| Title: | Leveraging Human Genetics to Estimate Clinical Risk Reductions Achievable by Inhibiting Factor XI |
| Journal: | Stroke |
| Published: | 27 Sep 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/31558144/ |
| DOI: | https://doi.org/10.1161/strokeaha.119.026545 |
Publication 9041
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Abstract
Background and Purpose- Coagulation factor XI (FXI) is a novel target for antithrombotic therapy addressed by various therapeutic modalities currently in clinical development. The expected magnitude of thrombotic event reduction mediated by targeting FXI is unclear. Methods- We analyzed the association of 2 common genetic variants, which alter levels of FXI, with a range of human phenotypes. We combined variants into a genetic score standardized to a 30% increase in relative activated partial thromboplastin time, equivalent to what can be achieved with pharmacological FXI reduction. Using data from 371 695 participants in the United Kingdom Biobank and 2 large-scale genome-wide association studies, we examined the effect of this FXI score on thrombotic and bleeding end points. Results- Genetic disposition to lower FXI levels was associated with reduced risks of venous thrombosis (odds ratio, 95% CI; P value; odds ratio=0.1, 0.07-0.14; P=3×10-43) and ischemic stroke (odds ratio=0.47, 0.36-0.61; P=2×10-8) but not with major bleeding (odds ratio=0.7, 0.45-1.04; P=0.0739). The observed relative risk reductions were consistent within a range of subgroups that were at high risk for thrombosis. Consistently, we observed higher absolute risk reductions conferred by genetically lower FXI levels in high-risk subgroups, such as patients with atrial fibrillation. Conclusions- Human genetic data suggest that pharmacological inhibition of FXI may achieve considerable reductions in ischemic stroke risk without clear evidence for an associated risk of major bleeding. The quantitative framework developed can be used to support the estimation of achievable risk reductions with pharmacological modulation of FXI.</p>
11 Authors
- Benjamin Georgi
- Johanna Mielke
- Mark Chaffin
- Amit V. Khera
- Lian Gelis
- Hardi Mundl
- J.J.J. van Giezen
- Patrick Ellinor
- Sekar Kathiresan
- Karl Ziegelbauer
- Daniel F. Freitag
1 Application
| Application ID | Title |
|---|---|
| 28807 | Use of UK Biobank genetic data to support drug discovery and development |
Enabling scientific discoveries that improve human health