Ron Do, PhD, associate professor, Charles Bronfman Institute for Personalized Medicine at the Icahn School of Medicine at Mount Sinai, and Iain Forrest, MD-PhD candidate in Dr Do’s lab, explain the differences between the biobanks used in their study on population-based penetrance of clinical variants.
Ron Do, PhD, associate professor, Charles Bronfman Institute for Personalized Medicine at the Icahn School of Medicine at Mount Sinai, and Iain Forrest, MD-PhD candidate in Dr Do’s lab, explain the differences between the biobanks used in their study on population-based penetrance of clinical variants.
Transcript
Your study used 2 biobanks that are a bit different from each other in terms of populations. What are the pros and cons of each?
Do: Just to recap, this study used 2 biobanks. The first was the BioMe Biobank, which was comprised of Mount Sinai patients recruited from the Mount Sinai Health System in and around New York City. Because of this, these individuals had a higher burden of diseases. As I mentioned, this can cause upward bias in penetrance estimates. The other biobank that we looked at was the UK Biobank, and these individuals were recruited instead from community sites in the UK. These individuals, on the other hand, were reported to be more healthy than the general population. So this actually has the opposite effect, which can cause a downward bias in penetrance estimates. In addition, BioMe is comprised of very diverse ancestry populations, as Iain had mentioned. About 30% were Hispanic Americans and 25% were African Americans. This enabled us to identify ethnic-specific variants. UK Biobank, however, was very homogeneous, with more than 90% European.
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