question about incorporting genotyping data in disease progression model

Dear NONMEM users, I am working on a model in asthma patients and trying to build a model of FEV1, which is the evaluation of lung function. I have 500,000 genotyping data. First, I screened the genotyping data by running GWAS to find out the potential genotyping data, which gave me about 60 genotypes. Then, I tried to add these 60 genotyping data into model to find out if the progress of FEV1 is related with gene expression. But the problem is that too many genotypes were related with a significant change in OFV, which does not sound reasonable to me. I was hoping to find few (2-3) genotypes are associated with the progress in lung function. I have tried to include the genotyping data as discrete covariate (if genotyping =1 then parameter=theta(1); if genotyping =2 then parameter=theta(2); if genotyping=3 then parameter =theta(3)), and power function (genotype**(theta)). Did I do something wrong when including the genotyping data in the model as covariate? Thanks a lot in advance! Kehua