The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Modifications and Responsiveness in Pre-Dementia Populations. A Narrative Review

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

A Brief Version of the LASSI-L Detects Prodromal Alzheimer's Disease States

BACKGROUND

The Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) is an increasingly utilized cognitive stress test designed to identify early cognitive changes associated with incipient neurodegenerative disease.

OBJECTIVE

To examine previously derived cut-points for cognitively unimpaired older adults that were suggestive of performance impairment on multiple subscales of the LASSI-L. These cut-points were applied to a new sample of older adults who were cognitive healthy controls (HC: n = 26) and those on the Alzheimer's disease (AD) continuum from early stage mild cognitive impairment (EMCI: n = 28), late stage MCI (LMCI: n = 18) to mild AD (AD: n = 27).

METHODS

All participants were administered the LASSI-L. All cognitively impaired participants were PET amyloid positive which likely reflects underlying AD neuropathology, while cognitively normal counterparts were deemed to have amyloid negative scans.

RESULTS

There was a monotonic relationship between the number of deficits on LASSI-L subscales and independent classification of study groups with greater severity of cognitive impairment. Importantly, taken together, impairment on maximum learning ability and measures of proactive semantic interference (both reflected by cued recall and intrusion errors) correctly classified 74.1% of EMCI, 94.4% of LMCI, and 96.3% of AD. Only 7.7% of HC were incorrectly classified as having impairments.

CONCLUSION

A modest number of LASSI-L subscales taking approximately 8 minutes to administer, had excellent discriminative ability using established cut-offs among individuals with presumptive stages of AD. This has potential implications for both clinical practice and clinical research settings targeting AD during early prodromal stages.

Rivastigmine in Parkinson's Disease Dementia with Orthostatic Hypotension

OBJECTIVE

The purpose of this study was to evaluate if the cognitive benefit of rivastigmine is affected by the presence of orthostatic hypotension (OH) in patients with Parkinson's disease dementia (PDD).

METHODS

We conducted a post hoc analysis on 1,047 patients with PDD from 2 randomized controlled trials comparing rivastigmine versus placebo at week 24 (n = 501) and rivastigmine patch versus capsule at week 76 (n = 546). A drop ≥ 20 mm Hg in systolic blood pressure (SBP) or ≥ 10 in diastolic blood pressure (DBP) upon standing classified subjects as OH positive (OH+); otherwise, OH negative (OH-). The primary end point was the Alzheimer's Disease Assessment Scale - Cognitive subscale (ADAS-Cog) at week 24 and the Mattis Dementia Rating Scale (MDRS) at week 76, using intention-to-treat with retrieved dropout at week 24 and observed cases at week 76, consistent with the original analyses.

RESULTS

Overall safety was comparable between OH+ (n = 288, 27.5%) and OH- (n = 730, 69.7%), except for higher frequency of syncope (9.2%) in the OH+ placebo arm. The placebo-adjusted effect of rivastigmine on ADAS-Cog at week 24 was 5.6 ± 1.2 for OH+ and 1.9 ± 0.9 in OH- (p = 0.0165). Among subjects with OH, the MDRS change from baseline at week 76 was higher for rivastigmine capsules versus patch (10.6 ± 2.9 vs -1.5 ± 3.0, p = 0.031). The overall prevalence of OH was lower for rivastigmine than placebo at week 24 (28.3% vs 44.6%, p = 0.0476).

INTERPRETATION

The cognitive benefit from rivastigmine is larger in patients with PDD with OH, possibly mediated by a direct antihypotensive effect. ANN NEUROL 2021;89:91-98.

Interaction between high-density lipoproteins and inflammation: Function matters more than concentration!

High-density lipoprotein (HDL) plays an important role in lipid metabolism and especially contributes to the reverse cholesterol transport pathway. Over recent years it has become clear that the effect of HDL on immune-modulation is not only dependent on HDL concentration but also and perhaps even more so on HDL function. This review will provide a concise general introduction to HDL followed by an overview of post-translational modifications of HDL and a detailed overview of the role of HDL in inflammatory diseases. The clinical potential of HDL and its main apolipoprotein constituent, apoA-I, is also addressed in this context. Finally, some conclusions and remarks that are important for future HDL-based research and further development of HDL-focused therapies are discussed.

Positron Emission Tomography in the Inflamed Cerebellum: Addressing Novel Targets among G Protein-Coupled Receptors and Immune Receptors

Inflammatory processes preceding clinical manifestation of brain diseases are moving increasingly into the focus of positron emission tomographic (PET) investigations. A key role in inflammation and as a target of PET imaging efforts is attributed to microglia. Cerebellar microglia, with a predominant ameboid and activated subtype, is of special interest also regarding improved and changing knowledge on functional involvement of the cerebellum in mental activities in addition to its regulatory role in motor function. The present contribution considers small molecule ligands as potential PET tools for the visualization of several receptors recognized to be overexpressed in microglia and which can potentially serve as indicators of inflammatory processes in the cerebellum. The sphingosine 1 phosphate receptor 1 (S1P1), neuropeptide Y receptor 2 (NPY2) and purinoceptor Y12 (P2Y12) cannabinoid receptors and the chemokine receptor CX3CR1 as G-protein-coupled receptors and the ionotropic purinoceptor P2X7 provide structures with rather classical binding behavior, while the immune receptor for advanced glycation end products (RAGE) and the triggering receptor expressed on myeloid cells 2 (TREM2) might depend for instance on further accessory proteins. Improvement in differentiation between microglial functional subtypes in comparison to the presently used 18 kDa translocator protein ligands as well as of the knowledge on the role of polymorphisms are special challenges in such developments.

Enriching the design of Alzheimer's disease clinical trials: Application of the polygenic hazard score and composite outcome measures

INTRODUCTION

Selecting individuals at high risk of Alzheimer's disease (AD) dementia and using the most sensitive outcome measures are important aspects of trial design.

