Genome-wide association studies can sleuth out genetic markers that raise or lower COVID risk, but they miss social factors
Imagine taking a genetic test that could tell you your personal risk of developing complications and dying from a particular disease, such as cancer, heart attack or even COVID. A version of such a test exists—albeit an imperfect one.
Manuel Ferreira, a researcher at genetics company Regeneron, is part of a team using GWAS to hunt loci related to COVID risk by sifting through thousands of genomes from four aggregated databases. In their most recent study, published in March in Nature Genetics, Ferreira and his co-authors crunched the numbers and found that individuals with a rare variant of the ACE2 gene seemed to be at nearly 40 percent lower risk than the general population of developing severe COVID.
But other researchers caution that when it comes to predicting severe COVID, it is nearly impossible to disentangle genetic risks from social risk factors such as access to health care and working conditions, even using genome-wide analysis. Geneticists do their best to account for such disparities in their analyses. “Epidemiologically, the way you can better understand the extent to which genetics [versus social risk factors] is driving the severity” of disease, Taveras says, is to “adjust for some of those variables.” By comparing individuals of similar ancestry, socioeconomic status, gender or medical history, scientists can establish a baseline for a patient’s odds of developing severe COVID.
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