Neuropsychological assessment of patients with dementing illness

Impaired cognition in narcolepsy: clinical and neurobiological perspectives

In addition to well-known symptoms such as sleepiness and cataplexy, many people with narcolepsy have impaired cognition, reporting inattention, poor memory, and other concerns. Unfortunately, research on cognition in narcolepsy has been limited. Strong evidence demonstrates difficulties with sustained attention, but evidence for executive dysfunction and impaired memory is mixed. Animal research provides some insights into how loss of the orexin neurons in narcolepsy type 1 may give rise to impaired cognition via dysfunction of the prefrontal cortex, and cholinergic and monoaminergic systems. This paper reviews some of these clinical and preclinical findings, provides a neurobiological framework to understand these deficits, and highlights some of the many key unanswered questions.

Measurement invariance of a neuropsychological battery across urban and rural older adults in Costa Rica

This study evaluated the measurement invariance of a neuropsychological battery across rural and urban older adults from Costa Rica. Rural and urban older adults (N = 295) from the Epidemiology and Development of Alzheimer's Disease (EDAD) study in Costa Rica were assessed. The baseline factor model for the EDAD neuropsychological measures was identified with nine neuropsychological measures and three cognitive constructs: Verbal Memory, Spatial Reasoning, and Cognitive Flexibility. Measurement and structural invariance were established, and, then, group comparisons of the latent cognitive factors were conducted to explore regional disparities. The findings showed that most of the neuropsychological tests in EDAD can be directly compared across the groups, allowing for cognitive constructs comparisons. The rural sample showed a disadvantage in the Spatial Reasoning and Cognitive Flexibility abilities. When age and education were included in the models, differences between the regions disappeared. Having more years of education was associated with higher cognitive abilities, with a larger effect for the rural group. Norms for Costa Rican older adults should consider age and education adjustments. This study contributes to the growing area of measurement invariance in neuropsychological assessment as it highlights the importance of examining the comparability of assessment measures across different cultural groups.

Neuropsychological tests used for dementia assessment in Japan: Current status

AIM

This study aimed to investigate the assessment tools dementia specialists use in clinical practice, reasons for their use and assessment-related factors.

METHODS

A questionnaire survey was carried out from 15 September 2021 to 20 October 2021 among 1858 dementia specialists in Japan, with responses obtained via mail or using a Web form accessed via a Web address.

RESULTS

Of the 1858 specialists who were sent the questionnaire, 574 responded, yielding a response rate of 32.2%. Almost all respondents stated that the main purposes of neuropsychological testing were to identify the pathophysiology and aid diagnosis. Most respondents identified behavioral and psychological symptoms of dementia as important factors for assessment. The most commonly used tests were the Hasegawa Dementia Scale-Revised and Mini-Mental State Examination, often used as screening tools. The Mini-Mental State Examination, Clock Drawing Test and Cube Copying Test were common assessments carried out directly by specialists. Quality of life and burden of care were less commonly assessed.

CONCLUSIONS

Despite the main purpose of carrying out neuropsychological tests on dementia patients is to "understand the pathophysiology" and "aid in diagnosis," many assessment methods were chosen as screening methods carried out in a short time during clinic hours. The lack of evaluation of care burden and QOL, considered important by specialists, is an issue for the future in treating people with dementia, a life disability. Geriatr Gerontol Int 2024; 24: 102-109.

Disrupted excitation-inhibition balance in cognitively normal individuals at risk of Alzheimer's disease

Background

Sex differences impact Alzheimer's disease (AD) neuropathology, but cell-to-network level dysfunctions in the prodromal phase are unclear. Alterations in hippocampal excitation-inhibition balance (EIB) have recently been linked to early AD pathology.

Objective

Examine how AD risk factors (age, APOE-ɛ4, amyloid-β) relate to hippocampal EIB in cognitively normal males and females using connectome-level measures.

Methods

Individuals from the OASIS-3 cohort (age 42-95) were studied (N = 437), with a subset aged 65+ undergoing neuropsychological testing (N = 231).

Results

In absence of AD risk factors (APOE-ɛ4/Aβ+), whole-brain EIB decreases with age more significantly in males than females (p = 0.021, β = -0.007). Regression modeling including APOE-ɛ4 allele carriers (Aβ-) yielded a significant positive AGE-by-APOE interaction in the right hippocampus for females only (p = 0.013, β = 0.014), persisting with inclusion of Aβ+ individuals (p = 0.012, β = 0.014). Partial correlation analyses of neuropsychological testing showed significant associations with EIB in females: positive correlations between right hippocampal EIB with categorical fluency and whole-brain EIB with the trail-making test (p < 0.05).

Conclusion

Sex differences in EIB emerge during normal aging and progresses differently with AD risk. Results suggest APOE-ɛ4 disrupts hippocampal balance more than amyloid in females. Increased excitation correlates positively with neuropsychological performance in the female group, suggesting a duality in terms of potential beneficial effects prior to cognitive impairment. This underscores the translational relevance of APOE-ɛ4 related hyperexcitation in females, potentially informing therapeutic targets or early interventions to mitigate AD progression in this vulnerable population.

One-year prediction of cognitive decline following cognitive-stimulation from real-world data

Clinical evidence based on real-world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40% male, 46% female, 14% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross-validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts.

