PhD Study : A stratified Medicine approach to drug repurposing for Alzheimer’s disease using cohort data and gene expression connectivity mapping

Summary

Study overview:

Alzheimer’s disease (AD) is the major form of dementia, and the healthcare and economic burden is increasing with our aging population. In this study, we propose to apply stratified medicine approaches to Alzheimer’s Disease, utilising the rich data sets from Dementias Platform UK (DPUK) and an in-house Alzheimer’s disease cohort from the Northern Ireland Centre for Stratified Medicine.

The specific aims of this study include:

1) Integration of multiple categories of data from Alzheimer’s disease cohorts for identification of subgroups, and informative biomarkers for such stratification.

2) Characterization of Alzheimer’s disease in terms of clinical and molecular biomarkers, and associating subgroups with clinical outcomes.

3) Drug repurposing for the identified sub-groups of AD patients, using our established gene expression connectivity mapping framework.

Utilizing DPUK cohorts, we will conduct exploratory analysis to identify key features (genetic, environmental, lifestyle) that are most informative in differentiating AD from healthy controls, using established statistical methods and machine learning-based feature selection (e.g. univariate filter methods as well as wrapper techniques combined with a greedy search algorithm). We will then apply state-of-art machine learning methods to build predictive models for diagnostic classification. Subsequently, we will experiment with deep learning approaches, such as convolutional neural network (CNN) and recurrent neural network (RNN)). Deep learning has shown superior performance in identifying intricate structures in high-dimensional data [Lecun et al 2015 Nature 521:436].

Finally, we will apply our tested gene expression connectivity mapping technology [Zhang & Gant 2008, 2009; McArt & Zhang2011; McArt et al 2013; Wen et al 2015; Thillaiyampalam et al 2017] to computationally screen a large collection of approved drugs  [O'Reilly et al 2016] to identify their potential new use for treatment of stratified subgroup(s) of AD patients. Our team have extensive experience and expertise in applying this data intensive approach to other human diseases, with a catalogue of successes, in cancer [Ramsey et al 2013; Wen et al 2016] and cystic fibrosis [Malcomson et al 2016, PNAS]. Our innovations include a robust framework for gene expression connectivity mapping, a similarity metric ‘Zhang Score’ with superior performance [De Wolf et al 2018, PMID:29658791], and a series of computational techniques for constructing disease query gene signatures, e.g. gene signature perturbation (McArt & Zhang 2011), gene signature progression (Wen et al 2016), and related software tools including sscMap (Zhang & Gant 2009), cudaMap (McArt et al 2013) and QUADrATiC (O'Reilly et al 2016).

New combinations of these innovative elements and their novel applications to AD as a new disease area represents a big step forward in our methodological innovation and drug repurposing research. This project is data intensive and analysis focused. Access to the DPUK Alzheimer’s disease cohort dataset is required. Data access approval is already obtained from DPUK.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Sound understanding of subject area as evidenced by a comprehensive research proposal
• Clearly defined research proposal detailing background, research questions, aims and methodology

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• Completion of Masters at a level equivalent to commendation or distinction at Ulster
• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal
• Work experience relevant to the proposed project
• Publications record appropriate to career stage
• Experience of presentation of research findings
• A comprehensive and articulate personal statement
• Relevant professional qualification and/or a Degree in a Health or Health related area

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living