METHODS

We divided participants from Alzheimer's Disease Neuroimaging Initiative at the 50th percentile of the predicted absolute risk of the polygenic hazard score (PHS). Outcome measures were the Alzheimer's Disease Assessment Schedule-Cognitive Subscale (ADAS-Cog), ADNI-Mem, Clinical Dementia Rating-Sum of Boxes (CDR SB), and Cognitive Function Composite 2 (CFC2). In addition to modeling, we use a power analysis compare numbers needed with each technique.

RESULTS

Data from 188 cognitively normal and 319 mild cognitively impaired (MCI) participants were analyzed. Using the ADAS-Cog to estimate sample sizes, without stratification over 24 months, would require 930 participants with MCI, while using the CFC2 and restricting participants to those in the upper 50th percentile would require only 284 participants.

DISCUSSION

Combining stratification by PHS and selection of a sensitive combined outcome measure in a cohort of patients with MCI can allow trial design that is more efficient, potentially less burdensome on participants, and more cost effective.

Cognition and motor function: The gait and cognition pooled index

BACKGROUND

There is a need for outcome measures with improved responsiveness to changes in pre-dementia populations. Both cognitive and motor function play important roles in neurodegeneration; motor function decline is detectable at early stages of cognitive decline. This proof of principle study used a Pooled Index approach to evaluate improved responsiveness of the predominant outcome measure (ADAS-Cog: Alzheimer's Disease Assessment Scale-Cognitive Subscale) when assessment of motor function is added.

METHODS

Candidate Pooled Index variables were selected based on theoretical importance and pairwise correlation coefficients. Kruskal-Wallis and Mann-Whitney U tests assessed baseline discrimination. Standardized response means assessed responsiveness to longitudinal change.

RESULTS

Final selected variables for the Pooled Index include gait velocity, dual-task cost of gait velocity, and an ADAS-Cog-Proxy (statistical approximation of the ADAS-Cog using similar cognitive tests). The Pooled Index and ADAS-Cog-Proxy scores had similar ability to discriminate between pre-dementia syndromes. The Pooled Index demonstrated trends of similar or greater responsiveness to longitudinal decline than ADAS-Cog-Proxy scores.

CONCLUSION

Adding motor function assessments to the ADAS-Cog may improve responsiveness in pre-dementia populations.

Development of a novel cognitive composite outcome to assess therapeutic effects of exercise in the EXERT trial for adults with MCI: The ADAS-Cog-Exec

INTRODUCTION

Use of cognitive composites as primary outcome measures is increasingly common in clinical trials of preclinical and prodromal Alzheimer's disease (AD). Composite outcomes can decrease intra-individual variability, resulting in improved sensitivity to detect longitudinal change and increased statistical power. We developed a novel composite outcome, the ADAS-Cog-Exec, for use in the EXERT trial-a Phase 3 randomized, controlled, 12-month exercise intervention in mild cognitive impairment (MCI).

METHODS

Three combinations of cognitive measures selected from the Alzheimer's Disease Assessment Scale-Cognitive Subscale version 13 (ADAS-Cog13), tests of executive function, and the Clinical Dementia Rating (CDR) were created based on previously documented sensitivity to longitudinal change in MCI and to the effects of exercise. Optimally weighted composites of each combination were modeled using data from the ADNI-1 MCI cohort. Ten-fold cross-validation was performed to obtain a bias-corrected mean to standard deviation ratio (MSDR). The cognitive composites were assessed for their sensitivity to detect 12-month change in MCI.

RESULTS

The MSDR of 12-month change for each of the composite outcomes tested exceeded that of the ADAS-Cog13 total score. The composite with the highest MSDR (MSDR = 0.48) and associated statistical power included scores on ADAS-Cog13 Word Recall, Delayed Word Recall, Orientation, and Number Cancellation subtests; Trail-Making Tests A & B, Digit Symbol Substitution and Category Fluency; and cognitive components of the CDR (Memory, Orientation, Judgement & Problem Solving).

DISCUSSION

An optimally weighted cognitive composite measure was identified and validated for use in EXERT. This composite contained selected subtests from the ADAS-Cog13, additional measures of executive function, and box scores for cognitive components of the CDR. Because this composite score demonstrated high sensitivity to longitudinal change in MCI it will be used as the primary outcome measure for the EXERT trial.

Predicting Alzheimer's disease based on survival data and longitudinally measured performance on cognitive and functional scales

This study assessed how well longitudinally taken cognitive and functional scales from people with mild cognitive impairment (MCI) predict conversion to Alzheimer's disease (AD). Participants were individuals with baseline MCI from the Alzheimer's Disease Neuroimaging Initiative. Scales included the Alzheimer Disease Assessment Scale-Cognitive (ADAS-Cog) 11 and 13, the Mini Mental State Examination (MMSE), and the Functional Assessment Questionnaire (FAQ). A joint modelling approach compared performance on the four scales for dynamic prediction of risk for AD. The goodness of fit measures included log likelihood, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The area under the curve (AUC) of the receiver operating characteristic assessed predictive accuracy. The parameter α in the ADAS-Cog11, ADAS-Cog13, MMSE, and FAQ joint models was statistically significant. Joint MMSE and FAQ models had better goodness of fit. FAQ had the best predictive accuracy. Cognitive and functional impairment assessment scales are strong screening predictors when repeated measures are available. They could be useful for predicting risk for AD in primary healthcare.

