Structural MRI discriminates individuals with Mild Cognitive Impairment from age-matched controls: A combined neuropsychological and voxel based morphometry study

Background: Several previous studies have reported that amnestic mild cognitive impairment (aMCI), a significant risk factor for Alzheimer\u27s disease (AD), is associated with greater atrophy in the medial temporal lobe (MTL) and posterior cingulate gyrus (PCG). Method: In the present study, we examined the cross-sectional accuracy (i.e., the sensitivity and specificity) of voxel-based morphometry (VBM) in discriminating individuals with MCI (n = 15) from healthy age-matched controls (n = 15). In addition, we also sought to determine whether baseline GM volume predicted aMCI patients that converted to AD from those that did not approximately 2 years after the baseline visit. Results: MCI patients were found to display significantly less GM volume in several hypothesized regions including the MTL and PCG relative to the age-matched controls (p \u3c 0.01). Logistic regression analysis and receiver operating characteristic (ROC) curves for GM volume in the anterior MTL and PCG revealed high discriminative accuracy of 87%. By contrast, baseline GM volume in anterior MTL and PCG did not appear to be sensitive to changes in clinical status at the follow-up visit. Conclusion: These results suggest that VBM might be useful at characterizing GM volume reductions associated with the diagnosis of aMCI. © 2006 The Alzheimer\u27s Association

“That's a good question”: University researchers' views on ownership and retention of human genetic specimens

To explore the views of university-based investigators conducting genetic research with human specimens regarding ownership and retention of specimens, and knowledge of related institutional review board and university policies

The clinical utility of pain classification in non-specific arm pain

Mechanisms-based pain classification has received considerable attention recently for its potential use in clinical decision making. A number of algorithms for pain classification have been proposed. Non-specific arm pain (NSAP) is a poorly defined condition, which could benefit from classification according to pain mechanisms to improve treatment selection. This study used three published classification algorithms (hereafter called NeuPSIG, Smart, Schafer) to investigate the frequency of different pain classifications in NSAP and the clinical utility of these systems in assessing NSAP. Forty people with NSAP underwent a clinical examination and quantitative sensory testing. Findings were used to classify participants according to three classification algorithms. Frequency of pain classification including number unclassified was analysed using descriptive statistics. Inter-rater agreement was analysed using kappa coefficients. NSAP was primarily classified as ‘unlikely neuropathic pain’ using NeuPSIG criteria, ‘peripheral neuropathic pain’ using the Smart classification and ‘peripheral nerve sensitisation’ using the Schafer algorithm. Two of the three algorithms allowed classification of all but one participant; up to 45% of participants (n = 18) were categorised as mixed by the Smart classification. Inter-rater agreement was good for the Schafer algorithm (к = 0.78) and moderate for the Smart classification (к = 0.40). A kappa value was unattainable for the NeuPSIG algorithm but agreement was high. Pain classification was achievable with high inter-rater agreement for two of the three algorithms assessed. The Smart classification may be useful but requires further direction regarding the use of clinical criteria included. The impact of adding a pain classification to clinical assessment on patient outcomes needs to be evaluated

Abilities to explicitly and implicitly infer intentions from actions in adults with autism spectrum disorder

Previous research suggests that Autism Spectrum Disorder (ASD) might be associated with impairments on implicit but not explicit mentalizing tasks. However, such comparisons are made difficult by the heterogeneity of stimuli and the techniques used to measure mentalizing capabilities. We tested the abilities of 34 individuals (17 with ASD) to derive intentions from others’ actions during both explicit and implicit tasks and tracked their eye-movements. Adults with ASD displayed explicit but not implicit mentalizing deficits. Adults with ASD displayed typical fixation patterns during both implicit and explicit tasks. These results illustrate an explicit mentalizing deficit in adults with ASD, which cannot be attributed to differences in fixation patterns

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Validity Evidence for the Research Category, “Cognitively Unimpaired – Declining,” as a Risk Marker for Mild Cognitive Impairment and Alzheimer’s Disease

<jats:p>While clinically significant cognitive impairment is the key feature of the symptomatic stages of the Alzheimer’s disease (AD) continuum, subtle cognitive decline is now known to occur years before a clinical diagnosis of mild cognitive impairment (MCI) or dementia due to AD is made. The primary aim of this study was to examine criterion validity evidence for an operational definition of “cognitively unimpaired-declining” (CU-D) in the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a longitudinal cohort study following cognition and risk factors from mid-life and on. Cognitive status was determined for each visit using a consensus review process that incorporated internal norms and published norms; a multi-disciplinary panel reviewed cases first to determine whether MCI or dementia was present, and subsequently whether CU-D was present, The CU-D group differed from CU-stable (CU-S) and MCI on concurrent measures of cognition, demonstrating concurrent validity. Participants who changed from CU-S to CU-D at the next study visit demonstrated greater declines than those who stayed CU-S. In addition, those who were CU-D were more likely to progress to MCI or dementia than those who were CU-S (predictive validity). In a subsample with positron emission tomography (PET) imaging, the CU-D group also differed from the CU-S and MCI/Dementia groups on measures of amyloid and tau burden, indicating that biomarker evidence of AD was elevated in those showing sub-clinical (CU-D) decline. Together, the results corroborate other studies showing that cognitive decline begins long before a dementia diagnosis and indicate that operational criteria can detect subclinical decline that may signal AD or other dementia risk.</jats:p&gt

Self-reported health behaviors and longitudinal cognitive performance in late middle age: Results from the Wisconsin Registry for Alzheimer's Prevention.

BackgroundStudies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimer's Prevention (WRAP), an Alzheimer's disease risk-enriched cohort who were non-demented and in late midlife at baseline.MethodWe analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2- and 3-way interactions. The IT approach was selected due to the large number of interactions of interest and to avoid pitfalls of traditional model selection approaches.ResultsModel-averaged results identified no significant self-reported health behavior*age interactions in relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores associated with slower decline in executive function. Men showed faster decline than women on delayed memory, independent of health behaviors. There were no other significant interactions among any other health behaviors and cognitive trajectories.ConclusionsWhen multiple covariates and health behaviors were considered simultaneously, there were limited weak associations with cognitive decline in this age range. These results may be explained alone or in combination by three alternative explanations: 1) the range of cognitive decline is in middle age is too small to observe relationships with health behaviors, 2) the putative associations of these health behaviors on cognition may not be robust in this age range, or 3) the self-reported measures of the health behaviors may not be optimal for predicting cognitive decline. More study may be needed that incorporates sensitive measures of health behaviors, AD biomarker profiles, and/or other disease comorbidities