Dementia: when is it not Alzheimer disease?

Intrusion errors during verbal fluency task in amyotrophic lateral sclerosis

BACKGROUND

Numerous studies have noted the presence of a dysexecutive component of the ALS-FTD. The most widely replicated result refers to the significantly reduced verbal fluency of ALS patients when compared to healthy people. As ALS patients have motor alterations that interfere with production, qualitative studies have the advantage of being independent of the degree of motor disability and revealing patients' cognitive state. This study examined the production differences between 42 ALS patients who presented with different degrees of dementia and motor impairment and 42 healthy people. Production processes were studied by extending the administration time of a letter fluency task to 2 minutes for the phonemic verbal fluency (PVF) and semantic verbal fluency (SVF) categories. This ensured that the qualitative aspects of verbal fluency were addressed, paying special attention to the new perseverations and intrusions, as well as any clinical correlates that may exist.

RESULTS

The ALS patients produced a significantly lower number of responses in PVF (p = .017) and SVF (p = .008). The rest of the indicators for frontal lobe alteration also suggested the existence of a dysfunction. The most remarkable results were the number of intrusions on the PVF task, which was much higher in the ALS group (p = .002). However, the number of perseverations did not differ significantly.

CONCLUSIONS

This study highlights the value of intrusions in addressing cognitive deterioration in ALS patients. This deterioration seems to be independent of the degree of motor impairment and of behavioural alterations. Therefore, the value of the intromissions on the verbal fluency task was highlighted as an indicator of a new cognitive alteration, which can be easily evaluated, even retrospectively.

Histone deacetylases enzyme, copper, and IL-8 levels in patients with Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive loss of cognitive abilities. Epigenetic modification, oxidative stress, and inflammation play an important role in the pathogenesis of the disease. We aimed to detect noninvasive peripheral biomarkers with a high degree of sensitivity and specificity in diagnosis and progression of AD.

METHODS

A total of 25 elderly patients with AD and 25 healthy control participants were selected and subjected to cognitive assessment and laboratory measures including histone deacetylases (HDACs), copper, and interleukin 8 (IL-8) levels.

RESULTS

The levels of HDACs, copper, and IL-8 were significantly higher in patients with AD (P < .001) and had a significant negative effect on all cognitive assessment tests. Receiver-operating curve (ROC) analysis revealed that HDACs and copper levels had higher sensitivity and specificity.

CONCLUSIONS

Plasma levels of HDACs and copper may be used as peripheral biomarkers in diagnosis of AD, while IL-8 level could be a useful biomarker in following AD progression.

Resting state cortical EEG rhythms in Alzheimer's disease: toward EEG markers for clinical applications: a review

The human brain contains an intricate network of about 100 billion neurons. Aging of the brain is characterized by a combination of synaptic pruning, loss of cortico-cortical connections, and neuronal apoptosis that provoke an age-dependent decline of cognitive functions. Neural/synaptic redundancy and plastic remodeling of brain networking, also secondary to mental and physical training, promote maintenance of brain activity and cognitive status in healthy elderly subjects for everyday life. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Growing evidence supports the idea that AD targets specific and functionally connected neuronal networks and that oscillatory electromagnetic brain activity might be a hallmark of the disease. In this line, digital electroencephalography (EEG) allows noninvasive analysis of cortical neuronal synchronization, as revealed by resting state brain rhythms. This review provides an overview of the studies on resting state eyes-closed EEG rhythms recorded in amnesic mild cognitive impairment (MCI) and AD subjects. Several studies support the idea that spectral markers of these EEG rhythms, such as power density, spectral coherence, and other quantitative features, differ among normal elderly, MCI, and AD subjects, at least at group level. Regarding the classification of these subjects at individual level, the most previous studies showed a moderate accuracy (70-80%) in the classification of EEG markers relative to normal and AD subjects. In conclusion, resting state EEG makers are promising for large-scale, low-cost, fully noninvasive screening of elderly subjects at risk of AD.

