Dataset Information

Apolipoprotein D Upregulation in Alzheimer's Disease but Not Frontotemporal Dementia.

ABSTRACT: Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are the two common forms of dementia. FTD syndromes are characterized by lobar atrophy (frontotemporal lobar degeneration or FTLD) and the presence of either cellular TDP43 (FTLD-TDP), tau (FTLD-tau), or FUS aggregates, while extracellular ?-amyloid plaques and hyperphosphorylated tau tangles develop in AD. Oxidative stress can induce these pathological modifications in disease models, and is thought to play a role in these syndromes. Apolipoprotein D (apoD) is a glial-expressed lipocalin known to protect against oxidative stress, with increased levels in AD, supporting a protective role. The expression of apoD has not been studied in FTLD. This study assesses apoD expression in FTLD-TDP and FTLD-tau in comparison to AD and controls. It also analyzes the effect of apoD on TARDBP (TDP43 gene) and ?-amyloid precursor protein (APP). The expression of apoD was analyzed by Western blotting in FTLD-TDP, FTLD-tau, AD, and control post-mortem brain tissue. An apoD-overexpressing cell model was used to study the impact of increased apoD on APP and TARDBP expression. We confirm that apoD expression was increased in AD but surprisingly it was not affected in either of the two main pathological forms of FTLD. Under oxidative stress conditions, apoD had no effect on TDP43 expression but it did decrease APP expression. This suggests that apoD does not act as a neuroprotective factor in FTLD in the same way as in AD. This could contribute to the more rapid degeneration observed in FTLD.

SUBMITTER: Bhatia S

PROVIDER: S-EPMC6344390 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Apolipoprotein D Upregulation in Alzheimer's Disease but Not Frontotemporal Dementia.

Bhatia Surabhi S Kim Woojin Scott WS Shepherd Claire E CE Halliday Glenda M GM

Journal of molecular neuroscience : MN 20181122 1

Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are the two common forms of dementia. FTD syndromes are characterized by lobar atrophy (frontotemporal lobar degeneration or FTLD) and the presence of either cellular TDP43 (FTLD-TDP), tau (FTLD-tau), or FUS aggregates, while extracellular β-amyloid plaques and hyperphosphorylated tau tangles develop in AD. Oxidative stress can induce these pathological modifications in disease models, and is thought to play a role in these syndromes. Ap ...[more]

PMID: 30467822

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Project description:Oculomotor behavior can provide insight into the integrity of widespread cortical networks, which may contribute to the differential diagnosis between Alzheimer's disease and frontotemporal dementia. Three groups of patients with Alzheimer's disease, behavioral variant of frontotemporal dementia (bvFTD) and semantic variant of primary progressive aphasia (svPPA) and a sample of cognitively unimpaired elders underwent an eye-tracking evaluation. All participants in the discovery sample, including controls, had a biomarker-supported diagnosis. Oculomotor correlates of neuropsychology and brain metabolism evaluated with 18F-FDG PET were explored. Machine-learning classification algorithms were trained for the differentiation between Alzheimer's disease, bvFTD and controls. A total of 93 subjects (33 Alzheimer's disease, 24 bvFTD, seven svPPA, and 29 controls) were included in the study. Alzheimer's disease was the most impaired group in all tests and displayed specific abnormalities in some visually-guided saccade parameters, as pursuit error and horizontal prosaccade latency, which are theoretically closely linked to posterior brain regions. BvFTD patients showed deficits especially in the most cognitively demanding tasks, the antisaccade and memory saccade tests, which require a fine control from frontal lobe regions. SvPPA patients performed similarly to controls in most parameters except for a lower number of correct memory saccades. Pursuit error was significantly correlated with cognitive measures of constructional praxis and executive function and metabolism in right posterior middle temporal gyrus. The classification algorithms yielded an area under the curve of 97.5% for the differentiation of Alzheimer's disease vs. controls, 96.7% for bvFTD vs. controls, and 92.5% for Alzheimer's disease vs. bvFTD. In conclusion, patients with Alzheimer's disease, bvFTD and svPPA exhibit differentiating oculomotor patterns which reflect the characteristic neuroanatomical distribution of pathology of each disease, and therefore its assessment can be useful in their diagnostic work-up. Machine learning approaches can facilitate the applicability of eye-tracking in clinical practice.