The Association between Longest-Held Lifetime Occupation and Late-Life Cognitive Impairment: Korean Longitudinal Study of Aging (2006-2016)

The association between longest-held lifetime occupation and late-life cognitive impairment: Korean Longitudinal Study of Aging (2006–2016). Backgrounds: Our study hypothesized that occupation in adulthood may be one of the modifiable factors in cognitive performance. This follow-up study aimed to examine whether there was an association between the longest-held occupation in a lifetime and cognitive impairment. Methods: This study used data from the 2006, 2012, and 2016 waves of the Korean Longitudinal Study of Aging, and a total of 1733 subjects aged over 65 were included. Longest-held occupation in a lifetime was classified into blue-collar, pink-collar, and white-collar. Cognitive function was evaluated using the Korean version of the Mini-Mental State Examination. Results: In males, no significant associations were observed. In females, on the contrary, risk of cognitive impairment in the blue-collar occupation was consistently higher than in the white-collar occupation over the 10-year follow-up (2006, OR = 2.49, 95% CI 1.05–5.88; 2016, OR = 2.17, 95% CI 1.02−4.65). Conclusions: Lifetime occupation should be taken into consideration in the process of screening for cognitive decline in the elderly, especially females. This study needs to be interpreted cautiously in view of inherent data and methodological limitations.

Cost-effectiveness of a non-pharmacological treatment vs. "care as usual" in day care centers for community-dwelling older people with cognitive impairment: results from the German randomized controlled DeTaMAKS-trial

BACKGROUND

Cognitive impairment in older adults causes a high economic and societal burden. This study assesses the cost-effectiveness of the multicomponent, non-pharmacological MAKS treatment vs. "care as usual" in German day care centers (DCCs) for community-dwelling people with mild cognitive impairment (MCI) or mild to moderate dementia over 6 months.

METHODS

The analysis was conducted from the societal perspective alongside the cluster-randomized controlled, multicenter, prospective DeTaMAKS-trial with waitlist group design. Outcomes were Mini-Mental Status Examination (MMSE) and Erlangen Test of Activities of Daily Living in Persons with Mild Dementia or Mild Cognitive Impairment (ETAM) of 433 individuals in 32 DCCs. Incremental differences in MMSE and ETAM were calculated via a Gaussian-distributed and incremental cost difference via a Gamma-distributed Generalized Linear Model. Cost-effectiveness was assessed via cost-effectiveness planes and cost-effectiveness acceptability curves (CEAC).

RESULTS

At 6 months, MMSE (adjusted mean difference = 0.92; 95% confidence interval (CI): 0.17 to 1.67; p = 0.02) and ETAM (adjusted mean difference = 1.00; CI: 0.14 to 1.85; p = 0.02) were significantly better in the intervention group. The adjusted cost difference was - €938.50 (CI: - 2733.65 to 763.13; p = 0.31). Given the CEAC, MAKS was cost-effective for 78.0% of MMSE and 77.4% for ETAM without a need for additional costs to payers.

CONCLUSIONS

MAKS is a cost-effective treatment to stabilize the ability to perform activities of daily living and cognitive abilities of people with MCI or mild to moderate dementia in German DCCs. Thus, MAKS should be implemented in DCCs.

Effects of sex, age, and apolipoprotein E genotype on hippocampal parenchymal fraction in cognitively normal older adults

Early detection of Alzheimer's disease (AD) is important for timely interventions and developing new treatments. Hippocampus atrophy is an early biomarker of AD. The hippocampal parenchymal fraction (HPF) is a promising measure of hippocampal structural integrity computed from structural MRI. It is important to characterize the dependence of HPF on covariates such as age and sex in the normal population to enhance its utility as a disease biomarker. We measured the HPF in 4239 structural MRI scans from 340 cognitively normal (CN) subjects aged 59-89 years from the AD Neuroimaging Initiative database, and studied its dependence on age, sex, apolipoprotein E (APOE) genotype, brain hemisphere, intracranial volume (ICV), and education using a linear mixed-effects model. In this CN cohort, HPF was inversely associated with ICV; was greater on the right hemisphere compared to left in both sexes with the degree of right > left asymmetry being slightly more pronounced in men; declined quadratically with age and faster in APOE ϵ4 carriers compared to non-carriers; and was significantly associated with cognitive ability. Consideration of HPF as an AD biomarker should be in conjunction with other subject attributes that are shown in this research to influence HPF levels in CN older individuals.

Assessing what matters most to patients with or at risk for Alzheimer's and care partners: a qualitative study evaluating symptoms, impacts, and outcomes

Background

The What Matters Most (WMM) study was initiated to evaluate symptoms, AD-related impacts, treatment-related needs, preferences, and priorities among individuals with or at risk for Alzheimer’s disease (AD) and their care partners. The objective of this qualitative study phase was to identify a comprehensive set of concepts of interest that are meaningful to individuals across the AD continuum.

Methods

Interviews were conducted with 60 clinically referred individuals and care partners across 5 AD stages (n = 12 each): group 1 (non-clinically impaired individuals with AD pathology), group 2 (individuals with mild cognitive impairment and AD pathology), group 3 (individuals with mild AD), group 4 (individuals with moderate AD and their care partners), and group 5 (care partners of individuals with severe AD). Interviews were conducted by experienced interviewers, audio-recorded, and transcribed. Dominant trends were identified in each interview and compared across subsequent interviews to generate themes or patterns in descriptions of AD symptoms, impacts, and desired treatment outcomes.

Results

All participants endorsed current issues related to memory; nearly all participants (n = 55; 92%) across the five groups endorsed symptoms related to communication and language. Groups 1–3 reported an impact on mood/emotions (n = 23; 64%) and a decrease in social activities or outgoingness (n = 17; 47%). Current and future concerns reported by the overall sample included memory (n = 48; 80%), dependence (n = 40; 67%), and “other” concerns (n = 33; 55.0%) (e.g., uncertainty about the future, burdening others). The most desired AD treatment outcomes were improvement or restoration of memory (n = 40; 67%) and stopping AD progression (n = 35; 58.3%). Group-level differences were observed in the symptoms, impacts, and desired treatment outcomes among patients and care partners across the AD continuum.

