# How does False Discovery Rate relate to linear models and regression?

My understanding of the FDR is that it is synonymous with the Type 1 error or rejecting the null when the null is true. However, I am not certain how this relates to linear models. I read that false discoveries occur in high dimensional logistic regression models. What exactly is the false discovery? Is it a positive estimated $\beta$ coefficient when it should be zero for the MLE of the coefficient's?