There are numerous reasons why the severity of COVID-19 differs from person to person, with age being the most obvious one. Given the nature of the virus, specifically how it utilizes ACE2 receptors to invade cells, genetics should be one of the major covariates that can predict COVID-19 severity.
The goal of this (very ambitious) project is to build a fully private data platform that will be used to discover genetic factors that affect COVID-19 severity. Once such genetic markers are identified, the tool will be used to identify people who are at higher risk. These findings would have an immense and immediate benefit to the public.
How does this work? We start by (i) building necessary private data analysis techniques (where either multi party computing or some variation of homomorphic encryption will be utilized) and (ii) identifying a range of SNPs that can be relevant to COVID-19. We then recruit COVID-19 patients who have done genetic testing via services such as 23andme or Ancestry, and ask them to use our platform to upload their (homomorphically encrypted) genetics data, COVID-19 severity and other relevant factors (e.g. age, preexisting conditions, smoking frequency). Finally, we run the world’s largest crowd sourced GWAS.
There is much much more to discuss (how to achieve private data analysis, how this would be marketed, how to convince people that this is fully private, the legal issues etc.) but I’ll stop here and ask for your first impressions and comments (constructive or destructive, both are welcome).