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The International HapMap project was a major international research collaboration to map the structure of common human genetic variation across populations from Europe, Asia and Africa. Mathematical Scientists from the University of Oxford played key roles in the development of statistical methods for the project, along with its overall design and management of the International HapMap Project.
Companies have used HapMap as the primary resource to design genome-wide microarrays to make novel discoveries in, for example, pharmacogenetic studies. The size of this market is estimated at $1.25 billion.
One novel discovery has led to a genetic test that is predictive of sustained viral suppression in patients treated for chronic hepatitis C. An estimated 2.7 to 3.9 million people are affected by HCV infection. This test is sold commercially by the company LabCorp and is a significant contributor to the company's testing volume. Finally, the project has been important in widening the public understanding of genetic variation.
Research carried out by the University of Southampton into the genetic causes of diseases, and the gene mapping techniques and applications derived from this research, has benefited patients worldwide through improved prediction, diagnosis and treatment for common diseases with a complex genetic basis. A particularly striking example is age-related macular degeneration which is a common cause of blindness. Commercially, the research provides cost-effective strategies for genotyping DNA samples, and marker-based selection strategies for economically relevant animal species, such as cattle. The work underpins the development of the personal genomics industry, which specialises in individual genetic risk profiling.
Age-related macular degeneration (AMD) is the most common cause of blindness in Western populations and reduces the quality of life of tens of millions of older people worldwide. In 2007 a research group at Cambridge University led by Professor John Yates in the Cambridge Institute for Medical Research discovered that a common genetic variant in the complement C3 gene was associated with an increased risk for AMD. This finding is now being used in a genetic test in North America and Europe to estimate individual risks for AMD. Those found to be at high risk are offered regular eye examinations to detect early development of the wet form of the disease before symptoms arise. This can be treated with anti-VEGF therapy. Early treatment gives the best chance of preserving sight by preventing irreversible damage to the retina.
Foal Immunodeficiency Syndrome (FIS) is an emerging fatal inherited equine disease which has caused much concern in the equine industry. Research at the University of Liverpool (UoL) into the genetic basis of this disease has identified the genetic mutation and developed a carrier test which led to equine population screening to understand the spread of this disease (>40% adult carriers in one breed, Fell ponies) and provided a tool for vets and owners to design selective breeding programmes to eradicate the disease. Since the introduction of the test in 2010, the number of cases has drastically fallen (only 1 detected in any breed in 2012) and FIS spread into other breeds is now considered most unlikely.
Research at the UCL Institute of Ophthalmology over the last 20 years has resulted in the identification of a large number of novel genes that cause inherited retinal disease. These genes have been incorporated into diagnostic tests, which have allowed molecular diagnosis, improved genetic counselling including pre-natal/pre-implantation diagnosis, better information about prognosis and have informed decisions about which diseases should be prioritised for clinical trials of novel treatments. The identification of these genes has greatly improved understanding of disease mechanisms, an essential prerequisite for developing new treatment approaches such as gene therapy.
Impact: BEAST software has widespread applications with impacts on public health policy, service provision and awareness, and in other contexts such as commercial disputes and criminal cases.
Beneficiaries: Public agencies such as health bodies and criminal courts; ultimately, global and local populations subject to infectious disease epidemic and pandemic outbreaks in which BEAST is used to inform the response.
Significance and Reach: BEAST is critical software that has been used to understand the spread of and to inform the response to global pandemics such as H1N1 swine-flu. It is also used to determine disease origin and transmission issues in specific situations (e.g. in criminal cases). The reach of this software is therefore both global and local.
Attribution: Rambaut (UoE) co-led the phylogenetic research and developed BEAST with Drummond (Auckland, NZ). The subsequent epidemic and pandemic analyses were variously led by Rambaut and Pybus (Oxford) and by Ferguson (Imperial College London).
Research at the University of Oxford into molecular evolution led to the development of BEAST, a powerful suite of computer programs for evolutionary analysis. Viral genome sequences from infected populations can be analysed to infer both viral population history and epidemiological parameters. This approach has been used to track and predict the transmission and evolution of pathogens, particularly viral infections of humans such as influenza and HIV. BEAST was used alongside traditional epidemiological methods by the World Health Organization to rapidly assess and identify the origins of the 2009 H1N1 `Swine Flu' pandemic; immediate recommendations for necessary international action followed. This approach is now widely adopted by health protection agencies and health ministries around the world and is being applied to understand viral diseases of both humans and animals.
The Cambridge-led Emerging Risk Factors Collaboration (ERFC) is a global consortium involving individual-participant data on 2.5 million participants from 130 cohort studies. The ERFC has helped optimise approaches to cardiovascular disease (CVD) risk assessment by: 1) quantifying the incremental predictive value provided by assessment of risk factors 2) evaluating the independence of associations between risk factors and CVD and 3) addressing uncertainties related to the implementation of screening. ERFC publications on lipids, lipoproteins, and inflammation biomarkers have been cited by 9 guidelines published since 2010, including those of the European Society of Cardiology and the American Heart Association.
Dr Brettschneider and collaborators proposed a conceptual framework for high-dimensional gene expression data quality assessment (QA) and developed a QA statistical toolbox tailored to short oligonucleotide microarray technology. The work has deepened understanding of sources of variation and has helped in removing noise and bias in microarray data sets. This has accelerated the invention of clinical instruments for molecular cancer diagnosis/prognosis. The toolbox has been applied widely, leading to impact through:
(A) process improvement in microarray facilities saving running costs, and standardisation of data quality targets ensuring reproducible research;
(B) individualisation of treatment decisions supported by enhanced data quality, thereby reducing healthcare costs through avoidance of unnecessary surgery and improved patient welfare.
Research into the genetic causes of Parkinson's disease by Professor Nick Wood's group at the UCL Department of Molecular Neuroscience, describing the mutations in the gene LRRK2, have led to the development of a new genetic test which is now available to patients and their families. This benefits them by providing a precise diagnosis, and an understanding of the risk of disease to relatives. The research has provided new insight into patterns of Parkinson's disease in particular ethnic groups, and given rise to improved public understanding and high profile philanthropy. This discovery has also opened up a new area of research into disease-modifying treatments in Parkinson's disease within the pharmaceutical industry, leading to new drug candidates.