Considerable effort is being made to detect dementia (particularly Alzheimer's disease) at its very early stages. Mild cognitive impairment (MCI) is described as the intermediate stage between normal aging and dementia. The diagnostic criteria for this disorder are currently not well defined and have been redefined over the past decade. Two of the major changes in definition of MCI are the inclusion of mild activities of daily living (ADL) impairments (that do not interfere with the ability to work and carry out life activites) and subtypes of MCI (those with amnestic and multiple-domain MCI). The types and degree of daily functional impairment are not well understood and predictors of such impairment need to be further investigated if we are to find better diagnostic criteria and early treatments for MCI. Biomedical markers, such as brain region atrophy has received much attention for the detection MCI and dementia in its earliest stages. These biomarkers alone, however, provide limited clinical utility. The current project has three major goals: 1) to examine the rate of functional decline in different subtypes of MCI (e.g., amnestic-MCI, multiple-domain MCI) over a 4-year period using an observation-based ADL task. Additionally, to examine how each ADL sub-task best predicts conversion from MCI to dementia in the different MCI subtypes, 2) to examine the relationship between biomarkers and specific types of ADL impairments, and 3) to determine the best predictors (i.e., biomarkers or neuropsychological performance) of ADL dysfunction at baseline and over time in MCI patients. A total of 55 MCI participants will be enrolled into this study from an Alzheimer's Disease Research Center (ADRC) and will be followed for a total 4 years. All participants will have already completed a neuropsychological test battery and will have undergone neuroimaging at the ADRC. Participants will be administered an observation-based ADL task. The relationship between specific CNS biomarkers and daily functional ability will be examined. How well the CNS biomarker measures, deficits in neuropsychological performance and daily functional impairment predict the rate of conversion to a specific type of MCI will also be analyzed; additionally, how specific biomarkers and neuropsychological performance predict functional disabilities will be examined in MCI subtypes at baseline as well as over a 4 year period. The results will better characterize functional impairment in the sub-types of MCI as well as better provide a better clinical understanding of abnormal biomarkers as they relate to ADL functioning.

Public Health Relevance

Considerable effort is being made to detect dementia at very early stages; therefore mild cognitive impairment (MCI) has received a great amount of attention. However, there are no clear diagnostic criteria for MCI and characterization of functional abilities would aid in clarifying such criteria. Also, predictors of poor functional abiity would aid in treatment planning.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Continuance Award (SC3)
Project #
5SC3GM094051-08
Application #
9315162
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Krasnewich, Donna M
Project Start
2010-07-01
Project End
2018-12-31
Budget Start
2017-08-01
Budget End
2018-12-31
Support Year
8
Fiscal Year
2017
Total Cost
Indirect Cost
Name
California State University Northridge
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
055752331
City
Northridge
State
CA
Country
United States
Zip Code
91330
Avila, Justina; Flowers, Amina; Scott, Travis M et al. (2015) Daily Activity Abilities in MCI, Alzheimer's Disease, and Healthy Controls. GeroPsych (Bern) 28:191-200
Razani, Jill; Corona, Roberto; Quilici, Jill et al. (2014) The Effects of Declining Functional Abilities in Dementia Patients and Increases Psychological Distress on Caregiver Burden Over a One-Year Period. Clin Gerontol 37:235-252
Miloyan, Beyon H; Razani, Jill; Larco, Andrea et al. (2013) Aspects of Attention Predict Real-World Task Performance in Alzheimer's Disease. Appl Neuropsychol Adult 20:203-210
Razani, Jill; Bayan, Stacey; Funes, Cynthia et al. (2011) Patterns of deficits in daily functioning and cognitive performance of patients with Alzheimer disease. J Geriatr Psychiatry Neurol 24:23-32