INS NYC 2024 Program

Poster	Poster Session 06 Program Schedule 02/15/2024 04:00 pm - 05:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 06: Aging \| MCI \| Neurodegenerative Disease - PART 2 Final Abstract #32 Cross-domain symptom profiles of MCI and dementia assessed with the NIH Toolbox Matthew Cohen, University of Delaware, Newark, United States Aaron Boulton, University of Delaware, Newark, United States Callie Tyner, University of Delaware, Newark, United States Jerry Slotkin, University of Delaware, Newark, United States Sandra Weintraub, Northwestern University, Chicago, United States Richard Gershon, Northwestern University, Chicago, United States Hiroko Dodge, Massachusetts General Hospital, Boston, United States David Tulsky, University of Delaware, Newark, United States Category: MCI (Mild Cognitive Impairment) Keyword 1: dementia - Alzheimer's disease Keyword 2: mild cognitive impairment Keyword 3: assessment Objective: Because of the complexity and heterogeneity of Alzheimer’s Disease (AD) clinical presentations, it has been important to use data-based approaches, such as latent profile analysis (LPA), to identify patient subtypes. Previous LPA research has advanced the more precise characterization and understanding of patients, better clarity regarding the probability and rate of disease progression, and an empirical approach to identifying those who might benefit most from early intervention. Whereas previous LPA research has revealed useful cognitive, neuropsychiatric, and functional subtypes of patients with AD, no study has identified patient profiles that span domains of health and functioning, including cognitive, social, emotional, motor, and sensory functioning. Participants and Methods: LPA was conducted with data from the Advancing Reliable Measurement in Alzheimer’s Disease and cognitive Aging (ARMADA) study. Participants were 165 older adults with amnestic MCI (aMCI) or mild dementia of the Alzheimer’s type (DAT). All LPA indicator variables were from the NIH Toolbox^Ⓡ and profile validity was supported with non-Toolbox measures. Results: The data were best modeled with a 4-profile solution. Profile 1 (“dysexecutive/low functioning”), the largest profile, contained 36% of the sample. Participants exhibited poor executive function scores as well as below average emotional health, social health, mobility, and auditory function scores. This profile contained over half of all participants with DAT and outnumbered participants with aMCI approximately 2 to 1 (65% to 35%). The remaining three profiles are most distinguished by differences in psychosocial functioning: low, average, and high. Profile 2 (“average psychosocial functioning”) contained 28% of the sample. Participants exhibited above average cognitive function and approximately average levels of emotional health, social health, mobility, and auditory function. Most Profile 2 participants had aMCI (72%). Profile 3 (“low psychosocial functioning”) contained 20% of the sample. These participants exhibited above average levels of cognitive function equivalent to Profile 2, yet very low (negative) levels of psychosocial health-- lower than individuals in Profile 1 who predominantly had more advanced disease and lower functioning overall. As with Profile 2, Profile 3 contained more individuals with aMCI (70%) than DAT (30%). Profile 4 (“high psychosocial functioning”), contained 15% of the sample. Participants exhibited positive levels of psychosocial health and average levels of cognition, mobility, and auditory function. This profile was more evenly split between aMCI (58%) and DAT (42%). Motor and sensory functioning did not strongly differ among the four profiles. Conclusions: Although the profiles did differ in cognitive functioning, the most striking difference among profiles was in emotional and social functioning. This indicates the importance of social and emotional factors for understanding individual patient differences in the experience of aMCI/DAT. Furthermore, because many aspects of psychosocial functioning (e.g., depression, loneliness) are modifiable, future research should investigate those profiles further, to better understand risk and resilience factors, the stability of these profiles over time, and responses to intervention. These multi-domain patient profiles using the NIH Toolbox support and extend previous findings on single-domain profiles and highlight the importance of psychosocial differences in understanding patient experiences of MCI and dementia.

Poster

02/15/2024
04:00 pm - 05:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 06: Aging | MCI | Neurodegenerative Disease - PART 2

Final Abstract #32

Cross-domain symptom profiles of MCI and dementia assessed with the NIH Toolbox

Matthew Cohen, University of Delaware, Newark, United States
Aaron Boulton, University of Delaware, Newark, United States
Callie Tyner, University of Delaware, Newark, United States
Jerry Slotkin, University of Delaware, Newark, United States
Sandra Weintraub, Northwestern University, Chicago, United States
Richard Gershon, Northwestern University, Chicago, United States
Hiroko Dodge, Massachusetts General Hospital, Boston, United States
David Tulsky, University of Delaware, Newark, United States

Category: MCI (Mild Cognitive Impairment)

Keyword 1: dementia - Alzheimer's disease
Keyword 2: mild cognitive impairment
Keyword 3: assessment

Objective:

Because of the complexity and heterogeneity of Alzheimer’s Disease (AD) clinical presentations, it has been important to use data-based approaches, such as latent profile analysis (LPA), to identify patient subtypes. Previous LPA research has advanced the more precise characterization and understanding of patients, better clarity regarding the probability and rate of disease progression, and an empirical approach to identifying those who might benefit most from early intervention. Whereas previous LPA research has revealed useful cognitive, neuropsychiatric, and functional subtypes of patients with AD, no study has identified patient profiles that span domains of health and functioning, including cognitive, social, emotional, motor, and sensory functioning.

Participants and Methods:

LPA was conducted with data from the Advancing Reliable Measurement in Alzheimer’s Disease and cognitive Aging (ARMADA) study. Participants were 165 older adults with amnestic MCI (aMCI) or mild dementia of the Alzheimer’s type (DAT). All LPA indicator variables were from the NIH Toolbox^Ⓡ and profile validity was supported with non-Toolbox measures.

Results:

The data were best modeled with a 4-profile solution. Profile 1 (“dysexecutive/low functioning”), the largest profile, contained 36% of the sample. Participants exhibited poor executive function scores as well as below average emotional health, social health, mobility, and auditory function scores. This profile contained over half of all participants with DAT and outnumbered participants with aMCI approximately 2 to 1 (65% to 35%). The remaining three profiles are most distinguished by differences in psychosocial functioning: low, average, and high. Profile 2 (“average psychosocial functioning”) contained 28% of the sample. Participants exhibited above average cognitive function and approximately average levels of emotional health, social health, mobility, and auditory function. Most Profile 2 participants had aMCI (72%). Profile 3 (“low psychosocial functioning”) contained 20% of the sample. These participants exhibited above average levels of cognitive function equivalent to Profile 2, yet very low (negative) levels of psychosocial health-- lower than individuals in Profile 1 who predominantly had more advanced disease and lower functioning overall. As with Profile 2, Profile 3 contained more individuals with aMCI (70%) than DAT (30%). Profile 4 (“high psychosocial functioning”), contained 15% of the sample. Participants exhibited positive levels of psychosocial health and average levels of cognition, mobility, and auditory function. This profile was more evenly split between aMCI (58%) and DAT (42%). Motor and sensory functioning did not strongly differ among the four profiles.

Conclusions:

Although the profiles did differ in cognitive functioning, the most striking difference among profiles was in emotional and social functioning. This indicates the importance of social and emotional factors for understanding individual patient differences in the experience of aMCI/DAT. Furthermore, because many aspects of psychosocial functioning (e.g., depression, loneliness) are modifiable, future research should investigate those profiles further, to better understand risk and resilience factors, the stability of these profiles over time, and responses to intervention. These multi-domain patient profiles using the NIH Toolbox support and extend previous findings on single-domain profiles and highlight the importance of psychosocial differences in understanding patient experiences of MCI and dementia.