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Identification and modelling of causal genetic and environmental factors for HD severity and progression

Project Description

The student will model the interplay between genetic and environmental risk factors and clinical outcomes in a longitudinal cohort of 300 manifest and pre-manifest HD gene carriers.
Huntington’s disease (HD) is a progressive neurodegenerative disorder caused by expanded CAG repeats in the HTT gene. Despite having a single genetic cause, HD exhibits considerable variation in age at onset, progression and symptoms. Recently, genome-wide association studies (GWAS) have implicated genetic variants as modifiers of age at onset and progression , but the mechanisms through which they act are still largely unknown. Likewise, there have been studies reporting associations between environmental factors such as physical activity and diet to HD onset and progression. However, in order to develop effective therapies for HD, it is important to be able to model the interplay between genetic and environmental factors and their causal effects on the progression and severity of clinical symptoms.
This project will use data from the recently funded DOMINO-HD (Multi-Domain Lifestyle Targets for Improving ProgNOsis in Huntington’s Disease) study. This consists of 300 manifest and pre-manifest HD patients with genetic data and detailed clinical (motor, cognitive, behavioural) and environmental (physical activity, sleep and dietary intake) endpoints measured longitudinally over a period of 12 months. The clinical data will be used to develop informative measures of disease severity and progression using a variety of statistical techniques such as principal component analysis and hidden Markov models. The relationships between the genetic and environmental factors and the model of disease progression will be modelled using linear (e.g. canonical correlation) and non-linear machine-learning techniques, and the accuracy of the resulting predictors to predict conversion from pre-manifest to manifest HD will be investigated. Causal relationships between the genetic and environmental factors and the clinical measures of severity and progression will be tested using methods such as Mendelian randomisation. In addition to including known genetic risk factors for HD onset and progression (either individually or combined in a polygenic risk score), the genetic data will be used to discover novel genetic variants and biological pathways influencing disease progression by performing a GWAS with the measures derived in this project.

Funding Notes

Open to all UK/EU students without further restrictions
Full UK/EU tuition fees
Doctoral stipend matching UK Research Council National Minimum
Applicants should possess a minimum of an upper second class Honours degree, master's degree, or equivalent in a relevant subject.
Applicants whose first language is not English are normally expected to meet the minimum University requirements (e.g. 6.5 IELTS)
Degree in mathematics/statistics/computing or similar. Alternatively: degree in life sciences/medicine with substantial component and/or experience in quantitative methods/biostatistics.


In order to be considered you must submit a formal application via Cardiff University’s online application service. (To access the system click 'Apply Online' at the bottom of this advert)
There is a box at the top right of the page labelled ‘Apply’, please ensure you select the correct ‘Qualification’ (Doctor of Philosophy), the correct ‘Mode of Study’ (Full Time) and the correct ‘Start Date’ (October 2019). This will take you to the application portal.
Your application must include the following supporting documents in order to be eligible for shortlisting:
• A personal statement in support of your application telling us your reasons for wanting to study this specific PhD programme and why you think you're suitable. This combined should be no more than 3,000 characters (including spaces).
• Two referee letters of support. Important: Unfortunately due to the high volume of applications received we cannot request references, therefore it is the applicant’s responsibility to request and upload references to their application.
• A CV detailing education and relevant work experience.
• Academic certificates/transcripts.
• (For students whose first language is not English) Evidence of competence in both written and spoken English.

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