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Visiting and Honorary Professors

  • Professor Tony Bjourson (Emeritus)
  • Professor Denis Alexander
  • Professor Julie Dumonceaux
  • Professor Maurice O’Kane
  • Professor Aaron Peace
  • Professor Francois Pradat
  • Professor Lady Maeve Rea

PhD Researchers

  • Angelina Thomas Villikudathil

    Thesis Title: Machine Learning based computational method development for biomarker discovery in inflammatory diseases

    Supervisors: Dr Priyank Shukla and Professor Tony Bjourson

    The concern for better diagnostics and tailored therapies for patients with multi-morbid inflammatory disease conditions raises a major need for their stratification. By determining the molecular phenotype and developing a range of biomarkers to assess individual patients is highly crucial. The combination of multi-omics data and clinical health records from multi-morbid patients could aid in developing improved machine learning based predictive tools that can effectively stratify multi-morbid patients and more accurately predict treatment outcomes. This project focuses on identifying biomarkers using machine learning based algorithms that can stratify patients with respect to: a) inflammation and comorbidity or multi-morbidity and b) inflammatory disease sub-groups which respond to specific treatments.

  • Stephen Morgan

    Thesis title : Network Medicine to explore the role of mucle in ALS

    Supervisors : Dr William Duddy and Dr Stephanie Duguez

    Amyotrophic Lateral Sclerosis (ALS) is a progressive motor neuron disease (MND) with life expectancy at diagnosis of around 2-5 years. The team has previously identified muscle secreted microvesicles to play a potential role in ALS pathology. This project aims to employ systems biology and network medicine approaches to understand the role of muscle in ALS and other MND’s. We will use in-house and public datasets, from muscle cells and tissue, to construct networks of functional associations representing known interactions between genes, proteins and other biomolecules in ALS and other MND’s. We will identify groups of interacting genes or proteins called disease modules that are dysregulated by the pathology. The aim of identifying these disease modules is to understand the pathological role of muscle in ALS, and what molecular changes are specific to ALS.

  • Tahanver Ahmed

    Thesis title : Stratification of rheumatoid arthritis patients by immunogenicity to biologic drugs

    Supervisors : Professor Tony Bjourson, Dr David Gibson

    Biological drugs targeting tumour necrosis factor (TNF) are an invaluable treatment option for patients who are ineligible or unresponsive to traditional anti-rheumatic drugs. These drugs show an initial response in 70% of patients. However, 50% of responders become insensitive to biological therapy overtime perhaps due to development of anti-drug antibodies.
    In this project we aim to identify genotypic and pharmacokinetic biomarkers which will be used to develop a model through which patients who initially respond, but then become non-responsive may be forecast; thereby allowing selection of the most appropriate treatment option and thus improving patient care and generating healthcare savings.

  • Vanessa Milla

    Thesis title : Characterization of the metabolite content of ALS exosomes: identification of ALS biomarkers and determination of their role in physiopathology

    Supervisor : Dr Stephanie Duguez

    Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease, characterised by a severe muscle atrophy and motor neurone degeneration leading to death within 5 years after the onset. ALS is notoriously difficult to diagnose and requires exclusion of mimicking diseases. S.Duguez’s team has shown that ALS muscle cells secrete toxic vesicles that may play a role in the spreading of physiopathology. The purpose of this PhD is to (1) characterize the metabolite profiles of ALS vesicles and identify specific biomarkers, and (2) determine the role of secreted vesicles in the metabolism switch observed in ALS patients.

  • Ryan Kelsey

    Thesis title : The Effect of CFTR on islet development and signalling

    Supervisors : Prof Neville McClenaghan, Dr Catriona Kelly

    Cystic Fibrosis Related Diabetes is the largest co-morbidity associated with CF but the exact mechanism for CFRD development remains unclear. The aim of this project is to explore the potential role of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) on islet formation, function and in intracellular communication. This project is part of a CF Trust funded Strategic Research Centre comprising researchers from Ulster, Newcastle, Lund, Iowa and Hungary.

