Combining European and US risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study

被引:8
|
作者
de La Harpe, Roxane [1 ,2 ]
Thorball, Christian W. [3 ,4 ]
Redin, Claire [3 ,4 ]
Fournier, Stephane [2 ,5 ]
Mueller, Olivier [2 ,5 ]
Strambo, Davide [2 ,6 ]
Michel, Patrik [2 ,6 ]
Vollenweider, Peter [1 ,2 ]
Marques-Vidal, Pedro [1 ,2 ]
Fellay, Jacques [3 ,4 ,7 ]
Vaucher, Julien [1 ,2 ]
机构
[1] Lausanne Univ Hosp, Dept Med, Div Internal Med, Rue Bugnon 46, CH-1011 Lausanne, Switzerland
[2] Univ Lausanne, Rue Bugnon 46, CH-1011 Lausanne, Switzerland
[3] Lausanne Univ Hosp, Biomed Data Sci Ctr, Precis Med Unit, Chemin Roches 1A-1B, CH-1010 Lausanne, Switzerland
[4] Univ Lausanne, Chemin Roches 1A-1B, CH-1010 Lausanne, Switzerland
[5] Lausanne Univ Hosp, Heart & Vessel Dept, Div Cardiol, Rue Bugnon 46, CH-1011 Lausanne, Switzerland
[6] Lausanne Univ Hosp, Dept Neurosci, Div Neurol, Rue Bugnon 46, CH-1011 Lausanne, Switzerland
[7] Ecole Polytech Fed Lausanne, Sch Life Sci, Stn 19, CH-1015 Lausanne, Switzerland
基金
瑞士国家科学基金会;
关键词
Adult; Primary prevention; Cardiovascular disease; Genetic predisposition to disease; Risk; Risk assessment; Sensitivity and specificity; ROC curve; Predictive value of tests; Polygenic risk score; CORONARY-ARTERY-DISEASE; VALIDATION; ACCURACY; COMMON; WOMEN;
D O I
10.1093/eurjpc/zwad012
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Lay Summary The aim of this study is to determine whether using polygenic risk scores improves the prediction of atherosclerotic cardiovascular disease risk when combined with clinical scores currently recommended by European and US guidelines on cardiovascular prevention. Aims A polygenic risk score (PRS) has the potential to improve individual atherosclerotic cardiovascular disease (ASCVD) risk assessment. To determine whether a PRS combined with two clinical risk scores, the Systematic COronary Risk Evaluation 2 (SCORE2) and the Pooled Cohort Equation (PCE) improves the prediction of ASCVD. Methods and results Using a population-based European prospective cohort, with 6733 participants at the baseline (2003-2006), the PRS presenting the best predictive accuracy was combined with SCORE2 and PCE to assess their joint performances for predicting ASCVD Discrimination, calibration, Cox proportional hazard regression, and net reclassification index were assessed. : 4218 subjects (53% women; median age, 53.4 years), with 363 prevalent and incident ASCVD, were used to compare four PRSs. The metaGRS_CAD PRS presented the best predictive capacity (AUROC = 0.77) and was used in the following analyses. 3383 subjects (median follow-up of 14.4 years), with 190 first-incident ASCVD, were employed to test ASCVD risk prediction. The changes in C statistic between SCORE2 and PCE models and those combining metaGRS_CAD with SCORE2 and PCE were 0.008 (95% CI, -0.00008-0.02, P = 0.05) and 0.007 (95% CI, 0.005-0.01, P = 0.03), respectively. Reclassification was improved for people at clinically determined intermediate-risk for both clinical scores [NRI of 9.6% (95% CI, 0.3-18.8) and 12.0% (95% CI, 1.5-22.6) for SCORE2 and PCE, respectively]. Conclusion Combining a PRS with clinical risk scores significantly improved the reclassification of risk for incident ASCVD for subjects in the clinically determined intermediate-risk category. Introducing PRSs in clinical practice may refine cardiovascular prevention for subgroups of patients in whom prevention strategies are uncertain.
引用
收藏
页码:561 / 571
页数:11
相关论文
共 50 条
  • [31] Polygenic scores in real-world cardiovascular risk prediction: the path forward for assessing worth?
