Astrid van Hylckama Vlieg1, Linda E Flinterman2, Lance A Bare2, Suzanne C Cannegieter2, Pieter H Reitsma2, Andre R Arellano2, Carmen H Tong2, James J Devlin2, Frits R Rosendaal2. 1. From the Department of Clinical Epidemiology (A.v.H.V., L.E.F., S.C.C., F.R.R.), Department of Thrombosis and Haemostasis (P.H.R., F.R.R.), and Einthoven Laboratory for Experimental Vascular Medicine (A.v.H.V., S.C.C., P.H.R., F.R.R.), Leiden University Medical Center, Leiden, the Netherlands; and Celera, Alameda, CA (L.A.B., A.R.A., C.H.T., J.J.D.). a.van_hylckama_vlieg@lumc.nl. 2. From the Department of Clinical Epidemiology (A.v.H.V., L.E.F., S.C.C., F.R.R.), Department of Thrombosis and Haemostasis (P.H.R., F.R.R.), and Einthoven Laboratory for Experimental Vascular Medicine (A.v.H.V., S.C.C., P.H.R., F.R.R.), Leiden University Medical Center, Leiden, the Netherlands; and Celera, Alameda, CA (L.A.B., A.R.A., C.H.T., J.J.D.).
Abstract
BACKGROUND: The prediction of recurrent venous thrombosis using individual genetic risk predictors has proven to be challenging. The aim of this study was to assess whether multiple genetic single nucleotide polymorphism (SNP) analysis would predict recurrent venous thrombosis. METHODS AND RESULTS: Patients with a first venous thrombosis were followed for a recurrent venous thrombosis up to 2009 (MEGA follow-up study), which occurred in 608 out of 4100 patients (2.7%/year). Thirty-one common thrombosis-associated single nucleotide polymorphisms (SNPs) were associated with the risk of recurrence. A genetic risk score (GRS) for each individual was calculated by summing the number of risk-increasing alleles for each of the 31 SNPs and for a simplified model consisting of 5 SNPs: rs6025, rs1799963, rs8176719, rs2066865, and rs2036914. The risk of recurrence associated with the GRS was calculated continuously and after stratification in a low and high score. All individual SNPs were at most mildly associated with recurrence risk. Regarding the 31-SNP GRS, recurrence risk was highest in patients with ≥31 and lowest in patients with <21 risk alleles. The discriminative power of the 5-SNP GRS was similar to that of the 31-SNP GRS. The 6-year cumulative incidence of recurrence was high for individuals with ≥5 (20.3%; 95% confidence interval, 16.5-24.1) and low for individuals with ≤1 (9.4%; 95% confidence interval, 6.7-12.1) risk alleles. Predictive power improved after stratification into provoked and unprovoked first events and sex. CONCLUSIONS: Multiple genetic SNP analysis is useful in the prediction of recurrent thrombosis, even more so when combining this model with clinical risk factors.
BACKGROUND: The prediction of recurrent venous thrombosis using individual genetic risk predictors has proven to be challenging. The aim of this study was to assess whether multiple genetic single nucleotide polymorphism (SNP) analysis would predict recurrent venous thrombosis. METHODS AND RESULTS:Patients with a first venous thrombosis were followed for a recurrent venous thrombosis up to 2009 (MEGA follow-up study), which occurred in 608 out of 4100 patients (2.7%/year). Thirty-one common thrombosis-associated single nucleotide polymorphisms (SNPs) were associated with the risk of recurrence. A genetic risk score (GRS) for each individual was calculated by summing the number of risk-increasing alleles for each of the 31 SNPs and for a simplified model consisting of 5 SNPs: rs6025, rs1799963, rs8176719, rs2066865, and rs2036914. The risk of recurrence associated with the GRS was calculated continuously and after stratification in a low and high score. All individual SNPs were at most mildly associated with recurrence risk. Regarding the 31-SNP GRS, recurrence risk was highest in patients with ≥31 and lowest in patients with <21 risk alleles. The discriminative power of the 5-SNP GRS was similar to that of the 31-SNP GRS. The 6-year cumulative incidence of recurrence was high for individuals with ≥5 (20.3%; 95% confidence interval, 16.5-24.1) and low for individuals with ≤1 (9.4%; 95% confidence interval, 6.7-12.1) risk alleles. Predictive power improved after stratification into provoked and unprovoked first events and sex. CONCLUSIONS: Multiple genetic SNP analysis is useful in the prediction of recurrent thrombosis, even more so when combining this model with clinical risk factors.
Authors: Maciej M Kowalik; Piotr Trzonkowski; Magdalena Łasińska-Kowara; Andrzej Mital; Tomasz Smiatacz; Miłosz Jaguszewski Journal: Cardiol J Date: 2020-05-07 Impact factor: 2.737