  • Boon Chin Tan

    Project title: An in vitro investigation of endo-cannabinoid receptor modulation of inflammation and pain pathways in arthritis

    Supervisors: Dr. David Gibson, Dr. Elaine Murray and Dr.Steven Watterson.

    Rheumatoid arthritis (RA) is an autoimmune disorder with multifactorial causes of chronic inflammation and pain. Current treatments for RA target inflammation and pain within joints to limit joint destruction and disability. However these medications are poorly tolerated, carry inherent risk of adverse events and frequently do not result in meaningful pain relief. In the last twenty years, research has revealed that endocannabinoid receptors can modify the inflammatory and neurotransmission activity of cells within the immune and nervous system. Phytocannabinoid compounds are thought to have anti-inflammatory, analgesic and anti-tumour effects. This project aims to investigate the mechanism of a non-psychoactive phytocannabinoid upon in vitro inflammatory and pain signalling pathways. An in silico pathway map of the endocannabinoid system effects upon the wider pathology of RA will be created and validated with in vitro data. These studies will contribute to pre-clinical knowledge of efficacy required for in human trials.

  • Owen Connolly

    Thesis title: Identification and regulation of toxic elements secreted by ALS vesicles.

    Supervisors: Dr Stephanie Duguez & Dr William Duddy

    Amyotrophic lateral sclerosis (ALS) is a fatal, adult-onset neurodegenerative disease characterised by degeneration of upper and lower motor neurons manifesting in severe muscular atrophy and respiratory failure. Work in the lab suggests that extracellular vesicles (EV) from ALS patients exert toxicity when added to healthy cells and so this project aims to: (1) regulate exosome secretion using siRNA and chemicals known to impair secretory pathways, thereby reducing the toxicity of the ALS secretome (2) regulate the production and secretion of specific EV elements that are thought to promote toxicity. This project aims to identify potential biomarkers and therapeutic targets for the diagnosis and treatment of ALS.

  • Joseph Mc Laughlin

    Thesis title: Metagenomic and culture-based characterisation of Propionibacterium acnes communities in patients with severe recalcitrant papulopustular and nodular acne.

    Supervisors : Dr Andrew McDowell, Prof Tony Bjourson

    The widespread use of topical and oral antibiotics for the treatment of acne has now led to the development of P. acnes strains that are resistant to first line antibiotic therapies. The emergence of such ‘super-bug’ strains is extremely alarming, raising the possibility that in the future patients will not respond to conventional antibiotics currently used to manage the condition. Indeed, patients with severe and recalcitrant forms of the condition due to multi-drug resistant strains are already being referred to secondary and tertiary care settings for specialised treatment. Even more worrisome is that some of these patients are also non-responsive to oral retinoids.
    Despite these serious problems, our knowledge of the aetiology of these most devastating forms of resistant acne is poor. This British Skin Foundation funded project will therefore attempt to better understand the underlying microbiology and pathophysiology of this type of acne, and develop novel antimicrobial treatments as alternates to antibiotics. This work should provide an invaluable platform for the generation of diagnostics that stratifies patients for the risk of aggressive forms of acne, and identify treatment non-responders

  • Laura Le Gall

    Thesis title : ALS signature in muscle stem cells : intercellular communication altered between muscle and nerve

    Supervisors : Dr Stephanie Duguez

    In line with other studies, S Duguez’s team have obtained data supporting that muscle involvement in ALS pathogenesis may not only be considered as a consequence of denervation but participates to the non-cell autonomous degenerative process. We have identified both a robust ALS gene expression signature and a new driver of toxicity in muscle cells and in muscle cell to motor neuron interactions in ALS patients.
    Laura Le Gall joined the team in 2015 to pursue her joint PhD between Université Pierre & Marie Curie P6 Thesis title : Sorbonne Universitées and Ulster University. She will explore this novel muscle component to ALS pathology. The purpose of her PhD is to (1) characterize the composition of secreted muscle vesicles (mRNA, microRNA, protein and metabolite content); (2) in collaboration with Cedric Raoul’s (INSERM, Montpellier, France) and Cecile Martinat’s (I-Stem, Evry, France) teams determine the effect of muscle vesicles on neurons; and (3) identify the toxic transcripts and proteins secreted through the vesicles.

