Genome-wide polygenic scores (GPSs) are currently available from multiple commercial companies and reports can identify whether the person has an increased risk for certain diseases. A problem with these risk scores is that the databases on which they rely are proprietary and secret and thus the user cannot know how reliable the information really is.
Previous attempts to create GPSs have had only limited success, providing insufficient risk stratification for clinical utility. A recent study published in Nature Genetics
has used genotype data from the UK Biobank to see whether GPSs can predict the risk of certain diseases as well as known very high risk single gene mutations that are relatively rare in the population. An example for coronary artery disease (CAD) is familial hypercholesterolaemia which is caused by single mutations in a couple of genes involved with cholesterol metabolism.
The researchers used data about the genotypes and phenotypes of participants (n = 409,258) from the UK Biobank. The final GPS they developed identified 8% of the population as being at greater than threefold increased risk for coronary artery disease, 6.1% for atrial fibrillation, 3.5% for type 2 diabetes, 3.2% for inflammatory bowel disease, and 1.5% for breast cancer. One interesting finding was that the GPS risk for CAD had a 20-fold higher prevalence than the carrier frequency of rare monogenic mutations that confer similar risk. The GPS for CAD (GPSCAD) involved over 6 million polygenic variants. It has long been known that the currently identified risk factors for CAD such as high cholesterol, high blood pressure, diabetes, smoking and diabetes only identified a fraction of the people who would go on to develop premature CAD. Family history of premature heart disease always was a very strong risk factor, independent of these other risk factors and this is because a lot of the risk must lie within these 6 million variants.
Sekar Kathiresan, MD, director, Massachusetts General Hospital, Center for Economic Medicine, Boston, and the Broad Institute's Cardiovascular Disease Initiative, Cambridge, Massachusetts, said in a press release; "We envision polygenic risk scores as a way to identify people at high or low risk for disease, perhaps as early as birth, and then use that information to target interventions — either lifestyle modifications or treatments — to prevent disease."
Independent commentators on this study have pointed out that while it is a very important advance, it is not yet ready for clinical implementation. This is because we do not yet have any data to show that using GPSs to direct lifestyle changes or therapies will actually lead to improved outcomes for the people tested. Such studies will take many years to complete. However, we can speculate that lifestyle changes are likely to lead to better outcomes for people predicted to be at risk for CAD or diabetes by the GPS since there is already abundant evidence that this is the case for people predicted to be at risk from current risk factor models.
Another potential limitation of the study is that it is based on data from the UK biobank which is predominantly composed of people of European origin. It will have to be validated for other populations from different parts of the world.
– after this news item was written, another study was published in Annals of Clinical Genetics
critiquing the Nature Genetics study. Study author Prof. David Curtis, of the UCL Genetics Institute in London re-examined the data used in the original study for CAD risk. Prof. Curtis found that he could not reproduce the findings of the original study and also states that the equivalence in identifying a three-fold increase in risk is also flawed as the actual increase in risk for familial hypercholesterolaemia is much higher than three-fold.
Readers should watch this space to see the outcome of this debate. As pointed out at the beginning of this article, genome-wide polygenic scores are already widely available from private companies so it is important to know if they are reliable or not.