Conclusions

Cognitive functioning issues—particularly in memory and communication—are present even in preclinical and early-stage AD, including among those without a formal AD diagnosis. While the impacts of AD vary across the disease-severity spectrum, improved memory and disease modification were treatment outcomes considered most important to participants across all 5 AD stages. Neuropsychological assessments traditionally used in AD clinical trials may not evaluate the often-subtle concepts that are important to patients and care partners. Results from this study will inform the second phase of the WMM project—a quantitative study to elicit the relative importance of these concepts of interest to people at risk for and living with AD and their care partners.

Parametric mode regression for bounded responses

We propose new parametric frameworks of regression analysis with the conditional mode of a bounded response as the focal point of interest. Covariate effects estimation and prediction based on the maximum likelihood method under two new classes of regression models are demonstrated. We also develop graphical and numerical diagnostic tools to detect various sources of model misspecification. Predictions based on different central tendency measures inferred using various regression models are compared using synthetic data in simulations. Finally, we conduct regression analysis for data from the Alzheimer's Disease Neuroimaging Initiative to demonstrate practical implementation of the proposed methods. Supporting Information that contain technical details and additional simulation and data analysis results are available online.

Dual-acting agents for improving cognition and real-world function in Alzheimer's disease: Focus on 5-HT6 and D3 receptors as hubs

To date, there are no interventions that impede the inexorable progression of Alzheimer's disease (AD), and currently-available drugs cholinesterase (AChE) inhibitors and the N-Methyl-d-Aspartate receptor antagonist, memantine, offer only modest symptomatic benefit. Moreover, a range of mechanistically-diverse agents (glutamatergic, histaminergic, monoaminergic, cholinergic) have disappointed in clinical trials, alone and/or in association with AChE inhibitors. This includes serotonin (5-HT) receptor-6 antagonists, despite compelling preclinical observations in rodents and primates suggesting a positive influence on cognition. The emphasis has so far been on high selectivity. However, for a multi-factorial disorder like idiopathic AD, 5-HT6 antagonists possessing additional pharmacological actions might be more effective, by analogy to "multi-target" antipsychotics. Based on this notion, drug discovery programmes have coupled 5-HT6 blockade to 5-HT4 agonism and inhibition of AchE. Further, combined 5-HT6/dopamine D3 receptor (D3) antagonists are of especial interest since D3 blockade mirrors 5-HT6 antagonism in exerting broad-based pro-cognitive properties in animals. Moreover, 5-HT6 and dopamine D3 antagonists promote neurocognition and social cognition via both distinctive and convergent actions expressed mainly in frontal cortex, including suppression of mTOR over-activation and reinforcement of cholinergic and glutamatergic transmission. In addition, 5-HT6 blockade affords potential anti-anxiety, anti-depressive and anti-epileptic properties, and antagonising 5-HT6 receptors may be associated with neuroprotective ("disease-modifying") properties. Finally D3 antagonism may counter psychotic episodes and D3 receptors themselves offer a promising hub for multi-target agents. The present article reviews the status of "R and D" into multi-target 5-HT6 and D3 ligands for improved treatment of AD and other neurodegenerative disorders of aging. This article is part of the special issue entitled 'Serotonin Research: Crossing Scales and Boundaries'.

Effect of the Casein-Derived Peptide Met-Lys-Pro on Cognitive Function in Community-Dwelling Adults Without Dementia: A Randomized, Double-Blind, Placebo-Controlled Trial

Background

Preventative measures have recently been taken to reduce the incidence of Alzheimer’s disease worldwide. We previously showed that Met-Lys-Pro (MKP), a casein-derived angiotensin-converting enzyme inhibitory peptide with the potential to cross the blood–brain barrier, attenuated cognitive decline in a mouse model of Alzheimer’s disease. However, the effect of MKP on cognitive function improvement in humans remains unknown. This exploratory study sought to investigate whether MKP intake could improve cognitive function in adults without dementia.

Methods

A total of 268 community-dwelling adults without dementia participated in this 24-week randomized controlled trial. Participants were randomly allocated to the MKP (n = 134) or placebo (n = 134) group. The MKP group received four tablets daily, each containing 50 μg MKP, while the placebo group received four dextrin tablets containing no detectable MKP for 24 weeks. Scores on the Japanese version of the cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog) were used as the primary outcome to compare cognitive function between the MKP and placebo groups. The study products were also evaluated for safety.

Results

The intention-to-treat analysis showed that there was no significant difference between the groups in terms of the ADAS-cog total score. Orientation, as measured by the respective ADAS-cog subscale, was significantly improved compared to placebo at 24 weeks post-MKP administration (P = 0.022). No serious adverse events due to MKP intake were observed.

Conclusion

To the best of our knowledge, this is the first study to report the effects of MKP on human cognition. These preliminary results suggested the safety of daily MKP intake and its potential to improve orientation in adults without dementia. Further clinical studies are needed to confirm the present findings and the benefits of MKP on cognitive function.

