Neutralise/remove feature from GBM

I need to remove a feature (variable) from my GBM without rebuilding the model and excluding the variable, what would be the best approach to do this?

If you set the column (in the data frame you give to h2o.predict) to all NA, then it will act as if the data is missing. According to the FAQ (and assuming you had no NAs in the training data) it will then "follow the majority direction (the direction with the most observations)".
For a category with very few levels like gender, another possibility is to run h2o.predict first with it set to male, then again with it set to female, and somehow merge the results. (Or inform the operator of "dependence on a sensitive variable" when the results disagree in an important way.)