Li Aolin, Gong Shuo, Yu Canqing, Pei Pei, Yang Ling, Millwood Iona Y, Walters Robin G, Chen Yiping, Du Huaidong, Yang Xiaoming, Hou Wei, Chen Junshi, Chen Zhengming, Lv Jun, Li Liming, Sun Dianjianyi
Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
Diabetes. 2025 Mar 1;74(3):320-331. doi: 10.2337/db24-0736.
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.
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.
关于基于人群的表型与遗传体重指数（BMI-PGM）之间的不匹配及其与2型糖尿病的关联，我们了解甚少。因此，我们使用了中国嘉道理生物银行和英国生物银行的数据，并计算了每位参与者的BMI-PGM，即基线时调整后的BMI百分位数与BMI调整后的多基因风险评分百分位数之间的差值。参与者被分为不一致低（BMI-PGM<第一四分位数）、一致（第一四分位数≤BMI-PGM<第三四分位数）和不一致高（BMI-PGM≥第三四分位数）组。我们在每个队列中使用Cox比例风险模型计算BMI-PGM与2型糖尿病关联的调整后风险比（HRs），并使用随机效应荟萃分析合并HRs。在两个队列均为期12年的中位随访期间，BMI-PGM与2型糖尿病风险相关，与一致组相比，不一致低组风险降低，不一致高组风险升高，且独立于BMI和其他传统风险因素。此外，BMI-PGM不一致高的正常体重个体患2型糖尿病的风险高于超重个体。这些发现表明，BMI-PGM可能在重新评估2型糖尿病风险中发挥潜在作用，尤其是在正常体重人群中。
社会发展促成了一种“致肥胖环境”，加剧了BMI的表型与遗传不匹配（BMI-PGM）以及2型糖尿病风险。该研究对BMI-PGM进行了量化，并在独立于BMI和其他传统因素的情况下检查了其与2型糖尿病的关联。以BMI-PGM一致组为参照，BMI-PGM不一致低组患2型糖尿病的风险较低，BMI-PGM不一致高组患2型糖尿病的风险较高。这些发现表明，通过在个体水平上量化BMI-PGM，有可能重新评估2型糖尿病风险。
