Quantitative Electroencephalography as a Diagnostic Tool for Alzheimer's Dementia in Adults with Down Syndrome

Toward the Identification of Neurophysiological Biomarkers for Alzheimer's Disease in Down Syndrome: A Potential Role for Cross-Frequency Phase-Amplitude Coupling Analysis

Cross-frequency coupling (CFC) mechanisms play a central role in brain activity. Pathophysiological mechanisms leading to many brain disorders, such as Alzheimer's disease (AD), may produce unique patterns of brain activity detectable by electroencephalography (EEG). Identifying biomarkers for AD diagnosis is also an ambition among research teams working in Down syndrome (DS), given the increased susceptibility of people with DS to develop early-onset AD (DS-AD). Here, we review accumulating evidence that altered theta-gamma phase-amplitude coupling (PAC) may be one of the earliest EEG signatures of AD, and therefore may serve as an adjuvant tool for detecting cognitive decline in DS-AD. We suggest that this field of research could potentially provide clues to the biophysical mechanisms underlying cognitive dysfunction in DS-AD and generate opportunities for identifying EEG-based biomarkers with diagnostic and prognostic utility in DS-AD.

Brain signal complexity in adults with Down syndrome: Potential application in the detection of mild cognitive impairment

Background

Down syndrome (DS) is considered the most frequent cause of early-onset Alzheimer’s disease (AD), and the typical pathophysiological signs are present in almost all individuals with DS by the age of 40. Despite of this evidence, the investigation on the pre-dementia stages in DS is scarce. In the present study we analyzed the complexity of brain oscillatory patterns and neuropsychological performance for the characterization of mild cognitive impairment (MCI) in DS.

Materials and methods

Lempel-Ziv complexity (LZC) values from resting-state magnetoencephalography recordings and the neuropsychological performance in 28 patients with DS [control DS group (CN-DS) (n = 14), MCI group (MCI-DS) (n = 14)] and 14 individuals with typical neurodevelopment (CN-no-DS) were analyzed.

Results

Lempel-Ziv complexity was lowest in the frontal region within the MCI-DS group, while the CN-DS group showed reduced values in parietal areas when compared with the CN-no-DS group. Also, the CN-no-DS group exhibited the expected pattern of significant increase of LZC as a function of age, while MCI-DS cases showed a decrease. The combination of reduced LZC values and a divergent trajectory of complexity evolution with age, allowed the discrimination of CN-DS vs. MCI-DS patients with a 92.9% of sensitivity and 85.7% of specificity. Finally, a pattern of mnestic and praxic impairment was significantly associated in MCI-DS cases with the significant reduction of LZC values in frontal and parietal regions (p = 0.01).

Conclusion

Brain signal complexity measured with LZC is reduced in DS and its development with age is also disrupted. The combination of both features might assist in the detection of MCI within this population.

Brain circuit pathology in Down syndrome: from neurons to neural networks

Down syndrome (DS), a genetic pathology caused by triplication of chromosome 21, is characterized by brain hypotrophy and impairment of cognition starting from infancy. While studies in mouse models of DS have elucidated the major neuroanatomical and neurochemical defects of DS, comparatively fewer investigations have focused on the electrophysiology of the DS brain. Electrical activity is at the basis of brain functioning. Therefore, knowledge of the way in which brain circuits operate in DS is fundamental to understand the causes of behavioral impairment and devise targeted interventions. This review summarizes the state of the art regarding the electrical properties of the DS brain, starting from individual neurons and culminating in signal processing in whole neuronal networks. The reported evidence derives from mouse models of DS and from brain tissues and neurons derived from individuals with DS. EEG data recorded in individuals with DS are also provided as a key tool to understand the impact of brain circuit alterations on global brain activity.

A new diagnostic approach in Alzheimer's disease: The critical flicker fusion threshold

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. Although AD treatment is still insufficient despite all the recent developments, detection and treatment in the early stage of disease have provided more clinical benefits.