Genetic studies in Alzheimer's disease

Alzheimer's disease (AD), the most common cause of dementia in aged populations, is believed to be caused by both environmental factors and genetic variations. Extensive linkage and association studies have established that a broad range of loci are associated with AD, including both causative and susceptibility (risk factor) genes. So far, at least three genes, APP, PS1, and PS2, have been identified as causative genes. Mutations in these genes have been found to cause mainly early-onset AD. On the other hand, APOE has been identified to be the most common high genetic risk factor for late-onset AD. Polymorphisms in the coding region, intron, and promoter region of certain genes constitute another kind of genetic variation associated with AD. A number of other genes or loci have been reported to have linkage with AD, but many show only a weak linkage or the results are not well reproduced. Currently, the measurable genetic associations account for about 50% of the population risk for AD. It is believed that more new loci will be found to associate with AD, either as causative genes or genetic risk factors, and that eventually the understanding of genetic factors in the pathogenesis of AD will be important for our efforts to cure this illness.

Electroencephalographic rhythms in Alzheimer's disease

Physiological brain aging is characterized by synapses loss and neurodegeneration that slowly lead to an age-related decline of cognition. Neural/synaptic redundancy and plastic remodelling of brain networking, also due to mental and physical training, promotes maintenance of brain activity in healthy elderly subjects for everyday life and good social behaviour and intellectual capabilities. However, age is the major risk factor for most common neurodegenerative disorders that impact on cognition, like Alzheimer's disease (AD). Brain electromagnetic activity is a feature of neuronal network function in various brain regions. Modern neurophysiological techniques, such as electroencephalography (EEG) and event-related potentials (ERPs), are useful tools in the investigation of brain cognitive function in normal and pathological aging with an excellent time resolution. These techniques can index normal and abnormal brain aging analysis of corticocortical connectivity and neuronal synchronization of rhythmic oscillations at various frequencies. The present review suggests that discrimination between physiological and pathological brain aging clearly emerges at the group level, with suggested applications also at the level of single individual. The possibility of combining the use of EEG together with biological/neuropsychological markers and structural/functional imaging is promising for a low-cost, non-invasive, and widely available assessment of groups of individuals at-risk.

Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease

OBJECTIVE

To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ(42), tau, ptau(181), tau/Aβ(42), and ptau(181)/Aβ(42).

METHODS

Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models' concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone.

RESULTS

APOE genotype including an ε4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022).

CONCLUSIONS

The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses.

Alzheimer disease identification using amyloid imaging and reserve variables: proof of concept

OBJECTIVE

Several factors may influence the relationship between Alzheimer disease (AD) lesions and the expression of dementia, including those related to brain and cognitive reserve. Other factors may confound the association between AD pathology and dementia. We tested whether factors thought to influence the association of AD pathology and dementia help to accurately identify dementia of the Alzheimer type (DAT) when considered together with amyloid imaging.

METHODS

Participants with normal cognition (n = 180) and with DAT (n = 25), aged 50 years or older, took part in clinical, neurologic, and psychometric assessments. PET with the Pittsburgh compound B (PiB) tracer was used to measure brain amyloid, yielding a mean cortical binding potential (MCBP) reflecting PiB uptake. Logistic regression was used to generate receiver operating characteristic curves, and the areas under those curves (AUC), to compare the predictive accuracy of using MCBP alone vs MCBP together with other variables selected using a stepwise selection procedure to identify participants with DAT vs normal cognition.

RESULTS

The AUC resulting from MCBP alone was 0.84 (95% confidence interval [CI] = 0.73-0.94; cross-validated AUC = 0.80, 95% CI = 0.68-0.92). The AUC for the predictive equation generated by a stepwise model including education, normalized whole brain volume, physical health rating, gender, and use of medications that may interfere with cognition was 0.94 (95% CI = 0.90-0.98; cross-validated AUC = 0.91, 95% CI = 0.85-0.96), an improvement (p = 0.025) over that yielded using MCBP alone.

CONCLUSION

Results suggest that factors reported to influence associations between AD pathology and dementia can improve the predictive accuracy of amyloid imaging for the identification of symptomatic AD.

Extending the administration time of the letter fluency test increases sensitivity to cognitive status in aging

The authors examined whether extending the administration time of letter fluency from 1 minute per letter trial (standard administration) to 2 minutes increased the sensitivity of this test to cognitive status in aging. Participants (mean age = 84.6) were assigned to cognitive impairment (n = 20) and control (n = 40) groups. Pearson correlations and scatter plot analyses showed that associations between the Dementia Rating Scale scores and letter fluency were higher and less variable when performance on the latter was extended to 2 minutes. Analysis of variance (ANOVA) showed that the cognitive impairment group generated fewer words in the second minute of the letter fluency task compared to the control group. Finally, discriminant function analyses revealed that extending the letter fluency trials to 2 minutes increased discrimination between the control and cognitive impairment groups.