Non-invasive Brain Stimulation in Alzheimer's Disease and Mild Cognitive Impairment-A State-of-the-Art Review on Methodological Characteristics and Stimulation Parameters

Background: Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have been proposed as a new therapeutic way to enhance the cognition of patients with dementia. However, serious methodological limitations appear to affect the estimates of their efficacy. We reviewed the stimulation parameters and methods of studies that used TMS or tDCS to alleviate the cognitive symptoms of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Moreover, we evaluated the risk of bias in these studies. Our aim was to highlight the current vulnerabilities of the field and to formulate recommendations on how to manage these issues when designing studies. Methods: Electronic databases and citation searching were used to identify studies administering TMS or tDCS on patients with AD or MCI to enhance cognitive function. Data were extracted by one review author into summary tables with the supervision of the authors. The risk of bias analysis of randomized-controlled trials was conducted by two independent assessors with version 2 of the Cochrane risk-of-bias tool for randomized trials. Results: Overall, 36 trials were identified of which 23 randomized-controlled trials underwent a risk of bias assessment. More than 75% of randomized-controlled trials involved some levels of bias in at least one domain. Stimulation parameters were highly variable with some ranges of effectiveness emerging. Studies with low risk of bias indicated TMS to be potentially effective for patients with AD or MCI while questioned the efficacy of tDCS. Conclusions: The presence and extent of methodical issues affecting TMS and tDCS research involving patients with AD and MCI were examined for the first time. The risk of bias frequently affected the domains of the randomization process and selection of the reported data while missing outcome was rare. Unclear reporting was present involving randomization, allocation concealment, and blinding. Methodological awareness can potentially reduce the high variability of the estimates regarding the effectiveness of TMS and tDCS. Studies with low risk of bias delineate a range within TMS parameters seem to be effective but question the efficacy of tDCS.

Music Therapy in the Treatment of Dementia: A Systematic Review and Meta-Analysis

Background: Dementia is a neurological condition characterized by deterioration in cognitive, behavioral, social, and emotional functions. Pharmacological interventions are available but have limited effect in treating many of the disease's features. Several studies have proposed therapy with music as a possible strategy to slow down cognitive decline and behavioral changes associated with aging in combination with the pharmacological therapy. Objective: We performed a systematic review and subsequent meta-analysis to check whether the application of music therapy in people living with dementia has an effect on cognitive function, quality of life, and/or depressive state. Methods: The databases used were Medline, PubMed Central, Embase, PsycINFO, and the Cochrane Library. The search was made up of all the literature until present. For the search, key terms, such as "music," "brain," "dementia," or "clinical trial," were used. Results: Finally, a total of eight studies were included. All the studies have an acceptable quality based on the score on the Physiotherapy Evidence Database (PEDro) and Critical Appraisal Skills Program (CASP) scales. After meta-analysis, it was shown that the intervention with music improves cognitive function in people living with dementia, as well as quality of life after the intervention and long-term depression. Nevertheless, no evidence was shown of improvement of quality of life in long-term and short-term depression. Conclusion: Based on our results, music could be a powerful treatment strategy. However, it is necessary to develop clinical trials aimed to design standardized protocols depending on the nature or stage of dementia so that they can be applied together with current cognitive-behavioral and pharmacological therapies.

The Cognitive-Functional Composite is sensitive to clinical progression in early dementia: Longitudinal findings from the Catch-Cog study cohort

INTRODUCTION

In an attempt to capture clinically meaningful cognitive decline in early dementia, we developed the Cognitive-Functional Composite (CFC). We investigated the CFC's sensitivity to decline in comparison to traditional clinical endpoints.

METHODS

This longitudinal construct validation study included 148 participants with subjective cognitive decline, mild cognitive impairment, or mild dementia. The CFC and traditional tests were administered at baseline, 3, 6, and 12 months. Sensitivity to change was investigated using linear mixed models and r 2 effect sizes.

RESULTS

CFC scores declined over time (β = -.16, P < .001), with steepest decline observed in mild Alzheimer's dementia (β = -.25, P < .001). The CFC showed medium-to-large effect sizes at succeeding follow-up points (r 2 = .08-.42), exhibiting greater change than the Clinical Dementia Rating scale (r 2 = .02-.12). Moreover, change on the CFC was significantly associated with informant reports of cognitive decline (β = .38, P < .001).

DISCUSSION

By showing sensitivity to decline, the CFC could enhance the monitoring of disease progression in dementia research and clinical practice.

Network topology and machine learning analyses reveal microstructural white matter changes underlying Chinese medicine Dengzhan Shengmai treatment on patients with vascular cognitive impairment

With the increasing incidence of cerebrovascular diseases and dementia, considerable efforts have been made to develop effective treatments on vascular cognitive impairment (VCI), among which accumulating practice-based evidence has shown great potential of the traditional Chinese medicine (TCM). Current randomized double-blind controlled trial has been designed to evaluate the 6-month treatment effects of Dengzhan Shengmai (DZSM) capsules, one TCM herbal preparations on VCI, and to explore the underlying neural mechanisms with graph theory-based analysis and machine learning method based on diffusion tensor imaging (DTI) data. A total of 82 VCI patients were recruited and randomly assigned to drug (45 with DZSM) and placebo (37 with placebo) groups, and neuropsychological and neuroimaging data were acquired at baseline and after 6-month treatment. After treatment, compared to the placebo group, the drug groups showed significantly improved performance in Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-cog) score (p < 0.001) and the other cognitive domains. And with the reconstruction of white matter structural network, there were more streamlines connecting the left thalamus and right hippocampus in the drug groups (p < 0.001 uncorrected), with decreasing nodal efficiency of the right olfactory associated with slower decline in the general cognition (r = -0.364, p = 0.048). Moreover, support vector machine classification analyses revealed significant white matter network alterations after treatment in the drug groups (accuracy of baseline vs. 6-month later, 68.18 %). Taking together, the present study showed significant efficacy of DZSM treatment on VCI, which might result from white matter microstructure alterations and the topological changes in brain structural network.

Advancing the Use of Mobile Technologies in Clinical Trials: Recommendations from the Clinical Trials Transformation Initiative

Mobile technologies offer the potential to reduce the costs of conducting clinical trials by collecting high-quality information on health outcomes in real-world settings that are relevant to patients and clinicians. However, widespread use of mobile technologies in clinical trials has been impeded by their perceived challenges. To advance solutions to these challenges, the Clinical Trials Transformation Initiative (CTTI) has issued best practices and realistic approaches that clinical trial sponsors can now use. These include CTTI recommendations on technology selection; data collection, analysis, and interpretation; data management; protocol design and execution; and US Food and Drug Administration submission and inspection. The scientific principles underpinning the clinical trials enterprise continue to apply to studies using mobile technologies. These recommendations provide a framework for including mobile technologies in clinical trials that can lead to more efficient assessment of new therapies for patients.

