141-OR: Discrepancy between Genetically-Predicted and Actual Body Mass Index Predicts Incident Diabetes Mellitus

Background: Body mass index (BMI) is a key predictor of metabolic disorders including type 2 diabetes mellitus (T2D). Polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) can predict BMI based on common variants, and genetically-predicted BMI (BMI-pred) could serve as a threshold for personal fat storage. We hypothesized that difference between BMI-pred and actual BMI (BMI-diff) could reflect severity of environmental factors affecting BMI and may predict incident T2D. Methods: From the UK Biobank cohort, we selected participants of white British descent without a history of T2D (n=383,160). The PRS for BMI was calculated using polygenic prediction via Bayesian regression and continuous shrinkage priors (PRS-CS) with summary statistics from the Genetic Investigation of ANthropometric Traits consortium GWAS. According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional-hazards model. Results were validated in an independent cohort from South Korea (n=8,840). Results: Participants (mean age 56.8 ± 8.0, male 45.3%) were randomly divided into train (n=268,041) and test set (n=115,119) to establish BMI-pred using PRS-CS. In the test set, the BMI-pred could explain 7.1% of the variance of BMI and T2D occurred in 3,599 (3.1%) cases during 10-year follow-up. The risk of T2D increased linearly according to the decrease of BMI-diff. Participants in the higher quintiles of BMI-diff (more obese than genetically-predicted), had significantly higher risk of T2D than those in the lowest quintile (less obese than genetically-predicted) regardless of their own BMI: adjusted HR (aHR) of 1st quintile 1.61, 95% confidence interval (CI) 1.26-2.05, P <0.001; aHR of 2nd quintile 1.48, 95% CI 1.21-1.81, P <0.001. Results were consistent when validated in the South Korean cohort. Conclusion: Deviation of actual BMI from BMI-pred which reflects severity of environmental factors is a significant predictor of incident T2D. Disclosure T.Rhee: None. H.Lee: None. J.Choi: None. J.S.Lee: None. S.Kwak: None. K.Park: None.