Gender-specificities in Alzheimer's disease and mild cognitive impairment

Background Amnestic Mild Cognitive Impairment (MCI) is a condition with an increased risk for developing Alzheimer's disease (AD). Presently, gender differences are neglected in the assessment of MCI and AD. Methods We examined verbal and visuospatial episodic memory in 143 subjects diagnosed as healthy controls (HC; N = 48, Mini-Mental State Examination (MMSE) 29.2 ± 1.0 (mean ± standard deviation)), MCI (N = 43,MMSE 28.5 ± 1.4), and AD (N = 49, MMSE 25.1 ± 2.2). Findings Female HC and MCI subjects performed better on verbal episodic memory tasks than males. In contrast, visuospatial episodic memory was better in male than female AD patients. Conclusions We interpret the results in light of a genderspecific cognitive reserve and conclude that the gender-specificity of neuropsychological performance needs to be accounted for in clinical diagnosis of Alzheimer’s disease.     

Nonlinear biomarker interactions in conversion from mild cognitive impairment to Alzheimer's disease

Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid‐β42, total tau, phosphorylated tau), [18^F]florbetapir, hippocampal volume and brain‐age. We examined: (a) the independent value of each biomarker; and (b) whether modelling nonlinear interactions between biomarkers improved predictions. Each measured added complementary information when predicting conversion to Alzheimer's. A linear model classifying stable from progressive MCI explained over half the variance (R² = 0.51, p < .001); the strongest independently contributing biomarker was hippocampal volume (R² = 0.13). When comparing sensitivity of different models to progressive MCI (independent biomarker models, additive models, nonlinear interaction models), we observed a significant improvement (p < .001) for various two‐way interaction models. The best performing model included an interaction between amyloid‐β‐PET and P‐tau, while accounting for hippocampal volume (sensitivity = 0.77, AUC = 0.826). Closely related biomarkers contributed uniquely to predict conversion to Alzheimer's. Nonlinear biomarker interactions were also implicated, and results showed that although for some patients adding additional biomarkers may add little value (i.e., when hippocampal volume is high), for others (i.e., with low hippocampal volume) further invasive and expensive examination may be warranted. Our framework enables visualisation of these interactions, in individual patient biomarker ‘space', providing information for personalised or stratified healthcare or clinical trial design.     

Modeling the prevalence and incidence of Alzheimer's disease and mild cognitive impairment

A number of systems have been proposed for classifying older adults who suffer from cognitive impairment or decline but do not yet meet criteria for Alzheimer's disease (AD). The classification, Mild Cognitive Impairment (MCI), has attracted much attention. It uses relatively specific diagnostic criteria and individuals who meet these criteria appear to be at substantial risk for the development of AD. However, little data is available to define the prevalence of MCI in any age group. We propose a simple mathematical model for the progression of patients from Non-Affected (NA) to MCI to AD. This first-order Markov model defines the likely prevalence of MCI at specific ages. Primary assumptions of the model include an AD prevalence of 1% at age 60 increasing to 25% at age 85 and a conversion rate from MCI to AD of 10% constant across all ages considered. We used the best available information for our model and found (1) that the MCI prevalence increased from 1% at age 60 to 42% at age 85 and (2) that the conversion rate from NA to MCI increased from 1% per year at age 60 to 11% at age 85. In conclusion, this model allows estimation of prevalence of MCI and conversion from NA to MCI based upon known prevalences of AD, conversion rates of MCI to AD, and death rates. Due to its substantial prevalence, MCI may be an important target for screening and possible intervention.     

Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: an fMRI study

Activity and reactivity of the default mode network in the brain was studied using functional magnetic resonance imaging (fMRI) in 28 nondemented individuals with mild cognitive impairment (MCI), 18 patients with mild Alzheimer's disease (AD), and 41 healthy elderly controls (HC). The default mode network was interrogated by means of decreases in brain activity, termed deactivations, during a visual encoding task and during a nonspatial working memory task. Deactivation was found in the default mode network involving the anterior frontal, precuneus, and posterior cingulate cortex. MCI patients showed less deactivation than HC, but more than AD. The most pronounced differences between MCI, HC, and AD occurred in the very early phase of deactivation, reflecting the reactivity and adaptation of the network. The default mode network response in the anterior frontal cortex significantly distinguished MCI from both HC (in the medial frontal) and AD (in the anterior cingulate cortex). The response in the precuneus could only distinguish between patients and HC, not between MCI and AD. These findings may be consistent with the notion that MCI is a transitional state between healthy aging and dementia and with the proposed early changes in MCI in the posterior cingulate cortex and precuneus. These findings suggest that altered activity in the default mode network may act as an early marker for AD pathology.     

