O3-01-06: Relationship between patient dependence on others and clinical measures of cognitive impairment, functional disability and behavioral problems in Alzheimer's disease (AD): Results from the Dependence in Alzheimer's Disease in England (DADE) Stud

Background: Gait, speech, and drawing behaviors have been shown to be sensitive to the diagnosis of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). However, previous studies focused on only analyzing individual behavioral modalities, although these studies suggested that each of these modalities may capture different profiles of cognitive impairments associated with AD. Objective: We aimed to investigate if combining behavioral data of gait, speech, and drawing can improve classification performance compared with the use of individual modality and if each of these behavioral data can be associated with different cognitive and clinical measures for the diagnosis of AD and MCI. Methods: Behavioral data of gait, speech, and drawing were acquired from 118 AD, MCI, and cognitively normal (CN) participants. Results: Combining all three behavioral modalities achieved 93.0%accuracy for classifying AD, MCI, and CN, and only 81.9%when using the best individual behavioral modality. Each of these behavioral modalities was statistically significantly associated with different cognitive and clinical measures for diagnosing AD and MCI. Conclusion: Our findings indicate that these behaviors provide different and complementary information about cognitive impairments such that classification of AD and MCI is superior to using either in isolation.

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O3-11-01: Comparing Functional Disability of Men and Women with Mild Cognitive Impairment from the Alzheimer's Disease Neuroimaging Initiative

Alzheimer s & Dementia ◽

10.1016/j.jalz.2016.06.567 ◽

2016 ◽

Vol 12 ◽

pp. P312-P313

Author(s):

Courtney Berezuk ◽

Konstantine K. Zakzanis ◽

Joel Ramirez ◽

Jodi D. Edwards ◽

Brandy L. Callahan ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Functional Disability ◽

Men And Women

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Early Identification of Alzheimer's Disease: What Have we Learned from Mild Cognitive Impairment?

CNS Spectrums ◽

10.1017/s1092852900017181 ◽

2008 ◽

Vol 13 (S3) ◽

pp. 4-7 ◽

Cited By ~ 1

Author(s):

Howard H. Feldman ◽

Nagaendran Kandiah

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Standard Deviation ◽

Cognitive Decline ◽

Functional Disability ◽

Neuropsychiatric Symptoms ◽

Cognitive Domain ◽

Therapeutic Window

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline, functional disability, and neuropsychiatric symptoms. Initial diagnosis is often delayed to a point when there is significant neurodegenerative pathology and secondary downstream pathogenic sequelae. The disease should be diagnosed during its earliest stage, as this would likely represent an ideal therapeutic window for disease-modifying therapies. Despite recent research that has focused on defining the clinically identifiable at-risk phase that precedes AD, reliable criteria for identifying patients in the prodromal to incipient stages of AD remain elusive.In addressing the prodrome of AD, it has been clearly recognized that there are age-inappropriate cognitive declines that fall short of meeting the criteria for dementia. Most broadly, patients in this category have been classified as cognitively impaired not demented (CIND). In epidemiological studies, it has been estimated that 19% to 37% of patients ≥65 years of age are CIND. Conditions within the taxonomy of CIND include age-associated memory impairment (AAMI), age-associated cognitive decline (AACD), and mild cognitive impairment (MCI) (Slide 1).AAMI is defined psychometrically by memory test scores that are ≥1 standard deviation below scores of young healthy control patients. AACD is characterized by scores in any cognitive domain that are ≥1 standard deviation below age- and education-adjusted normal measures. MCI is identified by memory function at a level ≥1.5 standard deviations below age- and education-adjusted means. Of these three conditions, MCI has been investigated most thoroughly and is defined by a clinical phenotype.

