Hierarchical Ensemble of Multi-level Classifiers for Diagnosis of Alzheimer’s Disease

2012 ◽  
pp. 27-35 ◽  
Author(s):  
Manhua Liu ◽  
Daoqiang Zhang ◽  
Pew-Thian Yap ◽  
Dinggang Shen
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Multi Level

Discriminative analysis of early Alzheimer's disease using multi-modal imaging and multi-level characterization with multi-classifier (M3)

NeuroImage ◽  
2012 ◽  
Vol 59 (3) ◽  
pp. 2187-2195 ◽  
Author(s):  
Zhengjia Dai ◽  
Chaogan Yan ◽  
Zhiqun Wang ◽  
Jinhui Wang ◽  
Mingrui Xia ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Multi Level ◽  
Discriminative Analysis ◽  
Early Alzheimer’S Disease

scholarly journals An Integrative Multi-omics Approach Reveals New Central Nervous System Pathway Alterations in Alzheimer’s Disease

2020 ◽  
Author(s):  
Christopher Clark ◽  
Loïc Dayon ◽  
Mojgan Masoodi ◽  
Gene L Bowman ◽  
Julius Popp
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Monocyte Chemoattractant Protein 1 ◽  
Individual Variations ◽  
Interleukin 15 ◽  
Multi Level ◽  
One Carbon Metabolism ◽  
Personalized Diagnosis ◽  
Normal Cognition ◽  
Multiple Interactions

Abstract Background: Multiple pathophysiological processes have been described in Alzheimer’s disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood, however. We tested the hypothesis that cerebrospinal fluid (CSF) integrative multi-omics analysis highlights novel interacting pathway alterations in AD.Methods: We performed multi-level CSF omics in a well-characterized cohort of older adults including subjects with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analysed applying Elastic-net regression and Multi-Omics Factor Analysis followed by pathway enrichment. Multivariate analysis was used to select best predictive models of AD pathology and cognitive decline.Results: Multi-omics integration identified five major dimensions of heterogenicity explaining the variance within the cohort and differentially associated with AD . Further analysis exposed multiple interactions between single ‘omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response and extracellular matrix signalling pathways in association with AD. Further, combinations of four selected molecules significantly improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1). Conclusions: Applying an integrative multi-omics approach we confirmed previously reported associations with AD pathology and report new molecular and pathways alterations. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.

scholarly journals Deep Learning for Alzheimer’s Disease Drug Repurposing using Knowledge Graph and Multi-level Evidence

2021 ◽  
Author(s):  
Kang-Lin Hsieh ◽  
German Plascencia-Villa ◽  
Ko-Hong Lin ◽  
George Perry ◽  
Xiaoqian Jiang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Development ◽  
Neuronal Response ◽  
Drug Combinations ◽  
Graph Representation ◽  
Knowledge Graph ◽  
Representation Model ◽  
Pharmacological Interactions ◽  
Multi Level

ABSTRACTDeveloping drugs for treating Alzheimer’s disease (AD) has been extremely challenging and costly due to limited knowledge on underlying biological mechanisms and therapeutic targets. Repurposing drugs or their combination has shown potential in accelerating drug development due to the reduced drug toxicity while targeting multiple pathologies. To address the challenge in AD drug development, we developed a multi-task machine learning pipeline to integrate a comprehensive knowledge graph on biological/pharmacological interactions and multi-level evidence on drug efficacy, to identify repurposable drugs and their combination candidates. We developed and computationally validated a heterogeneous graph representation model with transfer learning from universal biomedical databases and with joint optimization with AD risk genes. Using the drug embedding from the heterogeneous graph representation model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, mechanistic efficacy in preclinical models, population-based treatment effect, and Phase II/III clinical trials. We experimentally validated the top-ranked candidates in neuronal cells, identifying drug combinations with efficacy in reducing oxidative stress and safety in maintaining neuronal viability and morphology. Our neuronal response experiments confirmed several biologically efficacious drug combinations (e.g., Galantamine + Mifepristone). This pipeline showed that harmonizing heterogeneous and complementary data/knowledge, including human interactome, transcriptome patterns, experimental efficacy, and real-world patient data shed light on the drug development of complex diseases.

scholarly journals Narrative discourse in Persian-speaking patients with mild Alzheimer’s disease

2019 ◽  
Vol 13 (2) ◽  
pp. 225-231 ◽  
Author(s):  
Masumeh Farivar ◽  
Zahra Ghayoumi Anaraki ◽  
Fatemeh Derakhshandeh ◽  
Nahid Baharloei ◽  
Marziyeh Poorjavad
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Narrative Discourse ◽  
Syntactic Complexity ◽  
Specific Subject ◽  
Healthy Elderly ◽  
Picture Description ◽  
Multi Level ◽  
Level Analysis