Amnestic mild cognitive impairment in Parkinson's disease: A brain perfusion SPECT study

The purpose of this study was to investigate cortical dysfunction in Parkinson's disease (PD) patients with amnestic deficit (PD‐MCI). Perfusion single photon emission computed tomography was performed in 15 PD‐MCI patients and compared (statistical parametric mapping [SPM2]) with three groups, i.e., healthy subjects (CTR), cognitively intact PD patients (PD), and common amnestic MCI patients (aMCI). Age, depression, and UPDRS‐III scores were considered as confounding variables. PD‐MCI group (P < 0.05, false discovery rate–corrected for multiple comparisons) showed relative hypoperfusion in bilateral posterior parietal lobe and in right occipital lobe in comparison to CTR. As compared to aMCI, MCI‐PD demonstrated hypoperfusion in bilateral posterior parietal and occipital areas, mainly right cuneus and angular gyrus, and left precuneus and middle occipital gyrus. With a less conservative threshold (uncorrected P < 0.01), MCI‐PD showed hypoperfusion in a left parietal region, mainly including precuneus and inferior parietal lobule, and in a right temporal‐parietal‐occipital region, including middle occipital and superior temporal gyri, and cuneus‐precuneus, as compared to PD. aMCI versus PD‐MCI showed hypoperfusion in bilateral medial temporal lobe, anterior cingulate, and left orbitofrontal cortex. PD‐MCI patients with amnestic deficit showed cortical dysfunction in bilateral posterior parietal and occipital lobes, a pattern that can be especially recognized versus both controls and common aMCI patients, and to a lesser extent versus cognitively intact PD. The relevance of this pattern in predicting dementia should be evaluated in longitudinal studies. © 2008 Movement Disorder Society     

Applications of amyloid,tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment

Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease‐modifying therapeutic interventions. This review provides an overview of the current status and applications of in vivo molecular imaging of AD pathology, specifically amyloid, tau, and microglial activation. PET imaging studies were included and evaluated as potential biomarkers and for monitoring disease progression. Although the majority of radiotracers showed the ability to discriminate AD and MCI patients from healthy controls, they had various limitations that prevent the recommendation of a single technique or tracer as an optimal biomarker. Newer research examining amyloid, tau, and microglial PET imaging in combination suggest an alternative approach in studying the disease process.     

Subtypes of mild cognitive impairment in Parkinson's disease: progression to dementia.

The aim of this study was to establish the rate of progression from mild cognitive impairment (MCI) to dementia in patients with Parkinson's disease (PD). PD patients without dementia were recruited in 1997 from an ongoing prospective epidemiological study. The assessment included neurological and psychiatric examinations, a clinical interview based on the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III-R) criteria for dementia, and a battery of neuropsychological tests. PD was diagnosed according to established criteria, dementia was diagnosed according to the DSM-III-R criteria, and subtypes of MCI were classified according to modified Petersen's criteria. Seventy-two nondemented PD patients were included. A total of 34 were cognitively intact, whereas 38 were diagnosed with MCI (amnestic, n = 6; single nonmemory domain, n = 17; multiple domains slightly impaired, n = 15). Fifty-nine patients (82%) completed follow-up examination 4 years later, and 18 (62%) of the patients with MCI and 6 (20%) of the cognitively intact PD patients were demented (P = 0.001). Single domain nonmemory MCI and multiple domains slightly impaired MCI were associated with later development of dementia (P = 0.003; P = 0.04), whereas amnestic MCI subtype was not (P = 0.76). We conclude that patients with PD and MCI had a higher risk of developing dementia than cognitively intact PD patients, suggesting that MCI in PD is an early manifestation of dementia. However, these findings should be interpreted with caution due to the relatively small number of subjects included in this study.     

Measuring mild cognitive impairment in patients with Parkinson's disease

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 Parkinson's 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 Parkinson's 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. © 2013 Movement Disorder Society     

Caregiver perception of apathy in persons with mild cognitive impairment or Alzheimer's disease: a longitudinal study

Objective: Discrepancy between self- and caregiver apathy ratings was examined longitudinally for persons with mild cognitive impairment or Alzheimer's disease. Particular focus was on the distinction between the positive and negative caregiver bias and its predictive value for a clinical diagnosis of apathy.

Method: Apathy rating discrepancy was based on the apathy evaluation scale. Dyads were categorized depending on whether the caregiver reported fewer deficits (positive caregiver bias) or more deficits (negative caregiver bias) than the cognitively impaired person did.

Results: Caregiver ratings and rating discrepancy showed a significant increase from baseline to follow-up. By contrast, self- and clinician ratings showed no change across the two time points. Ratings with a negative caregiver bias remained stable, while those with a positive caregiver bias showed a significant increase in the caregiver ratings but also a significant decrease in the self-ratings. A negative caregiver bias at baseline was significantly related to greater likelihood of having clinical apathy at follow-up, adjusted for an array of control variables.

Conclusion: Positive and negative caregiver bias should be distinguished, as they seem to reflect distinct dyadic processes and are relevant for clinical outcome. Furthermore, negative rating discrepancies can be considered a risk factor for developing apathy.     

The cerebellum in mild cognitive impairment and Alzheimer's disease - a structural MRI study

Neuropathological research consistently revealed the cerebellum to undergo degenerative changes in Alzheimer's disease (AD). Whether these alterations affect cerebellar morphology in vivo has not yet been investigated in a comprehensive way. Magnetic resonance imaging was performed in 20 patients with AD, 20 with mild cognitive impairment (MCI), and 20 healthy controls. By manual tracing the cerebellum was divided in four substructures (anterior lobe, superior posterior lobe, inferior posterior lobe and corpus medullare, respectively) on each hemisphere. Posterior cerebellar lobes were significantly smaller in AD patients when compared to healthy controls. In the AD group, atrophy of the posterior cerebellar regions was associated with poorer cognitive performance. Our findings lend further support for cerebellar involvement in AD.