Skip to navigation Skip to main content Skip to footer

Approved research

Identifying traits associated with parkinsonism and dementia hits from genome-wide association studies

Principal Investigator: Dr Jose Bras
Approved Research ID: 11036
Approval date: July 1st 2017

Lay summary

Our understanding of the genetic architecture of neurological disease has seen significant advances over the last decade. Although we now know that many genetic loci are involved in modulating risk for these disease, the way in which they exert their effect is far from understood. We are requesting access to the full UK Biobank genotype and trait information that will allow us to gain a better understanding of the effects of genetic variability associated with disease on common traits. We will use data from GWAS recently published on Parkinson?s, Dementia with Lewy Bodies, Multiple System Atrophy and Frontotemporal Dementia. This research fits perfectly with UK Biobank?s purpose since it aims to identify associations between genetic variability and traits of medical relevance. This is work that would not be possible without the fantastic resource that Biobank represents, integrating genetic, biomarker, common traits, etc. It is plausible that this work will uncover novel biomarkers for these neurological diseases, something that is much needed. We will use standard data analysis techniques to test for association between genetic markers known to be involved in these neurological diseases and common traits measured as part of Biobank. We will test polygenic scores from these diseases in Biobank and correlate this with the same traits and phenotypes. Full cohort.

Scope extension:

Our understanding of the genetic architecture of neurological disease has seen significant advances over the last decade. Although we now know that many genetic loci are involved in modulating risk for these diseases, the way in which they exert their effect is far from understood. We are requesting access to the full UK Biobank genotype and trait information that will allow us to gain a better understanding of the effects of genetic variability associated with disease on common traits. We will use data from GWAS recently published on Parkinson's, Dementia with Lewy Bodies, Multiple System Atrophy and Frontotemporal Dementia.

We are interested in determining the role of copy number variability overall, but particularly in genes known to be involved in neurodegenerative diseases in UK Biobank traits. We know CNVs play a role in rare forms of neurodegeneration, but they have not been tested in large cohorts of these diseases. We would like to make use of the UKBB genotyping as well as WGS data to identify CNVs and correlate these with reported traits.