Combining Clinical and Polygenic Risk Improves Stroke Prediction among Individuals with Atrial Fibrillation
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Combining Clinical and Polygenic Risk Improves Stroke Prediction among Individuals with Atrial Fibrillation. / O'Sullivan, Jack W.; Shcherbina, Anna; Justesen, Johanne M.; Turakhia, Mintu; Perez, Marco; Wand, Hannah; Tcheandjieu, Catherine; Clarke, Shoa L.; Rivas, Manuel A.; Ashley, Euan A.
I: Circulation: Genomic and Precision Medicine, Bind 14, Nr. 3, e003168, 2021, s. 339-347.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Combining Clinical and Polygenic Risk Improves Stroke Prediction among Individuals with Atrial Fibrillation
AU - O'Sullivan, Jack W.
AU - Shcherbina, Anna
AU - Justesen, Johanne M.
AU - Turakhia, Mintu
AU - Perez, Marco
AU - Wand, Hannah
AU - Tcheandjieu, Catherine
AU - Clarke, Shoa L.
AU - Rivas, Manuel A.
AU - Ashley, Euan A.
N1 - Publisher Copyright: © 2021 Cambridge University Press. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Background: Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable; however, current risk stratification tools (CHA2DS2-VASc) do not include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods: Using data from the largest available genome-wide association study in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results: Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved Net Reclassification Index (2.3% [95% CI, 1.3%-3.0%]) and fit (χ2P=0.002). Using this improved tool, >115 000 people with AF would have improved risk classification in the United States. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (hazard ratio, 1.13 per 1 SD [95% CI, 1.06-1.23]). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson correlation coefficient, -0.018). Conclusions: In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors; however, the prediction of stroke remains challenging.
AB - Background: Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable; however, current risk stratification tools (CHA2DS2-VASc) do not include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods: Using data from the largest available genome-wide association study in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results: Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved Net Reclassification Index (2.3% [95% CI, 1.3%-3.0%]) and fit (χ2P=0.002). Using this improved tool, >115 000 people with AF would have improved risk classification in the United States. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (hazard ratio, 1.13 per 1 SD [95% CI, 1.06-1.23]). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson correlation coefficient, -0.018). Conclusions: In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors; however, the prediction of stroke remains challenging.
KW - atrial fibrillation
KW - biomarkers
KW - genetics
KW - ischemic stroke
KW - risk factor
U2 - 10.1161/CIRCGEN.120.003168
DO - 10.1161/CIRCGEN.120.003168
M3 - Journal article
C2 - 34029116
AN - SCOPUS:85108167764
VL - 14
SP - 339
EP - 347
JO - Circulation. Genomic and precision medicine
JF - Circulation. Genomic and precision medicine
SN - 2574-8300
IS - 3
M1 - e003168
ER -
ID: 276695870