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Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

Objective

Glutathione S-transferase (GST) genes as well as heme oxygenase 1 gene (HMOX1) encode enzymes that detoxify carcinogens and protect against oxidative stress. This study was undertaken to examine the impact of gene–smoking interactions on susceptibility to rheumatoid arthritis (RA).

Methods

Caucasian patients with RA and matched control subjects (n = 549 each) were selected from the Nurses' Health Study. Genotyping of the patients' blood by TaqMan and BioTrove assays identified homozygous deletions at the M1 and T1 loci of GST (GSTM1-null and GSTT1-null, respectively) as well as alleles for GSTP1 (rs1695) and HMOX1 (rs2071746). In addition, the effect of gene–smoking interactions on the risk of all RA and RA serologic phenotypes was studied in separate logistic models that were adjusted for covariates. Multiplicative interactions were assessed by including a product term in a logistic model, and additive interactions were assessed using the attributable proportion (AP) due to interaction. For replication of the results, analyses revealing significant interactions were repeated in an independent case–control cohort from the Epidemiological Investigation of Rheumatoid Arthritis study.

Results

For the risk of all RA, multiplicative (P = 0.05) and additive (AP = 0.53, P = 0.0005) interactions between the GSTT1-null polymorphism and smoking and multiplicative interactions (P = 0.05) between HMOX1 and smoking were observed. For the risk of seropositive RA, multiplicative (P = 0.01) and additive (AP = 0.62, P < 0.0001) interactions between GSTT1-null and smoking and additive interactions (AP = 0.41, P = 0.03) between HMOX1 and smoking were observed. After correction for multiple comparisons, the additive interactions between GSTT1-null and smoking remained significant. The M1-null and P1 variants of GST did not show significant interactions, and no associations with seronegative RA were observed. In replication analyses, significant multiplicative interactions (P = 0.04) and additive interactions (AP = 0.32, P = 0.02) were observed between GSTT1-null and smoking in the risk of anti–citrullinated protein antibody–positive RA.

Conclusion

Significant gene–environment interactions between the GSTT1-null polymorphism and heavy smoking were observed when assessing the risk of RA. Future studies are needed to assess the impact of these interactions on RA prediction.

Exposure to certain environmental factors within genetically predisposed individuals is thought to be an underlying cause of the development of rheumatoid arthritis (RA), a complex autoimmune disease affecting ∼1% of the adult population (1). Epidemiologic research has suggested that cigarette smoking is a strong environmental risk factor for RA (2–5). Evidence of dose effects for both smoking and the gene–environment effects of smoking have been demonstrated within the Nurses' Health Study (NHS) (2, 6). Genetic variants associated with an increased risk of RA within the HLA complex have been known for decades (7, 8), and numerous studies have shown strong gene–environment interactions between HLA and smoking (3, 6, 9–12).

Glutathione S-transferase (GST) genes are a widely expressed supergene family encoding biotransforming enzymes that catalyze the conjugation of glutathione and are involved in the detoxification of cytotoxic carcinogens and metabolites. GST substrates found in cigarette smoke include α- and β-unsaturated carbonyls, polycyclic aromatic hydrocarbons, and reactive oxygen species (ROS), which may lead to cellular damage through oxidative stress. Variations in these genes reduce glutathione conjugation, and therefore may increase susceptibility to the harmful effects of carcinogen exposure and oxidative stress (13–19).

Polymorphisms within the Mu (GSTM1), Theta (GSTT1), and Pi (GSTP1) classes of GST have been identified. Individuals with homozygous deletions at the M1 and T1 loci of GST (GSTM1-null and GSTT1-null, respectively) have no functional enzymatic activity (13–19). In GSTP1, an A-to-G single-nucleotide polymorphism (SNP) may result in reduced enzymatic activity for the AG and GG genotypes when compared with the AA genotype (18, 20, 21).

Numerous studies have examined the possible associations between GST polymorphisms and disease risk or disease-phenotype determination. It has been hypothesized that GST variations are associated with susceptibility to various cancers (22, 23), most notably lung cancer (17–19). Previous studies have shown relationships between the GSTT1-null or GSTM1 polymorphisms and RA risk and severity, but results have been inconsistent with regard to possible interactions between the GST variants and smoking (3, 24–27). Significant GST–smoking interactions have been reported (3, 16, 17, 22), suggesting that underlying environmental exposures play an important role in the effect of GST genotypes.

Heme oxygenase 1 (HO-1), the inducible form of heme oxygenase, catabolizes heme groups into biliverdin, free iron, and carbon monoxide. Heme oxygenase has been shown to have antioxidant, antiinflammatory, and cytoprotective properties and to be up-regulated under the presence of nicotine (28–32). An A-to-T SNP that may affect the extent of the HO-1 production response has been identified; subjects with the TA or TT genotypes have lower HO-1 expression when compared with those with the AA genotype (31). Previous studies have examined the associations between HMOX1 and several diseases (31, 32), including lung cancer (33). Recent studies have identified a role for HMOX1 enzymes in RA biology (34) and have shown associations between HMOX1 polymorphisms and RA susceptibility and severity (35, 36).

Our present study focuses on 3 genetic polymorphisms within the GSTM1-null, GSTT1-null, and GSTP1 (rs1695) classes and 1 polymorphism within the HMOX1 gene promoter (rs2071716). We hypothesized that significant gene–environment interactions exist between these genetic variations and heavy smoking. We studied the effect of these interactions on the risk of all RA and the risk of RA serologic phenotypes. We further hypothesized that the interactions would be stronger in relation to the risk of seropositive RA.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

Study sample.

