Mark Mapstone

Plasma phospholipids identify antecedent memory impairment in older adults

Alzheimers disease causes a progressive dementia that currently affects over 35 million individuals worldwide and is expected to affect 115 million by 2050 (ref. 1). There are no cures or disease-modifying therapies, and this may be due to our inability to detect the disease before it has progressed to produce evident memory loss and functional decline. Biomarkers of preclinical disease will be critical to the development of disease-modifying or even preventative therapies. Unfortunately, current biomarkers for early disease, including cerebrospinal fluid tau and amyloid-β levels, structural and functional magnetic resonance imaging and the recent use of brain amyloid imaging or inflammaging, are limited because they are either invasive, time-consuming or expensive. Blood-based biomarkers may be a more attractive option, but none can currently detect preclinical Alzheimers disease with the required sensitivity and specificity. Herein, we describe our lipidomic approach to detecting preclinical Alzheimers disease in a group of cognitively normal older adults. We discovered and validated a set of ten lipids from peripheral blood that predicted phenoconversion to either amnestic mild cognitive impairment or Alzheimers disease within a 2–3 year timeframe with over 90% accuracy. This biomarker panel, reflecting cell membrane integrity, may be sensitive to early neurodegeneration of preclinical Alzheimers disease.

Neuropsychological Assessment, 4th Edition

Neuropsychological Assessment, 4th Edition edited by Muriel D. Lezak, Diane B. Howieson, and David W. Loring, 1016 pp., New York, NY, Oxford University Press, 2004,

Identification of preclinical Alzheimer's disease by a profile of pathogenic proteins in neurally derived blood exosomes: A case-control study

89.50 Nearly a decade has passed since the publication of Lezaks third edition of Neuropsychological Assessment . In this time, the field of neuropsychology has grown at a tremendous pace. An explosion in the use of new research technologies such as fMRI has greatly advanced our understanding of brain-behavior relationships. In addition, there has been a proliferation of new assessment tools based on these basic research findings and …

A visuospatial variant of mild cognitive impairment: getting lost between aging and AD.

Proteins pathogenic in Alzheimers disease (AD) were extracted from neurally derived blood exosomes and quantified to develop biomarkers for the staging of sporadic AD.

The effect of modafinil on cognitive function in breast cancer survivors

Background: AD causes visuospatial disorientation that is associated with posterior cortical atrophy and impaired visual motion processing. Objective: The authors characterized memory capacity and visual motion processing in young normal (YN) and older normal (ON) adult subjects and in patients with mild cognitive impairment (MCI) and AD to see if deficits in these realms occur as isolated impairments. Methods: Each participant underwent neuropsychological testing and gave push-button responses to indicate perception of panoramic visual motion stimuli. Results: One fifth of the ON subjects, one third of the patients with MCI, and half of the patients with AD showed increasingly pervasive impairments of visual motion perception. These impairments were associated with poorer performance on the Money Road Map test of spatial navigation but not with verbal or visual memory deficits. Conclusion: Impaired visual motion processing may accompany memory deficits in MCI or AD, or may occur alone in otherwise intact ON subjects. This suggests that visuospatial impairment may develop as an independent sign of neurodegenerative disease, possibly preceding the clinical onset of AD.

Measuring mild cognitive impairment in patients with Parkinson's disease.

The authors conducted a randomized clinical trial examining the effects of modafinil in reducing persistent fatigue in patients after treatment for cancer and performed secondary analyses to assess the effect of modafinil on cognitive function.

