Carla Debernardi, Angelo Savoca, Alessandro De Gregorio, Elisabetta Casalone, Miriam Rosselli, Elton Jalis Herman, Cecilia Di Primio, Rosario Tumino, Sabina Sieri, Paolo Vineis, Salvatore Panico, Carlotta Sacerdote, Diego Ardissino, Rosanna Asselta, Giuseppe Matullo
{"title":"人群异质性与冠心病多基因评分的选择。","authors":"Carla Debernardi, Angelo Savoca, Alessandro De Gregorio, Elisabetta Casalone, Miriam Rosselli, Elton Jalis Herman, Cecilia Di Primio, Rosario Tumino, Sabina Sieri, Paolo Vineis, Salvatore Panico, Carlotta Sacerdote, Diego Ardissino, Rosanna Asselta, Giuseppe Matullo","doi":"10.3390/jpm14101025","DOIUrl":null,"url":null,"abstract":"<p><strong>Background/objectives: </strong>The identification of coronary artery disease (CAD) high-risk individuals is a major clinical need for timely diagnosis and intervention. Many different polygenic scores (PGSs) for CAD risk are available today to estimate the genetic risk. It is necessary to carefully choose the score to use, in particular for studies on populations, which are not adequately represented in the large datasets of European biobanks, such as the Italian one. This work aimed to analyze which PGS had the best performance within the Italian population.</p><p><strong>Methods: </strong>We used two Italian independent cohorts: the EPICOR case-control study (576 individuals) and the Atherosclerosis, Thrombosis, and Vascular Biology (ATVB) Italian study (3359 individuals). We evaluated 266 PGS for cardiovascular disease risk from the PGS Catalog, selecting 51 for CAD.</p><p><strong>Results: </strong>Distributions between patients and controls were significantly different for 49 scores (<i>p</i>-value < 0.01). Only five PGS have been trained and tested for the European population specifically. PGS003727 demonstrated to be the most accurate when evaluated independently (EPICOR AUC = 0.68; ATVB AUC = 0.80). Taking into account the conventional CAD risk factors further enhanced the performance of the model, particularly in the ATVB study (<i>p</i>-value = 0.0003).</p><p><strong>Conclusions: </strong>European CAD PGS could have different risk estimates in peculiar populations, such as the Italian one, as well as in various geographical macro areas. Therefore, further evaluation is recommended for clinical applicability.</p>","PeriodicalId":16722,"journal":{"name":"Journal of Personalized Medicine","volume":"14 10","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11508882/pdf/","citationCount":"0","resultStr":"{\"title\":\"Population Heterogeneity and Selection of Coronary Artery Disease Polygenic Scores.\",\"authors\":\"Carla Debernardi, Angelo Savoca, Alessandro De Gregorio, Elisabetta Casalone, Miriam Rosselli, Elton Jalis Herman, Cecilia Di Primio, Rosario Tumino, Sabina Sieri, Paolo Vineis, Salvatore Panico, Carlotta Sacerdote, Diego Ardissino, Rosanna Asselta, Giuseppe Matullo\",\"doi\":\"10.3390/jpm14101025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background/objectives: </strong>The identification of coronary artery disease (CAD) high-risk individuals is a major clinical need for timely diagnosis and intervention. Many different polygenic scores (PGSs) for CAD risk are available today to estimate the genetic risk. It is necessary to carefully choose the score to use, in particular for studies on populations, which are not adequately represented in the large datasets of European biobanks, such as the Italian one. This work aimed to analyze which PGS had the best performance within the Italian population.</p><p><strong>Methods: </strong>We used two Italian independent cohorts: the EPICOR case-control study (576 individuals) and the Atherosclerosis, Thrombosis, and Vascular Biology (ATVB) Italian study (3359 individuals). We evaluated 266 PGS for cardiovascular disease risk from the PGS Catalog, selecting 51 for CAD.</p><p><strong>Results: </strong>Distributions between patients and controls were significantly different for 49 scores (<i>p</i>-value < 0.01). Only five PGS have been trained and tested for the European population specifically. PGS003727 demonstrated to be the most accurate when evaluated independently (EPICOR AUC = 0.68; ATVB AUC = 0.80). Taking into account the conventional CAD risk factors further enhanced the performance of the model, particularly in the ATVB study (<i>p</i>-value = 0.0003).</p><p><strong>Conclusions: </strong>European CAD PGS could have different risk estimates in peculiar populations, such as the Italian one, as well as in various geographical macro areas. Therefore, further evaluation is recommended for clinical applicability.</p>\",\"PeriodicalId\":16722,\"journal\":{\"name\":\"Journal of Personalized Medicine\",\"volume\":\"14 10\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11508882/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Personalized Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/jpm14101025\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jpm14101025","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Population Heterogeneity and Selection of Coronary Artery Disease Polygenic Scores.
Background/objectives: The identification of coronary artery disease (CAD) high-risk individuals is a major clinical need for timely diagnosis and intervention. Many different polygenic scores (PGSs) for CAD risk are available today to estimate the genetic risk. It is necessary to carefully choose the score to use, in particular for studies on populations, which are not adequately represented in the large datasets of European biobanks, such as the Italian one. This work aimed to analyze which PGS had the best performance within the Italian population.
Methods: We used two Italian independent cohorts: the EPICOR case-control study (576 individuals) and the Atherosclerosis, Thrombosis, and Vascular Biology (ATVB) Italian study (3359 individuals). We evaluated 266 PGS for cardiovascular disease risk from the PGS Catalog, selecting 51 for CAD.
Results: Distributions between patients and controls were significantly different for 49 scores (p-value < 0.01). Only five PGS have been trained and tested for the European population specifically. PGS003727 demonstrated to be the most accurate when evaluated independently (EPICOR AUC = 0.68; ATVB AUC = 0.80). Taking into account the conventional CAD risk factors further enhanced the performance of the model, particularly in the ATVB study (p-value = 0.0003).
Conclusions: European CAD PGS could have different risk estimates in peculiar populations, such as the Italian one, as well as in various geographical macro areas. Therefore, further evaluation is recommended for clinical applicability.
期刊介绍:
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.