The NHS, established in 1976, comprises a prospective cohort of 121,700 female nurses ages 30–55 years. During 1989–1990, blood samples for future studies were obtained from 32,826 (27%) of the NHS participants (ages 43–70 years). An additional 33,040 participants (27%) provided buccal cell samples. The Nurses' Health Study II (NHS2), established in 1989, comprises a similar prospective cohort of 116,609 female nurses ages 25–42 years. During 1996–1999, blood samples for future studies were obtained from 29,611 (25%) of the NHS2 participants (ages 32–52). Among the participants of both the NHS and the NHS2, the demographic and exposure characteristics of those patients who provided blood were similar to those of the overall cohorts (37). In this study, we combined samples from both the NHS and NHS2, and the combined cohort is referred to simply as the NHS cohort.

All women in the NHS cohort completed initial questionnaires. Subsequent biennial questionnaires were used to update disease diagnoses, exposures, and other covariates of interest. Self-reports of RA status were confirmed through a 2-stage process of screening for the presence of RA symptoms on a connective tissue disease screening questionnaire (38), followed by medical record review for the American College of Rheumatology (ACR; formerly, the American Rheumatism Association) classification criteria for RA (39), as previously described (6). We determined the status of RA as seropositive (i.e., the presence of rheumatoid factor [RF] or anti–cyclic citrullinated peptide [anti-CCP] antibodies) versus seronegative primarily by chart review and, in some cases, by direct assay using the second generation DIASTAT enzyme-linked immunosorbent assay (Axis-Shield Diagnostics) (6). Each confirmed case of RA was matched to 1 healthy female control subject by cohort, year of birth, race/ethnicity, menopausal status, and postmenopausal hormone use.

Our initial nested case–control data set from the NHS consisted of 585 RA cases and 585 matched controls. We restricted our analysis to matched pairs of self-reported Caucasian subjects for whom DNA samples were available, in order to minimize potential population stratification, resulting in a sample of 549 RA cases and 549 matched controls for analyses of the risk of all RA. In analyses of the risk of seropositive RA, we further refined this sample to include 325 seropositive RA cases and all 549 controls, while for the risk of seronegative RA, the sample included 224 cases of seronegative RA and all 549 controls. All aspects of the study were approved by the Partners' HealthCare Institutional Review Board.

Covariate information.

Covariates related to the reproductive system, including parity, duration of breastfeeding, age at menarche, menopausal status, and postmenopausal hormone use, were chosen based on previously identified associations with RA risk in the NHS (40); these were selected from the questionnaire cycle prior to the date of RA diagnosis for cases or index date for controls. Information on lifetime history of smoking was collected at baseline, and data on current smoking and the number of cigarettes smoked per day were updated via biennial questionnaires. Pack-years of smoking (number of packs per day × number of years smoked) was computed from the last questionnaire completed prior to RA diagnosis or index date. We focused on smoking as a dichotomous variable, denoting the cutoffs as ≤10 pack-years versus >10 pack-years, based on previous epidemiologic data from this cohort that demonstrated an increased risk of disease in those reporting >10 pack-years of cigarette smoking (2). We herein refer to those with a history of >10 pack-years of smoking as heavy smokers. We also examined the smoking status dichotomized as never smoker versus ever smoker.

Genotyping.

Genotyping for GSTP1 and HMOX1 alleles was conducted using the BioTrove multiplex SNP genotyping assay. For the GSTP1 (rs1695) and HMOX1 (rs2071746) SNPs, we obtained allelic information on individual samples. For the GSTM1 and GSTT1 deletions, we used a TaqMan-based quantitative real-time polymerase chain reaction (PCR), similar to that described by Covault et al (41), but the information obtained was on homozygous-null or homozygous-present genotypes only. We included 126 blinded quality control (QC) samples in each assay, and the concordance rate in QC samples was 100%.

Statistical analysis.

We calculated the mean ± SD for continuous covariates, and calculated frequencies for categorical covariates, stratifying by case–control status. Chi-square statistics and t-tests were used to compare covariate frequency distributions and mean values between cases and controls. We studied both additive and multiplicative interactions between GST or HMOX1 polymorphisms and heavy smoking in relation to the risk of all RA or the risk of RA serologic phenotypes. GSTT1 and GSTM1 were dichotomized as those without deletions versus those with homozygous deletions (GSTT1-null and GSTM1-null, respectively). GSTP1 and HMOX1 SNPs were assessed using a dominant model, with subjects classified as having any risk allele (1 or 2 alleles) or no risk alleles. In addition, we examined interactions between the GST and HMOX1 polymorphisms and smoking according to classification as never smoker versus ever smoker.

Within each of our a priori hypotheses, namely, that the specific GST or HMOX1 polymorphisms would interact with smoking, we examined the association with heavy smoking or ever smoking with the risk of all RA, seropositive RA, and seronegative RA, totaling 6 analyses under each hypothesis. We assessed false positive results, which could be attributed to multiple comparisons, in 2 ways: 1) the conservative Bonferroni correction was applied for determining the level of significance, with a corrected P value of 0.008 (0.05 divided by 6); and 2) significant results (P < 0.05) were replicated in a large independent cohort from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study.

For the risk of all RA, we assessed these associations using a conditional logistic regression model, controlling for matching factors and adjusting for age at menarche, regularity of menses, parity, breastfeeding, menopausal status, and postmenopausal hormone use. For the risks of seronegative or seropositive RA, we used unconditional logistic regression models, adjusted for matching factors and reproductive covariates, within the serologically defined subsets of RA described above. Odds ratios (ORs) were interpreted as estimates of the relative risk, since the study was population based and the outcome is rare. All analyses were conducted using SAS version 9.1 (SAS Institute).

Assessing interaction.

The assessment of additive interaction was based on disease rates connected to the “pie model” introduced by Rothman (42). To test for this type of interaction, we followed the methods discussed by Lundberg et al (43) and Andersson et al (44) and calculated the attributable proportion (AP) due to interaction, as described previously (6). The 95% confidence intervals (95% CIs) were calculated using the methods described by Hosmer and Lemeshow (45). We assessed multiplicative interactions by including a product term (gene × smoking) in the regression model. After correction for multiple comparisons, P values less than 0.008 or P values less than 0.05 in both the primary and replication analyses were considered evidence of a significant interaction on the additive or multiplicative scale.

