A recent study by Emmi Tikkanen (Senior Data Scientist, Nightingale Health) provides new information of joint effects of genes and lifestyle on cardiovascular disease risk. In this article we look at how biobank data has played a crucial role in making this study possible.
Ask most people about their genes and the response you typically get is a mixture of curiosity and uneasy apprehension. For many, there is a genuine fear associated with finding out about their personal genetics. A prevailing and widely held misconception is that because your genes are broadly static and fixed, so is your long-term health (especially if you have an increased genetic risk for a certain type of disease). When diagnosed with a genetic predisposition that indicates an increased risk of developing heart disease for example, it’s not uncommon for patients to assume that their disease is a forgone conclusion – that they’ll develop heart disease quickly and very little can be done prevent it from progressing.
The truth however, is more complex because lifestyle factors also have a strong impact on disease risk. Emmi Tikkanen’s groundbreaking study (published in the American Heart Association journal, Circulation) has provoked discussion among public health researchers with its findings. One of the largest observational studies on fitness and heart disease to date, its results demonstrate similar benefits of exercise for people with a high genetic risk for cardiovascular disease than for those without genetic burden. Using genetic risk scoring, the investigation found consistent inverse associations between cardiovascular disease risk and exercise in all genetic risk levels, suggesting that an elevated genetic risk can potentially be compensated for by exercise. Whilst these outcomes can’t be used to make causal connections, or provide a prescribed course of exercise, they could be taken into account in future medical guidelines, especially if genetic risk scores will be incorporated into clinical practice (see: Knowles and Ashley, PLOS Med. 2018). They also have a powerful take-home message – higher levels of physical activity and fitness may lower your risk of cardiovascular events, regardless of personal genetics.
In the study, between 2006 to 2010 approximately half a million individuals aged 40-69 years old were tracked for levels of activity and fitness through self-reported questionnaires, accelerometer, grip strength measurements and fitness tests (cycle ergometry). Linking this data to electronic health records enabled researchers to study associations between these measurements and cardiovascular disease events that occurred during the 6-year follow-up. Until very recently, it would had been extremely difficult to carry out an observational study on this scale due to small sample sizes, inaccurate measurements and issues with harmonizing the data across cohorts. The use of biobank data was instrumental in overcoming these limitations as fitness and physical activity was measured in the same way for the participants involved. All the individuals in the study were from UK Biobank (a longitudinal cohort study based in the United Kingdom), which also has genetic data for most of the study participants available, enabling acquirement of genetic risk scores for coronary heart disease risk and atrial fibrillation. As very little is known about the modifying effects of exercise on cardiovascular disease risk among individuals with an increase genetic disease risk, these findings pave the way for future research that could evaluate the effects of different types of exercise on clinical cardiovascular outcomes – leading to the development of new intervention and prevention strategies.
Emmi’s work contributes towards Nightingale’s approach to solving the burden of chronic diseases. Her projects include developing effective risk screening tools, allowing for better detection of high-risk individuals. “In my previous research, I have mostly focused on genetic risk, but I think there is now a great potential to improve risk models by combining genomics and metabolomics. I think that they can provide complementary information; for example, genomics can be used for initial risk categorization and metabolomics to tract the effectiveness of lifestyle and drug interventions,” says Emmi. As the findings of this study shows, lifestyle interventions (such as exercise regimes) offer individuals an opportunity to reduce their disease risk. “Individuals can be motivated to take proactive steps to improve their health if they can track the effectiveness of interventions.” Emmi’s research involves analyzing data from international biobanks (for example, she is currently working with data from Finland’s largest National biobank, THL Biobank), to explore risk prediction and the effectiveness of interventions.
With biobank data, it is now possible to obtain high-quality health information faster and use it to make powerful clinical discoveries. In the future, biobank data will make more studies like this one possible, accelerating novel findings and the development of personalized health treatments.
Further reading on genetic risk scoring: Ripatti et al. Lancet. 2010, Tikkanen et al. Arterioscler Thromb Vasc Biol. 2013, Ganna et al. Arterioscler Thromb Vasc Biol. 2013, Abraham et al. Eur Heart J.2016, Khera et al. bioRxiv. 2017, and Inouye et al. bioRxiv. 2018.
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