scholarly journals Anatomically Standardized Detection of MRI Atrophy Patterns in Early-Stage Alzheimer’s Disease

2021 ◽  
Vol 11 (11) ◽  
pp. 1491
Author(s):  
Lukas Lenhart ◽  
Stephan Seiler ◽  
Lukas Pirpamer ◽  
Georg Goebel ◽  
Thomas Potrusil ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Verbal Memory ◽  
Early Stage ◽  
Disease Onset ◽  
Principal Component ◽  
Clinical Dementia Rating ◽  
Individual Subject ◽  
Whole Brain

MRI studies have consistently identified atrophy patterns in Alzheimer’s disease (AD) through a whole-brain voxel-based analysis, but efforts to investigate morphometric profiles using anatomically standardized and automated whole-brain ROI analyses, performed at the individual subject space, are still lacking. In this study we aimed (i) to utilize atlas-derived measurements of cortical thickness and subcortical volumes, including of the hippocampal subfields, to identify atrophy patterns in early-stage AD, and (ii) to compare cognitive profiles at baseline and during a one-year follow-up of those previously identified morphometric AD subtypes to predict disease progression. Through a prospectively recruited multi-center study, conducted at four Austrian sites, 120 patients were included with probable AD, a disease onset beyond 60 years and a clinical dementia rating of ≤1. Morphometric measures of T1-weighted images were obtained using FreeSurfer. A principal component and subsequent cluster analysis identified four morphometric subtypes, including (i) hippocampal predominant (30.8%), (ii) hippocampal-temporo-parietal (29.2%), (iii) parieto-temporal (hippocampal sparing, 20.8%) and (iv) hippocampal-temporal (19.2%) atrophy patterns that were associated with phenotypes differing predominately in the presentation and progression of verbal memory and visuospatial impairments. These morphologically distinct subtypes are based on standardized brain regions, which are anatomically defined and freely accessible so as to validate its diagnostic accuracy and enhance the prediction of disease progression.

scholarly journals P1-471: THE UTILITY OF VERBAL MEMORY TESTS AS SENSITIVE MARKERS FOR EARLY-STAGE ALZHEIMER'S DISEASE IN ELDERLY CHINESE AMERICANS

2019 ◽  
Vol 15 ◽  
pp. P449-P449
Author(s):  
Clara Li ◽  
Judith Neugroschl ◽  
Carolyn W. Zhu ◽  
Mari Umpierre ◽  
Jane Martin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Verbal Memory ◽  
Early Stage ◽  
Chinese Americans ◽  
Memory Tests ◽  
Elderly Chinese

scholarly journals NEUBOrg: artificially induced pluripotent stem cell-derived brain organoid to model and study genetics of Alzheimer’s disease progression.

2020 ◽  
Author(s):  
Sally Esmail ◽  
Wayne Danter
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Stem Cell ◽  
Disease Progression ◽  
Pluripotent Stem Cell ◽  
Induced Pluripotent Stem Cell ◽  
Whole Brain ◽  
Learning Platform ◽  
Brain Organoid ◽  
Induced Pluripotent

Abstract Alzheimer's disease (AD) is the most common type of neurodegenerative diseases. There are over 44 million people living with the disease worldwide. While there are currently no effective treatments for AD, induced pluripotent stem cell-derived brain organoids have the potential to provide a better understanding of Alzheimer’s pathogenesis. Nevertheless, developing brain organoid models is expensive, time consuming and often does not reflect disease progression. Using accurate and inexpensive computer simulations of human brain organoids can overcome the current limitations. Induced whole brain organoids (aiWBO) will greatly expand our ability to model AD and can guide wet lab research. In this study, we have successfully developed and validated artificially induced a whole brain organoid platform (NEUBOrg) using our previously validated machine learning platform, DeepNEU (v6.1). Using NEUBorg platform, we have generated aiWBO simulations of AD and provided a novel approach to test genetic risk factors associated with AD progression and pathogenesis.

scholarly journals Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Qi Wang ◽  
Yinghua Chen ◽  
Benjamin Readhead ◽  
Kewei Chen ◽  
Yi Su ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Longitudinal Data ◽  
Disease Progression ◽  
Peripheral Blood ◽  
Early Stage ◽  
Underlying Mechanism ◽  
Methylation Data ◽  
Brain Tissues

