Dr D Barraclough
Prof J A Gallagher
Prof L Ranganath
Applications accepted all year round
Self-Funded PhD Students Only
Alkaptonuria (AKU) is a serious autosomal recessive disease characterised by a multisystem involvement including stones (renal, prostate, gallbladder, salivary), ruptures (tendon, ligament, muscle), hearing impairment, aortic stenosis, and spondyloarthropathy. The aetiology is a monogenic deficiency of homogentisate dioxygenase, resulting in unmetabolized excessive levels of homogentisic acid (HGA), an intermediate in tyrosine catabolism. Despite being present from birth, morbidity in this mostly irreversible disease is typically delayed commencing around age 30 years. There is a lack of effective biomarkers to anticipate morbidity until it is advanced. Furthermore, as a severe osteoarthritis (OA) phenotype, developing novel biomarkers in arthritis associated with AKU may also be relevant to OA. It is also possible that new treatment targets may be revealed by novel biomarkers. There is also an effective HGA-lowering therapy called Nitisinone. Any biomarkers developed in AKU may also be useful to study the effect of Nitisinone on the disease itself.
MicroRNAs are critical molecular regulators that play important roles in the regulation of gene expression and biological functional networks. However, most microRNA studies have been carried out using cultured cells or animal model systems. Few studies have investigated microRNAs in clinical samples from patients suffering metabolic diseases. Thus, there is a need to investigate the relevance of microRNAs in clinical application.
This research aims to identify functional microRNAs associated with AKU, using advanced RNA-sequencing technology and /or PCR arrays. The identified potential biomarker microRNAs will be validated using clinical specimens to develop innovative diagnostic and therapeutic applications in the future.
The project will provide an excellent opportunity for a PhD student to pursue a career in the clinical science research area, to be trained to work closely with medical professionals to learn clinical research skills combined with basic science research skills. The project will involve the analysis of clinical samples using advanced molecular biology tools including RT-qPCR to identify differentially expressed microRNAs in AKU patients and validation of the pilot results.
The Institute of Ageing and Chronic Disease is fully committed to promoting gender equality in all activities. In recruitment we emphasize the supportive nature of the working environment and the flexible family support that the University provides. The Institute holds a silver Athena SWAN award in recognition of on-going commitment to ensuring that the Athena SWAN principles are embedded in its activities and strategic initiatives.
Applicants should have, or expect to have, a 2(i) or better in a B.Sc. (Hons) degree or equivalent in a relevant subject.
To apply please send your CV and a covering letter to [Email Address Removed] with a copy to [Email Address Removed]
There is NO funding attached to this studentship. The student will need to find their own living expenses, fees and research costs of £10,000 per year. See https://www.liverpool.ac.uk/study/postgraduate-research/fees-and-funding/
Mandourah, A.Y., Ranganath, L., Barraclough, R., Vinjamuri, S., Van’T Hof, R., Hamill, S., Czanner, G., Dera , A., Wang, D., and Barraclough, D.L. Circulating microRNAs as potential diagnostic biomarkers for osteoporosis. Scientific Reports (2018) Accepted for publication.
Milan, A.M., Hughes, A.T., Davison, A.S., Devine, J., Usher, J., Curtis, S., Khedr, M., Gallagher, J.A., Ranganath, L.R. The effect of nitisinone on homogentisic acid and tyrosine: a two-year survey of patients attending the National Alkaptonuria Centre, Liverpool. Ann Clin Biochem. 2017 May;54(3):323-330. doi: 10.1177/0004563217691065.
How good is research at University of Liverpool in Clinical Medicine?
(joint submission with Liverpool School of Tropical Medicine)
FTE Category A staff submitted: 143.50
Research output data provided by the Research Excellence Framework (REF)
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