Electroencephalographic functional connectivity is altered in persons with Down syndrome and Alzheimer's disease

BACKGROUND

Persons with Down syndrome (DS) are at increased risk of developing Alzheimer's dementia (DS-AD). Due to heterogeneity in the functioning in persons with DS, it is difficult to use cognitive testing to assess whether a person with DS has developed dementia due to AD. Electroencephalography (EEG) functional connectivity has shown promising results as a diagnostic tool for AD in persons without DS. In the current exploratory study, we investigated whether EEG functional connectivity could be used as a diagnostic marker of AD in persons with DS and the association with symptoms.

METHODS

Electroencephalography from 12 persons with DS and 16 persons with DS-AD were analysed, and both coherence and weighted phase lag index were calculated. In addition, we calculated the average coherence for fronto-parietal and temporo-parietal connections. Lastly, we investigated the correlation between the informant-based Dementia Screening Questionnaire in Intellectual Disability (DSQIID) and total alpha coherence.

RESULTS

Decreased alpha and increased delta coherence and weighted phase lag index were observed in DS-AD as compared with DS. The decrease in alpha coherence was more marked in the fronto-parietal connections as compared with the temporo-parietal connections. No significant correlation was found between DSQIID and total alpha coherence (P value = 0.095, rho = -0.335).

CONCLUSION

The decreased alpha coherence and weighted phase lag index have previously been found in AD. The increased delta coherence and weighted phase lag index may indicate a different initial neurophysiological presentation as compared with patients with AD or may be a sign of more advanced disease. Larger studies are needed to confirm the current findings.

Dynamic Causal Modeling of the Relationship between Cognition and Theta-alpha Oscillations in Adults with Down Syndrome

Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta–alpha activity (4–13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann’s Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta–alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4–13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.

Microstate Changes Associated With Alzheimer's Disease in Persons With Down Syndrome

Down syndrome (DS) is associated with development of dementia due to Alzheimer’s disease (AD). However, due to considerable heterogeneity in intellectual function among persons with DS, it is difficult to assess whether a person with DS has developed dementia due to AD (DS-AD). EEG spectral power has previously shown very promising results with increased slowing in DS-AD compared to DS. However, another technique called microstates may be used to assess whole-brain dynamics and has to our knowledge not previously been investigated in either DS or DS-AD. The aim of the current study was to assess whether microstates could be used to differentiate between adults with DS, and DS-AD. We included EEGs from 10 persons with DS and 15 persons with DS-AD in the analysis. For the microstate analyses, we calculated four global maps, which were then back-fitted to all the EEGs. Lastly, we extracted the duration, occurrence, and coverage for each of the microstates. Here, we found the four archetypical maps as has previously been reported in the literature. We did not find any significant difference between DS and DS-AD but the largest difference in microstate duration between DS and DS-AD was found in microstate A and D. These findings are in line with structural MR studies showing that both the frontal and temporal lobes are affected in persons with DS-AD. Microstates may potentially serve as a diagnostic marker, but larger studies are needed to confirm these findings.

Associations between electroencephalography power and Alzheimer's disease in persons with Down syndrome

BACKGROUND

It is complicated to diagnose dementia in persons with Down syndrome (DS). Older studies have, however, demonstrated low-frequency activity in electroencephalography (EEG) in persons with concurrent DS and Alzheimer's disease (DS-AD). The aim of this study was to examine whether it was possible to identify AD-associated changes (increased high-frequency power and decreased low-frequency power) in persons with DS-AD compared with DS.

METHODS

We included 21 persons with DS-AD and 16 with DS without cognitive deterioration assessed by the informant-based Dementia Screening Questionnaire in Intellectual Disability. EEG was recorded for all participants. Absolute power for each electrode and global power were calculated for all frequency bands for both eyes open and eyes closed.

RESULTS

For global power in the eyes closed condition, we found an increased global slow-frequency activity and a decreased global high-frequency activity in DS-AD compared with DS. In addition, we found a significant difference in the global alpha/delta ratio with the largest difference found for global alpha power in DS-AD compared with DS.

CONCLUSIONS

In the current study, we found that changes known to be associated with AD could also be identified when comparing DS-AD with DS using quantitative EEG. In general, these findings suggest that EEG might be a useful tool in diagnosing AD in persons with DS, but larger studies are needed.

