Disease Tracking Markers for Alzheimer's Disease at the Prodromal (MCI) Stage

Resting State Electrophysiological Profiles and Their Relationship with Cognitive Performance in Cognitively Unimpaired Older Adults: A Systematic Review

Background

Aging is a complex and natural process. The physiological decline related to aging is accompanied by a slowdown in cognitive processes, which begins shortly after individuals reach maturity. These changes have been sometimes interpreted as a compensatory sign and others as a fingerprint of deterioration.

Objective

In this context, our aim is to uncover the mechanisms that underlie and support normal cognitive functioning in the brain during the later stages of life.

Methods

With this purpose, a systematic literature search was conducted using PubMed, Scopus, and Web of Science databases, which identified 781 potential articles. After applying inclusion and exclusion criteria, we selected 12 studies that examined the brain oscillations patterns in resting-state conditions associated with cognitive performance in cognitively unimpaired older adults.

Results

Although cognitive healthy aging was characterized differently across studies, and various approaches to analyzing brain activity were employed, our review indicates a relationship between alpha peak frequency (APF) and improved performance in neuropsychological scores among cognitively unimpaired older adults.

Conclusions

A higher APF is linked with a higher score in intelligence, executive function, and general cognitive performance, and could be considered an optimal, and easy-to-assess, electrophysiological marker of cognitive health in older adults.

Association of Chronic Obstructive Pulmonary Disease with Risk of Psychiatric Disorders: A Two-Sample Mendelian Randomization Study

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder often accompanied by comorbidities. Although the past few years have witnessed significant scientific progress, the potential relationship between COPD and mental illness remains a subject of debate.

Materials and Methods

We retrieved COPD data from the genome-wide association studies (GWAS) directory and data on mental illnesses, including Alzheimer's disease, schizophrenia, panic disorder, attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder, multiple disabilities, obsessive-compulsive disorder, post-traumatic stress disorder, and schizophrenia, from the Psychiatric Genomics Consortium. A two-sample Mendelian randomization (MR) approach was applied to explore the association between COPD and mental illnesses, with subgroup analyses based on smoking history.

Results

Our two-sample MR analysis revealed no causal link between overall COPD and the development of common psychiatric disorders. Subgroup analyses based on smoking history showed no causal association between never-smokers with COPD and the occurrence of psychiatric disorders. However, ever-smokers with COPD were associated with a significantly increased risk of ADHD (OR: 2.303, 95% CI: 1.558-3.403, P = 0.001) and a modestly reduced risk of Alzheimer's disease (OR: 0.994, 95% CI: 0.988-0.999, P = 0.034).

Conclusion

COPD patients with a history of smoking face a higher risk of developing ADHD but may experience a slight reduction in the risk of Alzheimer's disease. Conversely, there was no observed causal association between COPD and psychiatric disorders among patients who never smoked.

The interaction of global small vessel disease burden and Alzheimer's disease pathologies do not change the independent association of amyloid-beta with hippocampal volume: A longitudinal study on mild cognitive impairment subjects

The purpose of this study was to investigate whether the co-existence of global small vessel disease (SVD) burdens and Alzheimer's disease (AD) pathologies change hippocampal volume (HV) and cognitive function of mild cognitive impairment (MCI) subjects. We obtained MRI images, cerebrospinal fluid biomarkers (Aβ1-42 and p-tau), and neuropsychological tests of 310 MCI subjects from ADNI. The global SVD score was assessed. We used linear regression and linear mixing effect to analyze the effects of global SVD burdens, AD pathologies, and their interactions (SVD*AD) on baseline and longitudinal HV and cognition respectively. We used simple mediation effect to analyze the influencing pathways. After adjusting for global SVD and SVD*AD, Aβ remained independently correlated with baseline and longitudinal HV (std β = 0.294, p = .007; std β = 0.292, p < .001), indicating that global SVD did not affect the correlation between Aβ and HV. Global SVD score was correlated with longitudinal but not baseline HV (std β = 0.470, p = .050), suggesting that global SVD may be more representative of long-term permanent impairment. Global SVD, AD pathologies, and SVD*AD were independently correlated with baseline and longitudinal cognitions, in which the association of Aβ (B = 0.005, 95% CI: 0.005; 0.024) and p-tau (B = -0.002, 95% CI: -0.004; -0.000) with cognition were mediated by HV, suggesting that HV is more likely to explain the progression caused by AD pathology than SVD. The co-existence of global SVD and AD pathologies did not affect the individual association of Aβ on HV; HV played a more important role in the influence of AD pathology on cognition than in SVD.

Alzheimer's early detection in post-acute COVID-19 syndrome: a systematic review and expert consensus on preclinical assessments

Introduction

The risk of developing Alzheimer's disease (AD) in older adults increasingly is being discussed in the literature on Post-Acute COVID-19 Syndrome (PACS). Remote digital Assessments for Preclinical AD (RAPAs) are becoming more important in screening for early AD, and should always be available for PACS patients, especially for patients at risk of AD. This systematic review examines the potential for using RAPA to identify impairments in PACS patients, scrutinizes the supporting evidence, and describes the recommendations of experts regarding their use.

Methods

We conducted a thorough search using the PubMed and Embase databases. Systematic reviews (with or without meta-analysis), narrative reviews, and observational studies that assessed patients with PACS on specific RAPAs were included. The RAPAs that were identified looked for impairments in olfactory, eye-tracking, graphical, speech and language, central auditory, or spatial navigation abilities. The recommendations' final grades were determined by evaluating the strength of the evidence and by having a consensus discussion about the results of the Delphi rounds among an international Delphi consensus panel called IMPACT, sponsored by the French National Research Agency. The consensus panel included 11 international experts from France, Switzerland, and Canada.

Results

Based on the available evidence, olfaction is the most long-lasting impairment found in PACS patients. However, while olfaction is the most prevalent impairment, expert consensus statements recommend that AD olfactory screening should not be used on patients with a history of PACS at this point in time. Experts recommend that olfactory screenings can only be recommended once those under study have reported full recovery. This is particularly important for the deployment of the olfactory identification subdimension. The expert assessment that more long-term studies are needed after a period of full recovery, suggests that this consensus statement requires an update in a few years.

Conclusion

Based on available evidence, olfaction could be long-lasting in PACS patients. However, according to expert consensus statements, AD olfactory screening is not recommended for patients with a history of PACS until complete recovery has been confirmed in the literature, particularly for the identification sub-dimension. This consensus statement may require an update in a few years.

Memory-driven eye movements prospectively predict dementia in people at risk of Alzheimer's disease

Introduction

Oculomotor behaviors linked to cognitive performance revealed neurocognitive features of Alzheimer's disease (AD) that can enhance the accuracy of its assessment and diagnosis.

Methods

A sample of 107 participants (i.e., 65 mild cognitive impairment [MCI] and 42 controls) were recruited and followed up for 40 months. At baseline, they underwent assessment with the ViewMind digital biomarker, which draws cognitive-related patterns of eye movement while people perform the visual short-term memory binding task.

Results

Baseline data predicted that 36 patients with MCI would progress to the AD clinical syndrome (ADS Progressing). The remaining 29 MCI patients were predicted to remain as MCI or progress to other forms of dementia. After 40 months of follow-up, 94% of ADS Progressing patients had received a diagnosis of dementia, whereas none of the non-ADS Progressing had.

Discussion

The analysis of eye movement behavior combined with cognitive markers for AD can effectively predict progression to ADS among patients with MCI.

