Genotyping. We extracted DNA from EDTA (ethylenediaminetetraacetic acid)– anticoagulated blood using a salting out procedure. We selected 10 single-nucleotide polymorphisms (SNPs) for IL6 and 21 SNPs for FGA, FGB, and FGG and genotyped them as described previously (Peters et al. 2007). Genotyping success rates ranged between 97.9% for IL6 rs2069832 and 99.8% for FGB rs1800790. SNP selection. We selected IL6 SNPs that showed an association with IL-6 levels in our sample (p-value < 0.05) and were in Hardy- Weinberg equilibrium for gene–environment analyses (Ljungman et al. 2008). Five SNPs met this criterion, but IL6 rs2069832 and rs1800795 were in very high linkage disequi- librium (LD) (r2 = 0.99), as were rs1554606 and rs2069845 (r2 = 0.99). Therefore, one of each pair (rs2069832 and rs1554606) was cho- sen for further gene–environment interaction analyses. IL6 rs2069840 was, however, in weak LD (r2 = 0.31 to 0.35) with the other selected SNPs and might have independent effects. Associations have been seen between IL-6 lev- els and fibrinogen levels (Mannila et al. 2004), and previous analyses in our study population (Jacquemin et al. 2008) have shown evidence of modification of the effect of fibrinogen polymorphisms on fibrinogen levels by levels of IL-6. Consequently, we selected one SNP each from the genes coding the α-chain (FGA, rs2070011) and β-chain (FGB, rs1800790) of fibrinogen, which were both associated with fibrinogen levels in the previous study (Jacquemin et al. 2008), based on these results. Of the 1003 study participants, we restricted all further analyses to 955 (95%) for whom complete information on the five SNPs was available. Statistical analysis. We estimated the effect of the SNPs on IL-6 using linear mixed effects models with random subject-specific inter- cepts, adjusting linearly for the variables age, BMI, pack-years of cigarette smoking, HDL cholesterol, systolic blood pressure, alcohol intake, and logarithm of NT-proBNP and for the categorical variables city, HbA1c, num- ber of earlier MIs, history of heart failure or diabetes, and symptoms of phlegm. SNP gen- otypes were coded as an ordinal variable by the number of copies of the minor allele (0, 1, 2; denoted 1 1, 1 2, and 2 2 in tables and figures) as described in Ljungman et al. (2008). For detailed information on model selec- tion procedures, see Rückerl et al. (2007). We estimated the overall effects of air pollutants on IL-6 in city-specific additive mixed mod- els [see Supplemental Material, Table 1 (doi: 10.1289/ehp.0800370.S1 via http://dx.doi. org/)], adjusting for the above-described patient characteristics, time trend, and the weather parameters air temperature and rela- tive humidity to accommodate the different characteristics and meteorologic conditions across Europe, as previously reported (Rückerl et al. 2007). We tested the robustness of the model to exclusion of all time-invariant vari- ables in sensitivity analyses. Gene–environment interactions were esti- mated for each SNP by including in these models the main effect of the SNP (addi- tive genetic model), the main effect of the air pollution effect, and the interaction term between air pollution and SNP. We deter- mined the a priori exposure window for all gene–environment interaction analyses to be the average exposure during the 24 hr imme- diately preceding blood withdrawal based on results from previous analyses (Rückerl et al. 2007) and the short half-life of IL-6. Secondary analyses were performed for other time windows of exposure as well as for gene–gene combinations of polymorphisms showing effect modification. We explored consistency of patterns of association in city- specific analyses. In assessing the contribu- tions of the different exposure windows to the interaction effect, we also performed analyses for the subjects carrying at least one risk allele using distributed lags, thus allowing for inde- pendence of effects for each time window of exposure in a common model. Effect estimates by genotypes are pre- sented together with 95% confidence intervals (CIs). Because the study of gene–environment interactions was of an exploratory nature, we did not attempt to correct for multiple Air pollution, genes, and IL-6 comparisons for these analyses. Estimates are presented for an increase of the pollutants by a one interquartile increase in pollutant expo- sure range and expressed as a relative change of the overall geometric mean in IL-6. We tested the assumption of an additive genetic effect by using an indicator variable for the heterozygote genotype in the model. For overall results, we pooled city-specific estimates using meta- analysis methodology (van Houwelingen et al. 2002). Heterogeneity of effect estimates was assessed with a chi-square test with 5 degrees of freedom. If the p-value was < 0.1, random effect models were applied for combining effect estimates. Results Mean IL-6 ranged from 2.5 pg/mL in Augsburg to 3.5 pg/mL in Barcelona (Table 1). The con- secutive 24-hr mean levels of CO ranged from 0.29 mg/m3 in Stockholm to 1.48 mg/m3 in Athens. The within-interquartile difference ranged from 0.08 in Helsinki to 0.73 in Athens. Less than 5% of the subjects were homozygotes for the minor allele of FGB rs1800790, whereas 9–19% of subjects were homozygotes for minor allele of the IL6 and FGA polymorphisms (Table 2). Genotype frequencies differed among the cities for all SNPs (chi-square test, p < 0.03), displaying a north–south gradient, with the minor alleles of IL6 rs2069832 and IL6 rs2069845 having higher frequencies in the northern cities and the minor alleles of IL6 rs2069840 having higher frequencies in the southern cities. The fibrinogen SNPs did not show such a pattern (data not shown). Overall effect of genotype on IL-6 levels. Table 2 shows the associations of SNPs with an increased plasma level of IL-6 in this data set. The minor alleles of IL6 rs2069832 and IL6 rs2069845 and the major allele of IL6 rs2069840 were significantly associated with an increased plasma level (at p < 0.05) (Ljungman et al. 2008). The minor allele of FGA rs2070011 showed nonsignificant asso- ciation to increased plasma levels of IL-6, whereas FGB rs1800790 polymorphism showed no clear association to plasma IL-6. Table 2. SNPs and SNP–IL-6 association: characteristics of the analyzed SNPs of IL6, FGB, and FGA and their association with plasma IL-6 concentrations. Alleles Genotype frequency [% (n)] Difference in IL-6a level ll Functional Major (1)/ Minor allele Homozygote of Heterozygote Homozygote of [% overall mean: effect of SNP region Minor (2) frequency [% (n)] major allele (1 1) (1 2) minor allele (2 2) two alleles (2 2 vs. 1 1)] IL6 rs2069832 Intron G/A 40 (768) 36 (696) 47 (892) 17 (322) 13.4 (3.7 to 24.0) rs2069840 Intron C/G 31 (602) 46 (884) 45 (850) 9 (176) –9.6 (–17.2 to –1.3) rs2069845 Intron A/G 43 (820) 33 (632) 48 (918) 19 (360) 14.6 (4.7 to 25.4) FGA rs2070011 Promoter C/T 39 (744) 39 (738) 45 (858) 16 (314) 8.1 (–0.5 to 17.5) FGB rs1800790 Promoter G/A 20 (386) 63 (1,210) 33 (628) 4 (72) –5.6 (–14.7 to 4.4) aEffect estimates and 95% CIs from linear mixed model analysis with log IL-6 as outcome, with a random effect for subject to account for repeated measurements, using an additive genetic model for the genotypes, and adjusted for age, city, glycosylated hemoglobin, number of earlier MIs, earlier diagnosed heart failure or diabetes, symptoms of phlegm, BMI, pack-years of cigarette smoking, HDL cholesterol, systolic blood pressure, alcohol intake, and log NT-proBNP. Environmental Health Perspectives • volume 117 | number 9 | September 2009 1375