Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155756
Title: Interactions of comorbid neuropsychiatric subsyndromes with neurodegenerative and cerebrovascular pathologies on cognition
Authors: Kan, Cheuk Ni
Xu, Xin
Schmetterer, Leopold
Venketasubramanian, Narayanaswamy
Chen, Christopher
Tan, Chin Hong
Keywords: Science::Medicine
Issue Date: 2022
Source: Kan, C. N., Xu, X., Schmetterer, L., Venketasubramanian, N., Chen, C. & Tan, C. H. (2022). Interactions of comorbid neuropsychiatric subsyndromes with neurodegenerative and cerebrovascular pathologies on cognition. Neurobiology of Aging, 109, 239-246. https://dx.doi.org/10.1016/j.neurobiolaging.2021.10.008
Project: M40824100 
NMRC/CG/NUHS/2010 
M4012193. 
R-184-006-184-511 
NMRC/CSA/038/2013 
Journal: Neurobiology of Aging 
Abstract: Comorbid neuropsychiatric symptoms are commonly found in individuals with dementia and is likely influenced by a combination of neurodegenerative and cerebrovascular pathophysiology. We evaluated the associations of a validated composite MRI-based quantitative measure of both neurodegeneration (hippocampus volume and cortical thickness of AD-specific regions) and cerebrovascular disease (CeVD; white matter hyperintensities and infarcts) with neuropsychiatric subsyndromes, and their interactions on cognition in a community-based sample across the disease spectrum (N = 773). Lower composite MRI scores corresponding to greater comorbid neurodegeneration and CeVD burden were associated with hyperactivity (OR = 1.48) and apathy (OR = 1.90) subsyndromes. Lower MRI scores with concomitant hyperactivity was associated with greater cognitive impairment, especially in patients who were at least moderately impaired, while the interaction with apathy was not dependent on disease stage. These MRI scores interaction models resulted in a better fit than models consisting of neurodegeneration or CeVD alone. Integrating multiple biomarkers with specific, disease stage-dependent neuropsychiatric subsyndromes may provide a more holistic risk profile to facilitate the identification of individuals at the highest risk of disease progression.
URI: https://hdl.handle.net/10356/155756
ISSN: 0197-4580
DOI: 10.1016/j.neurobiolaging.2021.10.008
Schools: School of Chemical and Biomedical Engineering 
Lee Kong Chian School of Medicine (LKCMedicine) 
School of Social Sciences 
Organisations: Singapore National Eye Center
Duke-NUS Medical School
Research Centres: SERI-NTU Advanced Ocular Engineering (STANCE)
Rights: © 2021 Elsevier Inc. All rights reserved. This paper was published in Neurobiology of Aging and is made available with permission of Elsevier Inc.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles
SCBE Journal Articles
SSS Journal Articles

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