Sarah A Abramowitz, Kristin Boulier, Karl Keat, Katherine Cardone, Manu Shivakumar, John M. DePaolo, Renae M. Judy, Penn Medicine BioBank, Dokyoon Kim, Daniel J Rader, Marylyn D Ritchie, Benjamin F Voight, Bogdan Pasaniuc, Michael Levin, Scott M. Damrauer
{"title":"冠状动脉疾病多基因风险评分的人群表现和个体一致性","authors":"Sarah A Abramowitz, Kristin Boulier, Karl Keat, Katherine Cardone, Manu Shivakumar, John M. DePaolo, Renae M. Judy, Penn Medicine BioBank, Dokyoon Kim, Daniel J Rader, Marylyn D Ritchie, Benjamin F Voight, Bogdan Pasaniuc, Michael Levin, Scott M. Damrauer","doi":"10.1101/2024.07.25.24310931","DOIUrl":null,"url":null,"abstract":"Importance: Polygenic risk scores (PRSs) for coronary artery disease (CAD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease liability is a critical consideration for clinical implementation that remains uncharacterized. Objective:\nCharacterize the reliability of CAD PRSs that perform equivalently at the population level at predicting individual-level risk. Design:\nCross-sectional Study. Setting:\nAll of Us Research Program (AOU), Penn Medicine Biobank (PMBB), and UCLA ATLAS Precision Health Biobank. Participants: Volunteers of diverse genetic backgrounds enrolled in AOU, PMBB, and UCLA with available electronic health record and genotyping data. Exposures:\nPolygenic risk for CAD from previously published PRSs and new PRSs developed separately from the testing cohorts. Main Outcomes and Measures:\nSets of CAD PRSs that perform population prediction equivalently were identified by comparing calibration and discrimination (Brier score and AUROC) of generalized linear models of prevalent CAD using Bayesian analysis of variance. Among equivalently performing scores, individual-level agreement between risk estimates was tested with intraclass correlation (ICC) and Light's Kappa, measures of inter-rater reliability. Results:\n50 PRSs were calculated for 171,095 AOU participants. When included in a model of prevalent CAD, 48 scores had practically equivalent Brier scores and AUROCs (region of practical equivalence = 0.02). Across these scores, 84% of participants had at least one score in both the top and bottom risk quintile. Continuous agreement of individual risk predictions from the 48 scores was poor, with an ICC of 0.351 (95% CI; 0.349, 0.352). Agreement between two statistically equivalent scores was moderate, with an ICC of 0.649 (95% CI; 0.646, 0.652). Light's Kappa, used to evaluate consistency of assignment to high-risk thresholds, did not exceed 0.56 (interpreted as 'fair') across statistically and practically equivalent scores. Repeating the analysis among 41,193 PMBB and 50,748 UCLA participants yielded different sets of statistically and practically equivalent scores which also lacked strong individual agreement. Conclusions and Relevance:\nAcross three diverse biobanks, CAD PRSs that performed equivalently at the population level produced unreliable individual risk estimates. Approaches to clinical implementation of CAD PRSs must consider the potential for discordant individual risk estimates from otherwise indistinguishable scores.","PeriodicalId":501375,"journal":{"name":"medRxiv - Genetic and Genomic Medicine","volume":"94 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Population Performance and Individual Agreement of Coronary Artery Disease Polygenic Risk Scores\",\"authors\":\"Sarah A Abramowitz, Kristin Boulier, Karl Keat, Katherine Cardone, Manu Shivakumar, John M. DePaolo, Renae M. Judy, Penn Medicine BioBank, Dokyoon Kim, Daniel J Rader, Marylyn D Ritchie, Benjamin F Voight, Bogdan Pasaniuc, Michael Levin, Scott M. Damrauer\",\"doi\":\"10.1101/2024.07.25.24310931\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Importance: Polygenic risk scores (PRSs) for coronary artery disease (CAD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease liability is a critical consideration for clinical implementation that remains uncharacterized. Objective:\\nCharacterize the reliability of CAD PRSs that perform equivalently at the population level at predicting individual-level risk. Design:\\nCross-sectional Study. Setting:\\nAll of Us Research Program (AOU), Penn Medicine Biobank (PMBB), and UCLA ATLAS Precision Health Biobank. Participants: Volunteers of diverse genetic backgrounds enrolled in AOU, PMBB, and UCLA with available electronic health record and genotyping data. Exposures:\\nPolygenic risk for CAD from previously published PRSs and new PRSs developed separately from the testing cohorts. Main Outcomes and Measures:\\nSets of CAD PRSs that perform population prediction equivalently were