Stratified analyses.

If we observed P values less than 0.05 for any interaction in relation to the risk of RA, we performed a stratified analysis within the specific subset (all RA, seropositive RA, or seronegative RA) in which the effect was observed. We stratified our sample into subsets based on the presence or absence of the significant genetic risk factor, to test whether the effect of smoking would be stronger among those with genetic polymorphisms. We then examined the relationship between smoking and RA risk in logistic regression models, adjusting for matching factors and covariates within these strata.

Replication sample.

We conducted replication analyses using data from participants in the EIRA study, a population-based case–control study on incident RA in Sweden established between May 1996 and December 2006, as described in detail elsewhere (10). A case was defined as a person in the population who, for the first time, had received a diagnosis of RA according to the ACR 1987 criteria for the classification of RA. Eighty-five percent of the patients had their symptoms for <1 year. For each potential case, a control was randomly selected from the population, taking into consideration the subject's age, sex, and residential area. In total, 1,771 cases and 1,107 controls were available for analysis. For subset analyses, we defined cases based on anti–citrullinated protein antibody (ACPA) status, with 1,123 cases of ACPA-positive RA and 648 cases of ACPA-negative RA, compared with all 1,107 controls.

Information on GSTT1 deletions in the EIRA cohort was obtained using the TaqMan-based quantitative real-time PCR, similar to that described by Covault et al (41), and information was obtained on homozygous-null or homozygous-present genotypes only, as in the NHS samples. HMOX1 genotyping was performed by imputing the SNP (rs2071746) in the EIRA cohort using Mach version 1.0 (46) based on the Phase II HapMap data (average posterior probability for the most likely genotype for this imputation = 0.91). All aspects of the EIRA study were approved by the Karolinska Institutet Institutional Review Board.

For those gene–environment interactions that were observed to be significant at the level of P < 0.05 in the NHS cohort, we replicated the analyses in the EIRA cohort using unconditional logistic regression models, controlling for age, sex, and residential area, for all phenotypes of RA (all RA, ACPA-positive RA, and ACPA-negative RA).

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

Characteristics of the subjects.

The characteristics and genotype frequencies in the NHS sample are presented in Table 1. The mean ± SD age at RA diagnosis was 56.9 ± 10.3 years, and 325 (59.2%) of the patients with RA were seropositive (positive for RF or anti-CCP). Two hundred forty-eight (46.0%) of the patients with RA were heavy smokers, compared with 187 (34.4%) of the controls (P < 0.0001). No significant differences were seen in the distributions of the GSTP1 alleles, HMOX1 alleles, or GSTT1 and GSTM1 deletions between cases and controls.

Table 1. Characteristics and genotype frequencies in patients with rheumatoid arthritis (RA) and matched control subjects from case–control cohorts of the Nurses' Health Study (NHS) and Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study*
 NHSEIRA
RA cases (n = 549)Controls (n = 549)RA cases (n = 1,771)Controls (n = 1,107)
  • *

    Except where indicated otherwise, values are the number (%) of subjects. Percentages are calculated based on group totals that differ according to availability of the data (unknown/missing data excluded). GST = glutathione S-transferase; HMOX1 = heme oxygenase 1 gene promoter; SE = shared epitope.

  • Defined as those with a history of >10 pack-years of smoking.

  • Calculated among parous women in the NHS.

Characteristic   
 Age at match, mean ± SD years55.4 ± 8.055.4 ± 8.051.5 ± 12.352.9 ± 11.5
 Ever cigarette smoker335 (61.7)304 (55.5)1,175 (66.7)672 (61.0)
 Heavy cigarette smoker248 (46.0)187 (34.4)803 (45.3)377 (34.1)
 Parous505 (93.2)513 (94.3)
 Breastfeeding ≥12 months78 (14.4)103 (18.9)
 Age at menarche <12 years160 (29.1)152 (27.7)
 Irregular menstrual cycles88 (16.0)70 (12.8)
 Body mass index, mean ± SD kg/m225.9 ± 4.925.9 ± 5.025.3 ± 4.325.8 ± 7.0
RA feature   
 Age at diagnosis, mean ± SD years56.9 ± 10.351.4 ± 12.5
 Seropositive325 (59.2)1,123 (63.4)
 Rheumatoid nodules71 (12.9)
 Radiographic changes161 (29.3)
Gene frequency   
 GSTT1   
  Present434 (81.3)445 (82.9)1,481 (83.6)878 (79.3)
  Null100 (18.7)92 (17.1)252 (14.2)150 (13.6)
 GSTM1   
  Present278 (52.2)247 (47.2)
  Null255 (47.8)276 (52.8)
 GSTP1   
  AA231 (44.0)218 (41.1)
  AG219 (41.7)245 (46.1)
  GG75 (14.3)68 (12.8)
 HMOX1   
  AA168 (31.5)164 (31.5)433 (27.9)239 (25.7)
  AT258 (48.4)255 (49.0)759 (49.0)475 (51.0)
  TT107 (20.1)101 (19.4)358 (23.1)217 (23.3)
 HLA–SE   
  No SE265 (48.8)337 (62.3)432 (26.0)467 (47.7)
  Any SE278 (51.2)204 (37.7)1,230 (74.0)512 (52.3)

Descriptive statistics for our replication sample from the EIRA study are also presented in Table 1. For this cohort, the mean ± SD age at diagnosis was 51.4 ± 12.5 years, and 1,123 (63.4%) were considered seropositive (positive for ACPAs). Eight hundred three (45.3%) of the patients with RA were heavy smokers, compared with 377 (34.1%) of the controls (P < 0.0001). No significant differences were seen in the distributions of GSTT1-null or HMOX1 alleles between cases and controls.

