Grant: Catalyst Grant: Secondary Analysis of Neuroimaging Databases
Centre for Addiction and Mental Health (Toronto)
$100,000.00
Effects of Gene-Gene Interactions within an Early Risk Pathway for Alzheimer's Disease on Established and Novel MRI-based Phenotypes
EF 2013-14
Résumé
A considerable proportion of the risk for Alzheimer's disease is due to genetic factors. However, aside from one well-known gene, Apoliprotein E (APOE), little has been uncovered regarding how other genetic factors might cause risk for Alzheimer's disease. In parallel, it is important to identify risk for Alzheimer's disease before clinically observable onset of memory problems and behavioural disturbances. To do that we need to study the relationship between variation in Alzheimer's risk genes and neuroimaging measures, since the brain signature of these risk genes can be measured prior to disease onset. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has now completed neuroimaging, genetics, and other biological measures on many hundreds of healthy people, people with Alzheimer's disease, and people in pre-Alzheimer's states known as early and late mild cognitive impairment. This database provides us with an opportunity to explore the effects of previously unexplored genetic interactions on several brain imaging measures. We will not only do this on established brain imaging measures of risk, but also on newer measures that our team has developed that target a part of the brain known as the medial temporal lobe, where the genes we are interested in have known effects on brain structure. If we can show that genes interact to impact brain structure in a way that is over and above that of any one gene alone, we can better predict who will develop Alzheimer's disease. Also, we can develop new treatments targeted toward those specific genetic risk pathways.
Programme
Catalyst Grant: Secondary Analysis of Neuroimaging Databases
Bénéficiaire
Emplacement
Ontario, Canada
Type
Grant
Source
CIHR Funding Decisions Database
Tel que publié
Id
293725
Name
Voineskos Aristotle N
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Aging
Theme2
Biomedical
Prcname2
Catalyst Grant: Secondary Analysis of Neuroimaging Databases
Projecttitle
Effects of Gene-Gene Interactions within an Early Risk Pathway for Alzheimer's Disease on Established and Novel MRI-based Phenotypes
Programtype2
Operating Grants
Orgnameinp2
Centre for Addiction and Mental Health (Toronto)
Cihramount2
$100,000
Cihrequipment2
$0
Programname2
Catalyst Grant: Secondary Analysis of Neuroimaging Databases
Keyworddelim
Alzheimer; Genetics; Imaging-Genetics; Mri; Phenotype
Abstract
A considerable proportion of the risk for Alzheimer's disease is due to genetic factors. However, aside from one well-known gene, Apoliprotein E (APOE), little has been uncovered regarding how other genetic factors might cause risk for Alzheimer's disease. In parallel, it is important to identify risk for Alzheimer's disease before clinically observable onset of memory problems and behavioural disturbances. To do that we need to study the relationship between variation in Alzheimer's risk genes and neuroimaging measures, since the brain signature of these risk genes can be measured prior to disease onset. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has now completed neuroimaging, genetics, and other biological measures on many hundreds of healthy people, people with Alzheimer's disease, and people in pre-Alzheimer's states known as early and late mild cognitive impairment. This database provides us with an opportunity to explore the effects of previously unexplored genetic interactions on several brain imaging measures. We will not only do this on established brain imaging measures of risk, but also on newer measures that our team has developed that target a part of the brain known as the medial temporal lobe, where the genes we are interested in have known effects on brain structure. If we can show that genes interact to impact brain structure in a way that is over and above that of any one gene alone, we can better predict who will develop Alzheimer's disease. Also, we can develop new treatments targeted toward those specific genetic risk pathways.
Competitiondate
201310
Approvedterm2
2 yrs 0 mth
Pinamesdelim
Voineskos, Aristotle N
Approvedterm
2 ans 0 mois
Cihrcontribution2
~ $100,000~ $0~