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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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