Advances in therapeutic strategies for Alzheimer's disease that lead to even small delays in onset and progression of the condition would significantly reduce the global burden of the disease. To ...effectively test compounds for Alzheimer's disease and bring therapy to individuals as early as possible there is an urgent need for collaboration between academic institutions, industry and regulatory organizations for the establishment of standards and networks for the identification and qualification of biological marker candidates. Biomarkers are needed to monitor drug safety, to identify individuals who are most likely to respond to specific treatments, to stratify presymptomatic patients and to quantify the benefits of treatments. Biomarkers that achieve these characteristics should enable objective business decisions in portfolio management and facilitate regulatory approval of new therapies.
To describe the patterns of cortical and subcortical changes in amyotrophic lateral sclerosis (ALS) stratified for the C9orf72 genotype.
A prospective, single-center, single-protocol, gray and white ...matter magnetic resonance case-control imaging study was undertaken with 30 C9orf72-negative patients with ALS, 9 patients with ALS carrying the C9orf72 hexanucleotide repeat expansion, and 44 healthy controls. Tract-based spatial statistics of multiple white matter diffusion parameters, cortical thickness measurements, and voxel-based morphometry analyses were carried out. All patients underwent comprehensive genetic and neuropsychological profiling.
A congruent pattern of cortical and subcortical involvement was identified in those with the C9orf72 genotype, affecting fusiform, thalamic, supramarginal, and orbitofrontal regions and the Broca area. White matter abnormalities in the C9orf72-negative group were relatively confined to corticospinal and cerebellar pathways with limited extramotor expansion. The body of the corpus callosum and superior motor tracts were affected in both ALS genotypes.
Extensive cortical and subcortical frontotemporal involvement was identified in association with the C9orf72 genotype, compared to the relatively limited extramotor pathology in patients with C9orf72-negative ALS. The distinctive, genotype-specific pathoanatomical patterns are consistent with the neuropsychological profile of the 2 ALS cohorts. Our findings suggest that previously described extramotor changes in ALS could be largely driven by those with the C9orf72 genotype.
Abstract Functional magnetic resonance imaging (fMRI) of default mode network (DMN) brain activity during resting is recently gaining attention as a potential noninvasive biomarker to diagnose ...incipient Alzheimer's disease. The aim of this study was to determine which method of data processing provides highest diagnostic power and to define metrics to further optimize the diagnostic value. fMRI was acquired in 21 healthy subjects, 17 subjects with mild cognitive impairment and 15 patients with Alzheimer's disease (AD) and data evaluated both with volumes of interest (VOI)-based signal time course evaluations and independent component analyses (ICA). The first approach determines the amount of DMN region interconnectivity (as expressed with correlation coefficients); the second method determines the magnitude of DMN coactivation. Apolipoprotein E (ApoE) genotyping was available in 41 of the subjects examined. Diagnostic power (expressed as accuracy) of data of a single DMN region in independent component analyses was 64%, that of a single correlation of time courses between 2 DMN regions was 71%, respectively. With multivariate analyses combining both methods of analysis and data from various regions, accuracy could be increased to 97% (sensitivity 100%, specificity 95%). In nondemented subjects, no significant differences in activity within DMN could be detected comparing ApoE ε4 allele carriers and ApoE ε4 allele noncarriers. However, there were some indications that fMRI might yield useful information given a larger sample. Time course correlation analyses seem to outperform independent component analyses in the identification of patients with Alzheimer's disease. However, multivariate analyses combining both methods of analysis by considering the activity of various parts of the DMN as well as the interconnectivity between these regions are required to achieve optimal and clinically acceptable diagnostic power.
Abstract The current study tested the accuracy of primary MRI and cerebrospinal fluid (CSF) biomarker candidates and neuropsychological tests for predicting the conversion from mild cognitive ...impairment (MCI) to Alzheimer's disease (AD) dementia. In a cross-validation paradigm, predictor models were estimated in the training set of AD (N = 81) and elderly control subjects (N = 101). A combination of CSF t-tau/Aβ1-4 ratio and MRI biomarkers or neuropsychological tests (free recall and trail making test B (TMT-B)) showed the best statistical fit in the AD vs. HC comparison, reaching a classification accuracy of up to 64% when applied to the prediction of MCI conversion (3.3-year observation interval, mean = 2.3 years). However, several single-predictor models showed a predictive accuracy of MCI conversion comparable to that of any multipredictor model. The best single predictors were right entorhinal cortex (prediction accuracy = 68.5% (95% CI (59.5, 77.4))) and TMT-B test (prediction accuracy 64.6% (95% CI (55.5, 73.4%))). In conclusion, short-term conversion to AD is predicted by single marker models to a comparable degree as by multimarker models in amnestic MCI subjects.
Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical ...studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these.
The study of multiple indices of diffusion, including axial (DA), radial (DR) and mean diffusion (MD), as well as fractional anisotropy (FA), enables WM damage in Alzheimer's disease (AD) to be ...assessed in detail. Here, tract-based spatial statistics (TBSS) were performed on scans of 40 healthy elders, 19 non-amnestic MCI (MCIna) subjects, 14 amnestic MCI (MCIa) subjects and 9 AD patients. Significantly higher DA was found in MCIna subjects compared to healthy elders in the right posterior cingulum/precuneus. Significantly higher DA was also found in MCIa subjects compared to healthy elders in the left prefrontal cortex, particularly in the forceps minor and uncinate fasciculus. In the MCIa versus MCIna comparison, significantly higher DA was found in large areas of the left prefrontal cortex. For AD patients, the overlap of FA and DR changes and the overlap of FA and MD changes were seen in temporal, parietal and frontal lobes, as well as the corpus callosum and fornix. Analysis of differences between the AD versus MCIna, and AD versus MCIa contrasts, highlighted regions that are increasingly compromised in more severe disease stages. Microstructural damage independent of gross tissue loss was widespread in later disease stages. Our findings suggest a scheme where WM damage begins in the core memory network of the temporal lobe, cingulum and prefrontal regions, and spreads beyond these regions in later stages. DA and MD indices were most sensitive at detecting early changes in MCIa.
Extensive research has demonstrated that rs1360780, a common single nucleotide polymorphism within the FKBP5 gene, interacts with early‐life stress in predicting psychopathology. Previous results ...suggest that carriers of the TT genotype of rs1360780 who were exposed to child abuse show differences in structure and functional activation of emotion‐processing brain areas belonging to the salience network. Extending these findings on intermediate phenotypes of psychopathology, we examined if the interaction between rs1360780 and child abuse predicts resting‐state functional connectivity (rsFC) between the amygdala and other areas of the salience network. We analyzed data of young European adults from the general population (N = 774; mean age = 18.76 years) who took part in the IMAGEN study. In the absence of main effects of genotype and abuse, a significant interaction effect was observed for rsFC between the right centromedial amygdala and right posterior insula (p < .025, FWE‐corrected), which was driven by stronger rsFC in TT allele carriers with a history of abuse. Our results suggest that the TT genotype of rs1360780 may render individuals with a history of abuse more vulnerable to functional changes in communication between brain areas processing emotions and bodily sensations, which could underlie or increase the risk for psychopathology.
In 774 young European adults, we examined if child abuse and rs1360780 of the FKBP5 gene interact in predicting resting‐state functional connectivity (rsFC) between the amygdala and other areas of the salience network. An interaction was found in rsFC with the right posterior insula, driven by stronger rsFC in TT allele carriers with a history of abuse. After exposure to childhood abuse, individuals with the rs1360780 TT genotype may become more vulnerable to develop psychopathology due to altered amygdala functional connectivity.
Background The orbitofrontal cortex (OFC) plays a crucial role in emotion-processing circuits and should therefore also be included in models of the pathophysiology of major depression. The aim of ...this study was to compare the functional connectivity of the OFC during emotion processing in patients with major depression and healthy control subjects. Methods Twenty-five untreated patients with major depression and 15 healthy control subjects were investigated using a functional magnetic resonance imaging face-matching task. Results Dorsal anterior cingulate cortex, precuneus, and cerebellum activity showed less connectivity with the OFC in patients than in control subjects. In contrast, functional connectivity between the OFC and the right dorsolateral prefrontal cortex (DLPFC), right inferior frontal operculum, and left motor areas was increased in patients compared with healthy control subjects. Conclusions The OFC plays a key role in the pathophysiology of major depression. The observed imbalance of OFC connectivity seems to represent a neural mechanism of the processing bias. From a neurobiological point of view, the uncoupling of precuneus and gyrus cinguli activity from the OFC might be associated with problems in the regulation of self-schemas, whereas the increased connectivity of the DLPFC to the OFC might represent a higher neural response to negative stimuli.
The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of ...systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.
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