Diagnosis of Parkinson's disease on the basis of clinical and genetic classification: a population-based modelling study

We examined the frequency of Parkinson disease with mild cognitive impairment (PD‐MCI) and its subtypes and the accuracy of 3 cognitive scales for detecting PD‐MCI using the new criteria for PD‐MCI proposed by the Movement Disorders Society. Nondemented patients with Parkinsons disease completed a clinical visit with the 3 screening tests followed 1 to 3 weeks later by neuropsychological testing. Of 139 patients, 46 met Level 2 Task Force criteria for PD‐MCI when impaired performance was based on comparisons with normative scores. Forty‐two patients (93%) had multi‐domain MCI. At the lowest cutoff levels that provided at least 80% sensitivity, specificity was 44% for the Montreal Cognitive Assessment and 33% for the Scales for Outcomes in Parkinsons Disease‐Cognition. The Mini‐Mental State Examination could not achieve 80% sensitivity at any cutoff score. At the highest cutoff levels that provided specificity of at least 80%, sensitivities were low (≤44%) for all tests. When decline from estimated premorbid levels was considered evidence of cognitive impairment, 110 of 139 patients were classified with PD‐MCI, and 103 (94%) had multi‐domain MCI. We observed dramatic differences in the proportion of patients who had PD‐MCI using the new Level 2 criteria, depending on whether or not decline from premorbid level of intellectual function was considered. Recommendations for methods of operationalizing decline from premorbid levels constitute an unmet need. Among the 3 screening tests examined, none of the instruments provided good combined sensitivity and specificity for PD‐MCI. Other tests recommended by the Task Force Level 1 criteria may represent better choices, and these should be the subject of future research.

Dopamine agonists reorient visual exploration away from the neglected hemispace.

BACKGROUND Accurate diagnosis and early detection of complex diseases, such as Parkinsons disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinsons disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts. METHODS We developed a model for disease classification using data from the Parkinsons Progression Marker Initiative (PPMI) study for 367 patients with Parkinsons disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinsons disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinsons disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinsons Disease Biomarkers Program (PDBP), the Parkinsons Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinsons Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). FINDINGS In the population from PPMI, our initial model correctly distinguished patients with Parkinsons disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900-0·946) with high sensitivity (0·834, 95% CI 0·711-0·883) and specificity (0·903, 95% CI 0·824-0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinsons disease, with AUCs of 0·894 (95% CI 0·867-0·921) in the PDBP cohort, 0·998 (0·992-1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896-0·962) in LABS-PD, and 0·939 (0·891-0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinsons disease converted to Parkinsons disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinsons disease underwent conversion (test of proportions, p=0·003). INTERPRETATION Our model provides a potential new approach to distinguish participants with Parkinsons disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinsons disease in prospective cohorts, it could facilitate identification of biomarkers and interventions. FUNDING National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.

Alterations of visual search strategy in Alzheimer's disease and aging.

Objective: To study the effects of bromocriptine, a dopamine agonist, on visual search. Background: The anatomic substrate of spatial attention takes the form of a distributed network with interconnected cortical (frontal, parietal, and cingulate) and subcortical (striatal and thalamic) components. Dopamine appears to exert a modulatory effect on the function of this network. Methods: Seven consecutive right-handed subjects with right-sided cerebral lesions were studied using a computerized target search paradigm. Eye movements were recorded. Results: Bromocriptine caused the subjects to spend more time exploring the ipsilesional hemispace and therefore increased the relative neglect of the contralesional left hemispace. However, target detection accuracy did not change. Bromocriptine thus had a differential impact on the exploratory-motor versus sensory-perceptual components of directed attention. Conclusions: Our results show that bromocriptine may worsen some aspects of hemispatial neglect in patients with lesions that include the postsynaptic components of ascending dopaminergic pathways.

Memory complaints and memory performance in the menopausal transition.

Visual search, characterized by eye fixation patterns, was examined in 8 patients with Alzheimers disease (AD), 8 cognitively intact, age-matched individuals, and 8 young control participants as they searched for a number among a nonlinear array of letters on a large computer screen. Among the 3 groups, target detection accuracy differed and detection time increased linearly. There were more fixations, and fixation duration was significantly longer in the AD patients than in the other 2 groups. These factors contributed to the lengthening of target detection time. This qualitative difference in the architecture of visual search between AD and aging may reflect a specific deficit in the disengagement of visual spatial attention, a prolongation of saccade initiation, or inefficiency in planning a search strategy.