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. 2011 Nov 22;3(2):261–268. doi: 10.3892/etm.2011.388

Table IV.

Genotype and allele frequencies of CYP11B2, CYP17A1, CYP2B6, CYP2C9, CYP2E1 and CYP7A1 polymorphisms in IS patients according to smoking status.

Gene
Genotype Smoking (−)
Smoking (+)
Model OR (95% CI) p-value pc
SNP n % n %
CYP11B2 T/T 51 56.7 17 58.6 Codominant 1 0.55 (0.19–1.56) 0.34 1.00
rs1799998 T/C 38 42.2 8 27.6 Codominant 2 10.51 (0.73–150.38) 0.26 1.00
−344 C/C 1 1.1 4 13.8 Dominant 0.76 (0.29–2.01) 0.57 1.00
Recessive 14.00 (1.03–190.90) 0.0220 0.13
Log-additive 1.19 (0.53–2.65) 0.67 1.00
CYP17A1 T/T 50 55.6 16 55.2 Codominant 1 1.02 (0.38–2.71) 0.98 1.00
rs2486758 T/C 34 37.8 11 37.9 Codominant 2 0.63 (0.11–3.83) 0.96 1.00
−190 C/C 6 6.7 2 6.9 Dominant 0.94 (0.37–2.37) 0.89 1.00
Recessive 0.63 (0.11–3.63) 0.60 1.00
Log-additive 0.89 (0.43–1.82) 0.74 1.00
CYP2B6 C/C 54 60.0 21 72.4 Codominant 1 0.53 (0.19–1.48) 0.35 1.00
rs4802100 G/C 32 35.6 8 27.6 Codominant 2 0.00 (0.00-NA)
−1180 G/G 4 4.4 0 0.0 Dominant 0.47 (0.17–1.29) 0.13 0.78
Recessive 0.00 (0.00-NA)
Log-additive 0.45 (0.18–1.15) 0.08 0.49
CYP2C9 T/T 34 37.8 12 41.4 Codominant 1 1.19 (0.44–3.26) 0.74 1.00
rs4918758 T/C 43 47.8 13 44.8 Codominant 2 1.21 (0.29–5.16) 0.84 1.00
−1163 C/C 13 14.4 4 13.8 Dominant 1.20 (0.46–3.08) 0.71 1.00
Recessive 1.11 (0.29–4.27) 0.88 1.00
Log-additive 1.12 (0.57–2.20) 0.73 1.00
CYP2E1 G/G 51 56.7 24 82.8 Codominant 1 0.42 (0.13–1.35) 0.15 0.90
rs3813867 G/C 32 35.6 5 17.2 Codominant 2 0.00 (0.00-NA)
−1272 C/C 7 7.8 0 0.0 Dominant 0.28 (0.09–0.87) 0.0190 0.11
Recessive 0.00 (0.00-NA)
Log-additive 0.30 (0.11–0.79) 0.0056 0.0336
CYP7A1 T/T 29 32.2 9 31.0 Codominant 1 1.50 (0.51–4.41) 0.10 0.60
rs3808607 T/G 42 46.7 13 44.8 Codominant 2 1.78 (0.49–6.46) 0.77 1.00
−278 G/G 19 21.1 7 24.1 Dominant 1.59 (0.58–4.33) 0.36 1.00
Recessive 1.41 (0.46–4.31) 0.55 1.00
Log-additive 1.35 (0.71–2.54) 0.36 1.00

IS, ischemic stroke; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; NA, not applicable; pc, For multiple comparisons, the Bonferroni correction was performed by multiplying the p-value by the number of SNPs analyzed (n=6). The p-values were calculated from logistic regression analysis. Bold numbers indicate significant associations.