Phenotypic Versus Genetic Mismatch of BMI and Type 2 Diabetes: Evidence From Two Prospective Cohort Studies

Little is known about the population-based mismatch between phenotypic and genetic BMI (BMI-PGM) and its association with type 2 diabetes. We therefore used data from the China Kadoorie Biobank and UK Biobank and calculated BMI-PGM for each participant as the difference between the percentile for adjusted BMI at baseline and the percentile for adjusted polygenic risk score for BMI. Participants were categorized into discordantly low (BMI-PGM < the first quartile), concordant (the first quartile ≤ BMI-PGM < the third quartile), and discordantly high (BMI-PGM ≥ the third quartile) groups. We calculated adjusted hazard ratios (HRs) for the association of BMI-PGM and type 2 diabetes using Cox proportional hazard models in each cohort, and combined HRs using random-effects meta-analyses. During a median follow-up of 12 years for both cohorts, BMI-PGM was associated with the risk of type 2 diabetes, with the discordantly low group showing reduced risk and the discordantly high group showing elevated risk compared with the concordant group, independent of BMI and other conventional risk factors. In addition, normal-weight individuals with discordantly high BMI-PGM faced a higher risk of type 2 diabetes than overweight individuals. These findings suggest that BMI-PGM may play a potential role in reassessing the risk of type 2 diabetes, particularly among normal-weight populations. ARTICLE HIGHLIGHTS: Social developments have fostered an "obesogenic environment" that exacerbated phenotypic versus genetic mismatch of BMI (BMI-PGM) and the risk of type 2 diabetes. The study quantified BMI-PGM and examined its association with type 2 diabetes independent of BMI and other conventional factors. The risk of type 2 diabetes was lower in the discordantly low BMI-PGM group and higher in the discordantly high BMI-PGM group, with concordant BMI-PGM group as reference. These findings indicate the potential to reassess type 2 diabetes risk by quantifying BMI-PGM on individual levels.