Neuroimaging Biomarkers for Alzheimer's Disease
Currently, over five million Americans suffer with Alzheimer's disease (AD). In the absence of a cure, this number could increase to 13.8 million by 2050. A critical goal of biomedical research is to establish indicators of AD during the preclinical stage (i.e. biomarkers) allowing for early di...
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Published in: | Molecular neurodegeneration Vol. 14; no. 1; pp. 21 - 14 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
England
BioMed Central Ltd
07-06-2019
BioMed Central BMC |
Subjects: | |
Online Access: | Get full text |
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Summary: | Currently, over five million Americans suffer with Alzheimer's disease (AD). In the absence of a cure, this number could increase to 13.8 million by 2050. A critical goal of biomedical research is to establish indicators of AD during the preclinical stage (i.e. biomarkers) allowing for early diagnosis and intervention. Numerous advances have been made in developing biomarkers for AD using neuroimaging approaches. These approaches offer tremendous versatility in terms of targeting distinct age-related and pathophysiological mechanisms such as structural decline (e.g. volumetry, cortical thinning), functional decline (e.g. fMRI activity, network correlations), connectivity decline (e.g. diffusion anisotropy), and pathological aggregates (e.g. amyloid and tau PET). In this review, we survey the state of the literature on neuroimaging approaches to developing novel biomarkers for the amnestic form of AD, with an emphasis on combining approaches into multimodal biomarkers. We also discuss emerging methods including imaging epigenetics, neuroinflammation, and synaptic integrity using PET tracers. Finally, we review the complementary information that neuroimaging biomarkers provide, which highlights the potential utility of composite biomarkers as suitable outcome measures for proof-of-concept clinical trials with experimental therapeutics. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
ISSN: | 1750-1326 1750-1326 |
DOI: | 10.1186/s13024-019-0325-5 |