Alzheimer's Disease: Efficacy of Mono- and Combination Therapy. A Systematic Review

IMPORTANCE

Alzheimer's disease (AD) is a complex neurodegenerative disorder and the most prevalent cause of dementia. In spite of the urgent need for more effective AD drug therapy strategies, evidence of the efficacy of combination therapy with existing drugs remains unclear.

OBJECTIVE

To assess the efficacy of combined drug therapy on cognition and progress in patients with AD in comparison to single agent drug therapy.

METHODS

The electronic databases MEDLINE and EMBASE were systematically searched to identify relevant publications. Only randomized controlled clinical trials were included, but no limits were applied to language or time published. Data were extracted from May 27th until December 29th, 2020.

RESULTS

Three trials found that a combination of ChEI with additional memantine provides a slight benefit for patients with moderate to severe AD over ChEI monotherapy and placebo. However, a further 4 trials could not replicate this effect. One trial reported benefits of add-on Gingko biloba in donepezil-treated patients with moderate AD (using a formula containing Gingko and other antioxidants) compared to donepezil with placebo. A further trial found no significant effect of combining EGb 761® and donepezil in patients with probable AD over donepezil with placebo. Approaches with idalopirdine, atorvastatin or vitamin supplementation in combination with ChEI have not proven effective and have not been retried since. Fluoxetine and ST101 have shown partial benefits in combination with ChEI over ChEI monotherapy and placebo. However, these effects must be replicated by further research.

CONCLUSION

Additional memantine in combination with ChEI might be of slight benefit in patients with moderate to severe AD, but evidence is ambiguous. Longer trials are needed. No major cognitive benefit is missed, if solely appropriate ChEI monotherapy is initiated.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

The Impact of Disease Registries on Advancing Knowledge and Understanding of Dementia Globally

To help address the increasing challenges related to the provision of dementia care, dementia registries have emerged around the world as important tools to gain insights and a better understanding of the disease process. Dementia registries provide a valuable source of standardized data collected from a large number of patients. This review explores the published research relating to different dementia registries around the world and discusses how these registries have improved our knowledge and understanding of the incidence, prevalence, risk factors, mortality, diagnosis, and management of dementia. A number of the best-known dementia registries with high research output including SveDem, NACC, ReDeGi, CREDOS and PRODEM were selected to study the publication output based on their data, investigate the key findings of these registry-based studies. Registries data contributed to understanding many aspects of the disease including disease prevalence in specific areas, patient characteristics and how they differ in populations, mortality risks, as well as the disease risk factors. Registries data impacted the quality of patients’ lives through determining the best treatment strategy for a patient based on previous patient outcomes. In conclusion, registries have significantly advanced scientific knowledge and understanding of dementia and impacted policy, clinical practice care delivery.

Characterising activity and diet compositions for dementia prevention: protocol for the ACTIVate prospective longitudinal cohort study

INTRODUCTION

Approximately 40% of late-life dementia may be prevented by addressing modifiable risk factors, including physical activity and diet. Yet, it is currently unknown how multiple lifestyle factors interact to influence cognition. The ACTIVate Study aims to (1) explore associations between 24-hour time-use and diet compositions with changes in cognition and brain function; and (2) identify duration of time-use behaviours and the dietary compositions to optimise cognition and brain function.

METHODS AND ANALYSIS

This 3-year prospective longitudinal cohort study will recruit 448 adults aged 60-70 years across Adelaide and Newcastle, Australia. Time-use data will be collected through wrist-worn activity monitors and the Multimedia Activity Recall for Children and Adults. Dietary intake will be assessed using the Australian Eating Survey food frequency questionnaire. The primary outcome will be cognitive function, assessed using the Addenbrooke's Cognitive Examination-III. Secondary outcomes include structural and functional brain measures using MRI, cerebral arterial pulse measured with diffuse optical tomography, neuroplasticity using simultaneous transcranial magnetic stimulation and electroencephalography, and electrophysiological markers of cognitive control using event-related potential and time frequency analyses. Compositional data analysis, testing for interactions between time point and compositions, will assess longitudinal associations between dependent (cognition, brain function) and independent (time-use and diet compositions) variables.

CONCLUSIONS

The ACTIVate Study will be the first to examine associations between time-use and diet compositions, cognition and brain function. Our findings will inform new avenues for multidomain interventions that may more effectively account for the co-dependence between activity and diet behaviours for dementia prevention.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from the University of South Australia's Human Research Ethics committee (202639). Findings will be disseminated through peer-reviewed manuscripts, conference presentations, targeted media releases and community engagement events.

TRIAL REGISTRATION NUMBER

Australia New Zealand Clinical Trials Registry (ACTRN12619001659190).

Cross-sectional associations of tau protein biomarkers with semantic and episodic memory in older adults without dementia: A systematic review and meta-analysis

Pathological tau is suggested to play a role in cognitive deterioration in the preclinical phase of Alzheimer's disease. We investigated cross-sectional associations of tau burden with episodic and semantic memory performance in older adults without dementia. A systematic search in MEDLINE (via PubMed), PsychINFO, and Embase resulted in 24 eligible studies for meta-analysis. Tau burden was assessed using CSF, PET, or histopathological measures. All studies evaluated associations of tau with episodic memory: weighted effect sizes were -0.46 (95 % CI [-0.73; -0.20], p < .001) for episodic composite scores, -0.19 ([-0.36; -0.03], p = .024) for delayed word list recall, and -0.05 ([-0.14; 0.04], p = .257) for logical memory. Fourteen studies evaluated associations of tau with semantic memory: weighted effect sizes were -0.28 ([-0.52; -0.04], p = .023) for semantic composite scores, -0.06 ([-0.16; 0.03], p = .194) for semantic fluency, and 0.06 ([-0.06; 0.18], p = .319) for picture naming. Our findings indicate that tau burden related to both episodic and semantic memory impairment in older individuals without a diagnosis of mild cognitive impairment or manifest dementia, with episodic composite scores showing the strongest association with tau burden. Future potential lies in developing more sensitive scores to detect this subtle cognitive impairment, which could contribute to early identification of individuals in the preclinical phase of Alzheimer's disease, thereby improving early diagnosis and timely intervention.

The diagnosis of amnestic mild cognitive impairment by combining the characteristics of brain functional network and support vector machine classifier

BACKGROUND

Amnestic mild cognitive impairment (aMCI) is an essential stage of early detection and potential intervention for Alzheimer's disease (AD). Patients with aMCI exhibit partially abnormal functional brain connectivity and it is suggested that these features may represent a new diagnostic marker of early AD.

NEW METHOD

In this paper, we constructed two brain network models, a phase synchronization index (PSI) undirected network and a directed transfer function (DTF) directed network, to evaluate the cognitive function in patients with aMCI. We then built SVM classification models using the network clustering coefficient, global efficiency and average node degree as features to distinguish between aMCI patients and controls.

RESULTS

Our results reveal a classification accuracy and AUC of 66.6 ± 1.7% and 0.7475 and 80.0 ± 2.2% and 0.7825, respectively, for the two network models (PSI and DTF). As the directed network model performed better than the undirected model, we introduced an improved graph theory feature, efficiency density, which resulted in an increased classification accuracy and AUC value 86.6 ± 2.6% and 0.8295, respectively.

COMPARISON WITH EXISTING METHODS

The analysis of network models and the directionality of information flow is suitable for analysis of nonlinear EEG signals for assessment of the functional state of the brain. Compared with traditional network features, our proposed improved features more comprehensively evaluate transmission efficiency and density of the brain.

