Social Implications of Relatedness Methodologies in Genomics Research

The Department of Health Sciences is pleased to offer a funded studentship for October 2012 entry to its Doctor of Philosophy (PhD) programme. The studentship will pay full-time University UK/EU tuition fees for 3.5 years (with the possibility of funding for a further six months subject to performance) and include a tax-free annual maintenance grant worth at least £13,590 a year.

Research Areas and Supervision

We are offering an exciting opportunity to join a transdisciplinary team examining contemporary data use in the biosciences – the Data to Knowledge for Practice group.

Genomics is now an everyday part of modern life for many, and new methodologies are being created. In addition, many people want genetic data about themselves. The public are increasingly aware of and making personal use of DNA technologies in their clinical and healthcare applications. While testing to determine paternity has been in place for many years, people are now also using genetic services to look for answers about their ‘roots’, seeking birth or donor parents, or for their ancestors or their homeland, through genealogical tourism.

This ability to determine relatedness through genetic knowledge allows us to link ourselves to others, whether through a family, an ancestry or culture, or a community (e.g., a disease community such as cancer sufferers.) Relatedness studies are important in population and genomic sciences. Large-scale datasets from cohort studies and population biobanks are being used for a wide range of association and linkage studies to investigate genetic risk factors for common diseases. They collect data and samples from a prescribed population in order to discover characteristics inherent to that particular group of individuals and create a resource for future investigations. Researchers can identify and track deleterious gene mutations in families with affected and non-affected members but require the pedigree to confirm the link. Therefore, confirming relatedness can be important if one wishes to ensure that cases are or are not related to one another. Indeed, in seeking to find rare genes with small effects, finding relatives is vital. Statistical methodologies are the basic research tools for quantitative-trait linkage analysis and several estimate identity by descent (IBD) in genetic data.

Focus of the PhD Research

This studentship will examine uses of statistical methodologies on genetic data and their potential to impact social and cultural values surrounding relatedness. The research will explore whether the data created using new and existing statistical methodologies are considered personal data to participants and other stakeholders. The research will be bring together the disciplines of sociology, anthropology, genetics and biostatistics to study the complexities and potential implications of what may seem to statisticians as a relatively straightforward manipulation of data.

Potential Research Questions

• Are the data discovered using statistical methodologies, such as pedigree reconstruction and IBD, understood as personal or sensitive by stakeholders (participants, researchers, health professionals)? How is the data used?
• What are the social implications of these understandings for future research?
• What are the potential impacts on trust in science and/or recruitment to research? How can these impacts be managed or ameliorated?

Potential Research Aims and Methods

Interviews, (video) ethnographic observational methods and literature reviews will be employed in order to meet the following objectives:

• Determine how IBD and pedigree reconstruction methodologies are currently being or will be used, in what research projects, and to produce what kinds of data
• Examine the data collection and use of IBD and pedigree reconstruction methodologies
• Draw conclusions as to how data collected under these methodologies should be classified, how stakeholders might be engaged in making decisions about appropriate protections for research participants and make recommendations for future research

Entry Requirements

Applicants must have a first-class or high upper second-class honours degree (or equivalent qualification) in sociology, anthropology, or a related discipline that includes a grounding in sociology of science, philosophy of science, science and technology studies, or similar. The studentship forms part of a suite of work examining data use and will be adapted to the particular interests and skills of the successful candidate. Applicants must also meet the University's standard English language entry requirements.

This studentship is open to suitable UK/EU and International (i.e., outside the EU) applicants. Please note though that the award covers tuition fees at the UK/EU rate only. International applicants (and those not eligible to pay UK/EU tuition fees) must demonstrate at the time of their application that they can fund the difference in tuition fee rates.

The studentship is for full-time study only and applicants must be able to commence their studies in October 2012.

Informal Enquiries

Informal enquiries are welcomed - please contact:

• Dr Madeleine Murtagh
• mm399@le.ac.uk
• Tel. +44 (0)116 252 2926

Apply Now

To apply, simply follow our three-point checklist:

1. Draft a brief personal statement explaining why you would like to work in this area and describing any relevant research experience (including any research projects that you have undertaken - for example, as part of a previous degree - and listing any academic work you have published or which is currently in press awaiting publication). Your personal statement should be no more than 1,000 words.
2. Prepare your supporting documents - including a full Curriculum Vitae
3. Submit your online application or apply by post

The studentship will remain open until filled - however early application is encouraged.

IMPORTANT - In the Fees and Financial Support section of the application, you must state that you wish to be considered for this "PhD Studentship Health Sciences Ref. MBSP-12/01"

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