In analyses using logistic models that were adjusted for matching factors, reproductive covariates, and pack-years of smoking, we observed no significant main effects of GST or HMOX1 polymorphisms on the risk of all RA or RA serologic phenotypes in either sample (results not shown).

Effects of gene–environment interactions.

The results of analyses testing for additive and multiplicative gene–environment interactions between GST or HMOX1 polymorphisms and heavy smoking are presented in Table 2. When assessing the effects on the risk of all RA, we observed a 2.47-times increased risk (95% CI 1.48 to 4.12) in heavy smokers with the GSTT1-null polymorphism compared with never or light smokers with GSTT1 present. We observed multiplicative interactions (P = 0.05) and significant additive interactions (AP = 0.53, 95% CI 0.23 to 0.82; P = 0.0005) between GSTT1-null and heavy smoking. For heavy smokers with any HMOX1 alleles, we observed a 1.85-times increased risk of all RA (95% CI 1.29 to 2.65) when compared with never or light smokers with no HMOX1 alleles. There were significant multiplicative interactions (P = 0.05), but no additive interactions (AP = 0.29, 95% CI −0.06 to 0.63; P = 0.10) between HMOX1 and heavy smoking.

Table 2. Gene–environment interactions between GST and HMOX1 polymorphisms and heavy smoking in relation to the risk of all RA and RA serologic phenotypes in subjects from the Nurses' Health Study*
RA risk, polymorphism, smoking statusNo. cases/no. controlsOR (95% CI)AP (95% CI)Additive PMultiplicative P
  • *

    Heavy smoking was defined as >10 pack-years of cigarette smoking. 95% CI = 95% confidence interval (see Table 1 for other definitions).

  • Attributable proportion (AP) due to interaction was calculated as ([RRG+,E+ − RRG+,E− − RRG−,E+] + 1)/RRG+,E+, where RR is the relative risk, G is the genetic polymorphism, and E is the environmental factor; AP = 0 if there is no interaction.

  • For the risk of all RA, the odds ratios (ORs) were determined from conditional logistic regression models controlled for matching factors and adjusted for age at menarche, regularity of menses, parity, and breastfeeding.

  • §

    For the risk of seropositive or seronegative RA, the ORs were determined from unconditional logistic regression models adjusted for matching factors, age at menarche, regularity of menses, parity, and breastfeeding.

All RA    
 GSTT1     
  Present     
   ≤10 pack-years240/2851.0 (referent)0.53 (0.23 to 0.82)0.00050.05
   >10 pack-years186/1571.34 (1.01 to 1.77)   
  Null     
   ≤10 pack-years44/630.83 (0.54 to 1.28)   
   >10 pack-years55/272.47 (1.48 to 4.12)   
 GSTM1     
  Present     
   ≤10 pack-years148/1651.0 (referent)−0.30 (−0.86 to 0.27)0.310.67
   >10 pack-years127/811.76 (1.23 to 2.52)   
  Null     
   ≤10 pack-years138/1760.93 (0.68 to 1.26)   
   >10 pack-years111/971.30 (0.91 to 1.86)   
 GSTP1     
  AA     
   ≤10 pack-years108/1401.0 (referent)−0.36 (−0.96 to 0.24)0.240.18
   >10 pack-years121/751.81 (1.25 to 2.62)   
  AG/GG     
   ≤10 pack-years170/2060.96 (0.70 to 1.30)   
   >10 pack-years118/1051.30 (0.91 to 1.85)   
 HMOX1     
  AA     
   ≤10 pack-years88/991.0 (referent)0.29 (−0.06 to 0.63)0.100.05
   >10 pack-years75/651.39 (0.92 to 2.11)   
  AT/TT     
   ≤10 pack-years194/2450.93 (0.67 to 1.28)   
   >10 pack-years166/1061.85 (1.29 to 2.65)   
Seropositive RA§     
 GSTT1     
  Present     
   ≤10 pack-years137/2851.0 (referent)0.62 (0.35 to 0.89)<0.00010.01
   >10 pack-years111/1571.35 (0.98 to 1.85)   
  Null     
   ≤10 pack-years21/630.68 (0.40 to 1.16)   
   >10 pack-years38/272.70 (1.58 to 4.61)   
 GSTM1     
  Present     
   ≤10 pack-years89/1651.0 (referent)−0.13 (−0.72 to 0.45)0.660.96
   >10 pack-years78/811.74 (1.17 to 2.58)   
  Null     
   ≤10 pack-years72/1760.80 (0.55 to 1.15)   
   >10 pack-years70/971.36 (0.91 to 2.02)   
 GSTP1     
  AA   ≤10 pack-years59/1401.0 (referent)−0.36 (−1.01 to 0.29)0.280.16
   >10 pack-years74/751.99 (1.30 to 3.03)   
  AG/GG     
   ≤10 pack-years98/2061.00 (0.69 to 1.44)   
   >10 pack-years75/1051.46 (0.97 to 2.19)   
 HMOX1     
  AA     
   ≤10 pack-years52/991.0 (referent)0.41 (0.04 to 0.78)0.030.06
   >10 pack-years44/651.29 (0.79 to 2.09)   
  AT/TT     
   ≤10 pack-years104/2450.79 (0.55 to 1.15)   
   >10 pack-years107/1061.82 (1.22 to 2.72)   
Seronegative RA§     
 GSTT1     
  Present     
   ≤10 pack-years103/2851.0 (referent)0.25 (−0.34 to 0.84)0.400.51
   >10 pack-years75/1571.28 (0.90 to 1.83)   
  Null     
   ≤10 pack-years23/631.04 (0.61 to 1.76)   
   >10 pack-years17/271.76 (0.92 to 3.38)   
 GSTM1     
  Present     
   ≤10 pack-years59/1651.0 (referent)−0.56 (−1.43 to 0.30)0.200.17
   >10 pack-years49/811.73 (1.09 to 2.72)   
  Null     
   ≤10 pack-years66/1761.10 (0.74 to 1.64)   
   >10 pack-years41/971.17 (0.73 to 1.86)   
 GSTP1     
  AA     
   ≤10 pack-years49/1401.0 (referent)−0.44 (−1.28 to 0.41)0.310.25
   >10 pack-years47/751.59 (0.99 to 2.55)   
  AG/GG     
   ≤10 pack-years72/2060.91 (0.61 to 1.37)   
   >10 pack-years43/1051.05 (0.66 to 1.66)   
 HMOX1     
  AA     
   ≤10 pack-years36/991.0 (referent)0.04 (−0.51 to 0.60)0.880.75
   >10 pack-years31/651.45 (0.83 to 2.51)   
  AT/TT     
   ≤10 pack-years90/2451.13 (0.74 to 1.71)   
   >10 pack-years59/1061.64 (1.03 to 2.63)   

