Cargando…
Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction
BACKGROUND: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. METHODS: Using the UK Biobank resource, we developed our own polygenic r...
Autores principales: | , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284388/ https://www.ncbi.nlm.nih.gov/pubmed/33651632 http://dx.doi.org/10.1161/CIRCGEN.120.003304 |
_version_ | 1783723389283729408 |
---|---|
author | Riveros-Mckay, Fernando Weale, Michael E. Moore, Rachel Selzam, Saskia Krapohl, Eva Sivley, R. Michael Tarran, William A. Sørensen, Peter Lachapelle, Alexander S. Griffiths, Jonathan A. Saffari, Ayden Deanfield, John Spencer, Chris C.A. Hippisley-Cox, Julia Hunter, David J. O’Sullivan, Jack W. Ashley, Euan A. Plagnol, Vincent Donnelly, Peter |
author_facet | Riveros-Mckay, Fernando Weale, Michael E. Moore, Rachel Selzam, Saskia Krapohl, Eva Sivley, R. Michael Tarran, William A. Sørensen, Peter Lachapelle, Alexander S. Griffiths, Jonathan A. Saffari, Ayden Deanfield, John Spencer, Chris C.A. Hippisley-Cox, Julia Hunter, David J. O’Sullivan, Jack W. Ashley, Euan A. Plagnol, Vincent Donnelly, Peter |
author_sort | Riveros-Mckay, Fernando |
collection | PubMed |
description | BACKGROUND: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. METHODS: Using the UK Biobank resource, we developed our own polygenic risk score for coronary artery disease (CAD). We used an additional 60 000 UK Biobank individuals to develop an integrated risk tool (IRT) that combined our polygenic risk score with established risk tools (either the American Heart Association/American College of Cardiology pooled cohort equations [PCE] or UK QRISK3), and we tested our IRT in an additional, independent set of 186 451 UK Biobank individuals. RESULTS: The novel CAD polygenic risk score shows superior predictive power for CAD events, compared with other published polygenic risk scores, and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an IRT, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared with 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI, 4.7–7.0). When individuals were stratified into age-by-sex subgroups, the improvement was larger for all subgroups (range, 8.3%–15.4%), with the best performance in 40- to 54-year-old men (15.4% [95% CI, 11.6–19.3]). Comparable results were found using a different risk tool (QRISK3) and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12 000 deaths in the United States over a 5-year period. CONCLUSIONS: An IRT that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person’s polygenic risk. |
format | Online Article Text |
id | pubmed-8284388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-82843882021-08-02 Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction Riveros-Mckay, Fernando Weale, Michael E. Moore, Rachel Selzam, Saskia Krapohl, Eva Sivley, R. Michael Tarran, William A. Sørensen, Peter Lachapelle, Alexander S. Griffiths, Jonathan A. Saffari, Ayden Deanfield, John Spencer, Chris C.A. Hippisley-Cox, Julia Hunter, David J. O’Sullivan, Jack W. Ashley, Euan A. Plagnol, Vincent Donnelly, Peter Circ Genom Precis Med Original Articles BACKGROUND: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. METHODS: Using the UK Biobank resource, we developed our own polygenic risk score for coronary artery disease (CAD). We used an additional 60 000 UK Biobank individuals to develop an integrated risk tool (IRT) that combined our polygenic risk score with established risk tools (either the American Heart Association/American College of Cardiology pooled cohort equations [PCE] or UK QRISK3), and we tested our IRT in an additional, independent set of 186 451 UK Biobank individuals. RESULTS: The novel CAD polygenic risk score shows superior predictive power for CAD events, compared with other published polygenic risk scores, and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an IRT, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared with 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI, 4.7–7.0). When individuals were stratified into age-by-sex subgroups, the improvement was larger for all subgroups (range, 8.3%–15.4%), with the best performance in 40- to 54-year-old men (15.4% [95% CI, 11.6–19.3]). Comparable results were found using a different risk tool (QRISK3) and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12 000 deaths in the United States over a 5-year period. CONCLUSIONS: An IRT that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person’s polygenic risk. Lippincott Williams & Wilkins 2021-03-02 /pmc/articles/PMC8284388/ /pubmed/33651632 http://dx.doi.org/10.1161/CIRCGEN.120.003304 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Circulation: Genomic and Precision Medicine is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited. |
spellingShingle | Original Articles Riveros-Mckay, Fernando Weale, Michael E. Moore, Rachel Selzam, Saskia Krapohl, Eva Sivley, R. Michael Tarran, William A. Sørensen, Peter Lachapelle, Alexander S. Griffiths, Jonathan A. Saffari, Ayden Deanfield, John Spencer, Chris C.A. Hippisley-Cox, Julia Hunter, David J. O’Sullivan, Jack W. Ashley, Euan A. Plagnol, Vincent Donnelly, Peter Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title | Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title_full | Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title_fullStr | Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title_full_unstemmed | Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title_short | Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction |
title_sort | integrated polygenic tool substantially enhances coronary artery disease prediction |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284388/ https://www.ncbi.nlm.nih.gov/pubmed/33651632 http://dx.doi.org/10.1161/CIRCGEN.120.003304 |
work_keys_str_mv | AT riverosmckayfernando integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT wealemichaele integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT moorerachel integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT selzamsaskia integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT krapohleva integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT sivleyrmichael integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT tarranwilliama integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT sørensenpeter integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT lachapellealexanders integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT griffithsjonathana integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT saffariayden integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT deanfieldjohn integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT spencerchrisca integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT hippisleycoxjulia integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT hunterdavidj integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT osullivanjackw integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT ashleyeuana integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT plagnolvincent integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction AT donnellypeter integratedpolygenictoolsubstantiallyenhancescoronaryarterydiseaseprediction |