Abstract
Abstract 1238
SNPs within genes encoding factor XI (F11), fibrinogen genes (FGA, FGG) and other candidate genes within the procoagulant, anticoagulant, fibrinolytic, innate immunity and endocrine pathways have been reported as associated with VTE. However, the independent risk of VTE associated with many of these SNPs after controlling for factor V Leiden, Prothrombin G20210A and ABO blood group non-O carrier status is uncertain.
To replicate candidate gene SNPs previously reported as associated with VTE.
As part of a large replication study, we included 17 SNPs previously reported as associated with VTE in a custom Illumina Golden gate (total n=1093 SNPs) genotyping array. We genotyped 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status). Genotyping results from high-quality control DNA (SNP call rate ≥ 95%) was used to generate a cluster algorithm. The primary outcome was VTE status, a binary measure. The covariates were age at interview or blood sample collection, sex, stroke and/or MI status, and state of residence. To adjust for population stratification, we performed the multidimensional scaling (MDS) analysis option in PLINK v 1.07 to identify outliers in our population using the ancestry informative markers. We tested for an association between each SNP and VTE using unconditional logistic regression, adjusting for age, sex, stroke/MI status, state of residence and ABO rs514659 (in high linkage disequilibrium with non-O blood type). The analyses were corrected for multiple comparisons using an extension of false discovery rates. The false discovery rate (reported as a Q-value) is an analogue measure of the p-value that takes into account the number of statistical tests and estimates the expected proportion of false positive tests incurred when a particular SNP is significant. All analyses were performed using PLINK v 1.07.
MDS gave no evidence of population stratification. Genotyping was unsuccessful for two of the 17 SNPs. We found significant associations between VTE and SNPs in F11, FGG, TC2D and FGA (Table ). However, the false discovery rates for all significant SNPs except F11 rs3756008 were >0.05, suggesting that the observed associations were likely falsely positive due to multiple comparisons. Even at a false discovery rate of Q-value=0.0099, one would expect ∼13 SNPs (0.0099 × 1302 SNPs) to be falsely associated with VTE due to multiple comparisons. Consequently, even our observed association between F11 rs3756008 and VTE remains tentative.
We were unable to replicate reported associations between 15 SNPs and VTE. Our results emphasize the necessity of replication studies in different populations to confirm reported associations of SNPs with VTE.
SNP . | Gene† . | Odds ratio (95% CI) . | P-value . | Q-value . |
---|---|---|---|---|
rs3756008 | FXI | 1.25 (1.11, 1.40) | 0.0002 | 0.0099 |
rs2036914 | FXI | 0.84 (0.75, 0.94) | 0.0027 | 0.094 |
rs2066854 | FGG | 1.17 (1.03, 1.32) | 0.0171 | 0.33 |
rs10133762 | TC2D | 1.13 (1.01, 1.26) | 0.0351 | 0.42 |
rs6050 | FGA | 1.14 (1.00, 1.29) | 0.0488 | 0.47 |
rs2726953 | SCARA5 | 1.07 (0.95, 1.21) | 0.2653 | 0.77 |
rs2234693 | ESR1 | 0.95 (0.84, 1.06) | 0.3383 | 0.80 |
rs6585234 | HABP2 | 0.94 (0.81, 1.09) | 0.4023 | 0.83 |
rs10895068 | PGR | 1.10 (0.86, 1.41) | 0.4418 | 0.83 |
rs1799863 | CCR5 | 0.87 (0.60, 1.26) | 0.4711 | 0.83 |
rs33989577 | APOA4 | 1.07 (0.87, 1.30) | 0.5312 | 0.85 |
rs253061 | F2R | 0.97 (0.85, 1.10) | 0.5962 | 0.87 |
rs1800872 | IL10 | 1.02 (0.90, 1.17) | 0.7282 | 0.88 |
rs344782 | PLAUR | 0.99 (0.89, 1.11) | 0.891 | 0.89 |
rs2227589 | SERPINC1 | 1.00 (0.82, 1.21) | 0.9901 | 0.90 |
SNP . | Gene† . | Odds ratio (95% CI) . | P-value . | Q-value . |
---|---|---|---|---|
rs3756008 | FXI | 1.25 (1.11, 1.40) | 0.0002 | 0.0099 |
rs2036914 | FXI | 0.84 (0.75, 0.94) | 0.0027 | 0.094 |
rs2066854 | FGG | 1.17 (1.03, 1.32) | 0.0171 | 0.33 |
rs10133762 | TC2D | 1.13 (1.01, 1.26) | 0.0351 | 0.42 |
rs6050 | FGA | 1.14 (1.00, 1.29) | 0.0488 | 0.47 |
rs2726953 | SCARA5 | 1.07 (0.95, 1.21) | 0.2653 | 0.77 |
rs2234693 | ESR1 | 0.95 (0.84, 1.06) | 0.3383 | 0.80 |
rs6585234 | HABP2 | 0.94 (0.81, 1.09) | 0.4023 | 0.83 |
rs10895068 | PGR | 1.10 (0.86, 1.41) | 0.4418 | 0.83 |
rs1799863 | CCR5 | 0.87 (0.60, 1.26) | 0.4711 | 0.83 |
rs33989577 | APOA4 | 1.07 (0.87, 1.30) | 0.5312 | 0.85 |
rs253061 | F2R | 0.97 (0.85, 1.10) | 0.5962 | 0.87 |
rs1800872 | IL10 | 1.02 (0.90, 1.17) | 0.7282 | 0.88 |
rs344782 | PLAUR | 0.99 (0.89, 1.11) | 0.891 | 0.89 |
rs2227589 | SERPINC1 | 1.00 (0.82, 1.21) | 0.9901 | 0.90 |
FGG, fibrinogen gamma chainPGR, progesterone receptor
TC2D, tandem C2 domains, nuclearCCR5, chemokine receptor 5
FGA, fibrinogen alpha chainAPOA4, apolipoprotein A 4
SCARA5, scavenger receptor class A, member 5 F2R, thrombin receptor
ESR1, estrogen receptor 1PLAUR, uPA receptor
HABP2, hyaluran binding protein 2SERPINC1, antithrombin
Heit:Daiichi Sankyo: Consultancy, Honoraria.
Author notes
Asterisk with author names denotes non-ASH members.
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