The ambivalence toward neuropsychology in dementia research, diagnosis, and drug development: Myths and misconceptions

Clinical assessment remains the gold standard for diagnosing dementia, monitoring progression, and conducting clinical research. Biomarkers hold promise for targeted therapeutic approaches, selection of participants in clinical trials, and direct physiological efficacy readouts. However, the anchoring of biomarker research to clinical symptomatology is often based on short and insensitive cognitive screening. This gives the impression that cognitive symptoms occur relatively late and that their progression in the early stages of the disease is slow. A thorough cognitive assessment is a powerful tool and has a key role in the accurate and early diagnosis of dementia. It is very different from the cognitive testing usually seen in biomarker research and drug development. Yet the distinction between these approaches is unclear to many. This paper highlights the misconceptions around cognitive research in dementia and suggests a way forward to facilitate biomarker and drug development through the improved utility of cognitive assessment tools.

Disrupted Excitation-Inhibition Balance in Cognitively Normal Individuals at Risk of Alzheimer's Disease

BACKGROUND

Sex differences impact Alzheimer's disease (AD) neuropathology, but cell-to-network level dysfunctions in the prodromal phase are unclear. Alterations in hippocampal excitation-inhibition balance (EIB) have recently been linked to early AD pathology.

OBJECTIVE

Examine how AD risk factors (age, APOEɛ4, amyloid-β) relate to hippocampal EIB in cognitively normal males and females using connectome-level measures.

METHODS

Individuals from the OASIS-3 cohort (age 42-95) were studied (N = 437), with a subset aged 65+ undergoing neuropsychological testing (N = 231).

RESULTS

In absence of AD risk factors (APOEɛ4/Aβ+), whole-brain EIB decreases with age more significantly in males than females (p = 0.021, β= -0.007). Regression modeling including APOEɛ4 allele carriers (Aβ-) yielded a significant positive AGE-by-APOE interaction in the right hippocampus for females only (p = 0.013, β= 0.014), persisting with inclusion of Aβ+ individuals (p = 0.012, β= 0.014). Partial correlation analyses of neuropsychological testing showed significant associations with EIB in females: positive correlations between right hippocampal EIB with categorical fluency and whole-brain EIB with the Trail Making Test (p < 0.05).

CONCLUSIONS

Sex differences in EIB emerge during normal aging and progresses differently with AD risk. Results suggest APOEɛ4 disrupts hippocampal balance more than amyloid in females. Increased excitation correlates positively with neuropsychological performance in the female group, suggesting a duality in terms of potential beneficial effects prior to cognitive impairment. This underscores the translational relevance of APOEɛ4 related hyperexcitation in females, potentially informing therapeutic targets or early interventions to mitigate AD progression in this vulnerable population.

Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

OBJECTIVE

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

METHOD

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer's type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

RESULTS

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive-behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

CONCLUSION

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

Normative Data of Mini-Mental State Examination, Montreal Cognitive Assessment, and Alzheimer's Disease Assessment Scale-Cognitive Subscale of Community-Dwelling Older Adults in Taiwan

INTRODUCTION

Appropriate tools and references are essential for evaluating individuals' cognitive levels. This study validated the Taiwan version of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-cog) and provided normative data for the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and ADAS-cog in community-dwelling older adults.

METHODS

MMSE, MoCA, and ADAS-cog were administered to 150 nondemented healthy adults aged 55-85 years during 2018-2020 as part of the Northeastern Taiwan Community Medicine Research Cohort. ADAS-cog was translated from the original English version to traditional Chinese with cultural and language considerations in Taiwan. Cronbach's alpha (α) tested the reliability of ADAS-cog, and Pearson correlations examined its external validity using MMSE and MoCA as comparisons. Normative data were generated and stratified by age and education, and the one-way analysis of variance compared scores between age and education groups. Another 20 hospital-acquired participants with cognitive impairment joined the 150 healthy participants. Comparisons in the Clinical Dementia Rating (CDR) tiers tested the discriminability of the tests for different cognitive levels. The area under the receiver operating characteristic curve (AUROC) analyzed the power of ADAS-cog in predicting CDR 0.5 from CDR 0.

RESULTS

The Taiwan version of ADAS-cog had fair reliability between items (α = 0.727) and good correlations to MMSE (r = -0.673, p < 0.001) and MoCA (r = -0.746, p < 0.001). The normative data of MMSE, MoCA, and ADAS-cog showed ladder changes with age (p = 0.006, 0.001, and 0.437) and education (p < 0.001, <0.001, and <0.001) in the 150 nondemented older adults. Next, in the 170 mixed participants from the communities and the hospital, MMSE, MoCA, and ADAS-cog scores were well differentiable between CDR 0, 0.5, and 1. In addition, ADAS-cog discriminated CDR 0.5 from 0 by an AUROC of 0.827 (p < 0.001).

DISCUSSION/CONCLUSION

The three structured cognitive tests consistently reflect cognitive levels of healthy older adults. The Taiwan version of ADAS-cog is compatible with MMSE and MoCA to distinguish people with mildly impaired from normal cognition. In addition, this study derived MMSE, MoCA, and ADAS-cog norms tailored to demographic factors. The findings highlight the need for stratification of age and education rather than applying a fixed cutoff for defining normal and abnormal cognition.

