The Embryo Health Score Test (EHS) is designed to reduce disease risks by helping clinicians and patients to identify the embryo in an IVF cycle with the lowest genetic disease risks. It estimates many individual disease risks – such at diabetes, cardiovascular diseases and various cancers – and combines them into a single health score. In the calculator above, you can explore average disease specific risk reductions that have been measured using the EHS on real-life health data.

There are many details underlying these scientific results, which are all relevant in understanding how to accurately interpret the information. The most important points are summarized below, while the full descriptions are available in the public scientific articles.

For your individual case, we recommend that you contact us to learn more how the EHS can help you.

Explanation of the benefits of EHS

The EHS is a unique test developed by LifeView™ and assesses the impact from many diseases at once. It is the first and only preimplantation test to accomplish this. It estimates the genetic risk for multiple individual diseases – including common and impactful diseases such as cardiovascular diseases, diabetes I & II, certain cancers and schizophrenia – and combines them into a single score. Each disease has a different impact on the EHS, depending on the severity and incidence of the disease. The end result is a single score that proportionally takes all disease risks into account.

EHS assesses genetic risk but does not address environmental factors that further impact overall disease risk. Therefore this is a screening tool and not a diagnostic test, that is, this test provides risk estimates. However, by using the EHS to compare genetic risks across a cohort of embryos derived from the same sperm and egg source, the EHS can identify which embryo has a lower risk. The score thus provides an objective priority order for transfer, based on all the screened disease risk, without disqualifying any embryo.

Relative Risk Reduction – how to measure the EHS benefit

A way to measure the benefit of the EHS is to study the disease risk when using the EHS and compare it relative to the disease risk when the EHS is not being used, that is when the embryo is selected at random. This measure is called Relative Risk Reduction, or RRR for short. The RRR for different diseases is what is shown in the Risk Reduction Calculator above and can be as high as 40% for multiple diseases when selecting from 5 embryos. This means that the risk of developing the disease is 40% lower when selecting an embryo based on the EHS compared to choosing the embryo at random. Reducing the risk for a single disease may be even higher, depending on the disease.

The relative risk reduction varies based on the specific condition being screened, ancestry and also on the number of tested embryos. Due to the natural genetic variation, the more embryos you have, the more likely it is that one has low risk. So the benefit of EHS is greater the more embryos there are to choose from. However, even when choosing the best EHS out of two embryos there are significant benefits, as has been shown by studying 20,000 pairs of adult siblings.

It is also important to remember that the presented numbers are statistical summaries based on the general population. The risk reduction one can expect in an individual case may be different, especially in the presence of family history. Depending on how heritable the disease is, a family history may substantially change the expected risks. This typically means that the absolute risk reductions are larger for families with disease history and that such individuals therefore may benefit even more from using the EHS.

Results are based on real health records and genetic data

The presented risk reductions come from testing the EHS on DNA from over 40,000 adults late in life. Similar to embryos in an IVF setting, the studies grouped several individuals together and selected the one who was predicted by the EHS to be the healthiest.

The results were then compared with comprehensive health records for all the research participants. The selected individuals had significantly fewer diseases throughout their lives than the others, and it is this data that is shown in the calculator above.

The calculator related research used a subset of the UK Biobank of unrelated British individuals of European descent. Below, we further highlight some important aspects of how these results apply but also differ from embryo selection in the IVF setting. For the full analysis, including the statistical uncertainties, we refer to this study. Note that the data presented here has been updated since the publication of the paper but the method is the same. Further validations have also been done in other biobanks, such as the U.S.-based All of Us and eMERGE (see list of publications).

The EHS has also been validated on sibling data

The results in the calculator above are based on grouping unrelated individuals. This is because there are no large biobanks available that have thousands of families with many siblings late in life. While desirable, an “apples to apples” comparison using data for large sibling groups with comprehensive health records is simply not possible to do with current datasets. However, the EHS has been tested directly on about 20,000 sibling pairs with validated benefit. This directly proves that the EHS works for sibling embryos and with significant benefit already when there are two embryos to choose from.

The fact that the risk variation is smaller among siblings than between unrelated individuals means that one can expect somewhat smaller risk reductions in an IVF setting than illustrated in the calculator above. Importantly though, it has been scientifically demonstrated that there is a lot of variation of genetic disease risk among siblings – about 70% of the variation in the general population – so the data above is still a good indicator of what can be expected.

The role of ancestry

Genetic patterns vary depending on genetic ancestry and this also impacts the prediction of genetic disease risk. The data above is based on individuals of European descent and both the number of available diseases as well as the achieved risk reductions are different – typically lower – for other ancestries. This inequity is an unfortunate consequence of history: the development of the underlying technology of the EHS (polygenic risk prediction) is critically dependent on large amounts of data and the vast majority of participants of such large genetic biobanks has historically been of European ancestry. This is something we and the entire scientific community are working hard to rectify and we are constantly pushing the limits of the technology making it better and more equitable as more diverse biobanks are coming available.