Project description:BackgroundIn a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patterns of atrophy among three FTD clinical syndromes including behavioral variant FTD (bvFTD), non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA) give rise to the need for classification models at the individual level. In this study, we aimed to classify each individual subject into one of the diagnostic categories in a hierarchical manner by employing a machine learning-based classification method.MethodsWe recruited 143 patients with FTD, 50 patients with Alzheimer's disease (AD) dementia, and 146 cognitively normal subjects. All subjects underwent a three-dimensional volumetric brain magnetic resonance imaging (MRI) scan, and cortical thickness was measured using FreeSurfer. We applied the Laplace Beltrami operator to reduce noise in the cortical thickness data and to reduce the dimension of the feature vector. Classifiers were constructed by applying both principal component analysis and linear discriminant analysis to the cortical thickness data. For the hierarchical classification, we trained four classifiers using different pairs of groups: Step 1 - CN vs. FTD + AD, Step 2 - FTD vs. AD, Step 3 - bvFTD vs. PPA, Step 4 - svPPA vs. nfvPPA. To evaluate the classification performance for each step, we used a10-fold cross-validation approach, performed 1000 times for reliability.ResultsThe classification accuracy of the entire hierarchical classification tree was 75.8%, which was higher than that of the non-hierarchical classifier (73.0%). The classification accuracies of steps 1-4 were 86.1%, 90.8%, 86.9%, and 92.1%, respectively. Changes in the right frontotemporal area were critical for discriminating behavioral variant FTD from PPA. The left frontal lobe discriminated nfvPPA from svPPA, while the bilateral anterior temporal regions were critical for identifying svPPA.ConclusionsIn the present study, our automated classifier successfully classified FTD clinical subtypes with good to excellent accuracy. Our classifier may help clinicians diagnose FTD subtypes with subtle cortical atrophy and facilitate appropriate specific interventions.

Project description:BackgroundAlzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) cause distinct atrophy and functional disruptions within two major intrinsic brain networks, namely the default network and the salience network, respectively. It remains unclear if inter-network relationships and whole-brain network topology are also altered and underpin cognitive and social-emotional functional deficits.MethodsIn total, 111 participants (50 AD, 14 bvFTD, and 47 age- and gender-matched healthy controls) underwent resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessments. Functional connectivity was derived among 144 brain regions of interest. Graph theoretical analysis was applied to characterize network integration, segregation, and module distinctiveness (degree centrality, nodal efficiency, within-module degree, and participation coefficient) in AD, bvFTD, and healthy participants. Group differences in graph theoretical measures and empirically derived network community structures, as well as the associations between these indices and cognitive performance and neuropsychiatric symptoms, were subject to general linear models, with age, gender, education, motion, and scanner type controlled.ResultsOur results suggested that AD had lower integration in the default and control networks, while bvFTD exhibited disrupted integration in the salience network. Interestingly, AD and bvFTD had the highest and lowest degree of integration in the thalamus, respectively. Such divergence in topological aberration was recapitulated in network segregation and module distinctiveness loss, with AD showing poorer modular structure between the default and control networks, and bvFTD having more fragmented modules in the salience network and subcortical regions. Importantly, aberrations in network topology were related to worse attention deficits and greater severity in neuropsychiatric symptoms across syndromes.ConclusionsOur findings underscore the reciprocal relationships between the default, control, and salience networks that may account for the cognitive decline and neuropsychiatric symptoms in dementia.

Dataset Information

Apolipoprotein D Upregulation in Alzheimer's Disease but Not Frontotemporal Dementia.

Publications

Apolipoprotein D Upregulation in Alzheimer's Disease but Not Frontotemporal Dementia.

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