A simple counting of verbal fluency errors discriminates between normal cognition, mild cognitive impairment and Alzheimer's disease

For this observational cross-sectional study, different modalities of verbal fluency tasks (VFTs) were compared between 143 participants: 35 cognitively healthy controls (CHCs), 71 mild cognitive impairment (MCI) and 37 mild Alzheimer's disease (AD) patients. Binomial logistic regression models were defined to identify VFT variables associated with MCI and AD, with respect to CHC. The results showed that the best errors/repetitions variable associated with MCI and AD was the phonemic task, and with every error the odds of being in the MCI group increased 9.9 times and 12.2 times in AD group, accompanied by high accuracy values (MCI: AUC = 0.824, sensitivity = 0.676, specificity = 0.943; AD: AUC = 0.883, sensitivity = 0.784, specificity = 0.943). The results suggest that, in addition to solely register raw scores, a simple counting of errors and repetitions during VFT can offer valuable clues in detecting MCI and AD, especially in the phonemic task.

Cognitive Assessment in Culturally, Linguistically, and Educationally Diverse Older Populations in Europe

Due to increasing cultural, linguistic, and educational diversity in older populations across Europe, accurate assessment of cognitive functioning in people from diverse backgrounds becomes increasingly important. This paper aims to provide a state-of-the-art review of cognitive assessment in culturally, linguistically, and educationally diverse older populations in Europe, focusing on challenges and recent advances in cross-cultural assessment. Significant work has been carried out on the identification of challenges in cognitive assessment in culturally, linguistically, and educationally diverse older populations and on development and validation of cross-cultural cognitive tests. Most research has addressed the influences of language barriers, education and literacy, and culture and acculturation and in particular, the European Cross-Cultural Neuropsychological Test Battery (CNTB) and the Rowland Universal Dementia Assessment Scale (RUDAS) are well-validated across European countries. However, cross-cultural cognitive assessment is largely still a developing field in Europe, and there is a continuing need for developments within the field.

Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer's Disease

Background:

In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in describing the overall functional status.

Objective:

It remains unexamined how complex patterns of the test performances can be utilized to have specific predictive meaning when the machine learning approach is applied.

Methods:

In this study, the neuropsychological battery (CERAD-K) and assessment of functioning level (Clinical Dementia Rating scale and Instrumental Activities of Daily Living) were administered to 2,642 older adults with no impairment (n = 285), mild cognitive impairment (n = 1,057), and Alzheimer’s disease (n = 1,300). Predictive accuracy on functional impairment level with the linear models of the single total score or multiple subtest scores (Model 1, 2) and support vector regression with low or high complexity (Model 3, 4) were compared across different sample sizes.

Results:

The linear models (Model 1, 2) showed superior performance with relatively smaller sample size, while nonlinear models with low and high complexity (Model 3, 4) showed an improved accuracy with a larger dataset. Unlike linear models, the nonlinear models showed a gradual increase in the predictive accuracy with a larger sample size (n > 500), especially when the model training is allowed to exploit complex patterns of the dataset.

Conclusion:

Our finding suggests that nonlinear models can predict levels of functional impairment with a sufficient dataset. The summary index of the neuropsychological battery can be augmented for specific purposes, especially in estimating the functional status of dementia.

Adaptation and Validation of the Mini-Addenbrooke's Cognitive Examination in Dementia in Arabic Speakers in Egypt

BACKGROUND

The mini-Addenbrooke's Cognitive Examination (m-ACE) is a brief cognitive battery that assesses 5 subdomains of cognition (attention, memory, verbal fluency, visuospatial abilities, and memory recall). It is scored out of 30 and can be administered in under 5 min providing a quick screening tool for assessment of cognition.

OBJECTIVES

We aimed to adapt the m-ACE in Arabic speakers in Egypt and to validate it in dementia patients to provide cutoff scores.

METHODS

We included 37 patients with dementia (Alzheimer's disease [n = 25], vascular dementia [n = 8], and dementia with Lewy body [n = 4]) and 43 controls.

RESULTS

There was a statistically significant difference (p < 0.001) on the total m-ACE score between dementia patients (mean 10.54 and standard deviation [SD] 5.83) and controls (mean 24.02 and SD 2.75). There was also a statistically significant difference between dementia patients and controls on all sub-score domains of the m-ACE (p < 0.05). Performance on the m-ACE significantly correlated with both the Mini-Mental State Examination (MMSE) and the Addenbrooke's Cognitive Examination-III (ACE-III). Using a receiver operator characteristic curve, the optimal cutoff score for dementia on the m-ACE total score was found to be 18 (92% sensitivity, 95% specificity, and 94% accuracy).

CONCLUSIONS

We adapted the m-ACE in Arabic speakers in Egypt and provided objective validation of it as a screening tool for dementia, with high sensitivity, specificity, and accuracy.