identified by comparing calibration and discrimination (Brier score and AUROC) of generalized linear models of prevalent CAD using Bayesian analysis of variance. Among equivalently performing scores, individual-level agreement between risk estimates was tested with intraclass correlation (ICC) and Light's Kappa, measures of inter-rater reliability. Results:\\n50 PRSs were calculated for 171,095 AOU participants. When included in a model of prevalent CAD, 48 scores had practically equivalent Brier scores and AUROCs (region of practical equivalence = 0.02). Across these scores, 84% of participants had at least one score in both the top and bottom risk quintile. Continuous agreement of individual risk predictions from the 48 scores was poor, with an ICC of 0.351 (95% CI; 0.349, 0.352). Agreement between two statistically equivalent scores was moderate, with an ICC of 0.649 (95% CI; 0.646, 0.652). Light's Kappa, used to evaluate consistency of assignment to high-risk thresholds, did not exceed 0.56 (interpreted as 'fair') across statistically and practically equivalent scores. Repeating the analysis among 41,193 PMBB and 50,748 UCLA participants yielded different sets of statistically and practically equivalent scores which also lacked strong individual agreement. Conclusions and Relevance:\\nAcross three diverse biobanks, CAD PRSs that performed equivalently at the population level produced unreliable individual risk estimates. Approaches to clinical implementation of CAD PRSs must consider the potential for discordant individual risk estimates from otherwise indistinguishable scores.\",\"PeriodicalId\":501375,\"journal\":{\"name\":\"medRxiv - Genetic and Genomic Medicine\",\"volume\":\"94 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Genetic and Genomic Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.07.25.24310931\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Genetic and Genomic Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.25.24310931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Population Performance and Individual Agreement of Coronary Artery Disease Polygenic Risk Scores
Importance: Polygenic risk scores (PRSs) for coronary artery disease (CAD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease liability is a critical consideration for clinical implementation that remains uncharacterized. Objective:
Characterize the reliability of CAD PRSs that perform equivalently at the population level at predicting individual-level risk. Design:
Cross-sectional Study. Setting:
All of Us Research Program (AOU), Penn Medicine Biobank (PMBB), and UCLA ATLAS Precision Health Biobank. Participants: Volunteers of diverse genetic backgrounds enrolled in AOU, PMBB, and UCLA with available electronic health record and genotyping data. Exposures:
Polygenic risk for CAD from previously published PRSs and new PRSs developed separately from the testing cohorts. Main Outcomes and Measures:
Sets of CAD PRSs that perform population prediction equivalently were identified by comparing calibration and discrimination (Brier score and AUROC) of generalized linear models of prevalent CAD using Bayesian analysis of variance. Among equivalently performing scores, individual-level agreement between risk estimates was tested with intraclass correlation (ICC) and Light's Kappa, measures of inter-rater reliability. Results:
50 PRSs were calculated for 171,095 AOU participants. When included in a model of prevalent CAD, 48 scores had practically equivalent Brier scores and AUROCs (region of practical equivalence = 0.02). Across these scores, 84% of participants had at least one score in both the top and bottom risk quintile. Continuous agreement of individual risk predictions from the 48 scores was poor, with an ICC of 0.351 (95% CI; 0.349, 0.352). Agreement between two statistically equivalent scores was moderate, with an ICC of 0.649 (95% CI; 0.646, 0.652). Light's Kappa, used to evaluate consistency of assignment to high-risk thresholds, did not exceed 0.56 (interpreted as 'fair') across statistically and practically equivalent scores. Repeating the analysis among 41,193 PMBB and 50,748 UCLA participants yielded different sets of statistically and practically equivalent scores which also lacked strong individual agreement. Conclusions and Relevance:
Across three diverse biobanks, CAD PRSs that performed equivalently at the population level produced unreliable individual risk estimates. Approaches to clinical implementation of CAD PRSs must consider the potential for discordant individual risk estimates from otherwise indistinguishable scores.