Neuropsychological and neurophysiological characterization of mild cognitive impairment and Alzheimer's disease in Down syndrome

Down syndrome (DS) has been considered a unique model for the investigation of Alzheimer's disease (AD) but intermediate stages in the continuum are poorly defined. Considering this, we investigated the neurophysiological (i.e., magnetoencephalography [MEG]) and neuropsychological patterns of mild cognitive impairment (MCI) and AD in middle-aged adults with DS. The sample was composed of four groups: Control-DS (n = 14, mean age 44.64 ± 3.30 years), MCI-DS (n = 14, 51.64 ± 3.95 years), AD-DS (n = 13, 53.54 ± 6.58 years), and Control-no-DS (healthy controls, n = 14, 45.21 ± 4.39 years). DS individuals were studied with neuropsychological tests and MEG, whereas the Control-no-DS group completed only the MEG session. Our results showed that the AD-DS group exhibited a significantly poorer performance as compared with the Control-DS group in all tests. Furthermore, this effect was crucially evident in AD-DS individuals when compared with the MCI-DS group in verbal and working memory abilities. In the neurophysiological domain, the Control-DS group showed a widespread increase of theta activity when compared with the Control-no-DS group. With disease progression, this increased theta was substituted by an augmented delta, accompanied with a reduction of alpha activity. Such spectral pattern-specifically observed in occipital, posterior temporal, cuneus, and precuneus regions-correlated with the performance in cognitive tests. This is the first MEG study in the field incorporating both neuropsychological and neurophysiological information, and demonstrating that this combination of markers is sensitive enough to characterize different stages along the AD continuum in DS.

Outer Brain Oscillations in Down Syndrome

The present article reviews the relationship between sleep and oscillatory activity in Down Syndrome (DS), as well as the featuring emergent rhythmic activity across different brain states. A comprehensive discussion of the data from electroencephalographic studies in DS humans and transgenic/trisomic mouse models is provided, as well as data from signals collected from local field potentials (LFP) and intracellular recordings in DS mouse models. The first sections focus specially on the alpha phenotype consistently observed in DS subjects, as well as its description in DS childhood and aging. Subsequently, a review of the data reported in DS mouse models is presented with the aim to deepen on the mechanisms underlying altered rhythmic patterns. Further sections situate the state-of-the-art of the field, with a discussion on the possible circuit alterations that may underlie impaired alpha and gamma oscillatory activity. A further aim is to highlight the importance of studying network oscillatory activity in mouse models to infer alterations in the underlying circuits related to cognition, such as in intellectual disability. In this direction, a view of alpha and gamma rhythms generated by the cerebral cortex as a tool for evaluating an unbalance between excitation and inhibition in DS is claimed, which points out toward an over-inhibited network. A final aim is to situate oscillatory activity as a key phenomenon that may be used as a biomarker for monitoring as well the effect of novel therapeutic strategies.

Sleep Behavior and EEG Oscillations in Aged Dp(16)1Yey/+ Mice: A Down Syndrome Model

Down syndrome (DS) results from the triplication of genes located on human chromosome 21 (Hsa21). Though many cognitive and behavioral impairments are associated with DS, sleep disturbances remain poorly understood despite being a reported phenotype in approximately 60% of individuals diagnosed with DS. In this study, sleep and electroencephalography (EEG) oscillations were recorded from aged (12–14 mos.) Dp(16)1Yey/+ mice (Dp16), a mouse model of DS. We observed disrupted sleep demonstrated by increased activity during the dark phase and increased time awake at the expense of NREM sleep compared to wild-type mice. In addition, we found that Dp16 mice display significant differences in relative EEG power distribution among oscillation frequencies in both sleep and awake states. These results in Dp16 mice are consistent with sleep disturbances found in individuals with DS, and the abnormal EEG oscillations in aged Dp16 mice suggest a potential role for GABAergic activity in these sleep and EEG abnormalities. These sleep and EEG data reflect underlying differences in neuronal activity at the network level and thus are causative agents rather than merely symptoms of DS.

