Andrea Slachevsky1,2,3,4,5, Gonzalo Forno6,7,8, Paulo Barraza9, Eneida Mioshi10, Carolina Delgado11,12, Patricia Lillo6,13,12, Fernando Henriquez6,7,8,9, Eduardo Bravo14, Mauricio Farias14, Carlos Muñoz-Neira8, Agustin Ibañez15,16,17,18,19, Mario A Parra20,15, Michael Hornberger10,21. 1. Geroscience Center for Brain Health and Metabolism (GERO), Faculty of Medicine, University of Chile, Avenida Salvador 486, Providencia, Santiago, Chile. andrea.slachevsky@uhile.cl. 2. Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - ICBM, Neurocience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Avenida Salvador 486, Providencia, Santiago, Chile. andrea.slachevsky@uhile.cl. 3. Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Av. Salvador 364, Providencia, Santiago, Chile. andrea.slachevsky@uhile.cl. 4. Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile. andrea.slachevsky@uhile.cl. 5. Departamento de Neurociencia, Facultad de Medicina, Universidad de Chile, Santiago, Chile. andrea.slachevsky@uhile.cl. 6. Geroscience Center for Brain Health and Metabolism (GERO), Faculty of Medicine, University of Chile, Avenida Salvador 486, Providencia, Santiago, Chile. 7. Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - ICBM, Neurocience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Avenida Salvador 486, Providencia, Santiago, Chile. 8. Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Av. Salvador 364, Providencia, Santiago, Chile. 9. Center for Advanced Research in Education (CIAE), University of Chile, 8330014, Santiago, Chile. 10. School of Health Sciences, University of East Anglia, Norwich, UK. 11. Neurology and Neurosurgery Department, Clinical Hospital, University of Chile, Santiago, Chile. 12. Departamento de Neurociencia, Facultad de Medicina, Universidad de Chile, Santiago, Chile. 13. Departamento de Neurociencia y Neurología Sur, Facultad de Medicina, Universidad de Chile, Santiago, Chile. 14. Neuroradiologic Department, Institute of Neurosurgery Asenjo, Santiago, Chile. 15. Universidad Autonoma del Caribe, Barranquilla, Colombia. 16. Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina. 17. National Scientific and Technical Research Council (CONICET), Av. Rivadavia 1917, C1033AAJ, Buenos Aires, Argentina. 18. Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibañez, Diagonal Las Torres 2640, Santiago, Chile. 19. Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR), Sydney, Australia. 20. Psychology Department, School of Psychological Sciences & Health, University of Strathclyde, Glasgow, UK. 21. Norfolk and Suffolk Foundation Trust, Norwich, UK.
Abstract
BACKGROUND: Impairments in activities of daily living (ADL) are a criterion for Alzheimer's disease (AD) dementia. However, ADL gradually decline in AD, impacting on advanced (a-ADL, complex interpersonal or social functioning), instrumental (IADL, maintaining life in community), and finally basic functions (BADL, activities related to physiological and self-maintenance needs). Information and communication technologies (ICT) have become an increasingly important aspect of daily functioning. Yet, the links of ADL, ICT, and neuropathology of AD dementia are poorly understood. Such knowledge is critical as it can provide biomarker evidence of functional decline in AD. METHODS: ADL were evaluated with the Technology-Activities of Daily Living Questionnaire (T-ADLQ) in 33 patients with AD and 30 controls. ADL were divided in BADL, IADL, and a-ADL. The three domain subscores were covaried against gray matter atrophy via voxel-based morphometry. RESULTS: Our results showed that three domain subscores of ADL correlate with several brain structures, with a varying degree of overlap between them. BADL score correlated mostly with frontal atrophy, IADL with more widespread frontal, temporal and occipital atrophy and a-ADL with occipital and temporal atrophy. Finally, ICT subscale was associated with atrophy in the precuneus. CONCLUSIONS: The association between ADL domains and neurodegeneration in AD follows a traceable neuropathological pathway which involves different neural networks. This the first evidence of ADL phenotypes in AD characterised by specific patterns of functional decline and well-defined neuropathological changes. The identification of such phenotypes can yield functional biomarkers for dementias such as AD.
BACKGROUND: Impairments in activities of daily living (ADL) are a criterion for Alzheimer's disease (AD) dementia. However, ADL gradually decline in AD, impacting on advanced (a-ADL, complex interpersonal or social functioning), instrumental (IADL, maintaining life in community), and finally basic functions (BADL, activities related to physiological and self-maintenance needs). Information and communication technologies (ICT) have become an increasingly important aspect of daily functioning. Yet, the links of ADL, ICT, and neuropathology of AD dementia are poorly understood. Such knowledge is critical as it can provide biomarker evidence of functional decline in AD. METHODS: ADL were evaluated with the Technology-Activities of Daily Living Questionnaire (T-ADLQ) in 33 patients with AD and 30 controls. ADL were divided in BADL, IADL, and a-ADL. The three domain subscores were covaried against gray matter atrophy via voxel-based morphometry. RESULTS: Our results showed that three domain subscores of ADL correlate with several brain structures, with a varying degree of overlap between them. BADL score correlated mostly with frontal atrophy, IADL with more widespread frontal, temporal and occipital atrophy and a-ADL with occipital and temporal atrophy. Finally, ICT subscale was associated with atrophy in the precuneus. CONCLUSIONS: The association between ADL domains and neurodegeneration in AD follows a traceable neuropathological pathway which involves different neural networks. This the first evidence of ADL phenotypes in AD characterised by specific patterns of functional decline and well-defined neuropathological changes. The identification of such phenotypes can yield functional biomarkers for dementias such as AD.
Entities:
Keywords:
Activities of daily living; Alzheimer’s disease; Functional impairment; Technology–activities of daily living questionnaire
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