scholarly journals Robust Discovery of Mild Cognitive Impairment Subtypes and Their Risk of Alzheimer’s Disease Conversion Using Unsupervised Machine Learning and Gaussian Mixture Modeling

2021 ◽  
Vol 18 ◽  
Author(s):  
Fahimeh Nezhadmoghadam ◽  
Antonio Martinez-Torteya ◽  
Victor Treviño ◽  
Emmanuel Martínez ◽  
Alejandro Santos ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Gaussian Mixture ◽  
Low Risk ◽  
Latent Classes ◽  
Consensus Clustering ◽  
Prodromal Ad

Background: Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of Alzheimer’s disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans. Objective: This study aimed to determine whether the unsupervised discovering of latent classes of subjects with mild cognitive impairment (MCI) may be useful in finding different prodromal AD stages and/or subjects with a low MCI to AD conversion risk. Methods: Total 18 features relevant to the MCI to AD conversion process led to the identification of 681 subjects with early MCI. Subjects were divided into training (70%) and validation (30%) sets. Subjects from the training set were analyzed using consensus clustering, and Gaussian mixture models (GMM) were used to describe the latent classes. The discovered GMM predicted the latent class of the validation set. Finally, descriptive statistics, rates of conversion, and odds ratios (OR) were computed for each discovered class. Results: Through consensus clustering, we discovered three different clusters among MCI subjects. The three clusters were associated with low-risk (OR = 0.12, 95%CI = 0.04 to 0.3|), medium-risk (OR = 1.33, 95%CI = 0.75 to 2.37), and high-risk (OR = 3.02, 95%CI = 1.64 to 5.57) of converting from MCI to AD, with the high-risk and low-risk groups highly contrasting. Hence, prodromal AD subjects were present in only two clusters. Conclusion: We successfully discovered three different latent classes among MCI subjects with varied risks of MCI-to- AD conversion through consensus clustering. Two of the discovered classes may represent two different prodromal presentations of Alzheimer´s disease.

scholarly journals Robust Discovery of Mild Cognitive impairment subtypes and their Risk of Alzheimer’s Disease conversion using unsupervised machine learning and Gaussian Mixture Modeling

2020 ◽  
Author(s):  
Fahimeh Nezhadmoghadam ◽  
Antonio Martinez-Torteya ◽  
Victor Treviño ◽  
Emmanuel Martínez ◽  
Alejandro Santos ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Gaussian Mixture ◽  
Low Risk ◽  
Latent Classes ◽  
Consensus Clustering ◽  
Prodromal Ad

ABSTRACTBackgroundAlzheimer’s disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of Alzheimer’s disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans.ObjectiveTo determine whether the unsupervised discovering of latent classes of subjects with mild cognitive impairment (MCI) may be useful in finding different prodromal AD stages and/or subjects that have a low MCI to AD conversion risk.Methods18 features relevant with the MCI to AD conversion process described 681 subjects with early MCI. Subjects were split into training (70%) and validation (30%) sets. Subjects from the training set were analyzed using consensus clustering and Gaussian mixture models (GMM) were used to describe the shape of the discovered latent classes. The discovered GMM predicted the latent class of the validation set. Finally, descriptive statistics, rates of conversion, and odds ratios (OR) were computed for each discovered class.ResultsThrough consensus clustering we discovered three different clusters among MCI subjects. The three clusters were associated with low-risk (OR = 0.12, 95%CI = 0.04 to 0.3|), medium-risk (OR = 1.33, 95%CI = 0.75 to 2.37), and high-risk (OR = 3.02, 95%CI = 1.64 to 5.57) of converting from MCI to AD, with the high-risk and low-risk groups highly contrasting. Hence, prodromal AD subjects were present on only two clusters.ConclusionWe successfully discovered three different latent classes among MCI subjects with varied risk of MCI-to-AD conversion through consensus clustering. Two of the discovered classes may represent two different prodromal presentations of the Alzheimer’s disease.

Decisions and attitudes regarding participation and proxy in clinical trials among patients with impaired cognitive function

Dementia ◽  
2017 ◽  
Vol 18 (6) ◽  
pp. 2049-2061
Author(s):  
S Stormoen ◽  
IM Tallberg ◽  
O Almkvist ◽  
M Eriksdotter ◽  
E Sundström
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Decision Making ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Decision Making Capacity

