Approved research

Cortical genotype-phenotype influences on inter-individual variability in neurodegeneration

Lay summary

The causes of variability between individuals in brain function and disease are complex. Some of the differences may be due to differences in brain anatomy, for example the structure of someone?s brain may predispose them to more severe symptoms through disease related damage. Parkinson?s disease is a common condition well suited to study this question. We aim to: A) Understand whether genes associated with higher risk of PD modify the structure of the brain in healthy individuals. B) Whether structural brain changes, which we have previously characterised in PD and pre-clinical dementia, have any genetic associations. These questions are designed to provide new insights into the interaction between genes, environment and brain structure. The objective driving these questions is to develop ways of improving precision medicine. By understanding how these factors alter the structure of the brain in the normal population, this project will contribute to ongoing work into detecting pre-clinical disease and predicting how these conditions will progress in individuals. This work will also identify and quantify individuals ?at risk? of Parkinson?s disease, and we have local institutional support to follow these up and later assess the longitudinal health care outcomes. Using structural MRI, genetic, demographic and cognitive data acquired for 100,000 healthy individuals: Question 1: All individuals who have common genetic variants associated with an increased risk of either developing PD, or progressing more quickly once it has manifested, will be identified. Using these subgroups, differences in brain structure and physical characteristics will be identified. If there are significant differences in brain structure, these measures will be used to try and identify related genes. Question 2: The similarity between healthy and diseased brains will be quantified, and used to measure differences between groups, and to search for genetic associations. This work will focus on individuals with no pre-existing neurological disease. We have requested the maximum available MRI dataset to provide sufficient frequencies of the outcomes of interest (see below) Using the full dataset will allow the MRI derived metrics to be used in genome wide association analyses using pathological patterns of disease. This latter objective will identify other genetic variants that modulate anatomical structures involved in disease and may therefore contribute to the observed pathological variability.