Data integration to understand cognitive decline

Principal Investigators:  JF DEMONET & O ROUAUD & B DRAGANSKI

 

Overview:

Given the ascent in disease prevention and medical care, the number of individuals living into old age increases, with the consequence of proportional rise in elderly people with dementia. Clinical research using biochemical and brain imaging markers sheds light on the patho-physiological processes in advanced stages of dementia. However, our knowledge about the multi-directional interactions between cardio-vascular risk factors, physical activity and brain anatomy/neural activity that explain individuals’ cognitive performance in old age is still scarce.

Our research addresses in a systematic way unanswered questions about the impact of modifiable lifestyle factors on cognitive health in a large cohort (n≈1600, age-range: 45-90 years old) drawn from the general population (CoLaus|PsyCoLaus cohort). The main focus here is on cardio-vascular risk factors and physical activity, whilst adjusting for the impact of education and socio-economic status. Using the already acquired large-scale multi-domain neuroimaging and lifestyle data we will create predictive, i.e. causal models that will capture main effects and interactions between the factors of interest and explain the extent of inter-subject variability. We will then evaluate the validity of these models as biomarkers for cognitive performance in old age by assessing their ability to predict individual cognitive outcome within the time-scale of the current project. The proposed in vivo histology approach will enable translational research projects through characterisation of age-related brain tissue property changes.

 

Research topics:

• Data-driven description of "core" phenotype features in dementia
• Methods development for differentiating vascular from neurodegeneration-induced dementia 
• Individual patient tailored prediction of clinical outcome
• Impact of chemotherapy on cognitive performance and brain anatomy

 

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Key publications:

Baratali L, Major K, Rouaud O, Draganski B. Cancer-related cognitive impairment in older adults. Rev Med Suisse. 2020 Nov 11;16(714):2172-2175.

Draganski B, Kherif F, Damian D, Demonet JF; MemoNet consortium. A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres. Curr Opin Neurol. 2019 Aug;32(4):557-563. doi: 10.1097/WCO.0000000000000721

Zufferey V, Donati A, Popp J, Meuli R, Rossier J, Frackowiak R, Draganski B, von Gunten A, Kherif F. Neuroticism, depression, and anxiety traits exacerbate the state of cognitive impairment and hippocampal vulnerability to Alzheimer's disease. Alzheimer's Dement Diagn Assess Dis Monit 2017;7:107-114

Draganski B Computer-based analysis of brain images: how close are we to clinical applications? Curr Opin Neurol. 2015 Aug;28(4):311-2

S Lorio, A Lutti, F Kherif, A Ruef, J Dukart, R Chowdhury, R.S. Frackowiak, J Ashburner, G Helms, N Weiskopf, B Draganski: Disentangling in vivo the effects of iron content and atrophy on the ageing human brain. NeuroImage 09/2014; 103., DOI:10.1016/j.neuroimage.2014.09.044

Artur Marchewka, Ferath Kherif, Gunnar Krueger, Anna Grabowska, Richard Frackowiak, Bogdan Draganski: Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease. Human Brain Mapping 05/2014;, DOI:10.1002/hbm.22297

Stanislaw Adaszewski, Juergen Dukart, Ferath Kherif, Richard Frackowiak, Bogdan Draganski: How early can we predict Alzheimer's disease using computational anatomy?. Neurobiology of Aging 12/2013; 34:2815-2826., DOI:10.1016/j.neurobiolaging.2013.06.015

Juergen Dukart, Ferath Kherif, Karsten Mueller, Stanislaw Adaszewski, Matthias L. Schroeter, Richard S. J. Frackowiak, Bogdan Draganski: Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease. PLoS Computational Biology 04/2013; 9(4):2987-., DOI:10.1371/journal.pcbi.1002987

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