Principal Investigator: Dr Angela Hodges
Institution: King's College London
Professor David Collier – Eli Lilly and Company Ltd
Dr Michelle Lupton – QIMR Berghofer Medical Research Institute (Australia)Tags: 19170, Alzheimer's Disease, Dementia, genetics, inflammation, Risk
Damage can accumulate in the brain as we age causing brain immune cells to overreact and increase the risk of developing dementia. By modulating how brain immune cells respond to damage we hope to develop a treatment for Alzheimer’s disease. Certain genetic factors may influence brain immune cell behaviour. We can study these to help find a treatment. We would like to analyse the genetic data collected in UK Biobank to identify relevant inflammatory genes or combinations of genes associated with cognition which we can use to conduct further functional analyses. There are ~47 million Alzheimer’s disease patients worldwide for whom only symptomatic relief is available despite >30 years of intense efforts to find a treatment. The ambition of our research aligns with the UK Biobank purpose to improve the lives of Alzheimer’s disease patients through a better understanding of genetic risk factors contributing to disease and using this knowledge to find a treatment. Recent genetic and systems biology approaches have uncovered a new brain inflammatory pathway which presents novel and attractive targets we can focus on to develop a treatment for Alzheimer’s disease and other dementias. We will assess the association between rare and common genetic variants in inflammatory genes with measures of cognition, health outcome and brain structure. We will analyse genes individually and genes collectively where we predict combinations of small incremental genetic effects may contribute to dementia risk. We will analyse genes which function together in pathways in brain immune cells, immune genes previously implicated in neurodegenerative disease(s) and new combinations of genes we find are associated with lower cognition and higher brain atrophy. We would like access to data from the full cohort including genetic (500,000 participants) and where available, associated MRI and cognitive data. This will allow us to analyse data from individuals with rare (~1% frequency) polymorphisms in inflammatory genes of interest with greater power than has ever been possible before.