Distributed functional connectivity predicts neuropsychological test performance among older adults

Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late-life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain-wide neural basis of the test performance remains unclear. Using the predictive modeling approach, we aimed to identify the optimal combination of functional connectivities that predicts neuropsychological test scores of novel individuals. Resting-state functional connectivity and neuropsychological tests included in the OASIS-3 dataset (n = 428) were used to train the predictive models, and the identified models were iteratively applied to the holdout internal test set (n = 216) and external test set (KSHAP, n = 151). We found that the connectivity-based predicted score tracked the actual behavioral test scores (r = 0.08-0.44). The predictive models utilizing most of the connectivity features showed better accuracy than those composed of focal connectivity features, suggesting that its neural basis is largely distributed across multiple brain systems. The discriminant and clinical validity of the predictive models were further assessed. Our results suggest that late-life neuropsychological test performance can be formally characterized with distributed connectome-based predictive models, and further translational evidence is needed when developing theoretically valid and clinically incremental predictive models.

A Comparison of the Greek ACE-III, M-ACE, ACE-R, MMSE, and ECAS in the Assessment and Identification of Alzheimer's Disease

OBJECTIVE

This study aimed to adapt the Addenbrooke's Cognitive Examination-III (ACE-III) and Mini-Addenbrooke's Cognitive Examination (M-ACE) into Greek and then to examine the convergent validity against their predecessors Addenbrooke's Cognitive Examination-Revised (ACE-R) and Mini-Mental State Examination (MMSE) in a Greek population. Moreover, a primary aim was to appraise the utility of each screen by conducting a comparison of the psychometric properties of ACE-III, M-ACE, ACE-R, MMSE, and the Edinburgh Cognitive and Behavioural Amyotrophic Lateral Sclerosis (ALS) Screen (ECAS) in detecting Alzheimer's disease (AD).

METHODS

Forty patients with AD were recruited and matched with 38 controls. Bayesian Pearson's correlation analysis was conducted to examine the convergent validity. Receiver operating characteristic curve analysis was implemented to appraise the sensitivity and specificity of the tests in detecting AD.

RESULTS

The ACE-III, M-ACE, and the ECAS scores robustly correlated with ACE-R and MMSE. The ACE-III and the ECAS-ALS Non-Specific score were the most sensitive and specific tools in detecting AD, closely followed by ECAS Total score and M-ACE. Only ECAS Total score correlated with the duration of disease. The ECAS scores were more resilient to ceiling effects than the other screens. M-ACE produced fewer ceiling effects than MMSE.

CONCLUSION

The Greek ACE-III and M-ACE were successfully adapted and showed good convergent validity against their predecessors. They showed very good psychometric properties in detecting AD and may be considered in hectic clinical settings. ECAS Total score and ECAS-ALS Non-Specific showed comparable psychometric properties in the detection of AD and may be considered in polypathological clinics where motor impairments are common.

Regional Cerebral Associations Between Psychometric Tests and Imaging Biomarkers in Alzheimer's Disease

Recently, imaging biomarkers have gained importance for the characterization of patients with Alzheimer's disease; however, the relationship between regional biomarker expression and cognitive function remains unclear. In our study, we investigated associations between scores on CERAD neuropsychological assessment battery (CERAD-NAB) subtests with regional glucose metabolism, cortical thickness and amyloid deposition in patients with early Alzheimer's disease (AD) using [18F]-fluorodeoxyglucose (FDG), structural MRI, and 11C-Pittsburgh Compound B (PiB) positron emission tomography (PET), respectively. A total of 76 patients (mean age 68.4 ± 8.5 years, 57.9% male) with early AD (median global clinical dementia rating (CDR) score = 0.5, range: 0.5-2.0) were studied. Associations were investigated by correlation and multiple regression analyses. Scores on cognitive subtests were most closely predicted by regional glucose metabolism with explained variance up to a corrected R² of 0.518, followed by cortical thickness and amyloid deposition. Prediction of cognitive subtest performance was increased up to a corrected R² of 0.622 for Word List-Delayed Recall, when biomarker information from multiple regions and multiple modalities were included. For verbal, visuoconstructive and mnestic domains the closest associations with FDG-PET imaging were found in the left lateral temporal lobe, right parietal lobe, and posterior cingulate cortex, respectively. Decreased cortical thickness in parietal regions was most predictive of impaired subtest performance. Remarkably, cerebral amyloid deposition significantly predicted cognitive function in about half of the subtests but with smaller extent of variance explained (corrected R² ≤ 0.220). We conclude that brain metabolism and atrophy affect cognitive performance in a regionally distinct way. Significant predictions of cognitive function by PiB-PET in half of CERAD-NAB subtests suggest functional relevance even in symptomatic patients with AD, challenging the concept of plateauing cortical amyloid deposition early in the disease course. Our results underscore the complex spatial relationship between different imaging biomarkers.

Cognitive and neuropsychological examination of the elderly

Neuropsychological assessment plays a prominent role in the evaluation and care of patients with neurodegenerative diseases throughout the dynamic course of disease. As a biomarker of disease, neuropsychological measurement can distinguish normal from pathologic aging processes. Further, neuropsychological data can help distinguish and classify underlying pathologies in dementing diseases, augmenting imaging and biofluid markers in this area. Neuropsychological data can predict increased or reduced risk for dementia conferred by multiple factors, and describe disease trajectory in affected individuals. Cognitive evaluation can also estimate and address functional outcomes that are most important to patients and their loved ones and that are clinically relevant to diagnostic staging. In informing intervention and patient care needs, areas of cognitive weakness highlight targets for support/intervention, while areas of cognitive strength can be capitalized upon to modify the clinical course of disease. These functions can be accomplished through the complementary use of brief screening tools and comprehensive test batteries. However, for neuropsychological data to serve these functions, it is critical to understand neuropsychological test properties and nondisease factors that can account for variance in test performance. This chapter concludes with directions for future research.

