Integrated genomic and BMI analysis for type 2 diabetes risk assessment.

ABSTRACT: Type 2 Diabetes (T2D) is a chronic disease arising from the development of insulin absence or resistance within the body, and a complex interplay of environmental and genetic factors. The incidence of T2D has increased throughout the last few decades, together with the occurrence of the obesity epidemic. The consideration of variants identified by Genome Wide Association Studies (GWAS) into risk assessment models for T2D could aid in the identification of at-risk patients who could benefit from preventive medicine. In this study, we build several risk assessment models, evaluated with two different classification approaches (Logistic Regression and Neural Networks), to measure the effect of including genetic information in the prediction of T2D. We used data from to the Original and the Of

SUBMITTER: Lebron-Aldea D 

PROVIDER: S-EPMC4362394 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature