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The Genomics Policy Unit (GPU) has led on research into genetics and health since 1996, and has made a significant contribution to this field at both a national and international level. As one of the first Research Units in the UK to focus on the preparedness of the public and healthcare professionals for the `new genetics', we recognised how genetic advances would radically alter how we understand health and disease. The impact of our research has been to show audiences who would not typically engage with genetics, what new opportunities are being offered to improve human health and the social and ethical issues that surround these.
The GPU was an early pioneer of new, interactive research methods, such as Citizens' Juries, to help ordinary people make their views known to policy makers. By 2003 we were engaging nurses and midwives with genetics by supporting them in developing competent practice, setting a benchmark that has influenced competency development programmes for nurses in the UK, Europe and the US. This is important because advances in genetics mean it is moving out of its specialist sphere into wider clinical practice and broader society. This case study describes the two strands of our work — professional and public engagement — and illustrates the significant impact that exposure to genetics has had on ordinary members of the public when they are given the opportunity to acquire genetic literacy and on the nursing profession by contributing to policy and education in this field.
Impact: Economic: Genomic selection has revolutionised, and is now standard practice, in the major dairy cattle, pig and chicken breeding programmes, worldwide and provides multiple quantifiable benefits to breeders, producers, consumers and animals.
Significance: Increased food production world-wide
Beneficiaries: Breeding companies, primary producers, consumers, livestock.
Attribution: Work led by Haley and Woolliams (Roslin Institute now part of UoE).
Reach: Methodologies applied worldwide in livestock improvement, and more recently applied in human genetics and plant breeding.
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.
Cytomegalovirus (CMV) causes life-threatening disease, particularly in immunocompromised individuals. CMV antivirals are toxic and before 2010 there was no standard for quantifying patients' viral load to enable precise use of these drugs. Research at Cardiff University led to the isolation and characterisation of wild-type CMV strain Merlin. The strain was recognised by the WHO in 2010 as the best source of the CMV genome and adopted as the international prototype strain and PCR standard. All major pharmaceutical companies offering CMV testing swiftly recalibrated their kits, and now market the assays as standardised against the strain. As a consequence, the Standard is improving clinical CMV disease definition and regulation of antiviral therapy, aiding the management of toxicity and resistance worldwide.
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.
The wheat-breeding industry, including some of the largest plant breeders and seed-development companies in the world, has benefited from decreased production costs and increased productivity as a result of research led by the University of Bristol and carried out between 2009 and 2011. The Bristol researchers developed the tools necessary to differentiate point mutations in the complex DNA structure of wheat. This was a critical step in wheat genotyping and led to the public release of 95% of the wheat genome in 2010 and the development, by Bristol, of a cheap, easy-to-use assay for industry. These advances were quickly embraced by industrial wheat breeders aiming to deliver new varieties of wheat with improved yields and desirable traits such as disease resistance. Limagrain, the world's fifth-largest producer of field seeds (including wheat) with €595 million in sales of seeds, realised a ten-fold reduction in costs and a ten-fold increase in throughputs in their breeding laboratory. With the wheat-seed business worth over £16 million annually in the UK and over £1.8 billion globally, the new genotyping tools generated by Bristol have had, and continue to have, a major impact on the wheat industry and its ability to respond to the challenges of climate change and population growth.
In genetic studies of human disease it is now routine for studies to collect genetic data on thousands of individuals with and without a particular disease. However, the genetic data collected is incomplete, with many millions of sites of the genome unmeasured. The novel methods and software (IMPUTE) developed by researchers at the University of Oxford predict unobserved genetic data using reference datasets.
IMPUTE has been adopted by the company Affymetrix in the design of custom genotyping chips. Affymetrix recently won the tenders by the UK Biobank and UKBiLEVE studies to genotype >500,000 participants, with a total study cost of ~£25M. The company states that IMPUTE gave their project bid a significant competitive advantage. Affymetrix also purchased the IMPUTE source code for £250,000. In addition, Roche Pharmaceuticals have used the software in their research on the genetic basis of drug response. The use of imputation has saved Roche ~$1,000,000.
Automation of genomic data analysis has become essential. High-throughput sequencing technologies are producing data faster than can be managed and interpreted, meaning that much biomedical information remains unused.
Research led by Attwood introduced a unique method for protein sequence characterisation and a derived database of diagnostic protein signatures (PRINTS). This led directly to the development of a new database (InterPro), now routinely used to annotate the world's largest protein sequence archive (UniProt), and complete genomes and metagenomes. The databases and their search tools have been exploited in the private sector (including SMEs and multi-national pharmaceutical and agrichemical companies), generating workflows that have yielded candidate drug targets and provided insights into disease mechanisms.
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.
A health informatics platform supporting chronic disease management nationally and internationally creating impact upon: