Cognitive Training in Patients with Alzheimer's Disease: Findings of a 12-month Randomized Controlled Trial

2018 ◽  
Vol 15 (5) ◽  
pp. 452-461 ◽  
Author(s):  
Alessandro Trebbastoni ◽  
Letizia Imbriano ◽  
Livia Podda ◽  
Lidia Rendace ◽  
Maria Luisa Sacchett ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Cognitive Training ◽  
Cognitive Functions ◽  
Verbal Learning ◽  
Treated Group ◽  
Pharmacological Intervention ◽  
Randomized Controlled ◽  
Over Time

Background: Cognitive training (CT) is a non-pharmacological intervention based on a set of tasks that reflect specific cognitive functions. CT is aimed at improving cognition in patients with cognitive impairment, though no definitive conclusions have yet been drawn on its efficacy in Alzheimer's disease (AD). Objective: To assess the effectiveness of a CT program designed to improve cognition in AD patients. Method: This is a randomized, controlled, single-blind, longitudinal trial with a no-treatment control condition in mild-to-moderate AD. Treated patients received in-group CT twice a week for six months, whereas controls did not. CT consisted of tasks ranging from paper-and-pencil to verbal-learning exercises. Participants' cognitive levels were assessed at baseline, post-intervention and 6 months later by means of a complete neuropsychological test battery. Repeated measures ANOVA was used to analyze the effect of time on the outcome measures, as well as to compare treated and untreated patients over time, with demographic data considered as covariates. Results: Of the 140 patients enrolled, 45 in the treated group and 85 controls concluded the study. The CT significantly improved treated subjects' cognitive functions immediately after the CT. Six months later, some test scores remained stable when compared with those obtained at baseline. The control group performed significantly worse than the treated group at each time-point, displaying a progressive cognitive decline over time. Conclusion: Our results suggest that CT may improve cognitive functions in patients with AD and may help to temporarily slow their cognitive decline.

scholarly journals Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment

2021 ◽  
Vol 3 ◽  
Author(s):  
Jessica Robin ◽  
Mengdan Xu ◽  
Liam D. Kaufman ◽  
William Simpson
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Screening Tools ◽  
Rapid Decline ◽  
Assessment Task ◽  
Early Signs ◽  
Over Time

Detecting early signs of cognitive decline is crucial for early detection and treatment of Alzheimer's Disease. Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing. Recent findings have highlighted changes to speech and language patterns that occur in Alzheimer's Disease, and may be detectable prior to diagnosis. Automated tools to assess speech have been developed that can be used on a smartphone or tablet, from one's home, in under 10 min. In this study, we present the results of a study of older adults who completed a digital speech assessment task over a 6-month period. Participants were grouped according to those who scored above (N = 18) or below (N = 18) the recommended threshold for detecting cognitive impairment on the Montreal Cognitive Assessment (MoCA) and those with diagnoses of mild cognitive impairment (MCI) or early Alzheimer's Disease (AD) (N = 14). Older adults who scored above the MoCA threshold had better performance on speech composites reflecting language coherence, information richness, syntactic complexity, and word finding abilities. Those with MCI and AD showed more rapid decline in the coherence of language from baseline to 6-month follow-up, suggesting that this score may be useful both for detecting cognitive decline and monitoring change over time. This study demonstrates that automated speech assessments have potential as sensitive tools to detect early signs of cognitive impairment and monitor progression over time.

scholarly journals 3265 Analysis of High-Dimensional Patient Data in Characterizing Alzheimer’s Disease Progression

2019 ◽  
Vol 3 (s1) ◽  
pp. 3-3
Author(s):  
Daniel Baer ◽  
Andrew B. Lawson ◽  
Brandon Vaughan ◽  
Jane E. Joseph
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Graph Theory ◽  
Cognitive Decline ◽  
Brain Regions ◽  
Clustering Coefficient ◽  
Eigenvector Centrality ◽  
Research Hypothesis ◽  
The Brain ◽  
Over Time