Abstract Background While Alzheimer’s disease (AD) remains one of the most challenging diseases to tackle, genome-wide genetic/epigenetic studies reveal many disease-associated risk loci, which sheds new light onto disease heritability, provides novel insights to understand its underlying mechanism and potentially offers easily measurable biomarkers for early diagnosis and intervention. Methods We analyzed whole-genome DNA methylation data collected from peripheral blood in a cohort (n = 649) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and compared the DNA methylation level at baseline among participants diagnosed with AD (n = 87), mild cognitive impairment (MCI, n = 175) and normal controls (n = 162), to identify differentially methylated regions (DMRs). We also leveraged up to 4 years of longitudinal DNA methylation data, sampled at approximately 1 year intervals to model alterations in methylation levels at DMRs to delineate methylation changes associated with aging and disease progression, by linear mixed-effects (LME) modeling for the unchanged diagnosis groups (AD, MCI and control, respectively) and U-shape testing for those with changed diagnosis (converters). Results When compared with controls, patients with MCI consistently displayed promoter hypomethylation at methylation QTL (mQTL) gene locus PM20D1. This promoter hypomethylation was even more prominent in patients with mild to moderate AD. This is in stark contrast with previously reported hypermethylation in hippocampal and frontal cortex brain tissues in patients with advanced-stage AD at this locus. From longitudinal data, we show that initial promoter hypomethylation of PM20D1 during MCI and early stage AD is reversed to eventual promoter hypermethylation in late stage AD, which helps to complete a fuller picture of methylation dynamics. We also confirm this observation in an independent cohort from the Religious Orders Study and Memory and Aging Project (ROSMAP) Study using DNA methylation and gene expression data from brain tissues as neuropathological staging (Braak score) advances. Conclusions Our results confirm that PM20D1 is an mQTL in AD and demonstrate that it plays a dynamic role at different stages of the disease. Further in-depth study is thus warranted to fully decipher its role in the evolution of AD and potentially explore its utility as a blood-based biomarker for AD.

scholarly journals Detection of mild cognitive impairment and early stage dementia with an audio-recorded cognitive scale

2013 ◽  
Vol 25 (8) ◽  
pp. 1325-1333 ◽  
Author(s):  
Margaret C. Sewell ◽  
Xiaodong Luo ◽  
Judith Neugroschl ◽  
Mary Sano
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Memory ◽  
Early Stage ◽  
Neuropsychological Testing ◽  
Area Under The Curve ◽  
Cognitive Domain ◽  
Screening Measures

ABSTRACTBackground: Physicians often miss diagnosis of mild cognitive impairment (MCI) or early dementia and screening measures can be insensitive to very mild impairments. Other cognitive assessments may take too much time or be frustrating to seniors. This study examined the ability of an audio-recorded scale, developed in Australia, to detect MCI or mild Alzheimer's disease (AD) and compared cognitive domain-specific performance on the audio-recorded scale to in-person battery and common cognitive screens.Method: Seventy-six patients from the Mount Sinai Alzheimer's Disease Research Center were recruited. Patients were aged 75 years or older, with clinical diagnosis of AD or MCI (n = 51) or normal control (n = 25). Participants underwent in-person neuropsychological testing followed by testing with the audio-recorded cognitive screen (ARCS).Results: ARCS provided better discrimination between normal and impaired elderly individuals than either the Mini-Mental State Examination or the clock drawing test. The in-person battery and ARCS analogous variables were significantly correlated, most in the 0.4 to 0.7 range, including verbal memory, executive function/attention, naming, and verbal fluency. The area under the curve generated from the receiver operating characteristic curves indicated high and equivalent discrimination for ARCS and the in-person battery (0.972 vs. 0.988; p = 0.23).Conclusion: The ARCS demonstrated better discrimination between normal controls and those with mild deficits than typical screening measures. Performance on cognitive domains within the ARCS was well correlated with the in-person battery. Completion of the ARCS was accomplished despite mild difficulty hearing the instructions even in very elderly participants, indicating that it may be a useful measure in primary care settings.