ABSTRACT. Despite the significance of discourse impairments, they have not been thoroughly investigated in Persian-speaking patients with Alzheimer’s disease (AD). Objective: the aim of this study was to perform a multi-level analysis of narrative discourse in Persian-speaking patients with mild AD and to compare them with healthy elderly. Methods: the study included 14 older adults with mild AD and a matched group of 14 healthy elderly. Using a storytelling task based on serial pictures, both macro- and micro-linguistic aspects of narrative discourse were assessed. Cohesion ratio and coherence were investigated as macrolinguistic dimensions of discourse. The studied microlinguistic features included syntactic complexity and verbal errors (mostly involving phonological and semantic paraphasias and mazes). Severity of AD was determined using the Cognitive Dementia Rating (CDR). Results: there were significant differences between the groups regarding cohesion ratio (0.9 ± 0.34 vs. 1.29 ± 0.45, p = 0.02) and coherence scores (2.43 ± 0.41 vs. 3.02 ± 0.81, p = 0.03). Verbal errors and syntactic complexity did not differ significantly between the groups. Conclusion: Persian-speaking patients with mild AD show macrolinguistic impairments in producing discourses based on picture description. Therefore, intervention protocols should focus on the ability to organize information on a specific subject and also to connect sentences produced using appropriate cohesive ties.

Cognitive control constrains memory attributions

2019 ◽  
Vol 42 ◽  
Author(s):  
Colleen M. Kelley ◽  
Larry L. Jacoby
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cognitive Control

Abstract Cognitive control constrains retrieval processing and so restricts what comes to mind as input to the attribution system. We review evidence that older adults, patients with Alzheimer's disease, and people with traumatic brain injury exert less cognitive control during retrieval, and so are susceptible to memory misattributions in the form of dramatic levels of false remembering.

Formation of paired helical filaments in Alzheimer's disease

1984 ◽  
Vol 42 ◽  
pp. 302-303
Author(s):  
J. Metuzals ◽  
D. F. Clapin ◽  
V. Montpetit
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Frontal Lobe ◽  
Giant Axon ◽  
Paired Helical Filaments ◽  
Normal Brain ◽  
Protein Assemblies ◽  
Electron Microscopic ◽  
Helical Symmetry ◽  
Structural Levels

Information on the conformation of paired helical filaments (PHF) and the neurofilamentous (NF) network is essential for an understanding of the mechanisms involved in the formation of the primary lesions of Alzheimer's disease (AD): tangles and plaques. The structural and chemical relationships between the NF and the PHF have to be clarified in order to discover the etiological factors of this disease. We are investigating by stereo electron microscopic and biochemical techniques frontal lobe biopsies from patients with AD and squid giant axon preparations. The helical nature of the lesion in AD is related to pathological alterations of basic properties of the nervous system due to the helical symmetry that exists at all hierarchic structural levels in the normal brain. Because of this helical symmetry of NF protein assemblies and PHF, the employment of structure reconstruction techniques to determine the conformation, particularly the handedness of these structures, is most promising. Figs. 1-3 are frontal lobe biopsies.

Computer-aided methods for 3-D visualization of serial sections and thick biological specimens

1992 ◽  
Vol 50 (2) ◽  
pp. 1060-1061
Author(s):  
Mark Ellisman ◽  
Maryann Martone ◽  
Gabriel Soto ◽  
Eleizer Masliah ◽  
David Hessler ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Three Dimensional ◽  
Neuritic Plaque ◽  
Dimensional Structure ◽  
Data Sets ◽  
Molecular Physiology ◽  
Research Activities ◽  
Computer Aided ◽  
Dimensional Reconstruction

Structurally-oriented biologists examine cells, tissues, organelles and macromolecules in order to gain insight into cellular and molecular physiology by relating structure to function. The understanding of these structures can be greatly enhanced by the use of techniques for the visualization and quantitative analysis of three-dimensional structure. Three projects from current research activities will be presented in order to illustrate both the present capabilities of computer aided techniques as well as their limitations and future possibilities.The first project concerns the three-dimensional reconstruction of the neuritic plaques found in the brains of patients with Alzheimer's disease. We have developed a software package “Synu” for investigation of 3D data sets which has been used in conjunction with laser confocal light microscopy to study the structure of the neuritic plaque. Tissue sections of autopsy samples from patients with Alzheimer's disease were double-labeled for tau, a cytoskeletal marker for abnormal neurites, and synaptophysin, a marker of presynaptic terminals.

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