    Pillutla, Virimchi
    Aragam, Krishna G.
    EUROPEAN HEART JOURNAL, 2024, 45 (34) : 3161 - 3163
  • [32] Which are the opportunities and current challenges for the use of polygenic risk scores in risk prediction and the prevention of common adult onset conditions?
    Botta, G.
    EUROPEAN JOURNAL OF PUBLIC HEALTH, 2020, 30
  • [33] Integrating Polygenic Risk Scores into clinical breast cancer models improves prediction in diverse cohorts
    Bolli, Alessandro
    Kulm, Scott
    Kintzle, Jen
    Di Domenico, Paolo
    Botta, Giordano
    Busby, George
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2024, 32 : 54 - 55
  • [34] METHODOLOGICAL AND PERFORMANCE IMPLICATIONS OF ADDING POLYGENIC RISK SCORES TO EHR-BASED PREDICTION MODELS
    Morley, Theodore
    Choi, Karmel
    Michael, Ripperger
    Drew, Willimitis
    Kang, Jooeun
    Smoller, Jordan
    Walsh, Colin
    Ruderfer, Douglas
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2021, 51 : E32 - E32
  • [35] Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19
    Cordova-Palomera, Aldo
    Siffel, Csaba
    DeBoever, Chris
    Wong, Emily
    Diogo, Dorothee
    Szalma, Sandor
    PLOS ONE, 2023, 18 (05):
  • [36] Integrating polygenic risk scores into clinical breast cancer models: Influence on prediction in diverse cohorts
    Busby, George B. J.
    Bolli, Alessandro
    Kintzle, Jen
    Kulm, Scott
    Neary, John
    Di Domenico, Paolo
    Morganstern, Daniel
    Botta, Giordano
    JOURNAL OF CLINICAL ONCOLOGY, 2023, 41 (16)
  • [37] Risk prediction of ischemic heart disease using plasma proteomics, conventional risk factors and polygenic scores in Chinese and European adults
    Mazidi, Mohsen
    Wright, Neil
    Yao, Pang
    Kartsonaki, Christiana
    Millwood, Iona Y.
    Fry, Hannah
    Said, Saredo
    Pozarickij, Alfred
    Pei, Pei
    Chen, Yiping
    Wang, Baihan
    Avery, Daniel
    Du, Huaidong
    Schmidt, Dan Valle
    Yang, Ling
    Lv, Jun
    Yu, Canqing
    Sun, Dianjianyi
    Chen, Junshi
    Hill, Michael
    Peto, Richard
    Collins, Rory
    Bennett, Derrick A.
    Walters, Robin G.
    Li, Liming
    Clarke, Robert
    Chen, Zhengming
    China Kadoorie Biobank Collaborative Group
    EUROPEAN JOURNAL OF EPIDEMIOLOGY, 2024, 39 (11) : 1229 - 1240
  • [38] Adherence to 2020 ESC recommendations on physical activity in a population with different cardiovascular risk levels: A prospective population-based study from the CoLaus/PsyCoLaus study
    Hauser, Rafael
    Harpe, Roxane de la
    Vollenweider, Peter
    Hullin, Roger
    Vaucher, Julien
    Marques-Vidal, Pedro
    Mean, Marie
    PREVENTIVE MEDICINE REPORTS, 2024, 42
  • [39] Preeclampsia prediction with maternal and paternal polygenic risk scores: the TMM BirThree Cohort Study
    Hisashi Ohseto
    Mami Ishikuro
    Taku Obara
    Akira Narita
    Ippei Takahashi
    Genki Shinoda
    Aoi Noda
    Keiko Murakami
    Masatsugu Orui
    Noriyuki Iwama
    Masahiro Kikuya
    Hirohito Metoki
    Junichi Sugawara
    Gen Tamiya
    Shinichi Kuriyama
    Scientific Reports, 15 (1)
  • [40] Genetic risk scores used in cardiovascular disease prediction models: a systematic review
    Yun, Hyunok
    Noh, Nan Iee
    Lee, Eun Young
    REVIEWS IN CARDIOVASCULAR MEDICINE, 2022, 23 (01)