Neuroimaging and other modalities to assess Alzheimer's disease in Down syndrome

People with Down syndrome (DS) develop Alzheimer's disease (AD) at higher rates and a younger age of onset compared to the general population. As the average lifespan of people with DS is increasing, AD is becoming an important health concern in this group. Neuroimaging is becoming an increasingly useful tool in understanding the pathogenesis of dementia development in relation to clinical symptoms. Furthermore, neuroimaging has the potential to play a role in AD diagnosis and monitoring of therapeutics. This review describes major recent findings from in vivo neuroimaging studies analysing DS and AD via ligand-based positron emission tomography (PET), [18F] fluorodeoxyglucose (FDG)-PET, structural magnetic resonance imaging (sMRI), and diffusion tensor imaging (DTI). Electroencephalography (EEG) and retinal imaging are also discussed as emerging modalities. The review is organized by neuroimaging method and assesses the relationship between cognitive decline and neuroimaging changes. We find that amyloid accumulation seen on PET occurs prior to dementia onset, possibly as a precursor to the atrophy and white matter changes seen in MRI studies. Future PET studies relating tau distribution to clinical symptoms will provide further insight into the role this protein plays in dementia development. Brain activity changes demonstrated by EEG and metabolic changes seen via FDG-PET may also follow predictable patterns that can help track dementia progression. Finally, newer approaches such as retinal imaging will hopefully overcome some of the limitations of neuroimaging and allow for detection of dementia at an earlier stage.

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We review recent neuroimaging findings in the field of Down syndrome and Alzheimer's disease.

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Review is organized by neuroimaging methodology.

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Correlation between cognitive decline and imaging findings is considered.

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Neuroimaging is a useful tool for studying and monitoring Alzheimer's disease in the Down syndrome population.

Alzheimer's disease in people with Down's syndrome: the prospects for and the challenges of developing preventative treatments

People with Down's syndrome (DS) are at high risk for developing Alzheimer's disease (AD) at a relatively young age. This increased risk is not observed in people with intellectual disabilities for reasons other than DS and for this reason it is unlikely to be due to non-specific effects of having a neurodevelopmental disorder but, instead, a direct consequence of the genetics of DS (trisomy 21). Given the location of the amyloid precursor protein (APP) gene on chromosome 21, the amyloid cascade hypothesis is the dominant theory accounting for this risk, with other genetic and environmental factors modifying the age of onset and the course of the disease. Several potential therapies targeting the amyloid pathway and aiming to modify the course of AD are currently being investigated, which may also be useful for treating AD in DS. However, given that the neuropathology associated with AD starts many years before dementia manifests, any preventative treatment must start well before the onset of symptoms. To enable trials of such interventions, plasma, CSF, brain, and retinal biomarkers are being studied as proxy early diagnostic and outcome measures for AD. In this systematic review, we consider the prospects for the development of potential preventative treatments of AD in the DS population and their evaluation.

Cognitive decline and dementia in Down syndrome

PURPOSE OF REVIEW

Alzheimer's disease is most likely universal in older individuals with Down syndrome, due to having three copies of the amyloid precursor protein gene, resulting in amyloid-beta plaque deposition. Down syndrome is an important population in which to consider clinical trials of treatments to prevent or delay the development of dementia. However, assessment of subtler cognitive changes is challenging due to the presence of intellectual disability.

RECENT FINDINGS

Recent research confirmed that older adults with Down syndrome often present with cognitive decline: more than 80% may experience dementia by age 65 years. Efforts have been made to improve and validate neuropsychological assessment and to describe the relationship with comorbidities such as epilepsy and haemorrhagic stroke. There have also been advances in biomarkers such as neuroimaging using amyloid PET.

SUMMARY

Clinical trials of treatments, particularly in the presymptomatic phase of Alzheimer's disease, are important to consider in individuals with Down syndrome given their high dementia burden, and may also serve as proof of concept for other forms of Alzheimer's disease. However, further work is required to improve outcome measures and better understand the biomarkers of progression of disorder and their relationship with symptom development during the presymptomatic period.