13/12/2017

PhD in Medicine: Biological dissection of phenotypic heterogeneity in HD

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  • ORGANISATION NAME
    Cardiff University
  • ORGANISATION COUNTRY
    United Kingdom
  • DEADLINE DATE
    09/02/2018
  • RESEARCH FIELD
    Natural sciences
  • CAREER STAGE
    First Stage Researcher (R1) (Up to the point of PhD)

Outline

This project aims to refine this shared susceptibility into biological processes relevant to specific symptom combinations using novel methods leveraging functional annotations. Genetic overlap between psychiatric and neurological disorders and HD symptoms will be assessed by deriving polygenic risk scores (PRS) using large publically-available GWAS (Psychiatric Genomic Consortium, IGAP) as training sets. These will be tested in approximately 6,000 HD patients from the REGISTRY database for which we have GWAS genotypes, with 4,000 further genotyped individuals expected during the course of the project.

Methods will be developed to utilise the shared genetic liability between psychiatric and neurological disorders to derive more powerful PRS, and also to deconvolute the shared genetics among these disorders into components unique to particular disorders. These will also be used to investigate whether particular biological pathways relevant to HD and/or psychiatric disorders correlate with particular HD symptoms or symptom clusters. We will develop methods to utilise functional annotations shown to be enriched for association signal to improve the power of both PRS and pathway analysis methods, and also adapt these to analyse rare variation in the exome sequences of 500 REGISTRY HD patients. The methods developed in this project will be applicable to other disorders of interest to the DRI (such as Alzheimer’s disease).

What is funded

Full UK/EU tuition fees and Doctoral stipend matching UK Research Council National Minimum

Duration

3 Years

Eligibility

You will hold or expect to achieve a First or Upper Second Class degree in a relevant area (mathematics, statistics, computing, neuroscience). As this is a training doctorate, previous research experience is not essential. However, programming ability is necessary, and some knowledge of statistics and/or genetics is desirable.