African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Herein, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method (PRS-CS). We further tested the score in three independent studies with a total of 7,275 AAs. We then compared the PRSAA to other published scores. Results show that a 1 standard deviation increase in the PRSAA was associated with 40%-60% increase in the odds of T2D (OR=1.60, 95% CI 1.37-1.88; OR=1.40, 95% CI 1.16-1.70; and OR=1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0%-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values (PPV) for three calculated score thresholds (the top 2%, 5% 10%) ranged from 14% to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. Larger datasets remain needed to continue to evaluate the utility of within-ancestry scores in the AA population.

中文翻译：

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非裔美国人 2 型糖尿病的多基因风险

非裔美国人 (AA) 在多基因风险评分 (PRS) 研究中的代表性不足。在此，我们整合了来自多项 2 型糖尿病 (T2D) 观察性研究的全基因组数据（总共包含 101,987 个 AA），使用贝叶斯多基因建模方法 (PRS-CS) 来训练和优化以 AA 为重点的 T2D PRS (PRSAA) ）。我们在三项独立研究中进一步测试了该分数，总共 7,275 个 AA。然后我们将 PRSAA 与其他已发布的分数进行比较。结果显示，PRSAA 增加 1 个标准差与 T2D 几率增加 40%-60% 相关（OR=1.60，95% CI 1.37-1.88；OR=1.40，95% CI 1.16-1.70；OR=1.40，95% CI 1.16-1.70；OR =1.45，95% CI 1.30-1.62）在三个测试队列中。这些模型捕获了 T2D 责任规模中 1.0%-2.6% 的方差 (R2)。三个计算得分阈值（前 2%、5% 10%）的阳性预测值 (PPV) 范围为 14% 至 35%。一般来说，PRSAA 的性能与现有的 T2D PRS 类似。仍然需要更大的数据集来继续评估 AA 人群中血统内分数的效用。