Reddit mentions of Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health)

Classical testing for interaction using logistic regression is typically done using a likelihood ratio test. This will tell you if the genes relating to risk have an interaction. However, this generally tells you little about how well they predict Y. Are you sure prediction is of interest? If that's the case, you might use ROC curves to identify how well you predict the outcome given the model which does and does not adjust for the interaction of Gene A and B. I would consult Clinical prediction models from Ewout Steyerberg for clarification.