You don't choose a subset of your original 100-1 variables.
Each of the principal components are linear combinations of all 99 predictor variables (x-variables, IVs, ...). If you use the first 40 principal components, each of them is a function of all 99 original predictor-variables.
So you start with your 99 x-variables, from which you compute your 40 principal components by applying the corresponding weights on each of the original variables.
You then use your 40 new variables as if they were predictors in their own right, just as you would with any multiple regression problem.