Validation study of the Alzheimer's Disease Assessment Scale-Cognitive Subscale for people with mild cognitive impairment and Alzheimer's disease in Chinese communities

OBJECTIVE

Our study aimed to verify the validity of the Chinese version of Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) for the community-dwelling older people in China.

METHODS

A total of 1276 individuals composed by 628 normal controls (NCs), 572 people living with mild cognitive impairment (MCI), and 76 people living with Alzheimer's disease (AD) were recruited for the current study. All of the participants underwent ADAS-Cog, clinical interview and examination, Quick Cognitive Screening Scale for the Elderly, and Activities of Daily Living Scale. The sensitivity and specificity of ADAS-Cog were calculated, and a receiver operating characteristic curve (ROC curve) was drawn to decide the optimal cutoff points of ADAS-Cog for screening MCI and AD.

RESULTS

Statistically significant differences were observed among the three groups (P <. 001, NC < MCI <AD), in terms of the total and subtask scores of ADAS-Cog. The optimal cutoff value for MCI was 10 points with an area under the curve (AUC) of 0.824, sensitivity of 61.4%, and specificity of 93.2%. Comparatively, the best cutoff value for AD was 15 points with an AUC of 0.905, sensitivity of 73.7%, and specificity of 92.4%. The overall accuracy was 70.5%, and the accuracy of diagnosing cognitively healthy older people, MCI patients, and AD patients was 81.7%, 58.0%, and 71.1%, respectively.

CONCLUSION

The present study illustrates that the Chinese version of the ADAS-Cog total score is able to detect cognitive impairment of AD patients in Chinese communities but has a lower efficacy for MCI.

Forecasting the progression of Alzheimer's disease using neural networks and a novel preprocessing algorithm

INTRODUCTION

There is a 99.6% failure rate of clinical trials for drugs to treat Alzheimer's disease, likely because Alzheimer's disease (AD) patients cannot be easily identified at early stages. This study investigated machine learning approaches to use clinical data to predict the progression of AD in future years.

METHODS

Data from 1737 patients were processed using the "All-Pairs" technique, a novel methodology created for this study involving the comparison of all possible pairs of temporal data points for each patient. Machine learning models were trained on these processed data and evaluated using a separate testing data set (110 patients).

RESULTS

A neural network model was effective (mAUC = 0.866) at predicting the progression of AD, both in patients who were initially cognitively normal and in patients suffering from mild cognitive impairment.

DISCUSSION

Such a model could be used to identify patients at early stages of AD and who are therefore good candidates for clinical trials for AD therapeutics.

A practical computerized decision support system for predicting the severity of Alzheimer's disease of an individual

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heavily on cognitive and functional assessments (CFA). In this study, we developed a computational framework using a suite of machine learning tools for identifying key markers in predicting the severity of Alzheimer's disease (AD) from a large set of biological and clinical measures. Six machine learning approaches, namely Kernel Ridge Regression (KRR), Support Vector Regression, and k-Nearest Neighbor for regression and Support Vector Machine (SVM), Random Forest, and k-Nearest Neighbor for classification, were used for the development of predictive models. We demonstrated high predictive power of CFA. Predictive performance of models incorporating CFA was shown to consistently have higher accuracy than those based solely on biomarker modalities. We found that KRR and SVM were the best performing regression and classification methods respectively. The optimal SVM performance was observed for a set of four CFA test scores (FAQ, ADAS13, MoCA, MMSE) with multi-class classification accuracy of 83.0%, 95%CI = (72.1%, 93.8%) while the best performance of the KRR model was reported with combined CFA and MRI neuroimaging data, i.e., R ² = 0.874, 95%CI = (0.827, 0.922). Given the high predictive power of CFA and their widespread use in clinical practice, we then designed a data-driven and self-adaptive computerized clinical decision support system (CDSS) prototype for evaluating the severity of AD of an individual on a continuous spectrum. The system implemented an automated computational approach for data pre-processing, modelling, and validation and used exclusively the scores of selected cognitive measures as data entries. Taken together, we have developed an objective and practical CDSS to aid AD diagnosis.

Novel Method for Rapid Assessment of Cognitive Impairment Using High-Performance Eye-Tracking Technology

A rapid increase in the number of patients with dementia has emerged as a global health challenge. Accumulating evidence suggests that early diagnosis and timely intervention can delay cognitive decline. The diagnosis of dementia is commonly performed using neuropsychological tests, such as the Mini-Mental State Examination (MMSE), administered by trained examiners. While these traditional neuropsychological tests are valid and reliable, they are neither simple nor sufficiently short as routine screening tools for dementia. Here, we developed a brief cognitive assessment utilizing an eye-tracking technology. The subject views a series of short (178 s) task movies and pictures displayed on a monitor while their gaze points are recorded by the eye-tracking device, and the cognitive scores are determined from the gaze plots data. The cognitive scores were measured by both an eye tracking-based assessment and neuropsychological tests in 80 participants, including 27 cognitively healthy controls (HC), 26 patients with mild cognitive impairment (MCI), and 27 patients with dementia. The eye tracking-based cognitive scores correlated well with the scores from the neuropsychological tests, and they showed a good diagnostic performance in detecting patients with MCI and dementia. Rapid cognitive assessment using eye-tracking technology can enable quantitative scoring and the sensitive detection of cognitive impairment.

Can krill oil be of use for counteracting neuroinflammatory processes induced by high fat diet and aging?