Background Medical decision-making capacity is impaired in Alzheimer’s disease and mild cognitive impairment. Medical decision-making capacity depends on many different cognitive functions and varies due to situation and cognitive, social, and emotional status of the patient. Our aim was to analyze dementia patients’ capacity to estimate risks and benefits in different clinical trials and determine how cognitive decline affects their attitude toward possible participation and proxy consent. Methods Groups: Alzheimer’s disease (n = 20), mild cognitive impairment (n = 21) and healthy controls (n = 33). Two hypothetical clinical trials, a standardized interview and three visual analogue scales were used to investigate decisions, estimations, reasoning, and attitudes. Results A general positive attitude toward participation in clinical trials was shown among all groups. Both patients and controls motivated possible participation as “own-benefit” in the low-risk trial and to “help-others” in the high-risk trial. Individuals who accepted to participate in the high-risk trial scored lower in medical decision-making capacity in comparison to participants who would not have participated (p < .01). Patients in the Alzheimer’s disease but not mild cognitive impairment and healthy control groups underestimated risks and overestimated benefits in the high-risk/low-benefit trial (p < .05). A family member was most frequently chosen as possible proxy (91%). Conclusions Medical decisions and research consent should be interpreted with caution in patients who are already in early stages of dementia, as the patients’ acceptance to participate in high-risk trials may be due an insufficient decisional capacity and risk analysis, accelerated by a general desire to make good to society. We emphasize the use of a standardized tool to evaluate medical decisional capacity in clinical research.

P2-023: MILD COGNITIVE IMPAIRMENT WITH A HIGH RISK OF PROGRESSION TO ALZHEIMER'S DISEASE DEMENTIA (MCI-HR-AD): EFFECT OF SOUVENAID® TREATMENT ON COGNITION AND 18F-FDG PET SCANS

2006 ◽  
Vol 14 (7S_Part_12) ◽  
pp. P674-P675
Author(s):  
Maria Sagrario Manzano Palomo ◽  
Belen Anaya Caravaca ◽  
Maria Angeles Balsa Breton ◽  
Sergio Muñiz Castrillo ◽  
Maria Asuncion De La Morena Vicente ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Fdg Pet ◽  
Risk Of Progression ◽  
18F Fdg ◽  
Pet Scans ◽  
Alzheimer’S Disease Dementia

scholarly journals Precuneus and Cingulate Cortex Atrophy and Hypometabolism in Patients with Alzheimer’s Disease and Mild Cognitive Impairment: MRI and18F-FDG PET Quantitative Analysis Using FreeSurfer

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Matthieu Bailly ◽  
Christophe Destrieux ◽  
Caroline Hommet ◽  
Karl Mondon ◽  
Jean-Philippe Cottier ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Regions Of Interest ◽  
Posterior Cingulate ◽  
Amnestic Mci ◽  
Prodromal Ad

Objective.The objective of this study was to compare glucose metabolism and atrophy, in the precuneus and cingulate cortex, in patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), using FreeSurfer.Methods.47 individuals (17 patients with AD, 17 patients with amnestic MCI, and 13 healthy controls (HC)) were included. MRI and PET images using18F-FDG (mean injected dose of 185 MBq) were acquired and analyzed using FreeSurfer to define regions of interest in the hippocampus, amygdala, precuneus, and anterior and posterior cingulate cortex. Regional volumes were generated. PET images were registered to the T1-weighted MRI images and regional uptake normalized by cerebellum uptake (SUVr) was measured.Results.Mean posterior cingulate volume was reduced in MCI and AD. SUVr were different between the three groups: mean precuneus SUVr was 1.02 for AD, 1.09 for MCI, and 1.26 for controls (p<0.05); mean posterior cingulate SUVr was 0.96, 1.06, and 1.22 for AD, MCI, and controls, respectively (p<0.05).Conclusion.We found graduated hypometabolism in the posterior cingulate cortex and the precuneus in prodromal AD (MCI) and AD, whereas atrophy was not significant. This suggests that the use of18F-FDG in these two regions could be a neurodegenerative biomarker.

Mild cognitive impairment: An opportunity to identify patients at high risk for progression to Alzheimer's disease

2006 ◽  
Vol 28 (7) ◽  
pp. 991-1001 ◽  
Author(s):  
Allan Levey ◽  
James Lah ◽  
Felicia Goldstein ◽  
Kyle Steenland ◽  
Donald Bliwise
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk

scholarly journals Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao-Yan Ge ◽  
Kai Cui ◽  
Long Liu ◽  
Yao Qin ◽  
Jing Cui ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Bootstrap Method ◽  
Discrimination Performance ◽  
Clinical Assessments ◽  
Net Reclassification Improvement

AbstractIndividuals with mild cognitive impairment (MCI) are clinically heterogeneous, with different risks of progression to Alzheimer’s disease. Regular follow-up and examination may be time-consuming and costly, especially for MRI and PET. Therefore, it is necessary to identify a more precise MRI population. In this study, a two-stage screening frame was proposed for evaluating the predictive utility of additional MRI measurements among high-risk MCI subjects. In the first stage, the K-means cluster was performed for trajectory-template based on two clinical assessments. In the second stage, high-risk individuals were filtered out and imputed into prognosis models with varying strategies. As a result, the ADAS-13 was more sensitive for filtering out high-risk individuals among patients with MCI. The optimal model included a change rate of clinical assessments and three neuroimaging measurements and was significantly associated with a net reclassification improvement (NRI) of 0.246 (95% CI 0.021, 0.848) and integrated discrimination improvement (IDI) of 0.090 (95% CI − 0.062, 0.170). The ADAS-13 longitudinal models had the best discrimination performance (Optimism-corrected concordance index = 0.830), as validated by the bootstrap method. Considering the limited medical and financial resources, our findings recommend follow-up MRI examination 1 year after identification for high-risk individuals, while regular clinical assessments for low-risk individuals.