OBJECTIVES/SPECIFIC AIMS: Our research hypothesis is that resting state fMRI (rsfMRI) data can be used to identify regions of the brain which are associated with cognitive decline in patients – thereby providing a tool by which to characterize AD progression in patients. METHODS/STUDY POPULATION: We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to analyze Mini-Mental State Examination (MMSE) questionnaire scores from 14 patients diagnosed with AD at two measurement occasions. RsfMRI data was available at the first of these occasions for these patients. These rsfMRI data were summarized into 264 node-based graph theory measures of clustering coefficient and eigenvector centrality. To address our research hypothesis, we modeled changes in patient MMSE scores over time as a function of these rsfMRI data, controlling for relevant confounding factors. This model accounted for the high-dimensionality of our predictor data, the longitudinal nature of the outcome, and our desire to identify a subset of regions in the brain most associated with the MMSE outcome. RESULTS/ANTICIPATED RESULTS: The use of either the clustering coefficient or eigenvector centrality rsfMRI predictors in modeling MMSE scores for patients over time resulted in the identification of different subsets of brain regions associated with cognitive decline. This suggests that these predictors capture different information on patient propensity for cognitive decline. Further work is warranted to validate these results on a larger sample of ADNI patients. DISCUSSION/SIGNIFICANCE OF IMPACT: We conclude that different rsfMRI graph theory measures capture different aspects of cognitive function and decline in patients, which could be a future consideration in clinical practice.

scholarly journals Association between plasma exosome neurogranin and brain structure in patients with Alzheimer’s disease: a protocol study

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e036990 ◽  
Author(s):  
MengFei He ◽  
Li Sun ◽  
Wenhui Cao ◽  
Changhao Yin ◽  
Wenqiang Sun ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rating Scale ◽  
Early Stage ◽  
Verbal Learning ◽  
Blood Collection ◽  
Clinical Dementia Rating ◽  
Protocol Study ◽  
Medical University

IntroductionNeurogranin is known to be significantly elevated in patients with Alzheimer’s disease (AD) and may be an effective clinical predictor of cognitive decline and neurodegeneration. Amnestic mild cognitive impairment (aMCI) is an intermediate disease state between normal cognitive ageing and dementia, the latter of which can easily revert to AD. There remains significant uncertainty regarding the conversion of aMCI to AD, and therefore, elucidating such progression is paramount to the field of cognitive neuroscience. In this protocol study, we therefore aim to investigate the changes in plasma neurogranin in the early stage of AD and the mechanism thereof regarding the cognitive progression towards AD.Methods and analysisIn this study, patients with aMCI and AD patients (n=70 each) will be recruited at the memory clinic of the Department of Neurology of Hongqi Hospital affiliated with the Mudanjiang Medical University of China. Healthy older controls (n=70) will also be recruited from the community. All subjects will undergo neuroimaging and neuropsychological evaluations in addition to blood collection at the first year and the third year. We hope to identify a new biomarker of cognitive decline associated with AD and characterise its behaviour throughout the progression of aMCI to AD. This work will reveal novel targets for the therapeutic prevention, diagnosis and treatment of AD. The primary outcome measures will be (1) neuropsychological evaluation, including Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating scale, Shape Trail Test-A&B, Auditory Verbal Learning Test-HuaShan version; (2) microstructural alterations and hippocampal features from MRI scans; and (3) neurogranin levels in the neuronal-derived exosomes from peripheral blood samples.Ethics and disseminationThe ethics committee of the Hongqi Hospital affiliated with the Mudanjiang Medical University of China has approved this study protocol. The results will be published in peer-reviewed journals and presented at national or international scientific conferences.Trial registration numberChiCTR2000029055.

scholarly journals Kynurenic Acid Levels in Cerebrospinal Fluid from Patients with Alzheimer's Disease or Dementia with Lewy Bodies

2014 ◽  
Vol 7 ◽  
pp. IJTR.S13958 ◽  
Author(s):  
Malin Wennström ◽  
Henrietta M Nielsen ◽  
Funda Orhan ◽  
Elisabet Londos ◽  
Lennart Minthon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Cognitive Decline ◽  
Cognitive Functions ◽  
Dementia With Lewy Bodies ◽  
Kynurenic Acid ◽  
Lewy Bodies ◽  
Intercellular Adhesion Molecule ◽  
Intercellular Adhesion Molecule 1

Kynurenic acid (KYNA) is implicated in cognitive functions. Altered concentrations of the compound are found in serum and cerebrospinal fluid (CSF) of patients with Alzheimer's disease (AD). Further studies to determine whether KYNA serves as a biomarker for cognitive decline and dementia progression are required. In this study, we measured CSF KYNA levels in AD patients (n = 19), patients with dementia with Lewy bodies (DLB) (n = 18), and healthy age-matched controls (Ctrls)) (n = 20) to further explore possible correlations between KYNA levels, cognitive decline, and well-established AD and inflammatory markers. Neither DLB patients nor AD patients showed significantly altered CSF KYNA levels compared to Ctrls. However, female AD patients displayed significantly higher KYNA levels compared to male AD patients, a gender difference not seen in the Ctrl or DLB group. Levels of KYNA significantly correlated with the AD-biomarker P-tau and the inflammation marker soluble intercellular adhesion molecule-1 (sICAM-1) in the AD patient group. No associations between KYNA and cognitive functions were found. Our study shows that, although KYNA was not associated with cognitive decline in AD or DLB patients, it may be implicated in AD-related hyperphosphorylation of tau and inflammation. Further studies on larger patient cohorts are required to understand the potential role of KYNA in AD and DLB.

