What prompted you to shift your research focus?

I am a physician by training, so being able to bring my findings from the laboratory to a point where they can help patients has always been important.

The genomic research field has reached the point when it’s now possible to implement our research findings in a clinical setting. Before, we had a lot of research progress, but not many actionable results. Now that clinical translation is a real possibility, it made sense to move into this field. It also fits well with the profile of FIMM, in that we focus on basic research with a strong translational aim.
 

Can you tell me about the projects you are working on?

Our focus at the moment is the GeneRISK study. My group worked with Professor Samuli Ripatti to set up the study in 2015. This involves a population cohort of around 7,300+ people from southern Finland. The cohort is unique as the participants consented to receive personal disease risk information back from the study; information that also included their genomic risk information. They also consented to have their samples added to the THL (National Institute for Health and Welfare) Biobank, and to be followed up with over the course of the next 20 years.

The returning of research findings to patients is very unusual, but we were keen to try this as we felt it is an important part of the future vision of genomic medicine. We believe individuals should be empowered and to contribute and to take responsibility for their own health and the decisions surrounding this. However, to do this, they first need the tools, knowledge, and the opportunity to participate.
 

How were you able to convert the ideas behind GeneRISK into a study?

We had been working on the idea to develop a tool to communicate genomic disease risk information and had done an initial pilot study to test a concept. We had really positive feedback from the participants, so we knew that we already had a tool we could use, and this was KardioKompassi®.

We focused on cardiovascular disease as the current disease prediction methods in this area fail to detect up to half of the individuals with high disease risk. It was, therefore, an opportunity to use genomic data, to help to predict and prevent cardiovascular disease. The study has been going for some time now, with over 7350 people involved. At the start, all participants had a baseline health check-up and were asked questions about their health, lifestyle, behaviour and eating habits. We then carried out array-based genotyping on all participants. As part of the process, they also consented to the return of disease-risk data, to having their samples added to the biobank, and to receive personal information back that detailed their disease risk.

The study was observational and we are now in the follow-up stages, with the first round of follow-ups completed in the beginning of 2019. 5000 participants responded to this request for a follow-up (around 70% of the original cohort), which we were very pleased about. 

Who took part in the study, and what did they receive?

The participants are what we would call ‘typical’ Finnish middle-aged men and women. Many are overweight, with slightly higher blood pressure and somewhat elevated cholesterol levels. Around 15-20% are smokers, which is typical for the middle-aged group. The participants all received personal information about their 10-year risk for cardiovascular disease. We based the risk estimate both on traditional risk factors and a polygenic risk score, which included 49,000 markers. Since we initiated the study, new scores have been developed that utilize the information from ~6 million genetic variants.
 

How did participants interpret their data?

The cohorts’ risk information was interpreted and communicated using an interactive web tool, which was KardioKompassi. When logging in, users are met with a front page where they can see their risk information and the health information they originally submitted, such as their age, sex, and whether they smokers or example.

The information obtained from 49,000 genetic variants is compressed into one number, i.e. a genetic risk score for ease of interpretation, with the overall ten-year risk for coronary disease risk and stroke displayed. A score with a high positive value means that there are a lot of risk-increasing alleles in the score, whereas a score that is negative means you have more protection from cardiac disease than the population average. According to the Finnish national guidelines for disease prevention a 10-year disease risk >10% is considered high, so they should talk to their doctor to have their risk reduced, or discuss how to reduce the risk. We set the scale for this according to national guidelines. 

How did the participants react to the findings?

When we called the participants back 18 months after their baseline visit, we were obviously interested in what they thought about the tool, how they perceived the information, and whether they had done anything to try to reduce their risk factors.

In terms of the initial results found at the baseline visit, 25% of participants had a high or very high risk of developing cardiovascular disease or stroke. 40% were smokers and around one third had a BMI of 30. Only 17% were on lipid-lowering therapy. So, there were certainly several things there that they could work to change to help to lower their risk, such as sustained weight loss or giving up smoking.

When they came back at 18 months, we asked them questions about their attitudes to what the study had found and we were happy that they felt they had understood the information. 20% said they received unexpected results, and 30% said the results were concerning to them. However, given that 25% were in the high-risk category, it is understandable that this number could see their results as unexpected or concerning.

Then we asked them about what they thought about their disease risk overall, for example, and whether they felt genetics were important or not. They agreed that this played a role, but they also thought they themselves could take more responsibility for their health. 
 

How did they feel if they received a high-risk score?

