[BioC] Limma Modeling

[Katarzyna Bryc]

Dear List,

I have a question on correctly modeling a situtation to find
significantly differentiated genes with Limma. I have Affy arrays for
pediatric patients collected before the patients were treated with a
drug for 4 months. After this time period, some patients had a side
effect of significant weight gain, while others did not. I wish to find
the genes which significantly differentiate patients who gained weight
with the treatment from those who did not suffer this side effect. Since
these are pediatric patients, I also wish to control for Sex and Age
(continuous variable).

I understand that with Limma I can model the following:

Gene Expression = Age + Sex + Weight Gain

but I actually wish to look at Weight Gain as the dependent variable,
and Gene Expression as one of the independent variables (I still control
for Age and Sex). Thus, I actually wish to model

Weight Gain = Age + Sex + Gene Expression

My questions are:
1. Will these two models give me the same results for finding genes
significant in predicting Weight Gain?
2. If not, is there a way to model this using either Limma or another
Bioconductor method?

Thank you for any helpful words,
Kasia Bryc