyloid deposition across participants resembles neuropathologic observations and suggests a predictable regional sequence that may be used to stage an individual's progress of amyloid pathology in vivo

Retinal nerve fiber layer atrophy is associated with physical and cognitive disability in multiple sclerosis

Studying axonal loss in the retina is a promising biomarker for multiple sclerosis (MS). Our aim was to compare optical coherence tomography (OCT) and Heidelberg retinal tomography (HRT) techniques to measure the thickness of the retinal nerve fiber layer (RNFL) in patients with MS, and to explore the relationship between changes in the RNFL thickness with physical and cognitive disability. We studied 52 patients with MS and 18 proportionally matched controls by performing neurological examination, neuropsychological evaluation using the Brief Repetitive Battery-Neuropsychology and RNFL thickness measurement using OCT and HRT. RESULTS: We found that both OCT and HRT could define a reduction in the thickness of the RNFL in patients with MS compared with controls, although both measurements were weakly correlated, suggesting that they might measure different aspects of the tissue changes in MS. The degree of RNFL atrophy was correlated with cognitive disability, mainly with the symbol digit modality test (r=0.754, P<0.001). Moreover, temporal quadrant RNFL atrophy measured with OCT was associated with physical disability. CONCLUSION: In summary, both OCT and HRT are able to detect thinning of the RNFL, but OCT seems to be the most sensitive technique to identify changes associated with MS evolution

Decreased meta-memory is associated with early tauopathy in cognitively unimpaired older adults

The ability to accurately judge memory efficiency (meta-memory monitoring) for newly learned (episodic) information, is decreased in older adults and even worse in Alzheimer's disease (AD), whereas no differences have been found for semantic meta-memory. The pathological substrates of this phenomenon are poorly understood. Here, we examine the association between meta-memory monitoring for episodic and semantic information to the two major proteinopathies in AD: amyloid (Aβ) and tau pathology in a group of cognitively unimpaired older adults. All participants underwent multi-tracer PET and meta-memory monitoring was assessed using a feeling-of-knowing (FOK) task for non-famous (episodic) and famous (semantic) face-name pairs. Whole brain voxel-wise correlations between meta-memory and PET data were conducted (controlling for memory), as well as confirmatory region-of-interest analyses. Participants had reduced episodic FOK compared to semantic FOK. Decreased episodic FOK was related to tauopathy in the medial temporal lobe regions, including the entorhinal cortex and temporal pole, whereas decreased semantic FOK was related to increased tau in regions associated with the semantic knowledge network. No association was found with Aβ-pathology. Alterations in the ability to accurately judge memory efficiency (in the absence of memory decline) may be a sensitive clinical indicator of AD pathophysiology in the pre-symptomatic phase

Computational classifiers for predicting the short-term course of Multiple sclerosis

The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). METHODS: We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. RESULTS: We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. CONCLUSIONS: The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden

Disruption of functional connectivity between brain regions may represent an early functional consequence of β-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorodeoxyglucose-positron emission tomography. In healthy subjects without cognitive symptoms and patients with mild cognitive impairment, we used positron emission tomography to assess amyloid burden and cerebral glucose metabolism, structural magnetic resonance imaging to quantify atrophy and novel resting state functional magnetic resonance imaging processing methods to calculate whole-brain connectivity. Significant disruptions of whole-brain connectivity were found in amyloid-positive patients with mild cognitive impairment in typical cortical hubs (posterior cingulate cortex/precuneus), strongly overlapping with regional hypometabolism. Subtle connectivity disruptions and hypometabolism were already present in amyloid-positive asymptomatic subjects. Voxel-based morphometry measures indicate that these findings were not solely a consequence of regional atrophy. Whole-brain connectivity values and metabolism showed a positive correlation with each other and a negative correlation with amyloid burden. These results indicate that disruption of functional connectivity and hypometabolism may represent early functional consequences of emerging molecular Alzheimer's disease pathology, evolving prior to clinical onset of dementia. The spatial overlap between hypometabolism and disruption of connectivity in cortical hubs points to a particular susceptibility of these regions to early Alzheimer's-type neurodegeneration and may reflect a link between synaptic dysfunction and functional disconnection