CONCLUSION

In this study, we demonstrate that an improved efficiency density feature is helpful for enhancing classification the accuracy of aMCI. Moreover, directed brain network models exhibit better classification for aMCI diagnosis than undirected networks.

Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer's disease in a cross-sectional multi-cohort study

Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In this study, we assessed normative models based on deep autoencoders using structural neuroimaging data from patients with Alzheimer's disease (n = 206) and mild cognitive impairment (n = 354). We first trained the autoencoder on an independent dataset (UK Biobank dataset) with 11,034 healthy controls. Then, we estimated how each patient deviated from this norm and established which brain regions were associated to this deviation. Finally, we compared the performance of our normative model against traditional classifiers. As expected, we found that patients exhibited deviations according to the severity of their clinical condition. The model identified medial temporal regions, including the hippocampus, and the ventricular system as critical regions for the calculation of the deviation score. Overall, the normative model had comparable cross-cohort generalizability to traditional classifiers. To promote open science, we are making all scripts and the trained models available to the wider research community.

Cerebrospinal Fluid of Patients With Alzheimer's Disease Contains Increased Percentages of Synaptophysin-Bearing Microvesicles

Introduction

In Alzheimer’s disease, the severity of symptoms is linked to a loss of synaptic density and the spread of pathologically hyperphosphorylated tau. The established cerebrospinal fluid markers Aβ, tau and phospho-tau reflect the histopathological hallmarks of Alzheimer’s disease but do not indicate disease progression. Such markers are of special interest, especially for trials of disease modifying drugs. Microvesicles are produced by stressed cells and reflect part of the metabolism of their cells of origin. Therefore, we investigated microvesicles of neuronal origin in cerebrospinal fluid.

Materials and Methods

We used flow cytometry to analyze microvesicles carrying tau, phospho-tau-Thr181, phospho-tau-Ser202Thr205, synaptophysin, and SNAP-25 in the cerebrospinal fluid of 19 patients with Alzheimer’s disease and 15 non-inflammatory neurological disease controls.

Results

The percentages of synaptophysin-bearing microvesicles were significantly higher in the cerebrospinal fluid of patients with Alzheimer’s disease than in the CSF of non-inflammatory neurological disease controls. Tau, phospho-tau-Thr181, phospho-tau-Ser202Thr205, and SNAP-25 did not differ between the groups. The percentages of synaptophysin-bearing vesicles distinguished patients with Alzheimer’s disease from the controls (AUC = 0.81).

Conclusion

The loss of synapses in Alzheimer’s disease may be reflected by synaptophysin-bearing microvesicles in the cerebrospinal fluid. Future studies are needed to investigate the possibility of using these MVs as a marker to determine the activity of Alzheimer’s disease.

Mild Cognitive Impairment and Neurofeedback: A Randomized Controlled Trial

Background and Objectives: Mild cognitive impairment (MCI) is often a precursor of dementia, and in particular of Alzheimer's Disease (AD) which is the most common cause of dementia. Individuals with amnestic MCI are several-fold more likely to develop AD than the general population. Therefore, MCI comprises a well-detectable, early stage time-point for therapeutic intervention and strategic prevention. Based on common electroencephalographical (EEG) pattern changes seen in individuals with MCI, we postulated that EEG-based neurofeedback could help improve the memory performance of patients with MCI. Memory performance is of particular importance in these patients, since memory decline is the most prominent symptom in most patients with MCI, and is the most predictive symptom for cognitive deterioration and the development of AD.

Methods: In order to improve the memory performance of patients with MCI we used a system of EEG-based neurofeedback in an attempt to reverse alterations of the EEG that are known to be common in patients with MCI. Our protocol comprised the provision of positive feedback in order to enhance the activity level of the upper alpha band. Participants were divided to two groups receiving either neurofeedback training to enhance the upper alpha frequency (Experimental group) or random feedbacks (Sham group)

Results: We witnessed a significant improvement in memory performance in subjects in the experimental group compared to those in the sham group. This improvement was maintained for at least 1 month.

Conclusions: Neurofeedback may be a promising and affordable novel approach for treating the decline in memory witnessed in patients with MCI.

Subjective organization in the episodic memory of individuals with Parkinson's disease associated with mild cognitive impairment

Word clustering (i.e., the ability to reproduce the same word pairs in consecutive recall trials of an unrelated word list) has been extensively investigated as a proxy of subjective organization (SO) of memorandum. In healthy subjects and in groups of brain-damaged patients, the rate of SO generally predicts accuracy of word list recall. This study aimed at evaluating SO in the performance of patients with Parkinson's disease (PD) on a word list recall task in order to investigate the basic mechanisms of episodic memory impairment that are frequently observed in these patients. For this purpose, 56 PD patients, who were stratified according to the presence and quality of mild cognitive impairment (MCI), and a group of healthy controls (HCs) were administered a word list task and an extensive battery of neuropsychological tests. Results showed that recall accuracy on the word list task progressively decreased passing from HC to PD patients without cognitive impairment, to patients with single-domain dysexecutive MCI and to patients with multiple-domain dysexecutive and amnesic MCI. Conversely, only the latter PD group showed a lower SO score than that achieved by the other groups. In the overall PD group, correlational and regression analyses demonstrated that SO scores and a composite score of executive functions were not reciprocally related, but both provided an independent and significant contribution to the prediction of word list recall accuracy. These data are discussed in terms of the contribution of executive functions and hippocampal storage processes to the onset of memory impairment in PD.

Differences between episodic and semantic memory in predicting observation-based activities of daily living in mild cognitive impairment and Alzheimer's disease

Individuals with mild cognitive impairment (MCI) can often progress into Alzheimer's Disease (AD). Research suggests that decline in episodic memory and semantic memory, as well as functional abilities, can be sensitive in predicting disease progression. This study aimed to (a) investigate episodic and semantic memory performance differences between AD and MCI, (b) determine if memory performance predicts observation-based activities of daily living (ADLs), and (c) explore whether semantic memory mediates the relationship between episodic memory and ADLs. Fifty-eight AD, 53 MCI, and 72 healthy control participants were administered the Rey-O, California Verbal Learning Test, Animal Fluency Test, Boston Naming Test, and Direct Assessment of Functional Status (DAFS). The results revealed, first, that AD participants performed significantly lower than the MCI participants across semantic memory and episodic memory tasks, with the exception of the Boston Naming Test. Second, hierarchical-stepwise regression analyses found that semantic memory significantly predicted DAFS orientation, communication, and financial skills in AD, but episodic memory predicted shopping skills. Furthermore, semantic memory significantly predicted DAFS transportation skills in AD and MCI. Third, within the overall sample, semantic memory mediated the relationship between episodic memory and ADLs. Taken together, the findings suggest decline in semantic memory (as measured by confrontational naming and category fluency) and episodic memory (as measured by list and complex visual design learning and recall) may lead to decline in different and specific aspects of functional abilities in AD and MCI.