Most neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, demonstrate preceding or on-going inflammatory processes. Therefore, discovering effective means of counteracting detrimental inflammatory mediators in the brain could help alter aging-related disease onset and progression. Fish oil and marine-derived omega-3, long-chain polyunsaturated fatty acids (LC n-3) have shown promising anti-inflammatory effects both systemically and centrally. More specifically, krill oil (KO), extracted from small Antarctic crustaceans, is an alternative type of LC n-3 with reported health benefits including improvement of spatial memory and learning, memory loss, systemic inflammation and depression symptoms. Similar to the more widely studied fish oil, KO contains the long chain fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) which are essential for basic brain functions. Moreover, the phospholipid bound nature of fatty acids found in KO improves bioavailability and efficiency of absorption, thus supporting the belief that KO may offer a superior method of dietary n-3 delivery. Finally, KO contains astaxanthin, an antioxidant capable of reducing potentially excessive oxidative stress and inflammation within the brain. This review will discuss the potential benefits of KO over other marine-based LC n-3 on brain inflammation and cognitive function in the context of high fat diets and aging.

Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study

Introduction

The objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population.

Methods

The group classification on early AD population in both Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) and North American ADNI (NA-ADNI) was performed using the inclusion criteria including brain amyloid positivity on positron emission tomography or CSF. Participants with early AD from each cohort were stratified into two groups based on a cutoff 1.0 of Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) change at month 24 (m24): participants in "progress group" have CDR-SB change ≥ 1.0 and participants in "stable group" have CDR-SB change < 1.0. Then, we performed identification of prognostic factors from baseline items including neuropsychological scores (Assessment Scale-Cognitive Subscale[ADAS-cog 13], Mini-Mental State Examination (MMSE), CDR, FAQ, and Geriatric Depression Scale ), CSF markers (t-tau, p-tau, and beta-amyloid 1-42), vital signs (body weight, pulse rate, etc.,), by using two statistical approaches, Welch's t-test and simple linear regression by ordinary least squares. Comparisons between participants with J-ADNI and participants with NA-ADNI were also performed.

Results

Trends of CDR-SB changes were very similar between J-ADNI and NA-ADNI early AD population enrolled in this study. Baseline levels of CSF t-tau, p-tau, Mini-Mental State Examination, FAQ, and ADAS-cog13 were identified as prognostic factors in both J-ADNI and NA-ADNI. Based on a detailed subscale analysis on ADAS-cog13, four subscales (Q1: word recall, Q3: construction, Q4: delayed word recall, and Q8: word recognition) were identified as prognostic factors in both J-ADNI and NA-ADNI.

Discussion

Characterizing population with early AD can provide benefits for promoting efficiency in conducting AD clinical trials for disease-modifying treatments. Thus, implementing these prognostic factors into clinical trials may be potentially a good method to enrich participants with early AD who are suitable for evaluating treatment effects.

Assessing cognition and daily function in early dementia using the cognitive-functional composite: findings from the Catch-Cog study cohort

Background

The cognitive-functional composite (CFC) was designed to improve the measurement of clinically relevant changes in predementia and early dementia stages. We have previously demonstrated its good test-retest reliability and feasibility of use. The current study aimed to evaluate several quality aspects of the CFC, including construct validity, clinical relevance, and suitability for the target population.

Methods

Baseline data of the Capturing Changes in Cognition study was used: an international, prospective cohort study including participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD) dementia, and dementia with Lewy bodies (DLB). The CFC comprises seven existing cognitive tests focusing on memory and executive functions (EF) and the informant-based Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). Construct validity and clinical relevance were assessed by (1) confirmatory factor analyses (CFA) using all CFC subtests and (2) linear regression analyses relating the CFC score (independent) to reference measures of disease severity (dependent), correcting for age, sex, and education. To assess the suitability for the target population, we compared score distributions of the CFC to those of traditional tests (Alzheimer’s Disease Assessment Scale–Cognitive subscale, Alzheimer’s Disease Cooperative Study–Activities of Daily Living scale, and Clinical Dementia Rating scale).

Results

A total of 184 participants were included (age 71.8 ± 8.4; 42% female; n = 14 SCD, n = 80 MCI, n = 78 AD, and n = 12 DLB). CFA showed that the hypothesized three-factor model (memory, EF, and IADL) had adequate fit (CFI = .931, RMSEA = .091, SRMR = .06). Moreover, worse CFC performance was associated with more cognitive decline as reported by the informant (β = .61, p < .001), poorer quality of life (β = .51, p < .001), higher caregiver burden (β = − .51, p < .001), more apathy (β = − .36, p < .001), and less cortical volume (β = .34, p = .02). Whilst correlations between the CFC and traditional measures were moderate to strong (ranging from − .65 to .83, all p < .001), histograms showed floor and ceiling effects for the traditional tests as compared to the CFC.

Conclusions

Our findings illustrate that the CFC has good construct validity, captures clinically relevant aspects of disease severity, and shows no range restrictions in scoring. It therefore provides a more useful outcome measure than traditional tests to evaluate cognition and function in MCI and mild AD.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0500-5) contains supplementary material, which is available to authorized users.

Cognitive Profiling Related to Cerebral Amyloid Beta Burden Using Machine Learning Approaches

Background: Cerebral amyloid beta (Aβ) is a hallmark of Alzheimer’s disease (AD). Aβ can be detected in vivo with amyloid imaging or cerebrospinal fluid assessments. However, these technologies can be both expensive and invasive, and their accessibility is limited in many clinical settings. Hence the current study aims to identify multivariate cost-efficient markers for Aβ positivity among non-demented individuals using machine learning (ML) approaches.