When assessing the effects on the risk of seropositive RA, we observed multiplicative interactions (P = 0.01) and strong additive interactions (AP = 0.62, 95% CI 0.35 to 0.89; P < 0.0001) between GSTT1-null and heavy smoking. Moreover, we observed additive interactions between HMOX1 and heavy smoking (AP = 0.41, 95% CI 0.04 to 0.78; P = 0.03), but no significant multiplicative interactions (P = 0.06).

After comparing our results using the Bonferroni-adjusted P value threshold of 0.008, only the additive interactions between GSTT1-null and heavy smoking in the risk of all RA (P = 0.0005) and in the risk of seropositive RA (P < 0.0001) remained significant. The multiplicative interactions between GSTT1-null and heavy smoking showed borderline significance in the risk of seropositive RA (P = 0.01). No significant gene–environment interactions were seen between GSTM1-null or GSTP1 and heavy smoking in the risk of all RA or the risk of seropositive RA or between any of the GST or HMOX1 polymorphisms and heavy smoking in the risk of seronegative RA.

The results of analyses of interactions between the GST and HMOX1 polymorphisms and ever smoking are presented in Table 3. We observed additive interactions between GSTT1-null and ever smoking in the risk of all RA (AP = 0.44, 95% CI 0.06 to 0.83; P = 0.02) and the risk of seropositive RA (AP = 0.53, 95% CI 0.15 to 0.91; P = 0.01), but not multiplicative interactions. For the risk of seronegative RA, we observed multiplicative interactions (P = 0.04) between GSTM1-null and ever smoking. However, these interactions were no longer significant after adjusting for multiple comparisons. We observed no other significant interactions between the genetic polymorphisms and ever smoking when assessing the effects on RA risk.

Table 3. Gene–environment interactions between GST and HMOX1 polymorphisms and ever smoking in relation to the risk of all RA and RA serologic phenotypes in subjects from the Nurses' Health Study*
RA risk, polymorphism, smoking statusNo. cases/no. controlsOR (95% CI)AP (95% CI)Additive PMultiplicative P
  • *

    95% CI = 95% confidence interval (see Table 1 for other definitions).

  • Attributable proportion (AP) due to interaction was calculated as ([RRG+,E+ − RRG+,E− − RRG−,E+] + 1)/RRG+,E+, where RR is the relative risk, G is the genetic polymorphism, and E is the environmental factor; AP = 0 if there is no interaction.

  • For the risk of all RA, the odds ratios (ORs) were determined from conditional logistic regression models controlled for matching factors and adjusted for age at menarche, regularity of menses, parity, and breastfeeding.

  • §

    For the risk of seropositive or seronegative RA, the ORs were determined from unconditional logistic regression models adjusted for matching factors, age at menarche, regularity of menses, parity, and breastfeeding.

