Summary for non-experts
Over the last decades, there has been tremendous progress in modern DNA technologies that has made it possible to read virtually all 3 billion letters that make up the human genome in a fast, accurate and affordable way. With this progress, we now have a much better understanding of how our genes help control states of health and disease.
Analyses of DNA from patients are very important for understanding how diseases arise and develop and play increasingly important roles in clinical decision making. Genetic material collected from consenting patients through regular clinical practice and from other volunteers are typically stored in secure biobanks together with for example the patient’s digitalized medication and treatment records. Analyzing these vast collections of biological and health data from large number of people has great potential to help us understand exactly how our genetic makeup, in combination with lifestyle choices and environmental factors can make prone or resistant to the development of certain diseases.
Non-genetic and genetic risk factors
Disease risk can be influenced by our genetic background in several ways. In some instances, such as cystic fibrosis or Huntington’s disease, the disease is explained by single mutations in known individual genes, and it is therefore easy to test for the presence of risk-conferring genetic variants.
When it comes to complex diseases, such as diabetes, cardiovascular disease, and cancers, risk prediction is much less straightforward. These disorders arise through a complicate interplay involving numerous genetic variants acting together, and under the influence of non-genetic factors, such as environmental and lifestyle factors. Every disease is also different in the relative contributions of risk by non-genetic and genetic factors. For this reason, it is important to understand how the combined effect of genetic and non-genetic factors influence the risk for developing a particular disease and build models that can accurately predict disease risk, occurrence, and progress to inform clinical decision making regarding preferred treatment.
Polygenic risk scores
It is possible to identify genomic variants associated with a particular disease for example by comparing the genomes of large number of people with and without a particular disease. If a variant is found more frequently in individuals with the disease than in individuals without the disease, the variant may contribute to or indicate an increased disease risk.
Complex diseases are polygenic, meaning that they are caused by the combined action of many – even thousands of different genes acting together. For polygenic diseases, the contribution by individual genetic variants may be only very small and therefore not useful for predicting disease risk. Rather, it is more informative to evaluate the combined contribution of all individual risk-associated genetic regions into one number predicting the genetic susceptibility to a disease – the polygenic risk score.
Because polygenic risk scores are based on genetic information set at conception, they can be utilized early in life, enable scientists to estimate risk trajectories across a lifetime, and capture risks that are independent of traditional risk factors and clinical risk scores.
INTERVENE wants to take polygenic risk scores to the next level. By applying sophisticated computational approaches to genetic information and other data types from more than 1.7 million people, our ultimate goal is to create risk scores that have increased predictive ability, are validated in clinical studies, and understandable for clinicians, patients, policy makers, and citizens. We are actively collaborating with other researchers in the field, for example by establishing a computational infrastructure to allow other scientists to continuously refine and perfect risk scores across multiple diseases for societal benefit.
INTERVENE is an international collaboration between research groups working together with the joint mission to generate improved understanding of which individuals that are at risk for developing diseases and what treatment options would be best suited for them. We have brought together leading experts from genetics, statistics, data science, machine learning, ethics, and patient advocacy groups to transform the vast collections of genetic and health data into accurate, understandable, and clinically meaningful risk scores.
We are united in our common vision to relieve the economic pressure on health-care systems, provide better treatment options tailored to the unique genetic makeup of patients, and empower persons at risk for developing a disease to proactively take measures to reduce the risk of getting sick.
INTERVENE is funded by the European Commission’s Horizon 2020 programme and will run from 2021 to the end of 2025.