Event-related potentials using the auditory novel paradigm in patients with myotonic dystrophy

Many neuropsychological disorders, especially attentional abnormality, are present in patients with myotonic dystrophy type 1 (DM1), but the underlying mechanisms remain unclear. This study aimed to evaluate attention function by auditory event-related potential (ERP) P3a (novelty paradigm) in DM1 patients. A total of 10 young DM1 patients (mean age 30.4 years) and 14 age-matched normal controls participated in this study. ERPs were recorded using an auditory novel paradigm, consisting of three types of stimuli, i.e., standard sound (70%), target sound (20%), and various novel sounds (10%), and participants pressed buttons to the target sounds. ERP components P3b after the target stimuli and P3a following the novel stimuli were analyzed. Correlations of neuropsychological evaluations with the amplitudes and latencies of P3b and P3a were analyzed in DM1 patients. We found that P3a latency was significantly delayed in patients with DM1 compared with normal controls, although the latency and amplitude of P3b in DM1 patients were comparable with those in normal controls. The achievement rates of both the Symbol Digit Modality Test and the Paced Auditory Serial Addition Test were significantly correlated with P3a amplitude, as well as P3b amplitude. These results suggest that ERPs, including P3a and P3b, provide important insights into the physiological basis of neuropsychological abnormalities in patients with DM1, especially from the viewpoint of the frontal lobe and attention function.

A history of cigarette smoking is associated with faster functional decline and reduction of entorhinal cortex volume in mild cognitive impairment

Little is known about the longitudinal association of cigarette smoking with Alzheimer's Disease (AD) related markers in subjects with mild cognitive impairment (MCI). In this study, we aimed to examine the effect of a history of cigarette smoking on change in global cognition, verbal memory, functional performance, hippocampal volume, entorhinal cortex volume, brain glucose metabolism, and CSF AD pathologies over time in MCI subjects. At baseline, there were 870 subjects with MCI, including 618 non-smokers (no history of smoking) and 252 smokers (any lifetime history of smoking). Linear mixed models were fitted for each outcome with adjustment of several covariates. The major findings were: (1) Among older people with MCI, smokers showed faster decline in functional performance compared to non-smokers; (2) Smokers demonstrated steeper decline in entorhinal cortex volume than non-smokers; (3) A history of cigarette smoking was not associated with change in CSF Aβ42, t-tau or p-tau levels over time in MCI subjects. In conclusion, we found that a history of cigarette smoking was associated with faster decline in functional performance and entorhinal cortex volume over time at the prodromal stage of dementia.

Body Temperature Is Associated With Cognitive Performance in Older Adults With and Without Mild Cognitive Impairment: A Cross-sectional Analysis

Wearable devices for remote and continuous health monitoring in older populations frequently include sensors for body temperature measurements (i.e., skin and core body temperatures). Healthy aging is associated with core body temperatures that are in the lower range of age-related normal values (36.3 ± 0.6°C, oral temperature), while patients with Alzheimer's disease (AD) exhibit core body temperatures above normal values (up to 0.2°C). However, the relation of body temperature measures with neurocognitive health in older adults remains unknown. This study aimed to explore the association of body temperature with cognitive performance in older adults with and without mild cognitive impairment (MCI). Eighty community-dwelling older adults (≥65 years) participated, of which 54 participants were cognitively healthy and 26 participants met the criteria for MCI. Skin temperatures at the rib cage and the scapula were measured in the laboratory (single-point measurement) and neuropsychological tests were conducted to assess general cognitive performance, episodic memory, verbal fluency, executive function, and processing speed. In a subgroup (n = 15, nine healthy, six MCI), skin and core body temperatures were measured continuously during 12 h of habitual daily activities (long-term measurement). Spearman's partial correlation analyses, controlled for age, revealed that lower median body temperature and higher peak-to-peak body temperature amplitude was associated with better general cognitive performance and with better performance in specific domains of cognition; [e.g., rib median skin temperature (single-point) vs. processing speed: rs = 0.33, p = 0.002; rib median skin temperature (long-term) vs. executive function: rs = 0.56, p = 0.023; and peak-to-peak core body temperature amplitude (long-term) vs. episodic memory: rs = 0.51, p = 0.032]. Additionally, cognitively healthy older adults showed lower median body temperature and higher peak-to-peak body temperature amplitude compared to older adults with MCI (e.g., rib median skin temperature, single-point: p = 0.035, r = 0.20). We conclude that both skin and core body temperature measures are potential early biomarkers of cognitive decline and preclinical symptoms of MCI/AD. It may therefore be promising to integrate body temperature measures into multi-parameter systems for the remote and continuous monitoring of neurocognitive health in older adults.

Effects of Smoking on Regional Homogeneity in Mild Cognitive Impairment: A Resting-State Functional MRI Study

Background

Smoking is a modifiable risk factor for Alzheimer’s disease (AD). However, smoking-related effects on intrinsic brain activity in high-risk AD population are still unclear.

Objective

We aimed to explore differences in smoking effects on brain function between healthy elderly and amnestic mild cognitive impairment (aMCI) patients using ReHo mapping.

Methods

We identified 64 healthy elderly controls and 116 aMCI patients, including 98 non-smoking and 18 smoking aMCI. Each subject underwent structural and resting-state functional MRI scanning and neuropsychological evaluations. Regional homogeneity (ReHo) mapping was used to assess regional brain synchronization. After correction for age, gender, education, and gray matter volume, we explored the difference of ReHo among groups in a voxel-wise way based on analysis of covariance (ANCOVA), followed by post hoc two-sample analyses (p < 0.05, corrected). Further, we correlated the mean ReHo with neuropsychological scales.

Results

Three groups were well-matched in age, gender, and education. Significant ReHo differences were found among three groups, located in the left supramarginal gyrus (SMG) and left angular gyrus (AG). Specifically, non-smoking aMCI had lower ReHo in SMG and AG than smoking aMCI and controls. By contrast, smoking aMCI had greater AG ReHo than healthy controls (p < 0.05). Across groups, correlation analyses showed that left AG ReHo correlated with MMSE (r = 0.18, p = 0.015), clock drawing test (r = 0.20, p = 0.007), immediate recall (r = 0.36, p < 0.001), delayed recall (r = 0.34, p < 0.001), and auditory verbal learning test (r = 0.20, p = 0.007).

Conclusion

Smoking might pose compensatory or protective effects on intrinsic brain activity in aMCI patients.

The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease

BACKGROUND

Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects.

OBJECTIVE

The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls.

METHODS

AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes.

RESULTS

Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism.

CONCLUSION

Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively.

Cross-sectional associations of amyloid burden with semantic cognition in older adults without dementia: A systematic review and meta-analysis

Previous research suggests the presence of subtle semantic decline in early stages of Alzheimer's disease. This study investigated associations between amyloid burden, a biomarker for Alzheimer's disease, and tasks of semantic impairment in older individuals without dementia. A systematic search in MEDLINE, PsycINFO, and Embase yielded 3691 peer-reviewed articles excluding duplicates. After screening, 41 studies with overall 7495 participants were included in the meta-analysis and quality assessment. The overall weighted effect size of the association between larger amyloid burden and larger semantic impairment was 0.10 (95% CI [-0.03; 0.22], p = 0.128) for picture naming, 0.19 (95% CI [0.11; 0.27], p < 0.001) for semantic fluency, 0.15 (95% CI [-0.15; 0.45], p = 0.326) for vocabulary, and 0.10 (95% CI [-0.14; 0.35], p = 0.405; 2 studies) for WAIS Information. Risk of bias was highest regarding comparability, as effect sizes were often not calculated on covariate-adjusted statistics. The relevance of the indicated amyloid-related decline in semantic fluency for research and clinical applications is likely negligible due to the effect's small magnitude. Future research should develop more sensitive metrics of semantic fluency to optimize its use for early detection of Alzheimer's disease-related cognitive impairment.