All RA     
 GSTT1     
  Present     
   Never smoker173/1911.0 (referent)0.44 (0.06 to 0.83)0.020.14
   Ever smoker260/2531.05 (0.80 to 1.38)   
  Null     
   Never smoker32/460.77 (0.46 to 1.30)   
   Ever smoker64/461.48 (0.96 to 2.29)   
 GSTM1     
  Present     
   Never smoker102/1131.0 (referent)−0.48 (−1.06 to 0.10)0.100.22
   Ever smoker176/1341.48 (1.05 to 2.08)   
  Null     
   Never smoker104/1171.06 (0.74 to 1.54)   
   Ever smoker146/1591.04 (0.73 to 1.47)   
 GSTP1     
  AA     
   Never smoker77/971.0 (referent)−0.23 (−0.77 to 0.31)0.410.26
   Ever smoker152/1211.28 (0.89 to 1.84)   
  AG/GG     
   Never smoker124/1400.96 (0.67 to 1.38)   
   Ever smoker166/1731.01 (0.71 to 1.44)   
 HMOX1     
  AA     
   Never smoker63/711.0 (referent)0.04 (−0.37 to 0.45)0.840.56
   Ever smoker102/921.35 (0.90 to 2.03)   
  AT/TT     
   Never smoker139/1681.02 (0.71 to 1.46)   
   Ever smoker223/1881.43 (1.00 to 2.05)   
Seropositive RA§     
 GSTT1     
  Present     
   Never smoker97/1911.0 (referent)0.53 (0.15 to 0.91)0.010.08
   Ever smoker154/2531.06 (0.78 to 1.44)   
  Null     
   Never smoker16/460.66 (0.35 to 1.22)   
   Ever smoker40/461.53 (0.94 to 2.48)   
 GSTM1     
  Present     
   Never smoker63/1131.0 (referent)−0.21 (−0.82 to 0.40)0.510.61
   Ever smoker105/1341.36 (0.93 to 1.99)   
  Null     
   Never smoker53/1170.85 (0.55 to 1.31)   
   Ever smoker89/1591.01 (0.68 to 1.48)   
 GSTP1     
  AA     
   Never smoker44/971.0 (referent)−0.11 (−0.69 to 0.46)0.700.36
   Ever smoker88/1211.27 (0.84 to 1.92)   
  AG/GG     
   Never smoker70/1400.91 (0.59 to 1.39)   
   Ever smoker103/1731.05 (0.71 to 1.57)   
 HMOX1     
  AA     
   Never smoker40/711.0 (referent)0.37 (−0.08 to 0.81)0.100.14
   Ever smoker55/921.05 (0.66 to 1.68)   
  AT/TT     
   Never smoker72/1680.74 (0.48 to 1.14)   
   Ever smoker140/1881.25 (0.84 to 1.85)   
Seronegative RA§     
 GSTT1     
  Present     
   Never smoker76/1911.0 (referent)0.24 (−0.38 to 0.86)0.450.46
   Ever smoker106/2531.06 (0.74 to 1.50)   
   Never smoker16/460.95 (0.51 to 1.79)   
   Ever smoker24/461.33 (0.76 to 2.34)   
 GSTM1     
  Present     
   Never smoker39/1131.0 (referent)−0.87 (−1.78 to 0.03)0.060.04
   Ever smoker71/1341.60 (1.02 to 2.50)   
  Null     
   Never smoker51/1171.38 (0.86 to 2.23)   
   Ever smoker57/1591.06 (0.67 to 1.68)   
 GSTP1     
  AA     
   Never smoker33/971.0 (referent)−0.49 (−1.29 to 0.32)0.230.15
   Ever smoker64/1211.36 (0.85 to 2.17)   
  AG/GG     
   Never smoker54/1401.03 (0.64 to 1.66)   
   Ever smoker63/1730.94 (0.59 to 1.48)   
HMOX1     
  AA     
   Never smoker23/711.0 (referent)−0.50 (−1.18 to 0.19)0.150.31
   Ever smoker47/921.90 (1.09 to 3.31)   
  AT/TT     
   Never smoker67/1681.52 (0.91 to 2.54)   
   Ever smoker83/1881.61 (0.98 to 2.66)   

Results of stratified analyses.

Results from analyses stratified according to the presence or absence of the GSTT1 deletion or HMOX1 risk alleles, representing the 2 genotypes showing significant interactions (P < 0.05) with heavy smoking in our primary analyses, are presented in Table 4. When comparing the risk of all RA between heavy smokers and never or light smokers, we observed a 3.10-times increased risk (95% CI 1.65 to 5.89) in individuals with the GSTT1-null polymorphism. This association was stronger for seropositive RA, in which we observed a 4.25-times increased risk (95% CI 2.04 to 8.83) in those with GSTT1-null. Among individuals with the HMOX1 risk alleles (AT/TT), we observed a 1.90-times increased risk of all RA (95% CI 1.39 to 2.60) in heavy smokers when compared with never or light smokers. Again, this association was stronger for seropositive RA, in which a 2.26-times increased risk (95% CI 1.58 to 3.24) was observed in heavy smokers with the HMOX1 risk alleles.

Table 4. Stratified analyses of genotypes showing significant interactions with heavy smoking in relation to the risk of all RA and seropositive RA in subjects from the NHS and the EIRA study*
Study, genetic factor, smoking statusAll RASeropositive RA
No. cases/no. controlsOR (95% CI)PNo. cases/no. controlsOR (95% CI)P
  • *

    Stratified analyses were performed for those factors showing significant interactions (P < 0.05) in relation to the RA risk in interaction analyses (data shown in Tables 2, 3, 5, and 6). 95% CI = 95% confidence interval (see Table 1 for other definitions).

  • For the risk of all RA, the odds ratios (ORs) were determined from models adjusted for matching factors, age at menarche, regularity of menses, parity, and breastfeeding, in 549 cases/549 controls in the NHS and 1,771 cases/1,107 controls in the EIRA study.

  • For the risk of seropositive RA (defined as rheumatoid factor positive in the NHS, and anti–citrullinated protein antibody positive in the EIRA study), the ORs were determined from unconditional logistic regression models adjusted for age, sex, and geographic region of Sweden, in 325 cases/549 controls in the NHS and 1,123 cases/1,107 controls in the EIRA study.

NHS
 GSTT1-null   
  ≤10 pack-years44/631.00 (referent) 21/631.00 (referent) 
  >10 pack-years55/273.10 (1.65 to 5.89)0.000438/274.25 (2.04 to 8.83)0.0001
 GSTT1-present      
  ≤10 pack-years240/2851.00 (referent) 137/2851.00 (referent) 
  >10 pack-years186/1571.36 (1.02 to 1.79)0.03111/1571.41 (1.02 to 1.96)0.04
 GSTT1-null      
  Never smoker32/461.00 (referent) 16/461.00 (referent) 
  Ever smoker64/461.95 (1.06 to 3.59)0.0340/462.39 (1.14 to 5.00)0.02
 GSTT1-present      
  Never smoker173/1911.00 (referent) 97/1911.00 (referent) 
  Ever smoker260/2531.09 (0.83 to 1.43)0.55154/2531.16 (0.84 to 1.60)0.37
 HMOX1-AT/TT      
  ≤10 pack-years194/2451.00 (referent) 104/2451.00 (referent) 
  >10 pack-years166/1061.90 (1.39 to 2.60)<0.0001107/1062.26 (1.58 to 3.24)<0.0001
 HMOX1-AA      
  ≤10 pack-years88/991.00 (referent) 52/991.00 (referent) 
  >10 pack-years75/651.24 (0.79 to 1.95)0.3544/651.22 (0.72 to 2.08)0.46
EIRA      
 GSTT1-null      
  ≤10 pack-years131/1011.00 (referent) 70/1011.00 (referent) 
  >10 pack-years121/492.40 (1.52 to 3.78)0.000294/493.48 (2.09 to 5.78)<0.0001
 GSTT1-present     
  ≤10 pack-years821/5681.00 (referent) 485/5681.00 (referent) 
  >10 pack-years660/3101.61 (1.35 to 1.93)<0.0001450/3101.96 (1.60 to 2.39)<0.0001

