Gene variants associated with deep vein thrombosis

Abstract

Context: The genetic causes of deep vein thrombosis (DVT) are not fully understood.

Objective: To identify single-nucleotide polymorphisms (SNPs) associated with DVT.

Design, setting, and patients: We used 3 case-control studies of first DVT. A total of 19 682 gene-centric SNPs were genotyped in 443 cases and 453 controls from the Leiden Thrombophilia Study (LETS, 1988-1992). Twelve hundred six SNPs associated with DVT were reinvestigated in the Multiple Environmental and Genetic Assessment of Risk Factors for Venous Thrombosis study (MEGA-1, 1999-2004) in a subset of 1398 cases and 1757 controls. Nine SNPs associated with DVT in both LETS and MEGA-1 were investigated a third time in 1314 cases and 2877 controls from MEGA-2, a second subset of MEGA. Additional SNPs close to one SNP in CYP4V2 were genotyped in LETS and MEGA-1.

Main outcome measure: Odds ratios (ORs) for DVT were estimated by logistic regression. False discovery rates served to investigate the effect of multiple hypothesis testing.

Results: Of 9 SNPs genotyped in MEGA-2, 3 were strongly associated with DVT (P < .05; false discovery rate < or =.10): rs13146272 in CYP4V2 (risk allele frequency, 0.64), rs2227589 in SERPINC1 (risk allele frequency, 0.10), and rs1613662 in GP6 (risk allele frequency, 0.84). The OR for DVT per risk allele was 1.24 (95% confidence interval [95%CI], 1.11-1.37) for rs13146272, 1.29 (95% CI, 1.10-1.49) for rs2227589, and 1.15 (95% CI, 1.01-1.30) for rs1613662. In the region of CYP4V2, we identified 4 additional SNPs (in CYP4V2, KLKB1, and F11) that were also associated with both DVT (highest OR per risk allele, 1.39; 95% CI, 1.11-1.74) and coagulation factor XI level (highest increase per risk allele, 8%; 95% CI, 5%-11%).

Conclusions: We identified SNPs in several genes that were associated with DVT. We also found SNPs in the region around the SNP in CYP4V2 (rs13146272) that were associated with both DVT and factor XI levels. These results show that common genetic variation plays an important role in determining thrombotic risk.