MRC Centre for Genomics and Global Health

A major obstacle to the control of infectious disease is that pathogens and disease vectors are continually evolving. Epidemic disease outbreaks are one manifestation of this process. Another consequence is the progressive shift of endemic diseases towards forms that are more difficult to control. Increasing levels of resistance to drugs, vaccines and insecticides are threatening to destabilise and in some cases to ruin international efforts to reduce the burden of morbidity and mortality caused by malaria, tuberculosis, HIV, pneumococcus and other endemic diseases.

A fundamental dilemma in controlling endemic disease is that the whole purpose is to attack an established pathogen or vector population by all means possible, including large-scale public health interventions, but this strategy may backfire by creating a new evolutionary landscape that causes more virulent or resistant forms to emerge. There are many examples of control efforts that have reduced disease burden for a short period of time but have eventually led to the emergence of resistant pathogen strains and the rebound of disease in a less controllable form.

Pathogens do not recognise geographical boundaries, so it is essential that collaborating groups around the world can efficiently build, share and analyse large and complex datasets. This presents several challenges. Systems to integrate data across labs and field study sites working on the same disease are often lacking. Moreover, clinical and epidemiological researchers may lack the tools and training needed to make use of large-scale genome variation data, while genetics and genomics experts can lack the tools and data structures needed to make use of large-scale clinical and epidemiological data.

There is an urgent need for scientists who appreciate the challenge and have the necessary skill set to tackle this challenge.
The starting point for genomic surveillance is for researchers around the world to work together to identify common forms of variation in the global population. Parasites and insect vectors have large complex genomes that require advanced sequencing technologies and analytical methods. The Centre will develop statistical and population genetic methods to solve these analytical problems.

Capacity building is needed to enable researchers in resource-poor countries to participate and to develop leadership in this effort. The Centre will help to build data-sharing networks to characterise global patterns of genome variation.

Our translational goal is to provide web based tools to help disease control programmes.to plan and monitor the progress of their interventions. This requires changes in pathogen and vector populations to be captured at high spatial resolution and in near real time. The Centre will develop tools to enable groups in the field to do research on genetic micro-epidemiology.

To maximise the value of genome variation and population genetic data it needs to be integrated with other sources of information, such as epidemiological and ecological data, in an accessible format. The Centre will develop methods for collecting data from multiple sources to construct integrated maps of the different factors that determine disease transmission and the spread of resistance.

The Centre sets out to be an international centre of excellence in the field of genomic surveillance of infectious disease and identification of effective ways to use these new technologies to improve global health.

Our approach is based on new sequencing technologies that are transforming the practice of microbiology in western countries. These technologies could potentially have a great impact on the control of parasitic, vector-borne and other endemic diseases of the developing world, but to realise this potential it is necessary to address some challenging scientific and practical problems:

[1] Parasites and insect vectors have much larger and more complex genomes than viruses and bacteria, and require more advanced sequencing technologies and analytical methods. High rates of genetic recombination and complex life-cycles create additional challenges. The Centre will develop statistical and population genetic methods to solve these analytical problems.

[2] The starting point for genomic surveillance is for researchers around the world to work together to identify common forms of variation in the global population. Capacity building is needed to enable researchers in resource-poor countries to participate and to develop leadership in this effort. The Centre will help to build data-sharing networks to characterise global patterns of genome variation.

[3] Our translational goal is to provide tools to help disease control programmes.to plan and monitor the progress of their interventions. This requires evolutionary changes in pathogen and vector populations to be captured at high spatial resolution and in near real time. The Centre will develop tools to enable groups in the field to do research on genetic micro-epidemiology.

[4] To maximise the value of genome variation and population genetic data it needs to be integrated with other sources of information, such as epidemiological and ecological data, in an accessible format. The Centre will develop methods for collecting data from multiple sources to construct integrated maps of the different factors that determine disease transmission and the spread of resistance.

The Centre aims to have broad ranging influence
Improved methods and technologies for research:
The Centre will bring together existing expertise in large-scale epidemiology, genomic medicine, bioinformatics, and computer science to create an internationally leading centre of excellence for the analysis of large, complex, data sets for research into genome science, clinical and epidemiological research and the integration of these. The work of the Centre has the potential to extend the boundaries of these individual disciplines but, the greatest impact is likely to be achieved by close collaboration and working between disparate disciplines (e.g. computer science and epidemiology to develop new analytical tools for clinical, geographical and genetic science to better conduct and understand surveillance of malaria parasite diversity). The Centre will act as a focal point for fostering collaborative engagement with both national and international partners.

New advances in science: The expertise, methods and systems developed will provide big advances in the ability to understand disease mechanisms and will yield significant benefits for areas such as infectious disease surveillance & management, and the translation of genomics into routine medical practice. We intend to make our data, methods & tools widely available for scientific researchers.

Capacity building: The Centre sees training as a key part of its remit. Clinical and epidemiological researchers may lack the tools and training needed to make use of large-scale genome variation data, while genetics and genomics experts can lack the tools and data structures needed to make use of large-scale clinical and epidemiological data. We are working to overcome these challenges by establishing community standards for data sharing, and by developing web applications and statistical methods for analysis of large genomic and epidemiological datasets. This will be achieved by collaborative working across different disciplines and training individuals to lead integrated programmes of work in this area.

The Centre is supporting an African led research initiative, the Plasmodium Diversity Network, by providing financial support, training and management guidance. The Centre will work with them of the governance, financial and programme management structure required to establish such a network as well as providing training in data analysis for specific areas of their research goals. Members of the PDN will be expected to provide support internally and in addition, provide training to local investigators at their home institutions.

While not seeking financial support for studentships the Centre benefits from the training programmes available at the University of Oxford and the Wellcome Trust Sanger Institute and will be part of the new MRC Big Data Training Academy. The academy is being established under the University of Oxford Big Data Institute and will provide an extensive portfolio of training and development opportunities suitable for scientists at all stages of their career and readily accessible to external researchers. The Centre will take advantage of these available resources to establish a framework for PhD students (supported through other mechanisms) and scientists working in relevant areas.