Mengyi Liu, Yuanyuan Zhang, Ziliang Ye, Panpan He, Chun Zhou, Sisi Yang, Yanjun Zhang, Xiaoqin Gan, Xianhui Qin
{"title":"利用蛋白质组标记物增强心房颤动风险预测:与临床和多基因风险评分的比较分析。","authors":"Mengyi Liu, Yuanyuan Zhang, Ziliang Ye, Panpan He, Chun Zhou, Sisi Yang, Yanjun Zhang, Xiaoqin Gan, Xianhui Qin","doi":"10.1136/heartjnl-2024-324274","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank.</p><p><strong>Methods: </strong>We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS<sub>2</sub>-AF risk model and a polygenic risk score.</p><p><strong>Results: </strong>Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS<sub>2</sub>-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively).</p><p><strong>Conclusions: </strong>A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.</p>","PeriodicalId":12835,"journal":{"name":"Heart","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores.\",\"authors\":\"Mengyi Liu, Yuanyuan Zhang, Ziliang Ye, Panpan He, Chun Zhou, Sisi Yang, Yanjun Zhang, Xiaoqin Gan, Xianhui Qin\",\"doi\":\"10.1136/heartjnl-2024-324274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank.</p><p><strong>Methods: </strong>We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS<sub>2</sub>-AF risk model and a polygenic risk score.</p><p><strong>Results: </strong>Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS<sub>2</sub>-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively).</p><p><strong>Conclusions: </strong>A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.</p>\",\"PeriodicalId\":12835,\"journal\":{\"name\":\"Heart\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Heart\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/heartjnl-2024-324274\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Heart","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/heartjnl-2024-324274","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores.
Background: Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank.
Methods: We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score.
Results: Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively).
Conclusions: A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.
期刊介绍:
Heart is an international peer reviewed journal that keeps cardiologists up to date with important research advances in cardiovascular disease. New scientific developments are highlighted in editorials and put in context with concise review articles. There is one free Editor’s Choice article in each issue, with open access options available to authors for all articles. Education in Heart articles provide a comprehensive, continuously updated, cardiology curriculum.