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Low Vitamin D and Its Association with Cognitive Impairment and Dementia

Journal of Aging Research ◽

10.1155/2020/6097820 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Sadia Sultan ◽

Uzma Taimuri ◽

Shatha Abdulrzzaq Basnan ◽

Waad Khalid Ai-Orabi ◽

Afaf Awadallah ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Vitamin D ◽

Cognitive Impairment ◽

Behavioral Problems ◽

Small Sample Size ◽

Vitamin D Supplementation ◽

Small Sample ◽

Vitamin D Levels ◽

Prevention And Treatment

Vitamin D is a neurosteroid hormone that regulates neurotransmitters and neurotrophins. It has anti-inflammatory, antioxidant, and neuroprotective properties. It increases neurotrophic factors such as nerve growth factor which further promotes brain health. Moreover, it is also helpful in the prevention of amyloid accumulation and promotes amyloid clearance. Emerging evidence suggests its role in the reduction of Alzheimer’s disease hallmarks such as amyloid-beta and phosphorylated tau. Many preclinical studies have supported the hypothesis that vitamin D leads to attentional, behavioral problems and cognitive impairment. Cross-sectional studies have consistently found that vitamin D levels are significantly low in individuals with Alzheimer’s disease and cognitive impairment compared to healthy adults. Longitudinal studies and meta-analysis have also exhibited an association of low vitamin D with cognitive impairment and Alzheimer’s disease. Despite such evidence, the causal association cannot be sufficiently answered. In contrast to observational studies, findings from interventional studies have produced mixed results on the role of vitamin D supplementation in the prevention and treatment of cognitive impairment and dementia. The biggest issue of the existing RCTs is their small sample size, lack of consensus over the dose, and age of initiation of vitamin D supplements to prevent cognitive impairment. Therefore, there is a need for large double-blind randomized control trials to assess the benefits of vitamin D supplementation in the prevention and treatment of cognitive impairment.

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Diffusion MRI Indices and their Relation to Cognitive Impairment in Brain Aging: The updated multi-protocol approach in ADNI3

10.1101/476721 ◽

2018 ◽

Author(s):

Artemis Zavaliangos-Petropulu ◽

Talia M. Nir ◽

Sophia I. Thomopoulos ◽

Robert I. Reid ◽

Matt A. Bernstein ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

White Matter ◽

Rating Scale ◽

Brain Aging ◽

Screening Tools ◽

Disease Assessment ◽

Clinical Impairment ◽

Clinical Measures

AbstractBrain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter changes associated with brain aging and neurodegeneration. In its third phase, the Alzheimer’s Disease Neuroimaging Initiative (ADNI3) is collecting data across multiple sites and scanners using different dMRI acquisition protocols, to better understand disease effects. It is vital to understand when data can be pooled across scanners, and how the choice of dMRI protocol affects the sensitivity of extracted measures to differences in clinical impairment. Here, we analyzed ADNI3 data from 317 participants (mean age: 75.4±7.9 years; 143 men/174 women), who were each scanned at one of 47 sites with one of six dMRI protocols using scanners from three different manufacturers. We computed four standard diffusion tensor imaging (DTI) indices including fractional anisotropy (FADTI) and mean, radial, and axial diffusivity, and one FA index based on the tensor distribution function (FATDF), in 24 bilaterally averaged white matter regions of interest. We found that protocol differences significantly affected dMRI indices, in particular FADTI. We ranked the diffusion indices for their strength of association with four clinical assessments. In addition to diagnosis, we evaluated cognitive impairment as indexed by three commonly used screening tools for detecting dementia and Alzheimer’s disease: the Alzheimer’s Disease Assessment Scale (ADAS-cog), the Mini-Mental State Examination (MMSE), and the Clinical Dementia Rating scale sum-of-boxes (CDR-sob). Using a nested random-effects model to account for protocol and site, we found that across all dMRI indices and clinical measures, the hippocampal-cingulum and fornix (crus) / stria terminalis regions most consistently showed strong associations with clinical impairment. Overall, the greatest effect sizes were detected in the hippocampal-cingulum and uncinate fasciculus for associations between axial or mean diffusivity and CDR-sob. FATDF detected robust widespread associations with clinical measures, while FADTI was the weakest of the five indices for detecting associations. Ultimately, we were able to successfully pool dMRI data from multiple acquisition protocols from ADNI3 and detect consistent and robust associations with clinical impairment and age.

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