Diagnostic criteria influence dementia prevalence

OBJECTIVE

The objective of this study was to compare the prevalence of dementia using different diagnostic systems, and to investigate the influence of the different diagnostic components (memory impairment, personality changes, definition of other intellectual functions) on the prevalence.

METHODS

A general population sample of 1,019 elderly living in Gothenburg, Sweden was investigated by using the Comprehensive Psychopathological Rating Scale as well as specific assessments relevant for dementia diagnoses. Diagnoses were given according to the 9th and 10th version of the International Classification of Diseases (ICD-9, ICD-10) as well as the 3rd revised and 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R, DSM-IV). Further, "historical" criteria for dementia were applied as had been used in older studies.

RESULTS

DSM-IV dementia occurred most frequently (9.6%), followed by dementia according to "historical" criteria (7.4%), DSM-III-R (6.3%), ICD-10 (3.1%), and ICD-9 (1.2%). The kappa values for the agreement between the diagnostic systems were between 0.166 and 0.810. The requirement of both long-term and short-term memory impairment in DSM-III-R and personality changes in ICD-10 explained most of the differences. When these requirements were held constant, DSM-III-R, DSM-IV, ICD-10 and "historical" criteria identified predominantly the same persons as demented (kappa: 0.810-1.000).

CONCLUSION

Prevalence of dementia varied widely depending on diagnostic classification system used. For DSM-III-R, DSM-IV, ICD-10, and "historical" criteria, the definitions of personality changes and combinations of memory impairment lead to differing prevalence rates, whereas the definitions of other intellectual functions have little impact.

Clinical neurophysiology of aging brain: from normal aging to neurodegeneration

Physiological brain aging is characterized by a loss of synaptic contacts and neuronal apoptosis that provokes age-dependent decline of sensory processing, motor performance, and cognitive function. Neural redundancy and plastic remodelling of brain networking, also secondary to mental and physical training, promotes maintenance of brain activity in healthy elderly for everyday life and fully productive affective and intellectual capabilities. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Oscillatory electromagnetic brain activity is a hallmark of neuronal network function in various brain regions. Modern neurophysiological techniques including electroencephalography (EEG), event-related potential (ERP), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) can accurately index normal and abnormal brain aging to facilitate non-invasive analysis of cortico-cortical connectivity and neuronal synchronization of firing and coherence of rhythmic oscillations at various frequencies. The present review provides a perspective of these issues by assaying different neurophysiological methods and integrating the results with functional brain imaging findings. It is concluded that discrimination between physiological and pathological brain aging clearly emerges at the group level, with applications at the individual level also suggested. Integrated approaches utilizing neurophysiological techniques together with biological markers and structural and functional imaging are promising for large-scale, low-cost and non-invasive evaluation of at-risk populations. Practical implications of the methods are emphasized.

EEG dynamics in patients with Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder characterized by cognitive and intellectual deficits and behavior disturbance. The electroencephalogram (EEG) has been used as a tool for diagnosing AD for several decades. The hallmark of EEG abnormalities in AD patients is a shift of the power spectrum to lower frequencies and a decrease in coherence of fast rhythms. These abnormalities are thought to be associated with functional disconnections among cortical areas resulting from death of cortical neurons, axonal pathology, cholinergic deficits, etc. This article reviews main findings of EEG abnormalities in AD patients obtained from conventional spectral analysis and nonlinear dynamical methods. In particular, nonlinear alterations in the EEG of AD patients, i.e. a decreased complexity of EEG patterns and reduced information transmission among cortical areas, and their clinical implications are discussed. For future studies, improvement of the accuracy of differential diagnosis and early detection of AD based on multimodal approaches, longitudinal studies on nonlinear dynamics of the EEG, drug effects on the EEG dynamics, and linear and nonlinear functional connectivity among cortical regions in AD are proposed to be investigated. EEG abnormalities of AD patients are characterized by slowed mean frequency, less complex activity, and reduced coherences among cortical regions. These abnormalities suggest that the EEG has utility as a valuable tool for differential and early diagnosis of AD.