McCarty et al. We chose to group the genes this way based on experimental evidence indicating reduced or no enzyme activity for the variant and genotypes. In terms of metabolism, the GSTP1 valine genotype is thought to be asso- ciated with lower glutathione S-transferase pi enzyme activity compared with the GSTP1 isoleucine genotype, which plays a key role in the detoxification of benzo[a]pyrene diol epoxide, a major carcinogen present in tobacco smoke (Fields et al. 1998; Hecht 1999; Nakajima et al. 1995). To explore these potential gene–PAH interactions, we devel- oped separate models for women based on the presence or absence of the PAH exposure measure [PAH–DNA adducts (detectable/ not detectable); self-reported cigarette smok- ing status (ever/never, or current/past/never)] or pack years of smoking history (< 15 years, 15–30 years, > 30 years). We also developed models for all women that included multi- plicative interaction terms (Hosmer and Lemeshow 1989); gene–environment inter- actions were formally assessed by examining departures from multiplicity by comparing models with and without the interaction term using the likelihood ratio test (LRT) (Hosmer and Lemeshow 1989). In addition, we inves- tigated potential interactions on the additive scale (Hosmer and Lemeshow 1989) using Table 1. Age-adjusted ORs (95% CIs) for the individual GST genotypes on the associations between smok- ing status and breast cancer risk. Smoking status Cases (n) Controls (n) OR (95% CI) Genotype GSTT1 Present GSTM1 Present Null Null GSTP1 AA (common) AG or GG GSTA1 A*/A* (common) A*/B* or B*/B* Genotype GSTT1 Present GSTM1 Present Null Null GSTP1 AA (common) AG or GG GSTA1 A*/A* A*/B* or B*/B* 554 Never Ever Never Ever Never Ever Never Ever Never Ever Never Ever Never Ever Never Ever – + – + – + – + – + – + – + – + p-Valuea 0.27 0.62 0.86 0.60 p-Valuea 0.22 0.75 0.77 0.53 joint indicator terms for genotype only, for PAH measure only, and for both gen- otype and PAH measure (Tables 3 and 4). Interaction contrast ratios (ICRs) and their 95% CIs were calculated to measure the rela- tive excess risk due to interaction (Assmann et al. 1996; Rothman and Greenland 1998). We also considered other categorizations of smoking exposure status that incorporated information collected by the questionnaire on environmental tobacco smoke (Gammon et al. 2004a), but the cell sizes were too small to yield meaningful results, so we do not show these data. For our second set of analyses, our goal was to determine the association between PAH–DNA adducts and the GST variant alleles among control women only. We used unconditional logistic regression with detect- able adducts as the dependent variable, and GSTs as the independent variable, controlling for age at reference and season of blood draw (Table 4). We also investigated the main effect of each genotype or number of variant alleles on the outcome of detectable PAH–DNA adducts in a multivariate model adjusted for age, smoking status, and season of blood draw. In a previous study (Shantakumar et al. 2005), we found that cigarette smoking was a sig- nificant predictor of detectable PAH–DNA adducts among this population-based sample; thus, we also explored whether the GST geno- types modified the association between smok- ing status and detectable adducts. We also considered potential interactions with cigarette smoke because of its link to our biomarker, although we recognize that other PAH sources and other constituents of tobacco smoke could potentially interact with GST polymorphisms to affect risk; however, these other constitu- ents of tobacco smoke have not been linked to breast cancer risk in a human study. Results Individual GSTs, PAHs, and breast cancer risk. As shown in Tables 1 and 2, we did not observe substantial effect modification, on a multiplicative or additive scale, by any of the individual genotypes on the associations between breast cancer risk and PAH exposure (PAH–DNA adducts or cigarette smoking). Multiple GSTs and breast cancer risk. The ORs for the association between breast cancer risk and multiple GST variant alleles were 1.10 (95% CI, 0.77–1.57) for three or more vari- ants, 0.76 (95% CI, 0.56–1.03) for two vari- ants, and 0.80 (95% CI, 0.59–1.08) for one variant. When we considered the combined effects of GSTM1, -P1, -T1, and -A1 variants that are coded based on their PAH-related biologic activity (rather than for their isothio- cyanate-related activity), we did not find a significant association between the number of variant GST alleles and breast cancer risk. Common alleles: GSTT1 present, GSTM1 present, GSTP1 (AA), GSTA1 (A*/A*). Variant alleles: GSTT1 null, GSTM1 null, GSTP1 (AG or GG), GSTA1 (A*/B* or B*/B*). Symbols: +, PAH–DNA adducts detected; –, PAH–DNA adducts not detected. aFrom likelihood ratio test. ovlume 117 | number 4 | April 2009 • Environmental Health Perspectives 351 423 97 112 227 278 218 252 235 275 239 278 145 199 335 362 165 463 40 134 104 301 100 293 107 320 106 304 75 211 145 416 Common alleles: GSTT1 present, GSTM1 present, GSTP1 (AA), GSTA1 (A*/A*). Variant alleles: GSTT1 null, GSTM1 null, GSTP1 (AG or GG), GSTA1 (A*/B* or B*/B*). aFrom likelihood ratio test. Table 2. Age-adjusted ORs (95% CIs) for the individual GST genotypes on the associations between PAH–DNA adducts and breast cancer risk. PAH–DNA adducts Cases (n) Controls (n) OR (95% CI) 341 454 112 109 247 300 201 253 242 309 234 284 168 218 328 376 204 474 61 124 146 320 114 274 133 293 153 333 111 223 179 413 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.94 (0.80–1.11) 0.97 (0.66–1.16) 1.04 (0.78–1.37) 0.98 (0.81–1.19) 1.14 (0.92–1.42) 1.06 (0.86–1.29) 0.91 (0.75–1.10) 1.04 (0.85–1.28) 1.01 (0.83–1.22) 0.96 (0.77–1.20) 1.06 (0.88–1.28) 1.02 (0.85–1.22) 1.01 (0.87–1.19) 0.68 (0.45–1.03) 1.14 (0.87–1.48) 0.99 (0.82–1.19) 0.93 (0.70–1.23) 1.13 (0.93–1.37) 0.94 (0.78–1.13) 0.83 (0.63–1.09) 1.15 (0.95–1.38) 0.97 (0.78–1.20) 0.83 (0.65–1.05) 1.03 (0.86–1.22)