改良的 1 型糖尿病预测遗传风险评分算法。
Improved genetic risk scoring algorithm for type 1 diabetes prediction.
机构信息
The Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
出版信息
Pediatr Diabetes. 2022 May;23(3):320-323. doi: 10.1111/pedi.13310. Epub 2022 Jan 19.
BACKGROUND
Precise risk prediction of type 1 diabetes (T1D) facilitates early intervention and identification of risk factors prior to irreversible beta-islet cell destruction, and can significantly improve T1D prevention and clinical care. Sharp et al. developed a genetic risk scoring (GRS) system for T1D (T1D-GRS2) capable of predicting T1D risk in children of European ancestry. The T1D-GRS2 was developed on the basis of causal genetic variants, thus may be applicable to minor populations, while a trans-ethnic GRS for T1D may avoid the exacerbation of health disparities due to the lack of genomic information in minorities.
METHODS
Here, we describe a T1D-GRS2 calculator validated in two independent cohorts, including African American children and European American children. Participants were recruited by the Center for Applied Genomics at the Children's Hospital of Philadelphia.
RESULTS
It demonstrates that GRS2 is applicable to the T1D risk prediction in the AA cohort, while population-specific thresholds are needed for different populations.
CONCLUSIONS
The study highlights the potential to further improve T1D-GRS2 performance with the inclusion of additional genetic markers.
背景
1 型糖尿病（T1D）的精确风险预测有助于在不可逆的β胰岛细胞破坏之前进行早期干预和识别风险因素，从而显著改善 T1D 的预防和临床护理。Sharp 等人开发了一种用于 T1D 的遗传风险评分（GRS）系统（T1D-GRS2），能够预测欧洲血统儿童的 T1D 风险。T1D-GRS2 是基于因果遗传变异开发的，因此可能适用于少数民族，而 T1D 的跨种族 GRS 可以避免由于少数群体缺乏基因组信息而导致的健康差距扩大。
方法
在这里，我们描述了在两个独立队列中验证的 T1D-GRS2 计算器，包括非裔美国儿童和欧洲裔美国儿童。参与者是由费城儿童医院的应用基因组学中心招募的。
结果
它表明 GRS2 适用于 AA 队列的 T1D 风险预测，但需要针对不同人群制定特定于人群的阈值。
结论
该研究强调了通过纳入额外的遗传标记来进一步提高 T1D-GRS2 性能的潜力。
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