Dataset Information

Model-dependent contributions of FXII and FXI to venous thrombosis in mice.

ABSTRACT:

Background

The intrinsic pathway factors (F) XII and FXI have been shown to contribute to thrombosis in animal models. We assessed the role of FXII and FXI in venous thrombosis in three distinct mouse models.

Methods

Venous thrombosis was assessed in mice genetically deficient for either FXII or FXI. Three models were used: the inferior vena cava (IVC) stasis, IVC stenosis, and femoral vein electrolytic injury models.

Results

In the IVC stasis model, FXII and FXI deficiency did not affect the size of thrombi but their absence was associated with decreased levels of fibrin(ogen) and an increased level of the neutrophil extracellular trap marker citrullinated histone H3. In contrast, a deficiency of either FXII or FXI resulted in a significant and equivalent reduction in thrombus weight and incidence of thrombus formation in the IVC stenosis model. Thrombi formed in the IVC stenosis model contained significantly higher levels of citrullinated histone H3 compared with the thrombi formed in the IVC stasis model. Deletion of either FXII or FXI also resulted in a significant and equivalent reduction in both fibrin and platelet accumulation in the femoral vein electrolytic injury model.

Conclusions

Collectively, these data indicate that FXII and FXI contribute to the size of venous thrombosis in models with blood flow and thrombus composition in a stasis model. This study also demonstrates the importance of using multiple mouse models to assess the role of a given protein in venous thrombosis.

SUBMITTER: Grover SP

PROVIDER: S-EPMC7693194 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundRecurrent venous thromboembolism (VTE) is common. Current guidelines suggest that patients with unprovoked VTE should continue anticoagulants unless they have a high bleeding risk, whereas all others can stop. Prediction models may refine this dichotomous distinction, but existing models apply only to patients with unprovoked first thrombosis. We aimed to develop a prediction model for all patients with first VTE, either provoked or unprovoked.Methods and findingsData were used from two population-based cohorts of patients with first VTE from the Netherlands (Multiple Environment and Genetic Assessment of Risk Factors for Venous Thrombosis [MEGA] follow-up study, performed from 1994 to 2009; model derivation; n = 3,750) and from Norway (Tromsø study, performed from 1999 to 2016; model validation; n = 663). Four versions of a VTE prediction model were developed: model A (clinical, laboratory, and genetic variables), model B (clinical variables and fewer laboratory markers), model C (clinical and genetic factors), and model D (clinical variables only). The outcome measure was recurrent VTE. To determine the discriminatory power, Harrell's C-statistic was calculated. A prognostic score was assessed for each patient. Kaplan-Meier plots for the observed recurrence risks were created in quintiles of the prognostic scores. For each patient, the 2-year predicted recurrence risk was calculated. Models C and D were validated in the Tromsø study. During 19,201 person-years of follow-up (median duration 5.7 years) in the MEGA study, 507 recurrences occurred. Model A had the highest predictive capability, with a C-statistic of 0.73 (95% CI 0.71-0.76). The discriminative performance was somewhat lower in the other models, with C-statistics of 0.72 for model B, 0.70 for model C, and 0.69 for model D. Internal validation showed a minimal degree of optimism bias. Models C and D were externally validated, with C-statistics of 0.64 (95% CI 0.62-0.66) and 0.65 (95% CI 0.63-0.66), respectively. According to model C, in 2,592 patients with provoked first events, 367 (15%) patients had a predicted 2-year risk of >10%, whereas in 1,082 patients whose first event was unprovoked, 484 (45%) had a predicted 2-year risk of <10%. A limitation of both cohorts is that laboratory measurements were missing in a substantial proportion of patients, which therefore were imputed.ConclusionsThe prediction model we propose applies to patients with provoked or unprovoked first VTE-except for patients with (a history of) cancer-allows refined risk stratification, and is easily usable. For optimal individualized treatment, a management study in which bleeding risks are also taken into account is necessary.