  • Rebecca Kennedy

    Thesis title : Stratification in Alzheimers Disease

    Supervisors : Dr Paula McClean

    The project will focus on stratification of Alzheimer’s disease patients with respect to age of onset, rate of progression, presence of challenging behaviours and sleep disturbance and response to currently available therapeutics.

  • Ciara Devlin
  • Ekene Anakar

    Thesis Title: The role of exosomes in vivo in Amyotrophic Lateral Sclerosis (ALS).

    Supervisors: Dr Stephanie Duguez and Dr William Duddy

    This project will improve understanding of ALS pathophysiology and open new routes

    toward therapies. Studies in animal models and ALS patients show that motor neuron degeneration starts at the neuromuscular junction and that post-synaptic muscle changes may play an active role. This axonopathy could be due to the secretion of toxic elements from the muscle. In our lab, we have already shown that ALS muscle cells release toxic exosomes.

    The purpose of the current project will be to track ALS exosomes as well as explore their in vivo capacity to be transmitted to motor neurons.

  • Boodhayan Prasad
  • Wikatoria Ratajczak
  • Caitlain Devine

    Thesis title: Big Data Analytics for Early Diagnosis of Major Depressive Disorder

    Supervisors: Dr Elaine Murray, Professor Martin McGinnity, Professor Tony Bjourson

    In the UK, depression is predominantly diagnosed in primary care by general practitioners (GP’s), but diagnosis and treatment selection is largely subjective, and reliant on patient self-report and clinical judgment and experience. DSM-IV guidelines maintain that 5 out of 9 specific symptoms must be present for a minimum of two weeks, for a diagnosis of depression. Despite these standard guidelines, diagnosis and subsequent determination of episode severity is complex and variable. Based on DSM criteria there are over 200 possible ways to meet the criteria of symptoms of depression, and very little information to inform the best choice of treatment. Moderate to severe depression is predominantly treated with antidepressants, but this treatment is far from straightforward. Over 20 antidepressant medications are approved for clinical use and there is currently no empirical evidence to support treatment selection. 
    There are currently no validated biological markers for depression or response to treatment with antidepressant medications, but a number of candidate biomarkers have emerged. Development of a novel biomarker panel that could be integrated with clinical, physiological, behavioural, and environmental data to develop a decision tool which would allow clinicians to effectively diagnose and stratify patients with depression to determine the most appropriate medication for each individual would shorten the duration of untreated depression, help maintain compliance and ensure better treatment outcomes.My project focuses on the development of big data autonomous learning, computational intelligence techniques for major depressive disorder, combining the expertise in intelligent systems of the ISRC and the mental health and stratified medicine expertise of NI Centre for Stratified Medicine.

  • Kyrsti Bohnam-Noyle
  • Christina Vasipoulou

Past PhD Researchers

  • Fiona Manderson Koivula

    Thesis title : The Role of the Endocrine Pancreas in the Development of CF-related Diabetes

    Supervisors : Dr Catriona Kelly, Prof Neville McClenaghan

    This project focuses on Cystic Fibrosis-related Diabetes, and specifically the structural and functional effects of the mutant CF-causing gene (CFTR) on the endocrine pancreas. Using stable cell lines and primary tissue, we aim to elucidate the mechanisms behind impaired glucose homeostasis and insulin secretion in CF, which we hope will identify better treatment leading to a better quality of life for CF patients.