Validation of a European Cross-Cultural Neuropsychological Test Battery (CNTB) for evaluation of dementia

BACKGROUND

The aims of this study were to establish the diagnostic accuracy of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for dementia in different ethnic populations in Western Europe, to examine its ability to differentiate cognitive impairment profiles for dementia subtypes, and to assess the impact of demographic variables on diagnostic properties.

METHODS

The study was a Western European cross-sectional multi-center study. A total of 66 patients with dementia and 118 cognitively intact participants were included across six memory clinics; 93 had ethnic minority background and 91 had ethnic majority background. Tests in the CNTB cover global cognitive function, memory, language, executive functions, and visuospatial functions.

RESULTS

Significant differences with moderate to large effect sizes were present between patients with dementia and control participants on all CNTB measures. Area under the curves (AUC) ranged from .62 to .99 with a mean AUC across all measures of .83. Comparison of ethnic minority and majority groups generally revealed higher sensitivity in the minority group but no significant difference in the mean AUC's across all measures (.84 vs78, P = .42). Comparison of impairment profiles for patients with Alzheimer's disease (AD) and non-AD dementia revealed that AD patients were significantly more impaired on the memory domain, whereas patients with non-AD dementia were more impaired on the executive functions domain.

CONCLUSIONS

The CNTB was found to have promising cross-cultural diagnostic properties for evaluation of dementia in the targeted minority and majority populations and could represent a valid cross-cultural alternative to other well-established neuropsychological test batteries when assessing patients from these populations.

Convergent Results from Neuropsychology and from Neuroimaging in Patients with Mild Cognitive Impairment

BACKGROUND/AIMS

To investigate the correspondence between neuropsychological single measures and variation in fludeoxyglucose positron emission tomography (FDG PET) glucose metabolism and magnetic resonance imaging (MRI) cortical thickness in mild cognitive impairment (MCI) patients.

METHODS

Forty-two elderly controls and 73 MCI subjects underwent FDG PET and MRI scanning. Backward regression analyses with PET and MRI regions were used as dependent variables, while Rey Auditory Verbal Memory Test (RAVLT) recall, Trail Making Test B (TMT B), and a composite test score (RAVLT learning and immediate recall, TMT A, COWAT, and letter-number sequencing) were used as predictor variables.

RESULTS

The composite score predicted variation in cortical metabolism; supplementary analyses showed that TMT B was significantly correlated with PET metabolism as well. RAVLT and TMT B were significant predictors of variation in MRI cortical thickness.

CONCLUSION

Our results indicate that RAVLT and TMT B are sensitive to variation in Alzheimer disease neuroimaging markers.

Diagnostic Accuracy of Memory Measures in Alzheimer's Dementia and Mild Cognitive Impairment: a Systematic Review and Meta-Analysis

With an increasing focus on biomarkers in dementia research, illustrating the role of neuropsychological assessment in detecting mild cognitive impairment (MCI) and Alzheimer's dementia (AD) is important. This systematic review and meta-analysis, conducted in accordance with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) standards, summarizes the sensitivity and specificity of memory measures in individuals with MCI and AD. Both meta-analytic and qualitative examination of AD versus healthy control (HC) studies (n = 47) revealed generally high sensitivity and specificity (≥ 80% for AD comparisons) for measures of immediate (sensitivity = 87%, specificity = 88%) and delayed memory (sensitivity = 89%, specificity = 89%), especially those involving word-list recall. Examination of MCI versus HC studies (n = 38) revealed generally lower diagnostic accuracy for both immediate (sensitivity = 72%, specificity = 81%) and delayed memory (sensitivity = 75%, specificity = 81%). Measures that differentiated AD from other conditions (n = 10 studies) yielded mixed results, with generally high sensitivity in the context of low or variable specificity. Results confirm that memory measures have high diagnostic accuracy for identification of AD, are promising but require further refinement for identification of MCI, and provide support for ongoing investigation of neuropsychological assessment as a cognitive biomarker of preclinical AD. Emphasizing diagnostic test accuracy statistics over null hypothesis testing in future studies will promote the ongoing use of neuropsychological tests as Alzheimer's disease research and clinical criteria increasingly rely upon cerebrospinal fluid (CSF) and neuroimaging biomarkers.

[Diagnostic of prodromal dementia with Levy bodies]

The issues of diagnosis of prodromal dementia with Lewy bodies are considered. Despite numerous studies using international diagnostic criteria, clinical and diagnosis are often inconsistent. Early and more accurate detection of dementia with Lewy bodies is needed for prognosis, optimal management and effective pharmacotherapy.

