IP : Genomics plc - Genomics plc analysis demonstrates potential for genomic data to identify those most at risk for 16 common diseases

Genetic 'risk scores' for diseases including heart disease, breast cancer, prostate cancer, and type 2 diabetes, could save lives and save money for the NHS by enabling more effective disease prevention and screening

Following today's comments by the Rt Hon Matt Hancock MP, Secretary of State for Health and Social Care, about the potential of genomic data to improve disease management in the National Health Service, Genomics plc, the data science company specialising in analysis of human genetic information, announces its development of predictive tests, or 'polygenic risk scores', for 16 serious common diseases.

Polygenic risk scores combine information from large numbers of genetic variants to assess how people's genetic make-up affects risk of developing various diseases Diseases covered include: breast cancer, chronic obstructive pulmonary disease, coronary artery disease, obesity, prostate cancer and type 2 diabetes.

Polygenic risk scores can encourage people to make lifestyle changes to mitigate their elevated risk of certain diseases and improve early detection by helping health systems target screening at the most high-risk segments of the population.

This more proactive approach to disease management and prevention can save lives and money by making the NHS and other health systems more efficient and effective.

The genetic variants needed to calculate all the polygenic risk scores can be measured for about £20-£40 per person, much lower than the £500-£1,000 cost of whole genome sequencing.

Professor Peter Donnelly FRS, Founder and CEO, Genomics plc, said: 'Genomic data and analysis has the potential to transform healthcare by identifying people most at risk of certain diseases, allowing for targeted prevention measures and earlier detection and treatment.

'Through the 100,000 Genomes Project, the NHS has led the world in use of genetics for rare diseases and cancer. The next step is to harness the power of genomic analysis, through the use of polygenic risk scores, to more effectively manage common diseases. Doing so can save lives and money by making health systems more proactive and efficient.'

The idea behind polygenic risk scores is to combine information from large numbers (hundreds to millions) of genetic variants carried by a person. Each individual variant typically has only a small effect on a person's risk of developing common diseases. But the impact on risk can become significant when those many small effects are aggregated.

Using its powerful data analytics capabilities, Genomics plc has identified different sets of variants which are correlated with risk of developing 16 common serious diseases.

From this analysis, polygenic risk scores can be calculated to identify individuals whose DNA puts them most at risk of conditions including coronary artery disease, breast cancer, prostate cancer, and type 2 diabetes. The company leveraged published studies in millions of individuals to build the scores and has validated its polygenic risk scores by tracking the health outcomes of people whose genomes have been analysed as part of the UK Biobank resource. The genetic and health information in the Biobank allows the company to measure how much more or less likely certain groups of individuals are to develop each of the diseases, and at what ages, based on their DNA.

In coronary artery disease, for example, polygenic risk scores identify a subset of men whose DNA variants mean that they are likely to develop the disease on average 10 years earlier than normal.

While it has long been known that women who carry rare variants in the BRCA genes are at substantially increased risk for breast cancer, the analysis shows that it is also possible to identify groups of women whose risk of breast cancer differs significantly on the basis of many other genetic variants. Based only on these non-BRCA genes, the 3% of women most prone to breast cancer have the same level of risk when they are 45 as a typical woman who is 55, whereas the 3% at lowest risk won't reach the same level of risk until they are 75. Currently in the NHS, breast cancer screening is based solely on age, with all women being offered screening when they turn 50. The use of polygenic risk scores could allow earlier screening of those most at risk.

Although other academic and commercial groups have reported polygenic risk scores for individual diseases, today's announcement of scores for 16 different common diseases, with ongoing work in many other conditions, marks a step change in the applicability of the approach.

The genetic data required to calculate all the polygenic risk scores is much cheaper to obtain than the whole-genome sequencing approaches currently used in the NHS for rare diseases and cancer. While whole genome sequencing currently costs £500-£1,000 per person, the genotyping chips used for polygenic risk scores only cost £20-40 per person.

Dr Vincent Plagnol, Head of Precision Health at Genomics plc, said: 'For most of us there will be one or two diseases where we are at considerably higher risk based on our DNA, but the diseases will be different for each of us. Being able to calculate polygenic risk scores for many diseases enables us to identify those high-risk diseases for each individual, giving them and their doctors a head-start to reduce the risk.

'While genetics is an important part of disease risk, it is critical to remember that, whatever we inherit, we can move that risk up or down a lot through our lifestyle choices and in some cases through medical interventions.'

