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Predicting MCI outcome with clinically available MRI and CSF biomarkers

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TLDR
In this paper, the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI).
Abstract
Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8– 4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. Neurology ® 2011;77:1619–1628

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Clinical validity of delayed recall tests as a gateway biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

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Combining Polygenic Hazard Score With Volumetric MRI and Cognitive Measures Improves Prediction of Progression From Mild Cognitive Impairment to Alzheimer's Disease

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Multimodal Prediction of Dementia with up to 10 Years Follow Up: The Gothenburg MCI Study

TL;DR: Neuropsychological tests, CSF markers, and hippocampal volume predicted conversion from MCI to AD and general dementia and the absence of pathological markers provided a long-time protection from dementia.
Journal ArticleDOI

Neuroimaging Results Impose New Views on Alzheimer’s Disease—the Role of Amyloid Revised

TL;DR: It is argued that the canonical view of the role of amyloid as the main causal factor in AD may not be correct and that evidence from recent neuroimaging studies indicates that amyloids is neither necessary nor sufficient, for the manifestation of AD-like brain atrophy.
References
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Journal ArticleDOI

Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade

TL;DR: This work proposes a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegnerative biomarker become abnormal later, and correlate with clinical symptom severity.
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