Ron Do, PhD, Associate Professor, Charles Bronfman Institute for Personalized Medicine at Mount Sinai, and Iain Forrest, MD-PhD candidate in Dr. Do’s lab, discuss the results of their recent study measuring the population-based penetrance of pathogens and loss of functional clinical variants.
What were the results of your study?
Forest : There were 3 main results that came out of this study that really struck us.
The first was that when we looked at the penetrance, or risk of disease, of specifically pathogenic variants – those that were considered to have a very high risk of disease – we observed that there was actually a relatively high level of penetrance low in all areas for pathogenic variants, around 7% or 6%. This was more than what we found for mild variants, which was less than 1%, but still relatively low overall.
The second main conclusion we reached is that we were able to assess a diverse set of individuals within our study. So individuals of various ancestral origins. Besides European individuals, those of African ancestry, Hispanic ancestry, and Asian ancestry. Thanks to this, we were able to identify variants specific to very diverse ancestries, in particular non-European ancestries, traditionally under-represented in genetic studies. We found about 100 of these non-European and ethnic variants, and some of them were also very penetrating, meaning they were very relevant for clinical considerations.
A third major finding is that we took into account the age dependence of penetrance. This means that for some diseases, those diseases are more likely to occur at older ages and that penetrance, or the risk of variants of those diseases, might actually increase with age. For example, we found [that] various cardiovascular diseases, various types of cancers were associated with increased risk, or increased penetrance, with the older age of these participants.
I know I said only 3 main findings, but a fourth finding that was also very important was that we looked at penetrance not just at the gene level, but we actually went even more microscopic than that at a higher resolution fine, where we examined penetrance at the variant level. And what we’ve found is that if we look inside a given gene, for example, the breast cancer susceptibility gene, BRCA1– we found that there is actually a wide range of penetrance for different variants of this given gene. So that really underlined the importance for us to look at a very granular level in order to get the highest resolution and most relevant information for individuals.