Neuropsychological Testing and Machine Learning Distinguish Alzheimer's Disease from Other Causes for Cognitive Impairment

With promising results in recent treatment trials for Alzheimer’s disease (AD), it becomes increasingly important to distinguish AD at early stages from other causes for cognitive impairment. However, existing diagnostic methods are either invasive (lumbar punctures, PET) or inaccurate Magnetic Resonance Imaging (MRI). This study investigates the potential of neuropsychological testing (NPT) to specifically identify those patients with possible AD among a sample of 158 patients with Mild Cognitive Impairment (MCI) or dementia for various causes. Patients were divided into an early stage and a late stage group according to their Mini Mental State Examination (MMSE) score and labeled as AD or non-AD patients based on a post-mortem validated threshold of the ratio between total tau and beta amyloid in the cerebrospinal fluid (CSF; Total tau/Aβ(1–42) ratio, TB ratio). All patients completed the established Consortium to Establish a Registry for Alzheimer’s Disease—Neuropsychological Assessment Battery (CERAD-NAB) test battery and two additional newly-developed neuropsychological tests (recollection and verbal comprehension) that aimed at carving out specific Alzheimer-typical deficits. Based on these test results, an underlying AD (pathologically increased TB ratio) was predicted with a machine learning algorithm. To this end, the algorithm was trained in each case on all patients except the one to predict (leave-one-out validation). In the total group, 82% of the patients could be correctly identified as AD or non-AD. In the early group with small general cognitive impairment, classification accuracy was increased to 89%. NPT thus seems to be capable of discriminating between AD patients and patients with cognitive impairment due to other neurodegenerative or vascular causes with a high accuracy, and may be used for screening in clinical routine and drug studies, especially in the early course of this disease.

Lewy body dementias

The broad importance of dementia is undisputed, with Alzheimer's disease justifiably getting the most attention. However, dementia with Lewy bodies and Parkinson's disease dementia, now called Lewy body dementias, are the second most common type of degenerative dementia in patients older than 65 years. Despite this, Lewy body dementias receive little attention and patients are often misdiagnosed, leading to less than ideal management. Over the past 10 years, considerable effort has gone into improving diagnostic accuracy by refining diagnostic criteria and using imaging and other biomarkers. Dementia with Lewy bodies and Parkinson's disease dementia share the same pathophysiology, and effective treatments will depend not only on successful treatment of symptoms but also on targeting the pathological mechanisms of disease, ideally before symptoms and clinical signs develop. We summarise the most pertinent progress from the past 10 years, outlining some of the challenges for the future, which will require refinement of diagnosis and clarification of the pathogenesis, leading to disease-modifying treatments.

The Mini-Addenbrooke's Cognitive Examination: a new assessment tool for dementia

BACKGROUND/AIMS

We developed and validated the Mini-Addenbrooke's Cognitive Examination (M-ACE) in dementia patients. Comparisons were also made with the Mini Mental State Examination (MMSE).

METHOD

The M-ACE was developed using Mokken scaling analysis in 117 dementia patients [behavioural variant frontotemporal dementia (bvFTD), n = 25; primary progressive aphasia (PPA), n = 49; Alzheimer's disease (AD), n = 34; corticobasal syndrome (CBS), n = 9] and validated in an independent sample of 164 dementia patients (bvFTD, n = 23; PPA, n = 82; AD, n = 38; CBS, n = 21) and 78 controls, who also completed the MMSE.

RESULTS

The M-ACE consists of 5 items with a maximum score of 30. Two cut-offs were identified: (1) ≤25/30 has both high sensitivity and specificity, and (2) ≤21/30 is almost certainly a score to have come from a dementia patient regardless of the clinical setting. The M-ACE is more sensitive than the MMSE and is less likely to have ceiling effects.

CONCLUSION

The M-ACE is a brief and sensitive cognitive screening tool for dementia. Two cut-offs (25 or 21) are recommended.

Transcranial magnetic stimulation and transcranial direct current stimulation: treatments for cognitive and neuropsychiatric symptoms in the neurodegenerative dementias?

Introduction

Two methods of non-invasive brain stimulation, transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have demonstrable positive effects on cognition and can ameliorate neuropsychiatric symptoms such as depression. Less is known about the efficacy of these approaches in common neurodegenerative diseases. In this review, we evaluate the effects of TMS and tDCS upon cognitive and neuropsychiatric symptoms in the major dementias, including Alzheimer’s disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), Parkinson’s disease with dementia (PDD), and frontotemporal dementia (FTD), as well as the potential pre-dementia states of Mild Cognitive Impairment (MCI) and Parkinson’s disease (PD).

Methods

PubMed (until 7 February 2014) and PsycINFO (from 1967 to January Week 3 2014) databases were searched in a semi-systematic manner in order to identify relevant treatment studies. A total of 762 studies were identified and 32 studies (18 in the dementias and 14 in PD populations) were included.

Results

No studies were identified in patients with PDD, FTD or VaD. Of the dementias, 13 studies were conducted in patients with AD, one in DLB, and four in MCI. A total of 16 of the 18 studies showed improvements in at least one cognitive or neuropsychiatric outcome measure. Cognitive or neuropsychiatric improvements were observed in 12 of the 14 studies conducted in patients with PD.

Conclusions

Both TMS and tDCS may have potential as interventions for the treatment of symptoms associated with dementia and PD. These results are promising; however, available data were limited, particularly within VaD, PDD and FTD, and major challenges exist in order to maximise the efficacy and clinical utility of both techniques. In particular, stimulation parameters vary considerably between studies and are likely to subsequently impact upon treatment efficacy.

