Drzymalla Emily, Raffield Laura, Kolor Katherine, Koyama Alain, Moonesinghe Ramal, Pavkov Meda E, Spracklen Cassandra N, Khoury Muin J
Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Diabetes Care. 2025 Feb 1;48(2):212-219. doi: 10.2337/dc24-1537.
The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction.
Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire. A PRS was constructed from 1,289 variants identified from a large multiancestry genome-wide association study meta-analysis for T2D. Logistic regression models were run to generate odds ratios (ORs) and 95% CIs for T2D. All models were adjusted for age, sex, and BMI.
A total of 109,958 AoU research participants were included in the analysis. The odds of T2D increased with 1 SD PRS (OR 1.75; 95% CI 1.71-1.79) and positive T2D family history (OR 2.32; 95% CI 2.20-2.43). In the joint model, both 1 SD PRS (OR 1.69; 95% CI 1.65-1.72) and family history (OR 2.06; 95% CI 1.98-2.15) were significantly associated with T2D, although the ORs were slightly attenuated. Predictive models that included both the PRS and family history (area under the curve [AUC] 0.794) performed better than models including only family history (AUC 0.763) or the PRS (AUC 0.785).
In predicting T2D, inclusion of a T2D PRS in addition to family history of T2D (first-degree relatives) added statistical value. Further study is needed to determine whether consideration of both family history and a PRS would be useful for clinical T2D prediction.
本研究的目的是评估在2型糖尿病（T2D）预测中，除家族史外，考虑T2D多基因风险评分（PRS）的附加价值。
数据来自“我们所有人”（AoU）研究数据库。一级亲属的T2D家族史通过个人家族史健康问卷自行报告。PRS由从一项针对T2D的大型多血统全基因组关联研究荟萃分析中鉴定出的1289个变异构建而成。运行逻辑回归模型以生成T2D的比值比（OR）和95%置信区间（CI）。所有模型均根据年龄、性别和体重指数进行了调整。
共有109958名AoU研究参与者纳入分析。T2D的患病几率随PRS增加1个标准差（OR 1.75；95% CI 1.71 - 1.79）以及T2D家族史呈阳性（OR 2.32；95% CI 2.20 - 2.43）而增加。在联合模型中，PRS增加1个标准差（OR 1.69；95% CI 1.65 - 1.72）和家族史（OR 2.06；95% CI 1.98 - 2.15）均与T2D显著相关，尽管OR值略有减弱。同时包含PRS和家族史的预测模型（曲线下面积[AUC] 0.794）比仅包含家族史（AUC 0.763）或PRS（AUC 0.785）的模型表现更好。
在预测T2D时，除T2D家族史（一级亲属）外纳入T2D PRS增加了统计价值。需要进一步研究以确定同时考虑家族史和PRS对临床T2D预测是否有用。