Methods: The relationship between cost-efficient candidate markers and Aβ status was examined by analyzing 762 participants from the Alzheimer’s Disease Neuroimaging Initiative-2 cohort at baseline visit (286 cognitively normal, 332 with mild cognitive impairment, and 144 with AD; mean age 73.2 years, range 55–90). Demographic variables (age, gender, education, and APOE status) and neuropsychological test scores were used as predictors in an ML algorithm. Cerebral Aβ burden and Aβ positivity were measured using ¹⁸F-florbetapir positron emission tomography images. The adaptive least absolute shrinkage and selection operator (LASSO) ML algorithm was implemented to identify cognitive performance and demographic variables and distinguish individuals from the population at high risk for cerebral Aβ burden. For generalizability, results were further checked by randomly dividing the data into training sets and test sets and checking predictive performances by 10-fold cross-validation.

Results: Out of neuropsychological predictors, visuospatial ability and episodic memory test results were consistently significant predictors for Aβ positivity across subgroups with demographic variables and other cognitive measures considered. The adaptive LASSO model using out-of-sample classification could distinguish abnormal levels of Aβ. The area under the curve of the receiver operating characteristic curve was 0.754 in the mild change group, 0.803 in the moderate change group, and 0.864 in the severe change group, respectively.

Conclusion: Our results showed that the cost-efficient neuropsychological model with demographics could predict Aβ positivity, suggesting a potential surrogate method for detecting Aβ deposition non-invasively with clinical utility. More specifically, it could be a very brief screening tool in various settings to recruit participants with potential biomarker evidence of AD brain pathology. These identified individuals would be valuable participants in secondary prevention trials aimed at detecting an anti-amyloid drug effect in the non-demented population.

Body, Brain, Life for Cognitive Decline (BBL-CD): protocol for a multidomain dementia risk reduction randomized controlled trial for subjective cognitive decline and mild cognitive impairment

Background

With no cure for dementia and the number of people living with the condition predicted to rapidly rise, there is an urgent need for dementia risk reduction and prevention interventions. Modifiable lifestyle risk factors have been identified as playing a major role in the development of dementia; hence, interventions addressing these risk factors represent a significant opportunity to reduce the number of people developing dementia. Relatively few interventions have been trialed in older participants with cognitive decline (secondary prevention).

Objectives

This study evaluates the efficacy and feasibility of a multidomain lifestyle risk reduction intervention for people with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

Methods

This study is an 8-week, two-arm, single-blind, randomized controlled trial (RCT) of a lifestyle modification program to reduce dementia risk. The active control group receives the following four online educational modules: dementia literacy and lifestyle risk, Mediterranean diet (MeDi), cognitive engagement and physical activity. The intervention group also completes the same educational modules but receives additional practical components including sessions with a dietitian, online brain training and sessions with an exercise physiologist to assist with lifestyle modification.

Results

Primary outcome measures are cognition (The Alzheimer’s Disease Assessment Scale-Cognitive-Plus [ADAS-Cog-Plus]) and a composite lifestyle risk factor score for Alzheimer’s disease (Australian National University – Alzheimer’s Disease Risk Index [ANU-ADRI]). Secondary outcome measures are motivation to change lifestyle (Motivation to Change Lifestyle and Health Behaviour for Dementia Risk Reduction [MCLHB-DRR]) and health-related quality of life (36-item Short Form Health Survey [SF-36]). Feasibility will be determined through adherence to diet (Mediterranean Diet Adherence Screener [MEDAS] and Australian Recommended Food Score [ARFS]), cognitive engagement (BrainHQ-derived statistics) and physical activity interventions (physical activity calendars). Outcomes are measured at baseline, immediately post-intervention and at 3- and 6-month follow-up by researchers blind to group allocation.

Discussion

If successful and feasible, secondary prevention lifestyle interventions could provide a targeted, cost-effective way to reduce the number of people with cognitive decline going on to develop Alzheimer’s disease (AD) and other dementias.

Effect and Safety of Huannao Yicong Formula () in Patients with Mild-to-Moderate Alzheimer's Disease: A Randomized, Double-Blinded, Donepezil-Controlled Trial

OBJECTIVE

To assess the effect and safety of Huannao Yicong Formula (, HYF) in the treatment of patients with mild-to-moderate Alzheimer's disease (AD).

METHODS

Sixty patients with mild-tomoderate AD were evenly randomized into HYF group and donepezil group with the random number method. Patients in the HYF group took 5 g of HYF granules twice daily and 5 mg placebo of donepezil once daily. Patients in the donepezil group took 5 mg donepezil once daily and 5 g placebo of HYF granules twice daily. The intervention lasted for 6 months. Clinical researchers, participants and statisticians were blinded to the treatment assignment throughout the study. The primary outcomes were scores of Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) and Chinese Medicine Symptom Scale (CM-SS). The secondary outcomes were scores of Montreal Cognitive Assessment (MoCA) test and Mini-Mental State Exam (MMSE). The serum levels of acetylcholinesterase (AchE) and amyloid-β protein 42 (Aβ₄₂) were detected with enzymelinked immunosorbent assay kits. The scale assessments were conducted at baseline, the 3rd and 6th months of treatment, respectively. Biochemistry tests were conducted at baseline and the 6th month of treatment.

RESULTS

A total of 52 patients completed the trial, 28 in HYF group and 24 in donepezil group. Compared with the baseline, HYF and donepezil signifificantly decreased the total scores of ADAS-Cog and CM-SS, and signifificantly increased the scores of MoCA and MMSE after 6-month treatment (all P<0.01). Both treatments remarkably reduced the serum levels of AchE and Aβ₄₂ (both P<0.05). The CM-SS total effective rate of HYF was signifificantly higher than donepezil [75.00% (21/28) vs. 54.17% (13/24), P<0.05]. No severe adverse events were observed in both groups.

CONCLUSION

HYF is effective and safe for improving the cognitive function in mildto-moderate AD patients. [Trial registration: Chinese Clinical Trial Registry (Reg No. ChiCTR-IOR-17011746)].