Mild cognitive impairment and mild dementia: a clinical perspective

Mild cognitive impairment and mild dementia are common problems in the elderly. Primary care physicians are the first point of contact for most patients with these disorders and should be familiar with their diagnosis, prognosis, and management. Both mild cognitive impairment and mild dementia are characterized by objective evidence of cognitive impairment. The main distinctions between mild cognitive impairment and mild dementia are that in the latter, more than one cognitive domain is invariably involved and substantial interference with daily life is evident. The diagnosis of mild cognitive impairment and mild dementia is based mainly on the history and cognitive examination. The prognosis for mild cognitive impairment and mild dementia is an important motivation for diagnosis because in both, there is a heightened risk for further cognitive decline. The etiology of mild cognitive impairment and mild dementia can often be established through the clinical examination, although imaging and other laboratory tests may also contribute. Although Alzheimer disease is the most common cause of both, cerebrovascular disease and Lewy body disease make important contributions. Pharmacological treatments are of modest value in mild dementia due to Alzheimer disease, and there are no approved pharmacological treatments for mild cognitive impairment of any etiology. Nonetheless, new-onset cognitive impairment is a worrisome symptom to patients and families that demands answers and advice. If a patient is having difficulties managing medications, finances, or transportation independently, diagnosis and intervention are necessary to ensure the health and safety of the patient.

Overcoming barriers in cognitive assessment of Alzheimer's disease

Diagnosis of Alzheimer's disease (AD) requires a reliable neuropsychological assessment, but major barriers are still encountered when such tests are used across cultures and during the lifespan. This is particularly problematic in developing countries where most of the available assessment tools have been adapted from developed countries. This represents a major limitation as these tests, although properly translated, may not embody the wealth of challenges that a particular culture poses on cognition. This paper centers on two shortcomings of available cognitive tests for AD, namely, their sensitivity to the educational background and to the age of the individual assessed.

Functional brain networks and cognitive deficits in Parkinson's disease

Graph-theoretical analyses of functional networks obtained with resting-state functional magnetic resonance imaging (fMRI) have recently proven to be a useful approach for the study of the substrates underlying cognitive deficits in different diseases. We used this technique to investigate whether cognitive deficits in Parkinson's disease (PD) are associated with changes in global and local network measures. Thirty-six healthy controls (HC) and 66 PD patients matched for age, sex, and education were classified as having mild cognitive impairment (MCI) or not based on performance in the three mainly affected cognitive domains in PD: attention/executive, visuospatial/visuoperceptual (VS/VP), and declarative memory. Resting-state fMRI and graph theory analyses were used to evaluate network measures. We have found that patients with MCI had connectivity reductions predominantly affecting long-range connections as well as increased local interconnectedness manifested as higher measures of clustering, small-worldness, and modularity. The latter measures also tended to correlate negatively with cognitive performance in VS/VP and memory functions. Hub structure was also reorganized: normal hubs displayed reduced centrality and degree in MCI PD patients. Our study indicates that the topological properties of brain networks are changed in PD patients with cognitive deficits. Our findings provide novel data regarding the functional substrate of cognitive impairment in PD, which may prove to have value as a prognostic marker.

Prevalence and correlates of cognitive impairment in a north Indian elderly population

BACKGROUND

Cognitive impairment, an age-related condition, is often considered a precursor to more serious diseases such as depression/dementia/Alzheimer's disease. Alzheimer's disease, which is characterized by cognitive impairment, could have a devastating impact on low- and middle-income countries whose populations are ageing rapidly. The disease has, so far, largely remained neglected by researchers and national health services in India. In view of the growing elderly population and diverse sociocultural and geographical milieu of India, epidemiological data for the condition are desirable for different populations. Moreover, there is a dearth of population-based epidemiological studies on cognitive impairment in the Punjab state of India.

METHODS

Three thousand and thirty-eight consenting elderly adults aged over 60 years, of both sexes, residing in Ludhiana, Punjab state, India were examined for cognitive functioning, using a modified Hindi Mental State Examination, and a score of ≤25 was considered to be indicative of cognitive impairment. Data analysis included calculations of proportions; odds ratio and their 95% confidence intervals (CIs) were also calculated. The chi-square test and multiple logistic regression model were used to determine the association of cognitive impairment with various sociodemographic parameters.

RESULTS

The prevalence of cognitive impairment in the study population was 8.8% (95% CI = 8.06 to 9.54). Increasing age, unmarried/widowed status, illiteracy, unemployment and poverty were found to be independently associated with cognitive impairment.

CONCLUSIONS

The prevalence of cognitive impairment in this north Indian population of elderly individuals is higher than that found in northern India. With emerging focus on geriatric health services, cognitive impairment, which is a precursor of Alzheimer's disease/dementias, needs to be included in priority care within the national primary health-care framework.

The GGGGCC repeat expansion in C9ORF72 in a case with discordant clinical and FDG-PET findings: PET trumps syndrome

A hexanucleotide repeat expansion in the chromosome 9 open reading frame 72 (C9ORF72) gene was recently discovered as the cause underlying frontotemporal degeneration (FTD) and/or amyotrophic lateral sclerosis (ALS) linked to chromosome 9 (c9FTD/ALS). In this atypical case of c9FTD/ALS, the proband presented with amnestic mild cognitive impairment which evolved into Alzheimer's disease (AD)-type dementia and later developed ALS. Fluorodeoxyglucose-positron emission tomography of the brain demonstrated mild hypometabolism involving the medial frontal and lateral temporal lobes, left more so than right, which progressed over time. He was subsequently confirmed to have the C9ORF72 expansion. This report highlights the need to consider mutations in the FTD-associated genes when a familial disorder is suggested and neuroimaging studies reveal findings atypical of an AD pathophysiological process despite the typical anterograde amnestic syndrome.