Functional Alterations in the Olfactory Neuronal Circuit Occur before Hippocampal Plasticity Deficits in the P301S Mouse Model of Tauopathy: Implications for Early Diagnosis and Translational Research in Alzheimer's Disease

Alzheimer's disease (AD) is characterized by neuronal loss and impaired synaptic transmission, ultimately leading to cognitive deficits. Early in the disease, the olfactory track seems most sensitive to tauopathy, while most plasticity studies focused on the hippocampal circuits. Functional network connectivity (FC) and long-term potentiation (LTP), considered as the plasticity substrate of learning and memory, were longitudinally assessed in mice of the P301S model of tauopathy following the course (time and location) of progressively neurodegenerative pathology (i.e., at 3, 6, and 9 months of age) and in their wild type (WT) littermates. Using in vivo local field potential (LFP) recordings, early (at three months) dampening in the gamma oscillatory activity and impairments in the phase-amplitude theta-gamma coupling (PAC) were found in the olfactory bulb (OB) circuit of P301S mice, which were maintained through the whole course of pathology development. In contrast, LFP oscillatory activity and PAC indices were normal in the entorhinal cortex, hippocampal CA1 and CA3 nuclei. Field excitatory postsynaptic potential (fEPSP) recordings from the Shaffer collateral (SC)-CA1 hippocampal stratum pyramidal revealed a significant altered synaptic LTP response to high-frequency stimulation (HFS): at three months of age, no significant difference between genotypes was found in basal synaptic activity, while signs of a deficit in short term plasticity were revealed by alterations in the fEPSPs. At six months of age, a slight deviance was found in basal synaptic activity and significant differences were observed in the LTP response. The alterations in network oscillations at the OB level and impairments in the functioning of the SC-CA1 pyramidal synapses strongly suggest that the progression of tau pathology elicited a brain area, activity-dependent disturbance in functional synaptic transmission. These findings point to early major alterations of neuronal activity in the OB circuit prior to the disturbance of hippocampal synaptic plasticity, possibly involving tauopathy in the anomalous FC. Further research should determine whether those early deficits in the OB network oscillations and FC are possible mechanisms that potentially promote the emergence of hippocampal synaptic impairments during the progression of tauopathy.

Impaired Phasic Discharge of Locus Coeruleus Neurons Based on Persistent High Tonic Discharge-A New Hypothesis With Potential Implications for Neurodegenerative Diseases

The locus coeruleus (LC) is a small brainstem nucleus with widely distributed noradrenergic projections to the whole brain, and loss of LC neurons is a prominent feature of age-related neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD). This article discusses the hypothesis that in early stages of neurodegenerative diseases, the discharge mode of LC neurons could be changed to a persistent high tonic discharge, which in turn might impair phasic discharge. Since phasic discharge of LC neurons is required for the release of high amounts of norepinephrine (NE) in the brain to promote anti-inflammatory and neuroprotective effects, persistent high tonic discharge of LC neurons could be a key factor in the progression of neurodegenerative diseases. Transcutaneous vagal stimulation (t-VNS), a non-invasive technique that potentially increases phasic discharge of LC neurons, could therefore provide a non-pharmacological treatment approach in specific disease stages. This article focuses on LC vulnerability in neurodegenerative diseases, discusses the hypothesis that a persistent high tonic discharge of LC neurons might affect neurodegenerative processes, and finally reflects on t-VNS as a potentially useful clinical tool in specific stages of AD and PD.

Neurofeedback Improves Memory and Peak Alpha Frequency in Individuals with Mild Cognitive Impairment

Mild cognitive impairment (MCI) is a syndrome characterized by a decrease in cognitive abilities, while daily function is maintained. This condition, which is associated with an increased risk for the development of Alzheimer's disease, has no known definitive treatment at present. In this open-label pilot study we explored the possible benefits of neurofeedback for subjects with MCI. Eleven participants diagnosed with MCI were trained to increase the power of their individual upper alpha band of the electroencephalogram (EEG) signal over the central parietal region. This was achieved using an EEG-based neurofeedback training protocol. Training comprised ten 30-min sessions delivered over 5 weeks. Cognitive and electroencephalographic assessments were conducted before and after training and at 30 days following the last training session. A dose-dependent increase in peak alpha frequency was observed throughout the period of training. Memory performance also improved significantly following training, and this improvement was maintained at 30-day follow-up, while peak alpha frequency returned to baseline at this evaluation. Our findings suggest that neurofeedback may improve memory performance in subjects with mild cognitive impairment, and this benefit may be maintained beyond the training period.

New Horizons in Early Dementia Diagnosis: Can Cerebellar Stimulation Untangle the Knot?

Differentiating Mild Cognitive Impairment (MCI) from dementia and estimating the risk of MCI-to-dementia conversion (MDC) are challenging tasks. Thus, objective tools are mandatory to get early diagnosis and prognosis. About that, there is a growing interest on the role of cerebellum-cerebrum connectivity (CCC). The aim of this study was to differentiate patients with an early diagnosis of dementia and MCI depending on the effects of a transcranial magnetic stimulation protocol (intermittent theta-burst stimulation -iTBS) delivered on the cerebellum able to modify cortico-cortical connectivity. Indeed, the risk of MDC is related to the response to iTBS, being higher in non-responder individuals. All patients with MCI, but eight (labelled as MCI-), showed preserved iTBS aftereffect. Contrariwise, none of the patients with dementia showed iTBS aftereffects. None of the patients showed EEG aftereffects following a sham TBS protocol. Five among the MCI- patients converted to dementia at 6-month follow-up. Our data suggest that cerebellar stimulation by means of iTBS may support the differential diagnosis between MCI and dementia and potentially identify the individuals with MCI who may be at risk of MDC. These findings may help clinicians to adopt a better prevention/follow-up strategy in such patients.

Early Electrophysiological Disintegration of Hippocampal Neural Networks in a Novel Locus Coeruleus Tau-Seeding Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive, neurodegenerative disease characterized by loss of synapses and disrupted functional connectivity (FC) across different brain regions. Early in AD progression, tau pathology is found in the locus coeruleus (LC) prior to amyloid-induced exacerbation of clinical symptoms. Here, a tau-seeding model in which preformed synthetic tau fibrils (K18) were unilaterally injected into the LC of P301L mice, equipped with multichannel electrodes for recording EEG in frontal cortical and CA1-CA3 hippocampal areas, was used to longitudinally quantify over 20 weeks of functional network dynamics in (1) power spectra; (2) FC using intra- and intersite phase-amplitude theta-gamma coupling (PAC); (3) coherence, partial coherence, and global coherent network efficiency (Eglob) estimates; and (4) the directionality of functional connectivity using extended partial direct coherence (PDC). A sustained leftward shift in the theta peak frequency was found early in the power spectra of hippocampal CA1 networks ipsilateral to the injection site. Strikingly, hippocampal CA1 coherence and Eglob measures were impaired in K18-treated animals. Estimation of instantaneous EEG amplitudes revealed deficiency in the propagation directionality of gamma oscillations in the CA1 circuit. Impaired PAC strength evidenced by decreased modulation of the theta frequency phase on gamma frequency amplitude further confirms impairments of the neural CA1 network. The present results demonstrate early dysfunctional hippocampal networks, despite no spreading tau pathology to the hippocampus and frontal cortex. The ability of the K18 seed in the brainstem LC to elicit such robust functional alterations in distant hippocampal structures in the absence of pathology challenges the classic view that tau pathology spread to an area is necessary to elicit functional impairments in that area.

Associations of event-related brain potentials and Alzheimer's disease severity: A longitudinal study

BACKGROUND

So far, no cost-efficient, widely-used biomarkers have been established to facilitate the objectivization of Alzheimer's disease (AD) diagnosis and monitoring. Research suggests that event-related potentials (ERPs) reflect neurodegenerative processes in AD and might qualify as neurophysiological AD markers.

OBJECTIVES

First, to examine which ERP component correlates the most with AD severity, as measured by the Mini-Mental State Examination (MMSE). Then, to analyze the temporal change of this component as AD progresses.

METHODS

Sixty-three subjects (31 with possible, 32 with probable AD diagnosis) were recruited as part of the cohort study Prospective Dementia Registry Austria (PRODEM). For a maximum of 18 months patients revisited every 6 months for follow-up assessments. ERPs were elicited using an auditory oddball paradigm. P300 and N200 latency was determined with regard to target as well as difference wave ERPs, whereas P50 amplitude was measured from standard stimuli waveforms.

RESULTS

P300 latency exhibited the strongest association with AD severity (e.g., r = -0.512, p < 0.01 at Pz for target stimuli in probable AD subjects). Further, there were significant Pearson correlations for N200 latency (e.g., r = -0.407, p = 0.026 at Cz for difference waves in probable AD subjects). P50 amplitude, as measured by different detection methods and at various scalp sites, did not significantly correlate with disease severity - neither in probable AD, possible AD, nor in both subgroups of patients combined. ERP markers for the group of possible AD patients did not show any significant correlations with MMSE scores. Post-hoc pairwise comparisons between baseline and 18-months follow-up assessment revealed significant P300 latency differences (e.g., p < 0.001 at Cz for difference waves in probable AD subjects). However, there were no significant correlations between the change rates of P300 latency and MMSE score.

CONCLUSIONS

P300 and N200 latency significantly correlated with disease severity in probable AD, whereas P50 amplitude did not. P300 latency, which showed the highest correlation coefficients with MMSE, significantly increased over the course of the 18 months study period in probable AD patients. The magnitude of the observed prolongation is in line with other longitudinal AD studies and substantially higher than in normal ageing, as reported in previous trials (no healthy controls were included in our study).

Multivariate Prediction of Hippocampal Atrophy in Alzheimer's Disease

BACKGROUND

Hippocampal atrophy (HA) is one of the biomarkers for Alzheimer's disease (AD).

OBJECTIVE

To identify the best biomarkers and develop models for prediction of HA over 24 months using baseline data.

METHODS

The study included healthy elderly controls, subjects with mild cognitive impairment, and subjects with AD, obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI 1) and the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) databases. Predictor variables included cognitive and neuropsychological tests, amyloid-β, tau, and p-tau from cerebrospinal fluid samples, apolipoprotein E, and features extracted from magnetic resonance images (MRI). Least-mean-squares regression with elastic net regularization and least absolute deviation regression models were tested using cross-validation in ADNI 1. The generalizability of the models including only MRI features was evaluated by training the models with ADNI 1 and testing them with AIBL. The models including the full set of variables were not evaluated with AIBL because not all needed variables were available in it.

RESULTS

The models including the full set of variables performed better than the models including only MRI features (root-mean-square error (RMSE) 1.76-1.82 versus 1.93-2.08). The MRI-only models performed well when applied to the independent validation cohort (RMSE 1.66-1.71). In the prediction of dichotomized HA (fast versus slow), the models achieved a reasonable prediction accuracy (0.79-0.87).

CONCLUSIONS

These models can potentially help identifying subjects predicted to have a faster HA rate. This can help in selection of suitable patients into clinical trials testing disease-modifying drugs for AD.

Evaluating Peripersonal Space through the Functional Transcranial Doppler: Are We Paving the Way for Early Detecting Mild Cognitive Impairment to Dementia Conversion?

BACKGROUND

Identifying the patients with mild cognitive impairment (MCI) who may develop dementia (MDC) is challenging. The study of peripersonal space (PPS) by using functional transcranial Doppler (fTCD) could be used for this purpose.

OBJECTIVE

To identify changes in cerebral blood flow (CBF) during motor tasks targeting PPS, which can predict MDC.

METHODS

We evaluated the changes in CBF in 22 patients with MCI and 23 with dementia [Alzheimer's disease (AD) and vascular dementia (VaD)] during a motor task (passive mobilization, motor imagery, and movement observation) in which the hand of the subject moved forward and backward the face.

RESULTS

CBF increased when the hand approached the face and decreased when the hand moved from the face in the healthy controls (HCs). CBF changed were detectable only in patients with MCI but not in those with the AD and those who were MDC after 8-month follow-up. On the other hand, the patients with VaD presented a paradoxical response to the motor task (i.e., a decrease of CBF rather than an increase, as observed in HCs and MCI). Therefore, we found a modulation of PPS-related CBF only in HCs and patients with stable MCI (at the 8-month follow-up).

CONCLUSIONS

fTCD may allow preliminarily differentiating and following-up the patients with MCI and MDC, thus allowing the physician to plan beforehand more individualized cognitive rehabilitative training.

Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.

Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices

The increasing miniaturization and affordability of sensors and circuitry has led to the current level of innovation in the area of wearable and microsensor solutions for health monitoring. This facilitates the development of solutions that can be used to measure complex health outcomes in nonspecialist and remote settings. In this article, we review a number of innovations related to brain monitoring including portable and wearable solutions to directly measure brain electrical activity, and solutions measuring aspects related to brain function such as sleep patterns, gait, cognition, voice acoustics, and gaze analysis. Despite the need for more scientific validation work, we conclude that there is enough understanding of how to implement these approaches as exploratory tools that may provide additional valuable insights due to the rich and frequent data they produce, to justify their inclusion in clinical study protocols.

Sleep Disorders Associated With Alzheimer's Disease: A Perspective

Sleep disturbances, as well as sleep-wake rhythm disturbances, are typical symptoms of Alzheimer's disease (AD) that may precede the other clinical signs of this neurodegenerative disease. Here, we describe clinical features of sleep disorders in AD and the relation between sleep disorders and both cognitive impairment and poor prognosis of the disease. There are difficulties of the diagnosis of sleep disorders based on sleep questionnaires, polysomnography or actigraphy in the AD patients. Typical disturbances of the neurophysiological sleep architecture in the course of the AD include deep sleep and paradoxical sleep deprivation. Among sleep disorders occurring in patients with AD, the most frequent disorders are sleep breathing disorders and restless legs syndrome. Sleep disorders may influence circadian fluctuations of the concentrations of amyloid-β in the interstitial brain fluid and in the cerebrovascular fluid related to the glymphatic brain system and production of the amyloid-β. There is accumulating evidence suggesting that disordered sleep contributes to cognitive decline and the development of AD pathology. In this mini-review, we highlight and discuss the association between sleep disorders and AD.