The Differential Cognitive Deficits Between Patients with Early Stage Alzheimer's Disease and Patients with Early Stage Vascular Dementia

2017 ◽  
Vol 41 (S1) ◽  
pp. S175-S175 ◽  
Author(s):  
J.H. Park ◽  
K. Kyung Min ◽  
J. Byoung Sun
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Cognitive Deficits ◽  
Processing Speed ◽  
Comprehensive Evaluation ◽  
Early Stage ◽  
Word List ◽  
Clinical Dementia Rating ◽  
Korean Version

BackgroundThe study aims to examine whether cognitive deficits are different between patients with early stage Alzheimer's disease (AD) and patients with early stage vascular dementia (VaD) using the Korean version of the CERAD neuropsychological battery (CERAD-K-N).MethodsPatients with early stage dementia, global Clinical Dementia Rating (CDR) 0.5 or 1 were consecutively recruited among first visitors to a dementia clinic, 257 AD patients and 90 VaD patients completed the protocol of the Korean version of the CERAD clinical assessment battery. CERAD-K-N was administered for the comprehensive evaluation of the neuropsychological function.ResultsOf the total 347 participants, 257 (69.1%) were AD group (CDR 0.5 = 66.9%) and 90 (21.9%) were VaD group (CDR 0.5 = 40.0%). Patients with very mild AD showed poorer performances in Boston naming test (BNT) (P = 0.028), word list memory test (P < 0.001), word list recall test (P < 0.001) and word list recognition test (WLRcT) (P = 0.006) than very mild VaD after adjustment of T score of MMSE-KC. However, the performance of trail making A (TMA) was more impaired in VaD group than in AD group. The performance of WLRcT (P < 0.001) was the worst among neuropsychological tests within AD group, whereas TMA was performed worst within VaD group.ConclusionsPatients with early-stage AD have more cognitive deficits on memory and language while patients with early-stage VaD show worse cognitive function on attention/processing speed. In addition, as the first cognitive deficit, memory dysfunction comes in AD and deficit in attention/processing speed in VaD.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Predicting Alzheimer’s disease progression trajectory and clinical subtypes using machine learning

2019 ◽  
Author(s):  
Vipul K. Satone ◽  
Rachneet Kaur ◽  
Anant Dadu ◽  
Hampton Leonard ◽  
Hirotaka Iwaki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Disease Onset ◽  
Machine Learning Techniques ◽  
Progression Rate ◽  
Early Stages ◽  
Age Related ◽  
Learning Techniques

AbstractBackgroundAlzheimer’s disease (AD) is a common, age-related, neurodegenerative disease that impairs a person’s ability to perform day-to-day activities. Diagnosing AD is challenging, especially in the early stages. Many patients still go undiagnosed, partly due to the complex heterogeneity in disease progression. This highlights a need for early prediction of the disease course to assist its treatment and tailor therapy options to the disease progression rate. Recent developments in machine learning techniques provide the potential to not only predict disease progression and trajectory of AD but also to classify the disease into different etiological subtypes.Methods and findingsThe work shown here clusters participants in distinct and multifaceted progression subgroups of AD and discusses an approach to predict the progression rate from baseline diagnosis. We observed that the myriad of clinically reported symptoms summarized in the proposed AD progression space corresponds directly with memory and cognitive measures, which are routinely used to monitor disease onset and progression. Our analysis demonstrated accurate prediction of disease progression after four years from the first 12 months of post-diagnosis clinical data (Area Under the Curve of 0.96 (95% confidence interval (CI), 0.92-1.0), 0.81 (95% CI, 0.74-0.88) and 0.98 (95% CI, 0.96-1.0) for slow, moderate and fast progression rate patients respectively). Further, we explored the long short-term memory (LSTM) neural networks to predict the trajectory of an individual patient’s progression.ConclusionThe machine learning techniques presented in this study may assist providers in identifying different progression rates and trajectories in the early stages of the disease, hence allowing for more efficient and personalized healthcare deliveries. With additional information about the progression rate of AD at hand, providers may further individualize the treatment plans. The predictive tests discussed in this study not only allow for early AD diagnosis but also facilitate the characterization of distinct AD subtypes relating to trajectories of disease progression. These findings are a crucial step forward for early disease detection. These models can be used to design improved clinical trials for AD research.

scholarly journals NEUBOrg: Artificially Induced Pluripotent Stem Cell-Derived Brain Organoid to Model and Study Genetics of Alzheimer’s Disease Progression

2021 ◽  
Vol 13 ◽  
Author(s):  
Sally Esmail ◽  
Wayne R. Danter
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Stem Cell ◽  
Disease Progression ◽  
Pluripotent Stem Cell ◽  
Induced Pluripotent Stem Cell ◽  
Whole Brain ◽  
Learning Platform ◽  
Brain Organoid ◽  
Induced Pluripotent

