Neurobiological and cognitive markers of genetic risk for mental disorders
Approved Research ID: 17044
Approval date: September 1st 2016
Lay summaryThis project aims at investigating the association between common and rare genetic variation, and brain anatomy and function. Common genetic variation refers to changes in DNA sequence that are frequent in the population, while rare genetic variation are infrequent but more penetrant. Both these genetic variations are thought to confer genetic risk for mental disorders via impacting brain development, anatomically and functionally; however, what that impact represent is still scarcely known. We are interested in investigating these associations in neurodevelopmental mental disorders such are schizophrenia, bipolar disorder, ADHD or Alzheimer. The results from this project should improve our ability to identify biomarkers for mental disorders, and therefore inform strategies for early detection of vulnerable populations and for identification of potential neurobiological targets for treatment development. Therefore, this project meets the UK Biobank?s purpose with regards of prevention and treatment of mental disorders. Polygenic risk scores and associated pathways will be calculated on the basis of pre-existing GWAS studies, as well as rare pathogenic CNVs identified in the sample. Anatomical grey and white matter measures will be obtained from brain anatomical images. Functional connectivity indices across different established brain networks would be calculated from resting fMRI images. Cognitive test results and appropriate demographic variables will also be considered. Regression and canonical correlational analyses will allow establishing associations between different subsets of these measures, indicating how they group and interact with relation to different mental disorders? genetic risk. We require to download the brain imaging data acquired by UK Biobank (current 5,000 participants available, plus future samples when made available). We will also require permission to access the genetic datasets already stored in our institution as part of other research projects: imputed genetic data (downloaded for project 6553, PI: Daniel Smith) and SNP intensity data (downloaded for project 14421, PI: George Kirov). We will also require a link ID document to be able to associate each participant's neuroimaging data with their imputed genetic and SNP intensity data.
- Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank
- Polygenic risk for schizophrenia and subcortical brain anatomy in the UK Biobank cohort
- Analysis of Diffusion Tensor Imaging Data From the UK Biobank Confirms Dosage Effect of 15q11.2 Copy Number Variation on White Matter and Shows Association With Cognition