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印度人群 2 型糖尿病的全基因组多基因风险评分。

Genome-wide polygenic risk score for type 2 diabetes in Indian population.

机构信息

Mapmygenome India Limited, Hyderabad, India.

出版信息

Sci Rep. 2023 Jul 18;13(1):11568. doi: 10.1038/s41598-023-38768-5.

DOI:10.1038/s41598-023-38768-5
PMID:37463971
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10354074/
Abstract

Genome-wide polygenic risk scores (PRS) for lifestyle disorders, like Type 2 Diabetes (T2D), are useful in identifying at-risk individuals early on in life, and to guide them towards healthier lifestyles. The current study was aimed at developing PRS for the Indian population using imputed genotype data from UK Biobank and testing the developed PRS on data from GenomegaDB of Indians living in India. 959 T2D cases and 2,818 controls were selected from Indian participants of UK Biobank to develop the PRS. Summary statistics available for South Asians, from the DIAMANTE consortium, were used to weigh genetic variants. LDpred2 algorithm was used to adjust the effect of linkage disequilibrium among the variants. The association of PRS with T2D, after adjusting for age, sex and top ten genetic principal components, was found to be very significant (AUC = 0.7953, OR = 2.9856 [95% CI: 2.7044-3.2961]). When participants were divided into four PRS quartile groups, the odds of developing T2D increased sequentially with the higher PRS groups. The highest PRS group (top 25%) showed 5.79 fold increased risk compared to the rest of the participants (75%). The PRS derived using the same set of variants was found to be significantly associated with T2D in the test dataset of 445 Indians (AUC = 0.7781, OR = 1.6656 [95%CI = 0.6127-4.5278]). Our study demonstrates a framework to derive Indian-specific PRS for T2D. The accuracy of the derived PRS shows it's potential to be used as a prognostic metric to stratify individuals, and to recommend personalized preventive strategies.

摘要

基于全基因组多基因风险评分(PRS)的生活方式疾病(如 2 型糖尿病(T2D))可用于在生命早期识别高危个体,并指导他们走向更健康的生活方式。本研究旨在使用来自英国生物银行的基因型数据为印度人群开发 PRS,并在印度人生活在印度的 GenomegaDB 数据上测试所开发的 PRS。从英国生物库的印度参与者中选择了 959 例 T2D 病例和 2818 例对照来开发 PRS。使用来自 DIAMANTE 联盟的南亚人可用的汇总统计数据来权衡遗传变异。使用 LDpred2 算法调整变异之间的连锁不平衡效应。在调整年龄、性别和前 10 个遗传主成分后,发现 PRS 与 T2D 之间的关联非常显著(AUC=0.7953,OR=2.9856[95%CI:2.7044-3.2961])。当参与者被分为四个 PRS 四分位组时,随着更高的 PRS 组,患 T2D 的几率依次增加。与其余参与者相比,最高 PRS 组(前 25%)的发病风险增加了 5.79 倍(75%)。使用相同的一组变体得出的 PRS 被发现与 445 名印度人(AUC=0.7781,OR=1.6656[95%CI=0.6127-4.5278])的测试数据集的 T2D 显著相关。我们的研究演示了一种为 T2D 衍生印度特定 PRS 的框架。所衍生 PRS 的准确性表明它有可能被用作分层个体的预后指标,并推荐个性化的预防策略。

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本文引用的文献

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Inferring disease architecture and predictive ability with LDpred2-auto.利用 LDpred2-auto 推断疾病结构和预测能力。
Am J Hum Genet. 2023 Dec 7;110(12):2042-2055. doi: 10.1016/j.ajhg.2023.10.010. Epub 2023 Nov 8.
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