PhD Study : Bioinformatics approach to identifying effective sensitising therapeutics for rheumatoid arthritis

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Summary

Rheumatoid arthritis (RA) is a chronic destructive disease of joints, which affects ~ 25 million adults in the world. RA is a painful and disabling disease and presents significant healthcare burden to society. Connectivity mapping (Lamb et al 2006) is an advanced bioinformatics technique that establishes connections among different biological states via their gene expression profiles/signatures. An important application of connectivity mapping is the identification of small molecule compounds capable of inhibiting a disease state, or more generally, altering a disease state towards a more favourable condition, for example, enabling patients to be more responsive to an otherwise ineffective treatment.

Our team has undertaken pioneering research in this area, by developing a robust framework for connectivity mapping, releasing tested tools for such high throughput tasks, and successfully applying the developed technologies to different disease areas including cancers and inflammatory diseases [Zhang & Gant 2008, 2009; McArt & Zhang2011; McArt et al 2013; Wen et al 2015, 2016; Ramsey et al 2013;Malcomson et al 2016, PNAS;Wen et al 2017].

In this project, we will apply the connectivity mapping principle to rheumatoid arthritis (RA). This project aims to develop an integrated Bioinformatics and Big Data approach to the identification of sensitising agents that can improve RA patients’ response to biological treatments, such as infliximab (IFX), tocilizumab (TCZ), or abatacept (ABT).  Successful identification of such effective sensitising agents can help to address important unmet clinical needs, and bring great benefits to patients and NHS. While primarily focusing on non-responsive rheumatoid arthritis as a target disease, the approach developed and tested is also readily applicable to other disease areas of stratified medicine.

The Aims of the research project are:

1) To identify suitable public datasets of RA patients with gene expression profiling data (eg, those deposited in public data repository GEO and/or ArrayExpress) and clinical data on their response to standard DMARDs and biological treatments (eg. IFX, TCZ, ABT).

2) Use the multi-omics data and clinical data available in the retrieved public data sets, to identify gene signatures that are characteristic of response to biologic treatments for RA.

3) To process and analyse the drug-induced gene expression data to construct reference gene expression profiles for FDA-approved drugs and experimental compounds available through the LINCS database.

4) To establish the connections between the IFX-response gene signatures generated in Aim 2 and the reference drug profiles in Aim 3, to identify candidate chemical agents, particularly FDA approved drugs, which have the desirable effects on the specific IFX-response gene signatures and therefore be able to sensitise IFX-treatments and induce remission in otherwise non-responsive RA patients.

5) To validate the predicted effects of candidate drugs on model systems of the disease.

This is an interdisciplinary bioinformatics and BigData research project; it requires an individual with good computational skills and statistical knowledge.  A good understanding of basic biological processes and some experience with basic biological lab experiments would be desirable, but training on these aspects will be provided during the course of PhD study.

Researcher will be based at C-TRIC (Altnagelvin Hospital site).

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

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
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed
  • Publications record appropriate to career stage
  • Experience of presentation of research findings
  • A comprehensive and articulate personal statement
  • Use of personal initiative as evidenced by record of work above that normally expected at career stage.
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.
  • 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

The Doctoral College at Ulster University

Key dates

Submission deadline
Friday 7 February 2020
12:00AM

Interview Date
9 to 20 March 2020

Preferred student start date
Mid September 2020

Applying

Apply Online  

Contact supervisor

Dr Shu-Dong Zhang

Other supervisors