Network based biomarkers in Alzheimer's disease: review and future directions
By 2050 it is estimated that the number of worldwide Alzheimer’s (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitiv...
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2014-02-01
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doaj-856c1aa55eab4fa2a9d953ac5e778f912020-11-24T22:57:03ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652014-02-01610.3389/fnagi.2014.0001275530Network based biomarkers in Alzheimer's disease: review and future directionsJaime eGomez-Ramirez0Jaime eGomez-Ramirez1Jinglong eWu2Universidad Politécnica de MadridOkayama UniversityOkayama UniversityBy 2050 it is estimated that the number of worldwide Alzheimer’s (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitive tools for the early diagnoses of AD. The complex etiology and multiple pathogenesis of AD calls for a system-level understanding of the currently available biomarkers and the study of new biomarkers via network-based modeling of heterogeneous data types. In this review, we summarize recent research on the study of AD as a connectivity syndrome. We argue that a network-based approach in biomarker discovery, will provide key insights to fully understand the network degeneration hypothesis (disease starts in specific network areas and progressively spreads to connected areas of the initial loci-networks) with a potential impact for early diagnosis and disease-modifyig treatments. We introduce a new framework for the quantitative study of biomarkers that can help shorten the transition between academic research and clinical diagnosis in AD.http://journal.frontiersin.org/Journal/10.3389/fnagi.2014.00012/fullDefault Mode Networkpositron emission tomography (PET)amyloid-beta peptideBayesian inferenceModel selectionAD |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jaime eGomez-Ramirez Jaime eGomez-Ramirez Jinglong eWu |
spellingShingle |
Jaime eGomez-Ramirez Jaime eGomez-Ramirez Jinglong eWu Network based biomarkers in Alzheimer's disease: review and future directions Frontiers in Aging Neuroscience Default Mode Network positron emission tomography (PET) amyloid-beta peptide Bayesian inference Model selection AD |
author_facet |
Jaime eGomez-Ramirez Jaime eGomez-Ramirez Jinglong eWu |
author_sort |
Jaime eGomez-Ramirez |
title |
Network based biomarkers in Alzheimer's disease: review and future directions |
title_short |
Network based biomarkers in Alzheimer's disease: review and future directions |
title_full |
Network based biomarkers in Alzheimer's disease: review and future directions |
title_fullStr |
Network based biomarkers in Alzheimer's disease: review and future directions |
title_full_unstemmed |
Network based biomarkers in Alzheimer's disease: review and future directions |
title_sort |
network based biomarkers in alzheimer's disease: review and future directions |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Aging Neuroscience |
issn |
1663-4365 |
publishDate |
2014-02-01 |
description |
By 2050 it is estimated that the number of worldwide Alzheimer’s (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitive tools for the early diagnoses of AD. The complex etiology and multiple pathogenesis of AD calls for a system-level understanding of the currently available biomarkers and the study of new biomarkers via network-based modeling of heterogeneous data types. In this review, we summarize recent research on the study of AD as a connectivity syndrome. We argue that a network-based approach in biomarker discovery, will provide key insights to fully understand the network degeneration hypothesis (disease starts in specific network areas and progressively spreads to connected areas of the initial loci-networks) with a potential impact for early diagnosis and disease-modifyig treatments. We introduce a new framework for the quantitative study of biomarkers that can help shorten the transition between academic research and clinical diagnosis in AD. |
topic |
Default Mode Network positron emission tomography (PET) amyloid-beta peptide Bayesian inference Model selection AD |
url |
http://journal.frontiersin.org/Journal/10.3389/fnagi.2014.00012/full |
work_keys_str_mv |
AT jaimeegomezramirez networkbasedbiomarkersinalzheimer39sdiseasereviewandfuturedirections AT jaimeegomezramirez networkbasedbiomarkersinalzheimer39sdiseasereviewandfuturedirections AT jinglongewu networkbasedbiomarkersinalzheimer39sdiseasereviewandfuturedirections |
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