Combining Polygenic and Proteomic Risk Scores With Clinical Risk Factors to Improve Performance for Diagnosing Absence of Coronary Artery Disease in Patients With de novo Chest Pain.

IF 6 2区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Circulation: Genomic and Precision Medicine Pub Date : 2023-10-01 Epub Date: 2023-09-27 DOI:10.1161/CIRCGEN.123.004053

Peter Loof Møller, Palle Duun Rohde, Jonathan Nørtoft Dahl, Laust Dupont Rasmussen, Samuel Emil Schmidt, Louise Nissen, Victoria McGilligan, Jacob F Bentzon, Daniel F Gudbjartsson, Kari Stefansson, Hilma Holm, Simon Winther, Morten Bøttcher, Mette Nyegaard

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引用次数: 0

Abstract

Background: Patients with de novo chest pain, referred for evaluation of possible coronary artery disease (CAD), frequently have an absence of CAD resulting in millions of tests not having any clinical impact. The objective of this study was to investigate whether polygenic risk scores and targeted proteomics improve the prediction of absence of CAD in patients with suspected CAD, when added to the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS).

Methods: Genotyping and targeted plasma proteomics (N=368 proteins) were performed in 1440 patients with symptoms suspected to be caused by CAD undergoing coronary computed tomography angiography. Based on individual genotypes, a polygenic risk score for CAD (PRS_CAD) was calculated. The prediction was performed using combinations of PRS_CAD, proteins, and PMRS as features in models using stability selection and machine learning.

Results: Prediction of absence of CAD yielded an area under the curve of PRS_CAD-model, 0.64±0.03; proteomic-model, 0.58±0.03; and PMRS model, 0.76±0.02. No significant correlation was found between the genetic and proteomic risk scores (Pearson correlation coefficient, -0.04; P=0.13). Optimal predictive ability was achieved by the full model (PRS_CAD+protein+PMRS) yielding an area under the curve of 0.80±0.02 for absence of CAD, significantly better than the PMRS model alone (P<0.001). For reclassification purpose, the full model enabled down-classification of 49% (324 of 661) of the 5% to 15% pretest probability patients and 18% (113 of 611) of >15% pretest probability patients.

Conclusions: For patients with chest pain and low-intermediate CAD risk, incorporating targeted proteomics and polygenic risk scores into the risk assessment substantially improved the ability to predict the absence of CAD. Genetics and proteomics seem to add complementary information to the clinical risk factors and improve risk stratification in this large patient group.

Registration: URL: https://www.

Clinicaltrials: gov; Unique identifier: NCT02264717.

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将多基因和蛋白质组风险评分与临床风险因素相结合，提高诊断新发胸痛患者无冠状动脉疾病的能力。

背景：被转诊评估可能的冠状动脉疾病（CAD）的新发胸痛患者经常没有CAD，导致数百万次检测没有任何临床影响。本研究的目的是研究多基因风险评分和靶向蛋白质组学是否能改善疑似CAD患者无CAD的预测，将其添加到PROMISE（用于评估胸痛的前瞻性多中心成像研究）最低风险评分（PMRS）中。方法：对1440名接受冠状动脉计算机断层扫描血管造影术的疑似CAD症状患者进行基因分型和靶向血浆蛋白质组学（N=368种蛋白质）。根据个体基因型，计算CAD的多基因风险评分（PRSCAD）。在使用稳定性选择和机器学习的模型中，使用PRSCAD、蛋白质和PMRS的组合作为特征进行预测。结果：预测无CAD时，PRSCAD模型的曲线下面积为0.64±0.03；蛋白质组学模型，0.58±0.03；PMRS模型为0.76±0.02。遗传和蛋白质组学风险评分之间没有发现显著的相关性（Pearson相关系数，-0.04；P=0.013）。全模型（PRSCAD+蛋白质+PMRS）在没有CAD的情况下产生0.80±0.02的曲线下面积，实现了最佳的预测能力，明显优于单独的PMRS模型（P15%的预测概率患者。结论：对于胸痛和中低度CAD风险的患者，将靶向蛋白质组学和多基因风险评分纳入风险评估大大提高了预测无CAD的能力。遗传学和蛋白质组学似乎为临床风险因素增加了补充信息，并改善了这一大样本的风险分层ient组。注册：URL:https://www.Clinicaltrials:政府；唯一标识符：NCT02264717。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Circulation: Genomic and Precision Medicine Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

9.20

自引率

5.40%

发文量

144

期刊介绍： Circulation: Genomic and Precision Medicine is a distinguished journal dedicated to advancing the frontiers of cardiovascular genomics and precision medicine. It publishes a diverse array of original research articles that delve into the genetic and molecular underpinnings of cardiovascular diseases. The journal's scope is broad, encompassing studies from human subjects to laboratory models, and from in vitro experiments to computational simulations. Circulation: Genomic and Precision Medicine is committed to publishing studies that have direct relevance to human cardiovascular biology and disease, with the ultimate goal of improving patient care and outcomes. The journal serves as a platform for researchers to share their groundbreaking work, fostering collaboration and innovation in the field of cardiovascular genomics and precision medicine.