| Autor: |
Kuan-Han H. Wu, Nicholas J. Douville, Matthew C. Konerman, Michael R. Mathis, Scott L. Hummel, Brooke N. Wolford, Ida Surakka, Sarah E. Graham, Hyeon Joo, Jibril Hirbo, Nancy J. Cox, Simon Lee, Michael Preuss, Ruth J.F. Loos, Mark J. Daly, Benjamin M. Neale, Wei Zhou, Whitney E. Hornsby, Cristen. J. Willer |
| Rok vydání: |
2021 |
| DOI: |
10.1101/2021.12.06.21267389 |
| Popis: |
SUMMARYIdentifying individuals at high risk of heart failure during precursor stages could allow for earlier initiation of treatments to modify disease progression. We performed a GWAS meta- analysis to generate a heart failure (HF) polygenic risk score (PRS) then tested the association with phenotypic subtypes (reduced ejection fraction [HFrEF] and preserved ejection fraction [HFpEF]) to evaluate the value of polygenic risk prediction. Results from the European-ancestry analysis showed that an ancestry-matched PRS, calculated from GBMI meta-analysis outperformed the previous HF GWAS (HERMES), yielding an adjusted odds ratio (aOR) of 2.27 (95% CI: 2.05-2.51; p: 1.76×10−56) from GBMI compared to 1.30 (95% CI: 1.18-1.44; p: 1.42×10− 7) from HERMES, and 1.49 (95% CI: 1.33-1.66; p: 8.38×10−13) compared to 1.17 (95% CI: 1.05- 1.31; p: 0.004) for HFrEF and HFpEF, respectively. Next, we evaluated the performance differences between ancestry-matched and multi-ancestry PRS in the African American cohort. The GBMI multi-ancestry GWAS-based PRS had a significant aOR of 1.49 (p: 0.006). Findings suggest that a PRS for heart failure derived from the GBMI multi-ancestry study is useful in predicting HFrEF, but less powerful in predicting HFpEF in an independent cohort. The difficulty in predicting HFpEF could result from the GBMI HF phenotype, preferencing HFrEF over HFpEF, and/or greater genetic heterogeneity in the HFpEF phenotype. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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