Characterization of a family with c9FTD/ALS associated with the GGGGCC repeat expansion in C9ORF72

BACKGROUND

The hexanucleotide repeat in the chromosome 9 open reading frame 72 (C9ORF72) gene was recently discovered as the underlying genetic cause of many families with frontotemporal dementia (FTD) and/or amyotrophic lateral sclerosis (ALS) linked to chromosome 9 (c9FTD/ALS). We report the clinical, neuropsychologic, and neuroimaging findings of a family with the C9ORF72 mutation and clinical diagnoses bridging the FTD, parkinsonism, and ALS spectrum.

OBJECTIVE

To characterize the antemortem characteristics of a family with c9FTD/ALS associated with the GGGGCC repeat expansion in C9ORF72.

DESIGN

Clinical series.

SETTING

Tertiary care academic medical center. PATIENTS The members of a family affected by the mutation with features of FTD and/or ALS.

MAIN OUTCOME MEASURES

Clinical, neuropsychologic, and neuroimaging assessments.

RESULTS

All 3 examined subjects had the hexanucleotide expansion detected in C9ORF72. All had personality/behavioral changes early in the course of the disease. One case had levodopa-unresponsive parkinsonism, and 1 had ALS. Magnetic resonance imaging showed symmetric bilateral frontal, temporal, insular, and cingulate atrophy.

CONCLUSIONS

This report highlights the clinical and neuroimaging characteristics of a family with c9FTD/ALS. Further studies are needed to better understand the phenotypical variability and the cliniconeuroimaging-neuropathologic correlations.

P300 and neuropsychological assessment in mild cognitive impairment and Alzheimer dementia

Only a small proportion of individuals with Mild Cognitive Impairment (MCI) will convert to dementia. Methods currently available to identify risk for conversion do not combine enough sensitivity and specificity, which is even more problematic in low-educated populations. Current guidelines suggest the use of combined markers for dementia to enhance the prediction accuracy of assessment methods. The present study adhered to this proposal and investigated the sensitivity and specificity of the electrophysiological component P300 and standard neuropsychological tests to assess patients with Alzheimer's disease (AD) and MCI recruited from a low-income country. The neuropsychological battery comprised tests of memory, attention, language, praxis, and executive functions. The P300 was recorded using a classical visual odd-ball paradigm. Three variables were found to achieve sensitivity and specificity values above 80% (Immediate and Delayed recall of word list - CERAD - and the latency of P300) for both MCI and AD. When they entered the model together (i.e., combined approach) the sensitivity for MCI increased to 96% and the specificity remained high (80%). Our preliminary findings suggest that the combined use of sensitive neuropsychological tasks and the analysis of the P300 may offer a very useful method for the preclinical assessment of AD, particularly in populations with low socioeconomic and educational levels. Our results provide a platform and justification to employ more resources to convert P300 and related parameters into a biological marker for AD.

Universal health outcome measures for older persons with multiple chronic conditions

Older adults with multiple chronic conditions (MCCs) require considerable health services and complex care. Because the persistence and progression of diseases and courses of treatments affect health status in multiple dimensions, well-validated universal outcome measures across diseases are needed for research, clinical care, and administrative purposes. An expert panel meeting held by the National Institute on Aging in September 2011 recommends that older persons with MCCs complete a brief initial composite measure that includes general health; pain; fatigue; and physical health, mental health, and social role function, along with gait speed measurement. Suitable composite measures include the Medical Outcomes Study 8 (SF-8) and 36 (SF-36) -item Short-Form Survey and the Patient Reported Outcomes Measurement Information System 29-item Health Profile. Based on responses to items in the initial measure, short follow-on measures should be selectively targeted to symptom burden, depression, anxiety, and daily activities. Persons unable to walk a short distance to assess gait speed should be assessed using a physical function scale. Remaining gaps to be considered for measure development include disease burden, cognitive function, and caregiver burden. Routine outcome assessment of individuals with MCCs could facilitate system-based care improvement and clinical effectiveness research.

Progression of cortical thinning in early Parkinson's disease

The aim of this study was to investigate the progression of cortical thinning and gray-matter (GM) volume loss in early Parkinson's disease (PD). MRI and neuropsychological assessment were obtained at baseline and follow-up (mean ± standard deviation = 35.50 ± 1.88 months) in a group of 16 early-PD patients (H & Y stage ≤II and disease duration ≤5 years) and 15 healthy controls matched for age, gender, and years of education. FreeSurfer software was used for the analysis of cortical thickness as well as for cortical and subcortical volumetric analyses. Voxel-based morphometry analysis was performed using SPM8. Compared to controls, PD patients showed greater regional cortical thinning in bilateral frontotemporal regions as well as greater over-time total GM loss and amygdalar volume reduction. PD patients and controls presented similar over-time changes in cognitive functioning. In early-PD patients, global GM loss, amygdalar atrophy, and cortical thinning in frontotemporal regions are specifically associated with the PD-degenerative process.