The Causality between Diabetes and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study
- PMID: 36812941
- PMCID: PMC10460955
- DOI: 10.1055/a-2040-4850
The Causality between Diabetes and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study
Abstract
Background: Diabetes was considered as a risk factor for venous thromboembolism (VTE), but conflicting findings have been reported from observational studies. This study aimed at investigating the causal associations of type 1 and type 2 diabetes with VTE, including deep vein thrombosis (DVT) and pulmonary embolism (PE).
Methods: We designed a bidirectional two-sample Mendelian randomization (MR) analysis by using summary-level data from large genome-wide association studies performed in European individuals. Inverse variance weighting with multiplicative random effect method was used to obtain the primary causal estimates, and weighted median, weighted mode, and MR egger regression were replenished as sensitivity analyses to test the robustness of the results.
Results: We found no significant causal effects of type 1 diabetes on VTE (odds ratio [OR]: 0.98, 95% confidence interval [CI]: 0.96-1.00, p = 0.043), DVT (OR: 0.98, 95% CI: 0.95-1.00, p = 0.102), and PE (OR: 0.98, 95% CI: 0.96-1.01, p = 0.160). Similarly, no significant associations of type 2 diabetes with VTE (OR: 0.97, 95% CI: 0.91-1.03, p = 0.291), DVT (OR: 0.96, 95% CI: 0.89-1.03, p = 0.255), and PE (OR: 0.97, 95% CI: 0.90-1.04, p = 0.358) were also observed. Results from multivariable MR analysis were consistent with the findings in univariable analysis. In the other direction, the results showed no significant causal effects of VTE on type 1 and type 2 diabetes.
Conclusion: This MR analysis demonstrated no significant causal associations of type 1 and type 2 diabetes with VTE in both directions, in conflict with previous observational studies reporting positive association, which provided clues for understanding the underlying pathogenesis of diabetes and VTE.
The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Conflict of interest statement
None declared.
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