Polygenic Risk Score Assessment for Coronary Artery Disease in Asian Indians

被引：2

作者：

Rout, Madhusmita ^{[1
]}

Tung, Gurleen Kaur ^{[1
]}

Singh, Jai Rup ^{[2
]}

Mehra, Narinder Kumar ^{[3
]}

Wander, Gurpreet S. ^{[4
]}

Ralhan, Sarju ^{[4
]}

Sanghera, Dharambir K. ^{[1
,5
,6
,7
,8
]}

机构：

[1] Univ Oklahoma, Coll Med, Dept Pediat, Hlth Sci Ctr,Sect Genet, 940 Stanton L Young Blvd,Rm 317 BMSB, Oklahoma City, OK 73104 USA

[2] Guru Nanak Dev Univ, Amritsar, Punjab, India

[3] All India Inst Med Sci & Res, New Delhi, India

[4] Hero DMC Heart Inst, Ludhiana, Punjab, India

[5] Univ Oklahoma, Dept Pharmaceut Sci, Hlth Sci Ctr, Oklahoma City, OK 73104 USA

[6] Univ Oklahoma, Hlth Sci Ctr, Coll Med, Dept Physiol, Oklahoma City, OK 73190 USA

[7] Univ Oklahoma, Hlth Sci Ctr, Oklahoma Ctr Neurosci, Oklahoma City, OK 73104 USA

[8] Univ Oklahoma, Hlth Sci Ctr, Harold Hamm Diabet Ctr, Oklahoma City, OK 73106 USA

来源：

JOURNAL OF CARDIOVASCULAR TRANSLATIONAL RESEARCH | 2024年 / 17卷 / 05期

关键词：

Polygenic risk score; Clinical risk score; Coronary artery disease; Asian Indians; GENOME-WIDE ASSOCIATION; DIABETES SUSCEPTIBILITY; HEART-DISEASE; IDENTIFIES; 6; METAANALYSIS; INDIVIDUALS; POPULATION; SIKHS; PREDICTION; VARIANTS;

D O I：

10.1007/s12265-024-10511-z

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS.

引用

页码：1086 / 1096

页数：11

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