Environmental factor dependent maximum likelihood method for association study targeted to personalized medicine.

The most challenging strategy for analyzing genome-wide polymorphisms and/or expression profiles is to solve multi-factor causal-relationship simultaneously. As the first step, we propose a framework of association study using maximum likelihood method that simultaneously handles genetic polymorphisms and epi-genetic information, e.g. environmental factors. We evaluate the theory by applying it to genotyped data of myocardial infarction (MI) patients.