Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults

Department of Neurology, Massachusetts Alzheimer’s Disease Research Center, Massachusetts General Hospital, MA, USA.
Neurology (Impact Factor: 8.29). 04/2011; 76(16):1395-402. DOI: 10.1212/WNL.0b013e3182166e96
Source: PubMed

ABSTRACT Since Alzheimer disease (AD) neuropathology is thought to develop years before dementia, it may be possible to detect subtle AD-related atrophy in preclinical AD. Here we hypothesized that the "disease signature" of AD-related cortical thinning, previously identified in patients with mild AD dementia, would be useful as a biomarker to detect anatomic abnormalities consistent with AD in cognitively normal (CN) adults who develop AD dementia after longitudinal follow-up.
We studied 2 independent samples of adults who were CN when scanned. In sample 1, 8 individuals developing AD dementia (CN-AD converters) after an average of 11.1 years were compared to 25 individuals who remained CN (CN-stable). In sample 2, 7 CN-AD converters (average follow-up 7.1 years) were compared to 25 CN-stable individuals.
AD-signature cortical thinning in CN-AD converters in both samples was remarkably similar, about 0.2 mm (p < 0.05). Despite this small absolute difference, Cohen d effect sizes for these differences were very large (> 1). Of the 11 CN individuals with baseline low AD-signature thickness (≥ 1 SD below cohort mean), 55% developed AD dementia over nearly the next decade, while none of the 9 high AD-signature thickness individuals (≥ 1 SD above mean) developed dementia. This marker predicted time to diagnosis of dementia (hazard ratio = 3.4, p < 0.0005); 1 SD of thinning increased dementia risk by 3.4.
By focusing on cortical regions known to be affected in AD dementia, subtle but reliable atrophy is identifiable in asymptomatic individuals nearly a decade before dementia, making this measure a potentially important imaging biomarker of early neurodegeneration.

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Available from: Travis R Stoub, Sep 27, 2015
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    • "With the prospect of disease modifying therapies and the recent characterization of PD-MCI as a distinct clinical entity [7], concerted efforts have been made to identify biomarkers that are capable of quantifying pathological changes in a sensitive and reproducible manner. Advances in computational analyses have allowed the investigation of subtle regional atrophy, contributing to the recognition of structural magnetic resonance imaging (MRI) as a validated biomarker for AD [30] and MRI is also increasingly adopted as an outcome measure in clinical trials for AD [31]. In the following sections, we summarize principle findings from multiple imaging modalities across the cognitive spectrum of PD. "
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    ABSTRACT: There has been a gradual shift in the definition of Parkinson's disease, from a movement disorder to a neurodegenerative condition affecting multiple cognitive domains. Mild cognitive impairment (PD-MCI) is a frequent comorbidity in PD that is associated with progression to dementia (PDD) and debilitating consequences for patients and caregivers. At present, the pathophysiology underpinning cognitive impairment in PD is not established, although emerging evidence has suggested that multi-modal imaging biomarkers could be useful in the early diagnosis of PD-MCI and PDD, thereby identifying at-risk patients to enable treatment at the earliest stage possible. Structural MRI studies have revealed prominent grey matter atrophy and disruptions of white matter tracts in PDD, although findings in non-demented PD have been more variable. There is a need for further longitudinal studies to clarify the spatial and temporal progression of morphological changes in PD, as well as to assess their underlying involvement in the evolution of cognitive deficits. In this review, we discuss the aetiology and neuropsychological profiles of PD-MCI and PDD, summarize the putative imaging substrates in light of evidence from multi-modal neuroimaging studies, highlight limitations in the present literature, and suggest recommendations for future research. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Parkinsonism & Related Disorders 05/2015; DOI:10.1016/j.parkreldis.2015.05.013 · 3.97 Impact Factor
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    • "However, the accuracy of medial temporal lobe FDG-PET remained below a clinically significant level for the prediction of progression to MCI (Mosconi et al., 2008). Results from studies assessing volumetric MRI in elderly HC subjects suggested that regional GM volume decrease was associated with increased risk to develop AD dementia (den Heijer et al., 2006; Dickerson et al., 2011). However, the accuracy of FDG-PET and GM volume for predicting AD dementia in HC is still unclear, and to our best knowledge, no studies have compared the utility of FDG-PET and MRI for the detection of preclinical AD so far. "
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    ABSTRACT: Brain changes reminiscent of Alzheimer disease (AD) have been previously reported in a substantial portion of elderly cognitive healthy (HC) subjects. The major aim was to evaluate the accuracy of MRI assessed regional gray matter (GM) volume, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), and neuropsychological test scores to identify those HC subjects who subsequently convert to mild cognitive impairment (MCI) or AD dementia. We obtained in 54 healthy control (HC) subjects a priori defined region of interest (ROI) values of medial temporal and parietal FDG-PET and medial temporal GM volume. In logistic regression analyses, these ROI values were tested together with neuropsychological test scores (free recall, trail making test B (TMT-B)) as predictors of HC conversion during a clinical follow-up between 3 and 4 years. In voxel-based analyses, FDG-PET and MRI GM maps were compared between HC converters and HC non-converters. Out of the 54 HC subjects, 11 subjects converted to MCI or AD dementia. Lower FDG-PET ROI values were associated with higher likelihood of conversion (p = 0.004), with the area under the curve (AUC) yielding 82.0% (95% CI = (95.5%, 68.5%)). The GM volume ROI was not a significant predictor (p = 0.07). TMT-B but not the free recall tests were a significant predictor (AUC = 71% (95% CI = 50.4%, 91.7%)). For the combination of FDG-PET and TMT-B, the AUC was 93.4% (sensitivity = 82%, specificity = 93%). Voxel-based group comparison showed reduced FDG-PET metabolism within the temporo-parietal and prefrontal cortex in HC converters. In conclusion, medial temporal and-parietal FDG-PET and executive function show a clinically acceptable accuracy for predicting clinical progression in elderly HC subjects.
    Clinical neuroimaging 12/2014; 4:45–52. DOI:10.1016/j.nicl.2013.10.018 · 2.53 Impact Factor
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    • "The hippocampus, which is associated with memory, is particular vulnerable to damage at the earliest stages of AD [3,4]. Hippocampal brain changes, such as loss of thickness and volume in the medial temporal lobe, particular in the hippocampus, is thought to begin 7 years or more before AD symptoms, such as memory loss, appear [5-8]. "
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    BMC Medical Imaging 06/2014; 14(1):21. DOI:10.1186/1471-2342-14-21 · 1.31 Impact Factor
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