Alzheimer’s disease (AD) is the most common type of neurodegenerative diseases. There are over 44 million people living with the disease worldwide. While there are currently no effective treatments for AD, induced pluripotent stem cell-derived brain organoids have the potential to provide a better understanding of Alzheimer’s pathogenesis. Nevertheless, developing brain organoid models is expensive, time consuming and often does not reflect disease progression. Using accurate and inexpensive computer simulations of human brain organoids can overcome the current limitations. Induced whole brain organoids (aiWBO) will greatly expand our ability to model AD and can guide wet lab research. In this study, we have successfully developed and validated artificially induced a whole brain organoid platform (NEUBOrg) using our previously validated machine learning platform, DeepNEU (v6.1). Using NEUBorg platform, we have generated aiWBO simulations of AD and provided a novel approach to test genetic risk factors associated with AD progression and pathogenesis.

NEUROPSYCHOLOGICAL EVALUATION OF NARRATIVE DISCOURSE PATTERNS IN INDIVIDUALS WITH EARLY STAGE VASCULAR DEMENTIA VS. PATIENTS WITH EARLY STAGE ALZHEIMER’S DISEASE

2021 ◽  
Vol 19 (2) ◽  
pp. 187-207
Author(s):  
Natalia Gawron ◽  
Emilia Łojek ◽  
Beata Hintze ◽  
Anna Rita Egbert
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Fairy Tales ◽  
Verbal Memory ◽  
Fairy Tale ◽  
Early Stage ◽  
Narrative Discourse ◽  
Language Difficulties ◽  
And Control

Individuals in the early stages of dementia may demonstrate language difficulties. The aim of the study was an evaluation of the differences in narrative discourse abilities across two types of dementia, i.e., Vascular Dementia (VaD) and Alzheimer’s Disease (AD) in comparison to the young and old elderly. The AD and VaD groups displayed a lower performance than the age-matched YE on tasks involving reasoning. The VaD partici- pants outperformed patients with AD in verbal memory and narrative discourse. Discourse macrostructure analyses showed that the VaD reproduced more propositions than did the AD participants, but that these were comparable to YE and OE. There were more conjunctions in narratives reproduced by the VaD participants as compared to other groups, although this tendency was only present in the story but not in fairy tale reproductions themselves. Individ- uals in the AD group had more difficulties than YE and OE individuals in figuring out the moral of fairy tales. Clinical and control groups reproduced the microstructure and superstructure of texts comparatively well. Discourse recall correlated with performance on verbal memory, attention/working memory, and reasoning. Differences in narrative discourse abilities were found. Alzheimer’s Disease (AD) patients scored lower in verbal memory than did Vascular Dementia (VaD) patients. Both groups however obtained lower results than the young and old elderly.

scholarly journals Education, leisure activities and cognitive and functional ability of Alzheimer's disease patients: A follow-up study

2013 ◽  
Vol 7 (2) ◽  
pp. 181-189 ◽  
Author(s):  
Margarida Sobral ◽  
Constança Paúl
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Functional Ability ◽  
Rating Scale ◽  
Leisure Activities ◽  
Functional Decline ◽  
Clinical Dementia Rating ◽  
High Participation ◽  
Relevant Variables

ABSTRACT Education and participation in leisure activities appear to be highly relevant variables in Alzheimer's disease (AD) and usually form the basis of the Cognitive Reserve construct. Objective: [A] To determine the association between education, cognitive and functional ability of AD patients; [B] To determine the association between participation in leisure activities and cognitive and functional ability of AD patients; [C] To evaluate the association of education and participation in leisure activities in the course of AD. Methods: Functional and neuropsychological abilities of 120 outpatients with probable AD were evaluated at baseline, at 36 and 54 months. Data collected at baseline included socio-demographics, clinical variables, education and frequency of participation in leisure activities throughout life. All participants and/or caregivers answered the questionnaire, "Participation in leisure activities throughout life" while patients completed the MMSE, the Clinical Dementia Rating scale, neuropsychological tests from the Lisbon Screening for Dementia Assessment, Barthel Index and Lawton and Brody's Index. Results: AD patients with higher levels of education achieved better results on cognitive tests. The participants with higher participation in leisure activities exhibited better results on cognitive and functional tests than those with lower participation. The disease progression was linear and progressed similarly regardless of the level of education of participants. However, the results suggest a slower disease progression in patients with a higher level of participation in leisure activities throughout their lives. Conclusion: AD patients with high education and high participation in leisure activities may benefit from a slower cognitive and functional decline after diagnosis of AD.

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