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  Dr Maxim Freydin  No more applications being accepted  Awaiting Funding Decision/Possible External Funding

About the Project

  • Supervisors: Dr Maxim Freydin
  • Funding: China Scholarship Council (CSC)
  • Deadline: 31st January 2023

Research environment

The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services. 

Dr Maxim Freydin's group is engaged in research of genetics and genomics of complex human diseases and traits aiming to to discover underlying pathways and reveal predictive biomarkers. Current studies are based on analysis of large public datasets, such as UK Biobank (https://www.ukbiobank.ac.uk/), with application of state-of-the art approaches of statistical genetics, genetic epidemiology and bioinformatics. Among the main research interests is genetics of pain syndromes and genetics of multiomorbidity.

Training and development

Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.

Prospective student will receive training in contemporary approaches in genetic epidemiology and statistical genetics, such as genome-wide association studies, fine-mapping, co-localization, gene prioritisation, polygenic risk scores, and Mendelian randomization. Training in bioinformatics approaches concerning the analysis of global gene expression in context of complex human diseases will also be provided, as well as programming skills in bash and R.

Project description

Multimorbidity describes a phenomenon of a non-random co-existence of several diseases in a single patient. Multimorbidity significantly complicates diagnosis and treatment, is associated with increased disability and mortality, and leads to polypharmacy. Recognition of a non-random fashion of multimorbidity through the analysis of genetic component of diseases, led to the concept of diseasome, or the human disease network. The analysis of diseasome revealed shared genes underlying multimorbidity and their disease-specific functional modules. Thus, it is understood that the phenomenon of multimorbidity, at least in part, is founded on common genetic background. 

One of the most intriguing discoveries in framework of multimorbidity studies, is the presence of diseases that very rarely or never co-occur, called inverse comorbidity (IC). Examples include allergic diseases and tuberculosis, neuropsychiatric/CNS disorders and cancer, multiple sclerosis and lung diseases. Unlike co-morbidity, little is known about the genetic basis of IC, and little attention is given to the phenomenon as such in scientific literature. The importance of genetic studies of IC relies on the idea that finding the mechanisms by which the presence of one disease prevents the development of another, may pave the way for discovery of novel drug targets and improved diagnostic approaches.

This project will explore a hypothesis that genetic predisposition to one complex disease may be protective against another disease, thus leading to the phenomenon of IC. To test the hypothesis, genetic epidemiology (genetic correlations, co-localization, polygenic risk scores, Mendelian randomization) and bioinformatics (genome-wide differential gene expression analysis, pathway and network analyses) will be applied to large datasets (UK Biobank, in particular) and using publicly available transcriptomic datasets. This is an in silico project for a student with a strong interest in human and medical genetics and genetic epidemiology.

Funding

This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

Eligibility and applying

Applicants must be:

- Chinese students with a strong academic background.

- Students holding a PR Chinese passport.

- Either be resident in China at the time of application or studying overseas.

- Students with prior experience of studying overseas (including in the UK) are eligible to apply. Chinese QMUL graduates/Masters’ students are therefore eligible for the scheme.

Please refer to the CSC website for full details on eligibility and conditions on the scholarship. 

Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree [and a masters degree] in an area relevant to the project e.g. Human and Medical Genetics, Genomic Medicine, Molecular Medicine, Epidemiology. A masters degree is desirable, but not essential.

Desirable skills include solid knowledge of basic and medical genetics and at least basic knowledge in statistical analysis. Experience in programming in bash, R or python would be an advantage, but not absolutely necesserily.

Applicants from outside of the UK are required to provide evidence of their English language ability. Please see our English language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/

Informal enquiries about the project can be sent to Dr Maxim Freydin at [Email Address Removed]. Formal applications must be submitted through our online form by 31st January 2023 for consideration, including a CV, personal statement and qualifications. 

Shortlisted applicants will be invited for a formal interview by the project supervisor. Those who are successful in their application for our PhD programme will be issued with an offer letter which is conditional on securing a CSC scholarship along with academic conditions still required to meet our entry requirements.

Once applicants have obtained their offer letter from Queen Mary they should then apply to CSC for the scholarship by the advertised deadline with the support of the project supervisor.

For September 2023 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2023. 

Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme. For further information, please go to: https://www.qmul.ac.uk/scholarships/items/china-scholarship-council-scholarships.html

Apply Online


Funding Notes

This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

References

Goh, K.I., et al., The human disease network. Proc Natl Acad Sci U S A, 2007. 104(21): p. 8685-90.
Dong, G., et al., A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank. Genome Med, 2021. 13(1): p. 110.
Ibanez, K., et al., Molecular evidence for the inverse comorbidity between central nervous system disorders and cancers detected by transcriptomic meta-analyses. PLoS Genet, 2014. 10(2): p. e1004173.
Tabares-Seisdedos, R. and J.L. Rubenstein, Inverse cancer comorbidity: a serendipitous opportunity to gain insight into CNS disorders. Nat Rev Neurosci, 2013. 14(4): p. 293-304.
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