Reflections on Population Genetics with Immaculata de Vivo and Peter Kraft
It was really interesting to see how in genetics and risk factor research, the consensus for a causational effect is not necessarily always the most wanted approach - sometimes correlational factors are enough to help treat diseases. This may stem either from in a classroom setting, often the discovery of the root of a problem is the end goal, whereas in the real world, the root may not be necessary to treat a health outcome. Even Professor de Vivo's comment on how doctor's may not know the cause of every illness and cure but rather that there are strong correlational effects that the cure solves the illness. This often stems from the lack of data itself - that not every confound is able to be disentangled.
If I had conducted the interview, I would have asked about twin studies in which the genetic component is fixed but the expression of the gene may be altered depending on which environment someone is placed in. Specifically, cases where twins were separated at birth but grew up under vastly different conditions, whether by SES or culture. I also was curious about how fine gradients there are in assessing what were risk factors - examples such as if someone smokes or not is binary, and easier to gather data on, but if in medicine how often data is available for specific quantities of a risk factor.