The results from GSTT1-stratified analyses in which the GSTT1-null variant showed interactions with ever smoking (P = 0.02 versus never smoking) are also shown in Table 4. For the risk of all RA, when comparing ever smokers with never smokers, we observed a 1.95-times increased risk (95% CI 1.06 to 3.59) among individuals with the GSTT1-null polymorphism. This association was stronger for seropositive RA, in which we observed a 2.39-times increased risk (95% CI 1.14 to 5.00) in those with GSTT1-null. Although GSTM1 showed a significant interaction with ever smoking in the risk of seronegative RA, we observed only nonsignificant results in stratified analyses.

Results of replication analyses.

Analyses of gene–environment interactions in the NHS sample identified significant associations with heavy smoking for both the GSTT1-null and the HMOX1 risk alleles when assessing their effects on the risk of all RA and the risk of seropositive RA. The results of replication analyses in the EIRA cohort are presented in Table 5. For the risk of ACPA-positive RA, we observed an OR of 2.64 (95% CI 1.82 to 3.81) in heavy smokers with the GSTT1-null polymorphism compared with never or light smokers with GSTT1 present. We observed significant multiplicative interactions (P = 0.04) and strong additive interactions (AP = 0.32, 95% CI 0.04 to 0.60; P = 0.02) between GSTT1-null and heavy smoking. No significant interactions were observed between GSTT1-null and heavy smoking when assessing the risk of all RA or the risk of ACPA-negative RA. There was no evidence of significant interactions between the HMOX1 risk alleles and heavy smoking in the risk of all RA or the risk of RA serologic phenotypes. In the EIRA sample, we also tested for GSTT1 and HMOX1 interactions with ever smoking, but no significant interactions were observed (Table 6).

Table 5. Replication analyses of gene–environment interactions in relation to the risk of all RA and RA serologic phenotypes in subjects from the EIRA study*
RA risk, polymorphism, smoking statusNo. cases/no. controlsOR (95% CI)AP (95% CI)Additive PMultiplicative P
  • *

    95% CI = 95% confidence interval; ACPA = anti–citrullinated protein antibody (see Table 1 for other definitions).

  • The odds ratios (ORs) were determined from unconditional logistic regression models adjusted for age, sex, and geographic region of Sweden.

  • The attributable proportion (AP) due to interaction was calculated as ([RRG+,E+ − RRG+,E− − RRG−,E+] + 1)/RRG+,E+, where RR is the relative risk, G is the genetic polymorphism, and E is the environmental factor; AP = 0 if there is no interaction.

All RA     
 GSTT1     
  Present     
   ≤10 pack-years821/5681.0 (referent)0.19 (−0.14 to 0.51)0.250.21
   >10 pack-years660/3101.66 (1.40 to 1.97)   
  Null     
   ≤10 pack-years131/1010.90 (0.68 to 1.19)   
   >10 pack-years121/491.92 (1.36 to 2.73)   
 HMOX1     
  AA     
   ≤10 pack-years265/1691.0 (referent)0.17 (−0.27 to 0.60)0.460.27
   >10 pack-years189/821.37 (0.90 to 2.10)   
  AT/TT     
   ≤10 pack-years628/4740.73 (0.55 to 0.99)   
   >10 pack-years541/2641.32 (0.96 to 1.83)   
ACPA-positive RA     
 GSTT1     
  Present     
   ≤10 pack-years485/5681.0 (referent)0.32 (0.04 to 0.60)0.020.04
   >10 pack-years450/3101.99 (1.65 to 2.40)   
  Null     
   ≤10 pack-years70/1010.80 (0.58 to 1.11)   
   >10 pack-years94/492.64 (1.82 to 3.81)   
 HMOX1     
  AA     
   ≤10 pack-years143/1691.0 (referent)0.19 (−0.25 to 0.64)0.400.19
   >10 pack-years124/821.72 (1.06 to 2.79)   
  AT/TT     
   ≤10 pack-years338/4740.70 (0.50 to 1.00)   
   >10 pack-years375/2641.76 (1.21 to 2.56)   
ACPA-negative RA     
 GSTT1     
  Present     
   ≤10 pack-years336/5681.0 (referent)−0.26 (−1.00 to 0.48)0.490.56
   >10 pack-years210/3101.23 (0.98 to 1.53)   
  Null     
   ≤10 pack-years61/1011.02 (0.72 to 1.43)   
   >10 pack-years27/490.98 (0.60 to 1.62)   
 HMOX1     
  AA     
   ≤10 pack-years122/1691.0 (referent)0.08 (−0.55 to 0.71)0.800.72
   >10 pack-years65/821.09 (0.65 to 1.80)   
  AT/TT     
   ≤10 pack-years290/4740.77 (0.55 to 1.09)   
   >10 pack-years166/2640.93 (0.63 to 1.37)   
Table 6. Gene–environment interactions between GSTs and HMOX1 polymorphisms and ever smoking in the risk of all RA and RA serologic phenotypes in subjects from the EIRA study*
RA risk, polymorphism, smoking statusNo. cases/no. controlsOR (95% CI)AP (95% CI)AdditiveMultiplicative
PP
  • *

    95% CI = 95% confidence interval; ACPA = anti–citrullinated protein antibody (see Table 1 for other definitions).

  • The odds ratios (ORs) were determined from unconditional logistic regression models adjusted for age, sex, and geographic region of Sweden.

  • The attributable proportion (AP) due to interaction was calculated as ([RRG+,E+ − RRG+,E− − RRG−,E+] + 1)/RRG+,E+, where RR is the relative risk, G is the genetic polymorphism, and E is the environmental factor; AP = 0 if there is no interaction.