Professor Sir John Bell, Regius Professor of Medicine, University of Oxford, and leader of the government's life sciences industrial strategy said: 'In December 2018 the government announced the Accelerating Detection of Disease programme as part of its life sciences sector deal to harness the use of artificial intelligence (AI) to support research, early diagnosis, prevention and treatment across the major diseases. The data released today by Genomics plc clearly demonstrates the potential of approaches such as the use of polygenic risk scores to help catch diseases early or even prevent them altogether.'

Genomics plc has developed the largest database of its kind in the world, linking genetic variants at 14 million positions in our DNA to over 10,000 measurements on people, including disease outcomes, biomarkers, and molecular and cellular traits. The company uses sophisticated statistical and machine learning tools to interrogate the data to learn about the connections between genetics and disease. Genomics plc uses this approach in precision health, through polygenic risk scores, and in drug discovery, to identify new drug targets and to assess the likely efficacy and safety of novel medicines.

About Genomic plc

Genomics plc is a leading genome analysis company formed in 2014 by four leading scientists at the University of Oxford, including Professors Peter Donnelly (then Director of the Wellcome Centre for Human Genetics) and Gil McVean (Director of Oxford's Big Data Institute). Its vision is to use genomic insights to transform drug discovery and precision health.

By amassing and curating data from publicly available sources, Genomics plc has developed the largest engine of its kind in the world linking genetic variants to changes in thousands of measurements and disease outcomes, together with its own breakthrough machine learning algorithms that use this data at scale to learn directly about human biology.

Backed by some of the leading investors in life sciences, Genomics has an expert cross-disciplinary team of over 50 people, primarily scientists and software engineers, with offices in Oxford and Cambridge UK. For additional information about Genomics plc, please visit www.genomicsplc.com.

About Polygenic Risk Scores

More than a decade of successful large-scale human genetics studies has established that for all the common diseases there are many thousands of genetic variants which contribute to disease risk. Many of these individual risk-SNPs (single nucleotide polymorphisms) are common in the population, but each one typically only has a small effect on risk (<5%). This contrasts with many serious rare diseases where a single, rare, genetic change often has a large effect.

A key practical difference is that to identify the rare mutations which cause rare genetic diseases it is usually essential to sequence, or read, the entire genome of the individual, or the exome (the part which contains the genes). In contrast, the many common variants which affect risk of common diseases can be measured in an individual with a different, and much cheaper, technology using so-called genotyping chips which measure a pre-determined set of ~1 million of the 3 billion positions in the human genome.

For a particular disease or trait, a so-called polygenic risk score (PRS), combines information from large numbers of variants across the genome (hundreds to millions) to give a single numerical score which is an aggregate summary of an individual's propensity to develop that disease on the basis of the DNA variants they have inherited. In principle, polygenic risk scores can be constructed for many diseases - the SNPs involved, and the weightings for them, will typically differ from disease to disease. For an individual, one can thus simultaneously calculate polygenic risk scores for many diseases.

Across a large set of individuals, for a particular trait, there will be a distribution of values for the polygenic risk score. Individuals with higher values of the score will be at higher risk of developing the disease on the basis of the common genetic variants they have inherited. Depending on the disease, this information could be used by the individual to motivate lifestyle changes, by their doctors to suggest appropriate medical interventions or to help with to diagnosis, or in public health to better target screening programmes.

A critical point is that whilst most individuals will tend to have average risk for any particular disease, it is very likely that they will be at the extreme of genetic risk for something. Early identification of these risks, through the availability of genome-wide genetic information, could have a profound effect on individual and population health, and on health-related expenditure. The possibility of generating PRS for many common diseases at a population scale offers the exciting opportunity of identifying individuals in the tail of the risk distribution for a subset of diseases, and to optimise care, prevention, and screening accordingly.

The nature of genetic data means that the population the data comes from can be important. With current approaches, polygenic risk scores tend to be most accurate when they are applied to the same population as the individuals in the genetic study from which they were derived, typically those of European ancestry. A major focus at Genomics plc is to assess the methods carefully in people with ancestry from other parts of the world, and where necessary to improve the methods, and to take advantage of genetic studies underway in different ancestry groups, to produce tools that are equally effective for everyone.

Diseases for which Genomics plc has developed polygenic risk scores

• Age related macular degeneration
• Asthma
• Atrial fibrillation
• Breast cancer
• Chronic obstructive pulmonary disease
• Crohn's disease
• Coeliac disease
• Coronary artery disease
• Glaucoma
• Hypertension
• Multiple sclerosis
• Obesity
• Prostate cancer
• Systemic lupus erythematosus
• Type 2 diabetes
• Ulcerative colitis

Contact

John Colenutt (COO) at Genomics plc
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Ben Atwell and Andrew Ward at FTI Consulting
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