It would be expected that some might feel helpless or depressed if they were identified as having a high genetic risk for cardiac disease. However, pleasingly (although this could be down to Finnish pragmatism!), those that were told this seemed to be very motivated to take steps to try to do what they could to lower their risk, such as by losing weight. Almost 90% of the cohort agreed that receiving a high-risk score was motivating for them.

They also appeared very confident that clinical doctors also can use this type of genetic information. This was very interesting and might stir a reaction amongst GPs as this is not something, they are trained on how to deal with. I think in Finland though, people are very trusting of their GPs and the healthcare system in general. 
 

Did people actually manage to improve their health as a result of this first study phase?

It can definitely be said that feeling motivated and inspired is of course very different from taking action, so we were really interested in finding out how well they had accomplished their goals.

The GeneRISK cohort can be divided into two: those with elevated disease risk, and those with a lower risk. We found that sustained weight loss was seen amongst 16% in those with elevated risk. In general, the higher the risk, the more likely they were to have lost weight. Amongst the smokers, around 14-15% quit smoking. This is a great result, as the overall smoking cessation rate in the general population is around 4% annually, so this is positive. We also looked at who had sought help from a healthcare professional, and 20% of those from the high-risk group did go and seek advice from their GP. Overall, we can say 36% of those from the high-risk group took action, be it by sustained weight loss, quitting smoking or seeing their GP.
 

What can these results tell you?

We’re thrilled with the outcomes of the study so far. We were, however, interested to see what differentiates these individuals; for example, why did 36% take action, when the other 64% did not?

To examine this more closely, we divided the high-risk category into two: those who took action, and those who did not. When we compared their risk profile, we could see that it was pretty much the same. They were around the same age, with equal numbers of smokers and similar cholesterol values and BMI scores. We did, however, identify that the participants who took action to reduce their risk generally had a higher polygenic risk score.

Based on these findings, we can summarise that understanding personal risk information, in particular, if an individual is aware, they have a higher genetic risk, can inspire individuals to take action to improve their lifestyle. Using these findings, we think we can also show that elevated genomic risk, in combination with a tool for communication, is a motivation for an individual to change their lifestyle and so improve their health. 
 

What are the next steps for the study?

We’re now in the phase of writing up our findings from this initial study and aim to publish these as soon as possible.

GeneRISK as a study is still ongoing. We have completed the first follow-up round, so we need to let time pass before we can call the participants back. According to the consent we have, the initial GeneRISK findings will act as baseline data and the samples are now part of the THL Biobank so this is a resource available for research in a broader sense. 

Will KardioKompassi evolve further?

Whilst it was used as part of the GeneRISK study, KardioKompassi is a separate project. It took a lot of time to get approval from the ethics board as something like this had never been done before.

The ethics board required us to show both the risk estimated the traditional way with no genetic risk factors and then the new way of taking these risk factors into account. We had thought this might be very cumbersome and confusing for the participants but we found it wasn’t an issue at all. They liked that they could see both types of risk so that’s why we kept the traditional risk information in the app.

KardioKompassi has received a lot of interest and people have approached us who want to buy it. We have now received funding from Business Finland and have a grant to explore whether KardioKompassi can be commercialised. We have a few pilot projects ongoing for this where we have implemented or integrated KardioKompassi into electronic health records. We have a couple of collaborators in Finland, and we also have a collaborator in Estonia meaning that Estonian family doctors are using KardioKompassi to estimate the disease risk for their patients. 

What do you think KardioKompassi and GeneRISK mean for this type of genomic research in the future?

I think KardioKompassi and GeneRISK are really interesting examples of how genomic research findings can be used in practice. Cardiovascular disease is a good example as half of the disease risk in the population is down to genetic variation. It’s also a common disease and the leading cause of death in Finland and elsewhere. Furthermore, the current disease prediction methods are largely inaccurate and imprecise. Cardiovascular disease is also a good candidate for such a study as there are steps high-risk individuals can take to lower their risk.

Precise and accurate disease prediction is at the core of disease prevention, but first, you have to identify the individuals who need the attention so they can take steps to try to prevent disease.

There are many other complex disorders that have a strong genetic component, and I think this has been revealed to the extent that one could think about using a similar tool for other disorders in the future. I and other researchers at FIMM are certainly interested in expanding the concept to other disease areas.  

Learn more about KardioKompassi at www.kardiokompassi.fi

For more information about Widén´s research group, visit www.fimm.fi/en/research/groups/widen