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Using genetics to uncover clusters of commonly occurring comorbidities in patients with chronic inflammatory diseases


   Faculty of Biology, Medicine and Health

  ,  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

It is well established that people with chronic inflammatory diseases suffer from an increased risk of developing additional chronic diseases (comorbidity) which leads to a lower quality of life and early mortality. This is clearly illustrated by considering rheumatoid arthritis, as this patient group die ten years younger than the general population and approximately half of this excess mortality is due to the increased prevalence of coronary artery disease. These comorbidities occur in predictable clusters, as opposed to random independent events, suggesting shared disease pathways. These shared pathways could be defined by genetics, behavioural or environmental risk factors. Identifying these risk factors and clusters is an important research question which has the potential to lead to early diagnosis, interventions and prevention.

This project will focus on the use of genetics in large scale population studies (e.g. UK Biobank) to explore the relationship between a range of chronic inflammatory diseases and their related comorbidities. The project can be tailored to suit particular interests, for example this could involve the use of genetic data to identify genetic risk factors and shared biological pathways (pleiotropy), through the integration of genomic data, to help understand the mechanisms underlying the increased risk of comorbidities. Alternatively, a more statistically orientated project may look to develop prediction models to identify patients at high risk of developing additional disease. 

1.     Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area / subject.  Candidates with an interest in health informatics, genetics or statistics are encouraged to apply. 

2.     For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select the PhD title.

3.     For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit www.internationalphd.manchester.ac.uk


Funding Notes

Applications are invited from self-funded students. This project has a standard fee. Details of our different fee bands can be found on our website View Website
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website View Website

References

1. López-Isac, E., Smith, S. L., Marion, M. C., Wood, A., Sudman, M., Yarwood, A., Shi, C., Gaddi, V. P., Martin, P., Prahalad, S., Eyre, S., Orozco, G., Morris, A. P., Langefeld, C. D., Thompson, S. D., Thomson, W., & Bowes, J. (2020). Combined genetic analysis of juvenile idiopathic arthritis clinical subtypes identifies novel risk loci, target genes and key regulatory mechanisms. Annals of the rheumatic diseases, 80(3), 321–328.
2. Chen, J., Spracklen, C. N., Marenne, G., Varshney, A., Corbin, L. J., Luan, J., Willems, S. M., Wu, Y., Zhang, X., Horikoshi, M., Boutin, T. S., Mägi, R., Waage, J., Li-Gao, R., Chan, K., Yao, J., Anasanti, M. D., Chu, A. Y., Claringbould, A., Heikkinen, J., … Morris A. P., Barrosa I., Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) (2021). The trans-ancestral genomic architecture of glycemic traits. Nature genetics, 53(6), 840–860.

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