BACKGROUND
Many adults with major depression experience cognitive impairment even when their mood state has remitted. Cognitive impairment is a key determinant of ongoing disability, hindering return to occupational and social roles. Risk factors for cognitive impairment are poorly understood. Meta-analyses have not found clear relationships with sociodemographic or clinical variables. Efforts to model risk of cognitive impairment in depression should benefit substantially from the inclusion of genetic and neuroimaging data as well as sociodemographic, clinical and lifestyle measures. This project will use data from UK Biobank and Generation Scotland Scottish Family Health Study (GS:SFHS), both of which offer rich phenotypic data, including multimodal neuroimaging, along with genome-wide genotyping. Machine learning algorithms will be used to develop and cross-validate models in UK Biobank to predict scores on cognitive tests, and to classify participants with depression, cognitive impairment, both, or neither. Independent external validation will examine the accuracy of these models in GS:SFHS. This work will underpin future research aimed at stratifying patients with depression for targeted intervention development. The student will develop skills and experience in machine learning and bioinformatics as applied to neurosciences and mental health.
APPLICATION INSTRUCTIONS:
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit:
http://www.ed.ac.uk/usher/precision-medicine
APPLICATION ENQUIRIES:
Susan Mitchell/Maree Hardie
[Email Address Removed]
https://www.ed.ac.uk/usher/precision-medicine/app-process-eligibility-criteria