Longitudinal changes in awareness over 36 months in patients with mild Alzheimer's disease

2014 ◽  
Vol 27 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Asmus Vogel ◽  
Frans Boch Waldorff ◽  
Gunhild Waldemar
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Mmse Score ◽  
Neuropsychiatric Symptoms ◽  
Rapid Decline ◽  
Longitudinal Changes ◽  
Moderate Dementia ◽  
Over Time

ABSTRACTBackground:Longitudinal changes in awareness in dementia have been studied with short follow-up time and mostly in small patient groups (including patients with moderate dementia). We investigated awareness in patients with mild Alzheimer's disease (AD) over 36 months and studied if a decline in awareness was associated with decline in cognition and increase in neuropsychiatric symptoms.Methods:Awareness was measured on a categorical scale in 95 AD patients (age ≥50 years, Mini-Mental State Examination (MMSE) score ≥20). Awareness was rated at three time points (follow-up at 12 and 36 months) where MMSE, Neuropsychiatric Inventory (NPI-Q), and Cornell scale for Depression in Dementia also were applied.Results:At 12 months, 26% had lower awareness rating as compared to baseline and at 36 months lower awareness ratings were found in 39%. At both visits, 16% had higher awareness rating as compared to baseline. Patients with lower awareness at 36 months as compared to baseline had a more rapid increase in NPI-Q score (p = 0.002) over 36 months as compared to patients with stable or improved awareness over 36 months. A more rapid decline in MMSE score was observed for patients with lower awareness at 36 months (as compared to baseline) but only when compared to patients in whom awareness improved over time.Conclusions:The results show essentially no clear relationship between cognitive decline over three years and awareness. In some cases, awareness remained stable or even improved despite significant cognitive decline. In the subgroup where awareness declined over time, overall ratings of neuropsychiatric symptoms declined more rapidly than in the remaining patients.

scholarly journals Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Ellen Dicks ◽  
Lisa Vermunt ◽  
Wiesje M van der Flier ◽  
Frederik Barkhof ◽  
Philip Scheltens ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Executive Functioning ◽  
Cognitive Decline ◽  
Grey Matter ◽  
Disease Stage ◽  
Network Measures ◽  
Cognitive Continuum ◽  
Alzheimer’S Disease Dementia ◽  
Over Time

Abstract Biomarkers are needed to monitor disease progression in Alzheimer’s disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer’s disease. Here, we investigated how grey matter network measures evolve over time within individuals across the entire Alzheimer’s disease cognitive continuum and whether such changes relate to concurrent decline in cognition. We included 190 cognitively unimpaired, amyloid normal (controls) and 523 individuals with abnormal amyloid across the cognitive continuum (preclinical, prodromal, Alzheimer’s disease dementia) from the Alzheimer’s Disease Neuroimaging Initiative and calculated single-subject grey matter network measures (median of five networks per individual over 2 years). We fitted linear mixed models to investigate how network measures changed over time and whether such changes were associated with concurrent changes in memory, language, attention/executive functioning and on the Mini-Mental State Examination. We further assessed whether associations were modified by baseline disease stage. We found that both cognitive functioning and network measures declined over time, with steeper rates of decline in more advanced disease stages. In all cognitive stages, decline in network measures was associated with concurrent decline on the Mini-Mental State Examination, with stronger effects for individuals closer to Alzheimer’s disease dementia. Decline in network measures was associated with concurrent cognitive decline in different cognitive domains depending on disease stage: In controls, decline in networks was associated with decline in memory and language functioning; preclinical Alzheimer’s disease showed associations of decline in networks with memory and attention/executive functioning; prodromal Alzheimer’s disease showed associations of decline in networks with cognitive decline in all domains; Alzheimer’s disease dementia showed associations of decline in networks with attention/executive functioning. Decline in grey matter network measures over time accelerated for more advanced disease stages and was related to concurrent cognitive decline across the entire Alzheimer’s disease cognitive continuum. These associations were disease stage dependent for the different cognitive domains, which reflected the respective cognitive stage. Our findings therefore suggest that grey matter measures are helpful to track disease progression in Alzheimer’s disease.

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