  • Philip Egan

    Thesis title : Towards Individualisation of Combination Chemotherapy in Myeloma

    Supervisors : Dr Caroline Conway, Prof Tony Bjourson

    Multiple myeloma is an incurable cancer although several drug treatments are available that can significantly prolong life. Relapse is inevitable when the tumour develops drug resistance after a variable length of time. Genetic and cytokine markers may allow more accurate prediction of the time taken to relapse, allowing treatment to be better tailored to the individual

  • Declan McGuigan

    Thesis title : Predicting Response to Treatment in Type 2 Diabetes

    Supervisors : Dr Catriona Kelly, Dr Paula McClean

    Type 2 diabetes is a chronic disease for which there are numerous treatments available. However, it is common to see a variation in how individuals respond to these. The focus of this project is the response to, and adverse events associated with, sulphonylurea treatment. Sulphonylureas are a common first line treatment option, and their use has been associated with an increased risk of cardiac disease.

  • Eliza Yankova

    Thesis title : Towards a Personalised Medicine Strategy to Reduce Prostate Cancer Risk in Men

    Supervisors : Dr Andrew McDowell, Dr David Gibson

    Understanding the role of the anaerobic bacterium Propionibacterium acnes in the aetiology of prostate cancer, with an emphasis on the identification of novel biomarkers of infection.

  • Andrew Parton

    Thesis title : The dynamics of cholesterol metabolism and atherosclerosis across population subgroups

    Supervisor(s) : Dr Steven Watterson, Dr Victoria McGilligan

    The project involves the creation of a mathematical model of atherosclerosis, then using online data sources, bioinformatics tools and statistical analysis techniques to study how the dynamics of this pathway model change based upon publicly available genomic data.

  • Amanda Eakin

    Thesis title : Discovery of biomarkers of DMARD response in early stage rheumatoid arthritis

    Supervisor: Prof Tony Bjourson, Dr David Gibson

    The project focuses on identifying genetic alterations on the Glucagon-like peptide-1 receptor (GLP-1R) with the aim of identifying sequences of nucleotides indicative of either a responder or non-responder to GLP-1 analogue treatment or an individual that may experience adverse events such as nausea or vomiting. These will be further assessed by validating associated protein and genetic markers linked to weightless and improved glycaemic control.

  • Andrew English

    Thesis title : Biomarkers for stratification of responders and non responders to GLP-1 analogues in Type 2 diabetes

    Supervisors : Dr Paula McClean, Dr Catriona Kelly

    The project focuses on identifying genetic alterations on the Glucagon-like peptide-1 receptor (GLP-1R) with the aim of identifying sequences of nucleotides indicative of either a responder or non-responder to GLP-1 analogue treatment or an individual that may experience adverse events such as nausea or vomiting. These will be further assessed by validating associated protein and genetic markers linked to weightless and improved glycaemic control.

  • Michael Jones

    Thesis title : Developing an Integrated Approach to Identifying and Validating Candidate Therapeutic Compounds for Triple Negative Breast Cancer

    Supervisors : Professor Tony Bjourson and Dr Shu-Dong Zhang

    The project aims to develop an integrated approach to the identification and subsequent validation of candidate drugs with potential anti-cancer properties. Triple negative breast cancer will be the primary disease to test out this novel approach. Once developed, the process can be similarly applied to other diseases.

  • Melody El Chemaly

    Thesis title : Biomarkers in cardiovascular disease

    Supervisors : Dr Victoria McGilligan, Dr Aaron Peace

    Cardiovascular disease is the leading cause of mortality and morbidity worldwide. Cardiac biomarkers need to be developed in order to predict and prevent the occurrence of major adverse cardiovascular events. We are in the process of investigating potential inflammatory markers involved in endothelial dysfunction and platelet activation. The ultimate goal is to use those markers to better stratify patients at high risk of developing a cardiovascular event and give them the recommended treatment as early as possible.

  • Coral Lapsley

    Thesis title : Stratified Medicine in Health: Can immune status be used to predict response to antidepressant treatment?

    Supervisors : Dr Elaine Murray, Prof Tony Bjourson

    The development of a biomarker panel to predict antidepressant treatment response in patients with depression. Coral is investigating the potential of biological markers at protein, epigenetic and genetic level, and the overall aim is to be able to stratify patients with depression into responders and non-responders to first line antidepressant strategies.
    Successful biomarkers, integrated with clinical information, could greatly reduce the time for patients with depression to receive effective treatment.