scholarly journals Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries

Author(s):  
Michael E. Weale ◽  
Fernando Riveros-Mckay ◽  
Saskia Selzam ◽  
Priyanka Seth ◽  
Rachel Moore ◽  
...  
2017 ◽  
Vol 11 (3) ◽  
pp. 725-732.e5 ◽  
Author(s):  
Martine Paquette ◽  
Michael Chong ◽  
Sébastien Thériault ◽  
Robert Dufour ◽  
Guillaume Paré ◽  
...  

Author(s):  
Fernando Riveros-Mckay ◽  
Michael E. Weale ◽  
Rachel Moore ◽  
Saskia Selzam ◽  
Eva Krapohl ◽  
...  

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.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1645-P
Author(s):  
JOHANNE TREMBLAY ◽  
REDHA ATTAOUA ◽  
MOUNSIF HALOUI ◽  
RAMZAN TAHIR ◽  
CAROLE LONG ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 304-OR
Author(s):  
MICHAEL L. MULTHAUP ◽  
RYOSUKE KITA ◽  
NICHOLAS ERIKSSON ◽  
STELLA ASLIBEKYAN ◽  
JANIE SHELTON ◽  
...  

2015 ◽  
Vol 11 (7S_Part_19) ◽  
pp. P872-P872 ◽  
Author(s):  
Valentina Escott-Price ◽  
Rebecca Sims ◽  
Denise Harold ◽  
Maria Vronskaya ◽  
Peter Holmans ◽  
...  

2020 ◽  
Vol 7 (1) ◽  
pp. e000755
Author(s):  
Matthew Moll ◽  
Sharon M. Lutz ◽  
Auyon J. Ghosh ◽  
Phuwanat Sakornsakolpat ◽  
Craig P. Hersh ◽  
...  

IntroductionFamily history is a risk factor for chronic obstructive pulmonary disease (COPD). We previously developed a COPD risk score from genome-wide genetic markers (Polygenic Risk Score, PRS). Whether the PRS and family history provide complementary or redundant information for predicting COPD and related outcomes is unknown.MethodsWe assessed the predictive capacity of family history and PRS on COPD and COPD-related outcomes in non-Hispanic white (NHW) and African American (AA) subjects from COPDGene and ECLIPSE studies. We also performed interaction and mediation analyses.ResultsIn COPDGene, family history and PRS were significantly associated with COPD in a single model (PFamHx <0.0001; PPRS<0.0001). Similar trends were seen in ECLIPSE. The area under the receiver operator characteristic curve for a model containing family history and PRS was significantly higher than a model with PRS (p=0.00035) in NHWs and a model with family history (p<0.0001) alone in NHWs and AAs. Both family history and PRS were significantly associated with measures of quantitative emphysema and airway thickness. There was a weakly positive interaction between family history and the PRS under the additive, but not multiplicative scale in NHWs (relative excess risk due to interaction=0.48, p=0.04). Mediation analyses found that a significant proportion of the effect of family history on COPD was mediated through PRS in NHWs (16.5%, 95% CI 9.4% to 24.3%), but not AAs.ConclusionFamily history and the PRS provide complementary information for predicting COPD and related outcomes. Future studies can address the impact of obtaining both measures in clinical practice.


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