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Discrepancy Between Genetically Predicted and Observed BMI Predicts Incident Type 2 Diabetes

医学 2型糖尿病 危险系数 体质指数 比例危险模型 肥胖 人口学 内科学 生命银行 队列 队列研究 糖尿病 置信区间 内分泌学 遗传学 生物 社会学
作者
Tae-Min Rhee,Jaewon Choi,Hyunsuk Lee,J. Merino,Jun‐Bean Park,Soo Heon Kwak
出处
期刊:Diabetes Care [American Diabetes Association]
标识
DOI:10.2337/dc24-0879
摘要

OBJECTIVE Obesity is a key predictor of type 2 diabetes (T2D). However, metabolic complications are not solely due to increased BMI. We hypothesized that differences between genetically predicted BMI and observed BMI (BMI-diff) could reflect deviation from individual set point and may predict incident T2D. RESEARCH DESIGN AND METHODS From the UK Biobank cohort, we selected participants of European ancestry without T2D (n = 332,154). The polygenic risk score for BMI was calculated via Bayesian regression and continuous shrinkage priors (PRS-CS). According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional hazards model. Independent data from the Korean Genome and Epidemiology Study (KoGES) cohort from South Korea (n = 7,430) were used for replication. RESULTS Participants from the UK Biobank were divided into train (n = 268,041) and test set (n = 115,119) to establish genetically predicted BMI. In the test set, the genetically predicted BMI explained 7.1% of the variance of BMI, and there were 3,599 T2D cases (3.1%) during a 10-year follow-up. 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 after adjusting for observed BMI: the adjusted hazard ratio of the 1st quintile (vs. 5th quintile) was 1.61 (95% CI, 1.26–2.05, P < 0.001). Results were consistent among individuals in the KoGES study. Moreover, higher BMI than predicted was associated with impaired insulin sensitivity. CONCLUSIONS Having a higher BMI than genetically predicted is associated with an increased risk of T2D. These findings underscore the potential to reassess T2D risk based on individual levels of obesity using genetic thresholds for BMI.

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