Blood-Based Oligomeric and Other Protein Variant Biomarkers to Facilitate Pre-Symptomatic Diagnosis and Staging of Alzheimer's Disease

Oligomeric forms of amyloid-β (Aβ), tau, and TDP-43 play important roles in Alzheimer's disease (AD), and therefore are promising biomarkers. We previously generated single chain antibody fragments (scFvs) that selectively bind disease-related variants of these proteins including A4, C6T, and E1, which bind different oligomeric Aβ variants; D11C, which binds oligomeric tau; and AD-TDP1 and AD-TDP2, which bind disease related TDP-43 variants. To determine the utility of these disease-related variants as early biomarkers, we first analyzed 11 human sera samples obtained ∼2 years prior to an initial mild cognitive impairment (MCI) diagnosis. While the subsequent diagnoses for the cases covered several different conditions, all samples had elevated protein variant levels relative to the plasma controls although with different individual biomarker profiles. We then analyzed a set of longitudinal human plasma samples from four AD (encompassing time points prior to MCI diagnosis and continuing until after conversion to AD) and two control cases. Pre-MCI samples were characterized by high TDP-43 variant levels, MCI samples by high Aβ variant levels, and AD samples by high Aβ and tau variant levels. Sample time points ranged from ∼7 years pre-MCI to ∼9 years after AD conversion. Bivariate correlations showed a negative correlation with TDP-43 levels and positive correlations with cumulative Aβ and oligomeric tau levels indicating an increase in neurodegenerative processes with time in AD. Detection of disease related protein variants not only readily selects AD cases from controls, but also stages progression of AD and holds promise for a pre-symptomatic blood-based biomarker profile for AD.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Research criteria for Alzheimer's disease recommend the use of biomarkers for diagnosis, but whether biomarkers improve the diagnosis in clinical routine has not been systematically assessed. The aim is to evaluate the evidence for use of medial temporal lobe atrophy (MTA) as a biomarker for Alzheimer's disease at the mild cognitive impairment stage in routine clinical practice, with an adapted version of the 5-phase oncology framework for biomarker development. A literature review on visual assessment of MTA and hippocampal volumetry was conducted with other biomarkers addressed in parallel reviews. Ample evidence is available for phase 1 (rationale for use) and phase 2 (discriminative ability between diseased and control subjects). Phase 3 (early detection ability) is partly achieved: most evidence is derived from research cohorts or clinical populations with short follow-up, but validation in clinical mild cognitive impairment cohorts is required. In phase 4, only the practical feasibility has been addressed for visual rating of MTA. The rest of phase 4 and phase 5 have not yet been addressed.

Connectivity Changes in Parkinson's Disease

Parkinson's disease (PD) is a chronic and progressive movement disorder of the central nervous system characterized by widespread alterations in several non-motor aspects such as mood, sleep, olfactory, and cognition in addition to motor dysfunctions. Advanced neuroimaging using functional connectivity reconstruction of the human brain has provided a vast knowledge on the pathophysiological mechanisms underlying this disorder, but this, however, does not cover the overall inter-/intra-individual variability of PD phenotypes. The present review is aimed at discussing to what extent the evidence provided by group-based neuroimaging analysis in this field of study (using seed-based, network-based, or graph theory approaches) may be generalized. In particular, we summarized the literature on the application of resting-state functional connectivity studies to explore different neural correlates of motor and non-motor symptoms of PD and the neural mechanisms involved in treatment effects: effects of levodopa or deep brain stimulation. The lesson learnt from one decade of studies provides consistent evidence on the role of the altered communication between the striato-frontal pathways as a marker of PD-related motor degeneration, whereas in the non-motor domain, several missing pieces of a complex puzzle are provided. However, the main target is to present a new era of intelligent neuroimaging applications, where automated multivariate analysis of functional connectivity data may be used for moving from group-level statistical results to personalized predictions in a clinical setting. Although in its relative infancy, the evidence gathered so far suggests a new era of clinical neuroimaging is starting.

Reliability of EEG Interactions Differs between Measures and Is Specific for Neurological Diseases

Alterations of interaction (connectivity) of the EEG reflect pathological processes in patients with neurologic disorders. Nevertheless, it is questionable whether these patterns are reliable over time in different measures of interaction and whether this reliability of the measures is the same across different patient populations. In order to address this topic we examined 22 patients with mild cognitive impairment, five patients with subjective cognitive complaints, six patients with right-lateralized temporal lobe epilepsy, seven patients with left lateralized temporal lobe epilepsy, and 20 healthy controls. We calculated 14 measures of interaction from two EEG-recordings separated by 2 weeks. In order to characterize test-retest reliability, we correlated these measures for each group and compared the correlations between measures and between groups. We found that both measures of interaction as well as groups differed from each other in terms of reliability. The strongest correlation coefficients were found for spectrum, coherence, and full frequency directed transfer function (average rho > 0.9). In the delta (2–4 Hz) range, reliability was lower for mild cognitive impairment compared to healthy controls and left lateralized temporal lobe epilepsy. In the beta (13–30 Hz), gamma (31–80 Hz), and high gamma (81–125 Hz) frequency ranges we found decreased reliability in subjective cognitive complaints compared to mild cognitive impairment. In the gamma and high gamma range we found increased reliability in left lateralized temporal lobe epilepsy patients compared to healthy controls. Our results emphasize the importance of documenting reliability of measures of interaction, which may vary considerably between measures, but also between patient populations. We suggest that studies claiming clinical usefulness of measures of interaction should provide information on the reliability of the results. In addition, differences between patient groups in reliability of interactions in the EEG indicate the potential of reliability to serve as a new biomarker for pathological memory decline as well as for epilepsy. While the brain concert of information flow is generally variable, high reliability, and thus, low variability may reflect abnormal firing patterns.

A six-month longitudinal evaluation significantly improves accuracy of predicting incipient Alzheimer's disease in mild cognitive impairment

RATIONALE AND OBJECTIVES

Early prediction of incipient Alzheimer's disease (AD) dementia in individuals with mild cognitive impairment (MCI) is important for timely therapeutic intervention and identifying participants for clinical trials at greater risk of developing AD. Methods to predict incipient AD in MCI have mostly utilized cross-sectional data. Longitudinal data enables estimation of the rate of change of variables, which along with the variable levels have been shown to improve prediction power. While some efforts have already been made in this direction, all previous longitudinal studies have been based on observation periods longer than one year, hence limiting their practical utility. It remains to be seen if follow-up evaluations within shorter intervals can significantly improve the accuracy of prediction in this problem. Our aim was to determine the added value of incorporating 6-month longitudinal data for predicting progression from MCI to AD.

MATERIALS AND METHODS

Using 6-months longitudinal data from 247 participants with MCI, we trained two Random Forest classifiers to distinguish between progressive MCI (n=162) and stable MCI (n=85) cases. These models utilized structural MRI, neurocognitive assessments, and demographic information. The first model (cross-sectional) only used baseline data. The second model (longitudinal) used data from both baseline and a 6-month follow-up evaluation allowing the model to additionally incorporate biomarkers' rate of change.

RESULTS

The longitudinal model (AUC=0.87; accuracy=80.2%) performed significantly better (P<0.05) than the cross-sectional model (AUC=0.82; accuracy=71.7%).

CONCLUSION

Short-term longitudinal assessments significantly enhance the performance of AD prediction models.

Theta and Alpha Alterations in Amnestic Mild Cognitive Impairment in Semantic Go/NoGo Tasks

Growing evidence suggests that cognitive control processes are impaired in amnestic mild cognitive impairment (aMCI); however the nature of these alterations needs further examination. The current study examined differences in electroencephalographic theta and alpha power related to cognitive control processes involving response execution and response inhibition in 22 individuals with aMCI and 22 age-, sex-, and education-matched cognitively normal controls. Two Go/NoGo tasks involving semantic categorization were used. In the basic categorization task, Go/NoGo responses were made based on exemplars of a single car (Go) and a single dog (NoGo). In the superordinate categorization task, responses were made based on multiple exemplars of objects (Go) and animals (NoGo). Behavioral data showed that the aMCI group had more false alarms during the NoGo trials compared to controls. The EEG data revealed between group differences related to response type in theta (4–7 Hz) and low-frequency alpha (8–10 Hz) power. In particular, the aMCI group differed from controls in theta power during the NoGo trials at frontal and parietal electrodes, and in low-frequency alpha power during Go trials at parietal electrodes. These results suggest that alterations in theta power converge with behavioral deterioration in response inhibition, whereas alterations in low-frequency alpha power appear to precede behavioral changes in response execution. Both behavioral and electrophysiological correlates combined provide a more comprehensive characterization of cognitive control deficits in aMCI.

Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Efficacy of future treatments depends on biomarkers identifying patients with mild cognitive impairment at highest risk for transitioning to Alzheimer's disease. Here, we applied recently developed analysis techniques to investigate cross-sectional differences in subcortical shape and volume alterations in patients with stable mild cognitive impairment (MCI) (n = 23, age range 59–82, 47.8% female), future converters at baseline (n = 10, age range 66–84, 90% female) and at time of conversion (age range 68–87) compared to group-wise age and gender matched healthy control subjects (n = 23, age range 61–81, 47.8% female; n = 10, age range 66–82, 80% female; n = 10, age range 68–82, 70% female). Additionally, we studied cortical thinning and global and local measures of hippocampal atrophy as known key imaging markers for Alzheimer's disease. Apart from bilateral striatal volume reductions, no morphometric alterations were found in cognitively stable patients. In contrast, we identified shape alterations in striatal and thalamic regions in future converters at baseline and at time of conversion. These shape alterations were paralleled by Alzheimer's disease like patterns of left hemispheric morphometric changes (cortical thinning in medial temporal regions, hippocampal total and subfield atrophy) in future converters at baseline with progression to similar right hemispheric alterations at time of conversion. Additionally, receiver operating characteristic curve analysis indicated that subcortical shape alterations may outperform hippocampal volume in identifying future converters at baseline. These results further confirm the key role of early cortical thinning and hippocampal atrophy in the early detection of Alzheimer's disease. But first and foremost, and by distinguishing future converters but not patients with stable cognitive abilities from cognitively normal subjects, our results support the value of early subcortical shape alterations and reduced hippocampal subfield volumes as potential markers for the early detection of Alzheimer's disease.

Genome-wide significant risk factors for Alzheimer's disease: role in progression to dementia due to Alzheimer's disease among subjects with mild cognitive impairment

Few data are available concerning the role of risk markers for Alzheimer's disease (AD) in progression to AD dementia among subjects with mild cognitive impairment (MCI). We therefore investigated the role of well-known AD-associated single-nucleotide polymorphism (SNP) in the progression from MCI to AD dementia. Four independent MCI data sets were included in the analysis: (a) the German study on Aging, Cognition and Dementia in primary care patients (n=853); (b) the German Dementia Competence Network (n=812); (c) the Fundació ACE from Barcelona, Spain (n=1245); and (d) the MCI data set of the Amsterdam Dementia Cohort (n=306). The effects of single markers and combined polygenic scores were measured using Cox proportional hazards models and meta-analyses. The clusterin (CLU) locus was an independent genetic risk factor for MCI to AD progression (CLU rs9331888: hazard ratio (HR)=1.187 (1.054-1.32); P=0.0035). A polygenic score (PGS1) comprising nine established genome-wide AD risk loci predicted a small effect on the risk of MCI to AD progression in APOE-ɛ4 (apolipoprotein E-ɛ4) carriers (HR=1.746 (1.029-2.965); P=0.038). The novel AD loci reported by the International Genomics of Alzheimer's Project were not implicated in MCI to AD dementia progression. SNP-based polygenic risk scores comprising currently available AD genetic markers did not predict MCI to AD progression. We conclude that SNPs in CLU are potential markers for MCI to AD progression.

Pharmaco-EEG Studies in Animals: An Overview of Contemporary Translational Applications

The contemporary value of animal pharmaco-electroencephalography (p-EEG)-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. While p-EEG in humans and animals has been shown to be closely related in terms of underlying neuronal substrates, both translational and back-translational approaches are being used to address extrapolation issues and optimize the translational validity of preclinical animal p-EEG paradigms and data. Present applications build further on animal p-EEG and pharmaco-sleep EEG findings, but also on stimulation protocols, more specifically pharmaco-event-related potentials. Pharmaceutical research into novel treatments for neurological and psychiatric diseases has employed an increasing number of pharmacological as well as transgenic models to assess the potential therapeutic involvement of different neurochemical systems and novel drug targets as well as underlying neuronal connectivity and synaptic function. Consequently, p-EEG studies, now also readily applied in modeled animals, continue to have an important role in drug discovery and development, with progressively more emphasis on its potential as a central readout for target engagement and as a (translational) functional marker of neuronal circuit processes underlying normal and pathological brain functioning. In a similar vein as was done for human p-EEG studies, the contribution of animal p-EEG studies can further benefit by adherence to guidelines for methodological standardization, which are presently under construction by the International Pharmaco-EEG Society (IPEG).

Neuroimaging biomarkers in Alzheimer's disease and other dementias

In vivo imaging of β-amyloid (Aβ) has transformed the assessment of Aβ pathology and its changes over time, extending our insight into Aβ deposition in the brain by providing highly accurate, reliable, and reproducible quantitative statements of regional or global Aβ burden in the brain. This knowledge is essential for therapeutic trial recruitment and for the evaluation of anti-Aβ treatments. Although cross sectional evaluation of Aβ burden does not strongly correlate with cognitive impairment, it does correlate with cognitive (especially memory) decline and with a higher risk for conversion to AD in the aging population and MCI subjects. This suggests that Aβ deposition is a protracted pathological process starting well before the onset of symptoms. Longitudinal observations, coupled with different disease-specific biomarkers to assess potential downstream effects of Aβ are required to confirm this hypothesis and further elucidate the role of Aβ deposition in the course of Alzheimer's disease.

Impact of leptin on memory function and hippocampal structure in mild cognitive impairment

Metabolic changes have been suggested to contribute to dementia and its precursor mild cognitive impairment (MCI), yet previous results particularly for the "satiety hormone" leptin are mixed. Therefore, we aimed to determine if MCI patients show systematic differences in leptin, independent of sex, adipose mass, age, and glucose and lipid metabolism, and whether leptin levels correlated with memory performance and hippocampal integrity. Forty MCI patients (20 females, aged 67 years ± 7 SD) were compared to 40 healthy controls (HC) that were pair-wise matched for sex, age, and body fat. Memory performance was assessed using the auditory verbal learning test. Volume and microstructure of the hippocampus were determined using 3T-neuroimaging. Fasting serum markers of leptin, glucose and lipid metabolism, and other confounding factors were assayed. MCI patients, compared with HC, showed lower serum leptin, independent of sex, age, and body fat (P < 0.001). Glucose and lipid markers did not attenuate these results. Moreover, MCI patients exhibited poorer memory and lower volume and microstructural integrity within hippocampal subfields. While leptin and memory were not significantly correlated, mediation analyses indicated that lower leptin contributed to poorer memory through its negative effect on right hippocampus volume and left hippocampus microstructure. We demonstrated that MCI is associated with lower serum leptin independent of sex, age, body fat, glucose, and lipid metabolism. Our data further suggest that inefficient leptin signaling could partly contribute to decreases in memory performance through changes in hippocampus structure, a hypothesis that should now be verified in longitudinal studies. Hum Brain Mapp 37:4539-4549, 2016. © 2016 Wiley Periodicals, Inc.