Grant: Doctoral Research Award: Canada Graduate Scholarships
Sunnybrook Research Institute (Toronto, Ontario)
$120,000.00
Understanding Clinicopathological Heterogeneity and Mixed Pathologies across the Neurodegenerative Dementia Spectrums: A Multimodal Integrative Investigation
FY 2024-25
Summary
Dementia ranks among the top ten causes of mortality in Canada. Dementia can be described as a syndrome that leads to progressive loss of cognitive functions and independence. The presence of an underlying neurodegenerative disease, or often multiple neurodegenerative diseases in combination, is the major cause of the dementia syndrome. These multiple dementia-causing pathologies often co-exist to varying degrees as "mixed" disease, leading to overlap in clinical symptoms and variability in disease progression. Therefore, to address this variability and identify risks that are shared across neurodegenerative dementias, it is desirable to move away from the traditional approach of analyzing neurodegenerative disorders as discrete entities, but rather studying them as a group of related disorders along the dementia spectrum. In my research proposal, I will harmonize large, well-characterized, multimodal datasets consisting of "real world" patients representing the full spectrum of neurodegenerative dementias. I will evaluate how genomic and non-genomic (such as, age, education, sex, and cardiovascular) risk factors impact neuroimaging, blood/plasma, and cognitive/behavioural measures in a disease-agnostic fashion (that is, blinded to clinical diagnosis). More specifically, I will first identify robust genotype-phenotype and polygenic risk-phenotype relationships (endophenotypes), and then recategorize all patients into dementia "biotypes" using data-driven machine learning approaches irrespective of the clinical diagnostic categories. Neuropathological data will be assessed to investigate how the post-mortem relationships compare with antemortem relationships. I will also consider factors that may influence my results such as, sex, cardiovascular and lifestyle factors, and education. With this investigation, I hope to advance Canada's national strategy to reduce the burden of dementia through early detection and the application of precision medicine approaches.
Department
Program
Doctoral Research Award: Canada Graduate Scholarships
Location
Ontario, Canada
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
518735
Name
Saeed Usman
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Aging
Theme2
Biomedical
Prcname2
Doctoral Research Awards - A
Projecttitle
Understanding Clinicopathological Heterogeneity and Mixed Pathologies across the Neurodegenerative Dementia Spectrums: A Multimodal Integrative Investigation
Programtype2
Studentship Programs
Orgnameinp2
Sunnybrook Research Institute (Toronto, Ontario)
Cihramount2
$120,000
Cihrequipment2
$0
Programname2
Doctoral Research Award: Canada Graduate Scholarships
Keyworddelim
Alzheimer'S Disease Spectrum; Cerebrovascular Disease; Cognitive Neuropsychology; Frontotemporal Dementia Spectrum; Genomics; Lewy Body Dementia Spectrum; Magnetic Resonance Imaging (Mri); Mixed Neuropathology; Neurodegenerative Dementia
Abstract
Dementia ranks among the top ten causes of mortality in Canada. Dementia can be described as a syndrome that leads to progressive loss of cognitive functions and independence. The presence of an underlying neurodegenerative disease, or often multiple neurodegenerative diseases in combination, is the major cause of the dementia syndrome. These multiple dementia-causing pathologies often co-exist to varying degrees as "mixed" disease, leading to overlap in clinical symptoms and variability in disease progression. Therefore, to address this variability and identify risks that are shared across neurodegenerative dementias, it is desirable to move away from the traditional approach of analyzing neurodegenerative disorders as discrete entities, but rather studying them as a group of related disorders along the dementia spectrum. In my research proposal, I will harmonize large, well-characterized, multimodal datasets consisting of "real world" patients representing the full spectrum of neurodegenerative dementias. I will evaluate how genomic and non-genomic (such as, age, education, sex, and cardiovascular) risk factors impact neuroimaging, blood/plasma, and cognitive/behavioural measures in a disease-agnostic fashion (that is, blinded to clinical diagnosis). More specifically, I will first identify robust genotype-phenotype and polygenic risk-phenotype relationships (endophenotypes), and then recategorize all patients into dementia "biotypes" using data-driven machine learning approaches irrespective of the clinical diagnostic categories. Neuropathological data will be assessed to investigate how the post-mortem relationships compare with antemortem relationships. I will also consider factors that may influence my results such as, sex, cardiovascular and lifestyle factors, and education. With this investigation, I hope to advance Canada's national strategy to reduce the burden of dementia through early detection and the application of precision medicine approaches.
Competitiondate
202411
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Saeed, Usman
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $120,000~ $0~