Predicting MCI outcome with clinically available MRI and CSF biomarkers

Department of Radiology, University of California, San Diego, La Jolla, CA 92093-0841, USA.
Neurology (Impact Factor: 8.29). 10/2011; 77(17):1619-28. DOI: 10.1212/WNL.0b013e3182343314
Source: PubMed


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).
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.
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).
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.

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Available from: David Heister, Jan 09, 2014
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    • "Conversion from MCI to dementia has been more widely studied, with a duration of 7–10 years for the MCI stage and annualized conversion rates of 8–17 per 100 person-years (Ward et al., 2013). Cognitive performance, cortical amyloid deposition, hippocampal atrophy, hypometabolism in the parietotemporal cortex, and alteration in the cerebrospinal fluid (CSF) levels of 42-aminoacid amyloid beta peptide (Aβ 42 ), tau, and phosphorylated tau (p-tau) proteins have been consistently associated with higher conversion rates from MCI to AD dementia (Brooks and Loewenstein, 2010; Heister et al., 2011; Barnes et al., 2014). Other markers or comorbidities (e.g., vascular factors, sleep disturbance) may also be of relevance in the transitions from healthy state to AD (Dufouil et al., 2005; Frisardi et al., 2010; Osorio et al., 2011). "
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    • "Indeed, the notion of " pure " AD pathology is increasingly thought to be far more rare than multiple underlying neuropathologies (e.g., AD, cerebrovascular disease, Lewy bodies, hippocampal sclerosis, TDP-43) [40] [41] [42] for the vast majority of late-onset AD. Thus, a combination of biomarkers and sensitive neuropsychological tests that detect these various underlying pathologies is an improvement on any individual biomarker and can substantially improve prediction of dementia risk [17]. A strength of the present study was the use of individual test scores and actuarial neuropsychological criteria to operationalize subtle cognitive decline within the same conceptual framework we have previously used to define MCI [27]. "
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