检测升主动脉扩张的多基因评分法

IF 6 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS Circulation: Genomic and Precision Medicine Pub Date : 2024-10-01 Epub Date: 2024-09-26 DOI:10.1161/CIRCGEN.123.004512
John DePaolo, Gina Biagetti, Renae Judy, Grace J Wang, John J Kelly, Amit Iyengar, Nicholas J Goel, Nimesh D Desai, Wilson Y Szeto, Joseph E Bavaria, Michael G Levin, Scott M Damrauer
{"title":"检测升主动脉扩张的多基因评分法","authors":"John DePaolo, Gina Biagetti, Renae Judy, Grace J Wang, John J Kelly, Amit Iyengar, Nicholas J Goel, Nimesh D Desai, Wilson Y Szeto, Joseph E Bavaria, Michael G Levin, Scott M Damrauer","doi":"10.1161/CIRCGEN.123.004512","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.</p><p><strong>Methods: </strong>The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.</p><p><strong>Results: </strong>Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).</p><p><strong>Conclusions: </strong>We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540195/pdf/","citationCount":"0","resultStr":"{\"title\":\"Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation.\",\"authors\":\"John DePaolo, Gina Biagetti, Renae Judy, Grace J Wang, John J Kelly, Amit Iyengar, Nicholas J Goel, Nimesh D Desai, Wilson Y Szeto, Joseph E Bavaria, Michael G Levin, Scott M Damrauer\",\"doi\":\"10.1161/CIRCGEN.123.004512\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.</p><p><strong>Methods: </strong>The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.</p><p><strong>Results: </strong>Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).</p><p><strong>Conclusions: </strong>We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.</p>\",\"PeriodicalId\":10326,\"journal\":{\"name\":\"Circulation: Genomic and Precision Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540195/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Circulation: Genomic and Precision Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1161/CIRCGEN.123.004512\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/26 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circulation: Genomic and Precision Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/CIRCGEN.123.004512","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/26 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

背景:升胸主动脉扩张是一种复杂的遗传性状,涉及可改变和不可改变的风险因素。多基因评分(PGS)越来越多地被用于评估复杂疾病的风险。PGS 能在多大程度上改善不同人群的主动脉直径预测尚不清楚。目前,我们在一个多样化的生物库中测试了在临床预测算法中添加 PGS 是否能提高性能:分析队列由 6235 名宾夕法尼亚医学生物库参与者组成,这些参与者都有可用的超声心动图和临床数据以及全基因组基因型数据。线性回归模型用于整合英国生物库进行的胸主动脉直径全基因组关联研究得出的 PGS 权重,并与之前公布的胸主动脉瘤优化回归(AORTA)评分进行比较:队列参与者的中位年龄为 61 岁(IQR,53-70),升主动脉平均直径为 3.36 厘米(SD,0.49)。55%为男性,33%与非洲参考人群的基因相似。AORTA 评分对主动脉直径变异的解释率为 30.6%(95% CI,29.9%-31.4%),相比之下,AORTA 评分+英国生物库衍生 PGS 对主动脉直径变异的解释率为 33.1%(95% CI,32.3%-33.8%),重新加权的 AORTA 评分对主动脉直径变异的解释率为 32.5%(95% CI,31.8%-33.2%),重新加权的 AORTA 评分+英国生物库衍生 PGS 对主动脉直径变异的解释率为 34.9%(95% CI,34.2%-35.6%)。按人群分层时,在与欧洲参考人群基因相似的个体中,包含英国生物库衍生 PGS 的模型可持续改善临床 AORTA 评分,但在与非洲参考人群基因相似的个体中,改善效果甚微。在为区分胸主动脉扩张(≥4.0 厘米)病例/非病例而开发的模型中观察到了类似的性能差异:我们的研究表明,在 AORTA 评分中加入英国生物库衍生 PGS 可使模型性能得到有临床意义的改善,但这只适用于与欧洲参考人群基因相似的个体,而且可能会加剧现有的医疗保健差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation.

Background: Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.

Methods: The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.

Results: Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).

Conclusions: We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Circulation: Genomic and Precision Medicine
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.
期刊最新文献
Cardiovascular Disease Pathogenicity Predictor (CVD-PP): A Tissue-Specific In Silico Tool for Discriminating Pathogenicity of Variants of Unknown Significance in Cardiovascular Disease Genes. Yield of Genetic Testing for Long-QT Syndrome in Elderly Patients With Torsades de Pointes. How Normal Is Low-Normal Left Ventricular Ejection Fraction in Familial Dilated Cardiomyopathy? Polygenic Risk and Coronary Artery Disease Severity. Clinical Utility of Protein Language Models in Resolution of Variants of Uncertain Significance in KCNQ1, KCNH2, and SCN5A Compared With Patch-Clamp Functional Characterization.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1