scholarly journals Untargeted metabolomics reveals sugar and homocysteine dysregulations in prodromal AD

2020 ◽  
Author(s):  
Ihab Hajjar ◽  
Chang Liu ◽  
Dean P. Jones ◽  
Karan Uppal
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Resolution ◽  
Sugar Metabolism ◽  
Untargeted Metabolomics ◽  
List Type ◽  
Disease Phenotypes ◽  
Prodromal Ad

AbstractIntroductionAltered metabolism may occur early in Alzheimer’s disease (AD). We used untargeted high-resolution metabolomics in the cerebrospinal fluid (CSF) in mild cognitive impairment (MCI) to identify these alterations.MethodsCSF from 92 normal controls and 93 MCI underwent untargeted metabolomics using high-resolution mass spectrometry with liquid chromatography. Partial least squares discriminant analysis was used followed by metabolite annotation and pathway enrichment analysis (PES). Significant features were correlated with disease phenotypes using spearman correlation.ResultsWe identified 294 features differentially expressed between the 2 groups and 94 were annotated. PES showed that pathways related to sugar regulation (N-Glycan, p=0.0007; sialic acid, p=0.0014; Aminosugars, p=0.0042; galactose, p=0.0054) homocysteine regulation (p=0.0081) were differentially activated and significant features within these pathways correlated with disease phenotypes.ConclusionWe identified a metabolic signature characterized by impairments in sugar and homocysteine regulation in prodromal AD. Targeting these changes may offer new therapeutic approaches to ADResearch in ContextSystematic review: The authors searched PUBMED and Google Scholar for previous reports of metabolomics and Alzheimer’s disease. Search Terms included: mild cognitive impairment, Alzheimer’s disease “AND” metabolism, metabolomics. This search identified multiple small studies that have conducted untargeted metabolomics in AD. This search resulted in the following findings: Prior studies have either included small samples, used targeted approaches, or focused on plasma profiling. In this study, we conducted a case-control untargeted high resolution metabolomic study on the CSF of a larger sample of normal cognition and mild cognitive impairment.Interpretation: We discovered that pathways in sugar metabolism, homocysteine and tyrosine were dysregulated in AD. Further, features that were significantly different between MCI and normal cognition had different patterns of association with cognitive, neuroimaging and Amyloid and tau biomarkers.Future direction: These pathways offer new potential targets for ADHighlightsMetabolic signature is detectable in prodromal ADMultiple sugar metabolism pathways are dysregulated in prodromal AD.S-adenosylmethionine is under- and S-adenosylhomocysteine is overexpressed in AD

scholarly journals Mild Cognitive Impairment with a High Risk of Progression to Alzheimer’s Disease Dementia (MCI-HR-AD): Effect of Souvenaid® Treatment on Cognition and 18F-FDG PET Scans

2019 ◽  
Vol 3 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Maria Sagrario Manzano Palomo ◽  
Belen Anaya Caravaca ◽  
Maria Angeles Balsa Bretón ◽  
Sergio Muñiz Castrillo ◽  
Asuncion de la Morena Vicente ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Fdg Pet ◽  
Risk Of Progression ◽  
18F Fdg ◽  
Pet Scans ◽  
Alzheimer’S Disease Dementia

scholarly journals Spatial inhibition of return is impaired in mild cognitive impairment and mild Alzheimer’s disease

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252958
Author(s):  
Xiong Jiang ◽  
James H. Howard ◽  
G. William Rebeck ◽  
Raymond Scott Turner
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Task Performance ◽  
Inhibition Of Return ◽  
Older Individuals

Spatial inhibition of return (IOR) refers to the phenomenon by which individuals are slower to respond to stimuli appearing at a previously cued location compared to un-cued locations. Here with a group of older adults (n = 56, 58–80 (67.9±5.2) year old, 31 females, 18.7±3.6 years of education), we provide evidence supporting the notion that spatial IOR is mildly impaired in individuals with mild cognitive impairment (MCI) or mild Alzheimer’s disease (AD), and the impairment is detectable using a double cue paradigm. Furthermore, reduced spatial IOR in high-risk healthy older individuals is associated with reduced memory and other neurocognitive task performance, suggesting that the double cue spatial IOR paradigm may be useful in detecting MCI and early AD.

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