PhD Study : Improving the screening and diagnosis of familial hypercholesterolemia

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Summary

Background

Cardiovascular disease (CVD) is the leading cause of death globally, accounting for 17.9 million deaths globally annually1 with 3600 in Northern Ireland (NI)2. Familial Hypercholesterolaemia (FH) is a genetic disorder that elevates blood cholesterol increasing CVD risk, affecting 1 in every 250 individuals3.  Diagnosis and treatment reduce mortality 100-fold in young adults and 4-fold in older adults, yet current screening practices are ad hoc, with no systematic screening in any country and diagnostic tests that show a poor understanding of polygenic risk.  It is estimated that 70% of cases go undiagnosed and untreated.

We propose to:-

* use existing genome and proteome datasets (UK Biobank and NI Centre for Stratified Medicine - NICSM) with gene set association techniques and machine learning to identify new polygenic risk combinations.

* computationally model FH screening in the UK and Northern Ireland to identify strategies for maximising diagnosis.  At the NICSM, the supervisors SW and TSR have identified polygenic/polyproteomic risk panels for non-FH conditions with 8 invention disclosures under review.  FH cases are currently identified opportunistically with cascade screening of blood relatives.  Preliminary (unpublished) modelling of the UK population shows how random and cascade screening can combine to reduce the number of undiagnosed and untreated cases.

Aims

1) Using UK Biobank and NICSM clinical and whole exome data, and NICSM proteome data, we will calculate and validate new polygenic risk functions using machine learning methods.

2) Using census data and models of hereditary transmission, we will:-

* identify how to maximise the number of FH diagnoses made with existing screening resources

* calculate the resources needed for 100% FH diagnosis

* explore implications for national and international screening.

3) Using the NICHS-HSCNI database of FH screening results, we will:-

* evaluate the efficacy of current practices across Northern Ireland, identifying blackspots and suggesting solutions.

Supervisors

Dr Steven Watterson (SW) is a computational biologist, focussing on CVD.  Prof Huiru Zheng (HZ) is a computer scientist with interests in healthcare informatics and machine learning.  Dr Haiying Wang (HW) is a computer scientist with expertise in machine learning/bioinformatics/healthcare informatics. Dr Taranjit Singh Rai (TSR) is a laboratory biologist with interests in the pathophysiology of CVD.

Partners: Dr Maurice O’Kane (MOK) is a consultant clinical pathologist responsible for FH clinics in the Northwest of Ireland and the director of the NI clinical research network.  Dr Shane McKee (SM) is a consultant clinical geneticist in the NI Regional Genetics Service and the chief clinical information officer for the Belfast Trust.  Dr Padraig Hart (PH) is a clinical scientist in the NI Regional Genetics Service.

References

[1] WHO (2018), Noncommunicable diseases country profiles 2018, WHO.

[2] British Hearth Foundation (2018), Northern Ireland Fact Sheet.

[3] Henderson R, O’Kane M, McGilligan V, Watterson S (2016). The genetics and screening of familial hypercholesterolaemia, J Biomed Sci 23(1):39.

Campus - C-TRIC/Magee.

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.

  • Demonstrable programming skills and mathematical ability.
  • Familiarity with biomedical science is desirable, but not essential.
  • Completion of Masters at a level equivalent to commendation or distinction at Ulster is desirable, but not essential.
  • A background in biomedical science, stratified/personalised medicine, bioinformatics, biomedical engineering, computer science, mathematics, physics or another quantitative science.

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

Funding and eligibility

The University offers the following levels of support:

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

Preferred student start date
Mid September 2020

Applying

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Contact supervisor

Dr Steven Watterson

Other supervisors