All RA     
 GSTT1     
  Present     
   Never smoker476/3451.0 (referent)−0.11 (−0.56 to 0.34)0.660.62
   Ever smoker940/5291.29 (1.08 to 1.53)   
  Null     
   Never smoker75/511.07 (0.73 to 1.56)   
   Ever smoker163/971.22 (0.91 to 1.62)   
 HMOX1     
  AA     
   Never smoker142/991.0 (referent)−0.14 (−0.51 to 0.22)0.440.54
   Ever smoker196/1391.45 (1.05 to 2.01)   
  AT/TT     
   Never smoker363/2640.96 (0.71 to 1.30)   
   Ever smoker749/4241.23 (0.93 to 1.63)   
ACPA-positive RA     
 GSTT1     
  Present     
   Never smoker261/3451.0 (referent)0.08 (−0.30 to 0.46)0.660.67
   Ever smoker625/5291.56 (1.28 to 1.90)   
  Null     
   Never smoker35/510.91 (0.57 to 1.44)   
   Ever smoker117/971.59 (1.17 to 2.18)   
 HMOX1     
  AA     
   Never smoker70/991.0 (referent)−0.21 (−0.58 to 0.16)0.270.33
   Ever smoker196/1391.99 (1.37 to 2.90)   
  AT/TT     
   Never smoker198/2641.06 (0.74 to 1.52)   
   Ever smoker510/4241.70 (1.22 to 2.37)   
ACPA-negative RA     
 GSTT1     
  Present     
   Never smoker215/3451.0 (referent)−0.60 (−1.52 to 0.33)0.210.13
   Ever smoker315/5290.96 (0.77 to 1.19)   
  Null     
   Never smoker40/511.26 (0.80 to 1.97)   
   Ever smoker46/970.76 (0.52 to 1.12)   
 HMOX1     
  AA     
   Never smoker72/991.0 (referent)−0.01 (−0.57 to 0.56)0.980.93
   Ever smoker93/1390.92 (0.62 to 1.37)   
  AT/TT     
   Never smoker165/2640.86 (0.60 to 1.23)   
   Ever smoker239/4240.78 (0.55 to 1.09)   

Results from analyses stratified by the presence or absence of the GSTT1 deletion in the EIRA cohort are presented in Table 4. As in the NHS sample, the strongest association was observed in the risk of ACPA-positive RA, in which we observed a 3.48-times increased risk (95% CI 2.09 to 5.78) in heavy smokers with GSTT1-null.

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

Interest in the associations of GST and HMOX1 genes with RA risk stems from the role of the genes in the detoxification of carcinogens in cigarette smoke and in the protection against oxidative stress caused by ROS. This nested case–control study demonstrated gene–environment interactions for both GSTT1-null and HMOX1 risk alleles with heavy smoking (>10 pack-years) in the NHS cohort, although only the interactions between GSTT1-null and heavy smoking remained significant after correction for multiple comparisons. These interactions were strongest in the risk of seropositive RA. The effect of interactions between GSTT1-null and heavy smoking on the risk of seropositive RA was replicated in an independent Swedish case–control sample. In both cohorts, no significant interactions were observed between the GSTM1-null or GSTP1 alleles and heavy smoking. Moreover, we observed no significant relationships with the risk of seronegative RA.

To the best of our knowledge, this is the first study to examine and identify a convincing interaction between the GSTT1-null polymorphism and heavy smoking in the risk of seropositive RA, with replication in an independent cohort. A previous study by Bohanec Grabar et al, in which only RA cases were assessed, identified a significant interaction between GSTT1-null and smoking in relation to disease activity as the RA phenotype, observing an OR for high disease activity of 8.64 (95% CI 2.00 to 37.43) in smokers with GSTT1-null compared with smokers with GSTT1-present (24). We observed that the interaction between GSTT1-null and heavy smoking led to an increased risk for developing RA, with stronger effects on seropositive RA. We did not study the phenotype of RA disease activity. Our study showed that among subjects with the GSTT1-null polymorphism, heavy smokers were at a 3.1-times increased risk of developing RA compared with never or light smokers. This increase in risk was even greater for seropositive RA, in which we observed a 4.3-times increased risk among the subjects with GSTT1-null.

A similar association was seen in our replication analysis, in which we observed a 3.5-times increased risk of ACPA-positive RA among individuals with GSTT1-null who were heavy smokers. When we examined the effect of GSTT1-null among groups defined by smoking levels of ≤10, 10–20, and >20 pack-years, to determine whether this effect varies for even higher levels of smoking, we obtained similar results for those with a history of 10–20 pack-years and those with a history of >20 pack-years of smoking (results not shown). Our observation of modest interactions between GSTT1-null and ever smoking in the NHS cohort but no significant interaction in the EIRA cohort supports the importance of considering the dose effect of smoking in analyses of interactions (2, 6).

The effect of interaction between GSTT1-null and heavy smoking on RA risk may be due to the lack of enzymatic activity associated with the GSTT1-null polymorphism, which may decrease the detoxification of certain cytotoxic carcinogens and metabolites found in cigarette smoke and subsequently increase the harmful effects of heavy smoking, a proven risk factor for RA (2–5). These results establish the importance of considering genetic background when studying the effect of environmental risk factors.

Despite the similar functions between GST genes, we did not observe significant interactions between GSTM1-null or GSTP1 and heavy smoking in the risk of RA, as we had observed with GSTT1-null. These differing results may be due to the differences in catalytic activity between the GST classes. The GST-Theta class has a lower affinity toward glutathione conjugates, leading to less product inhibition and thus higher catalytic efficiency, and has an ∼10 times higher enzymatic activity rate when compared with the GST-Mu and GST-Pi classes (13, 19, 47). There are also established differences in specific substrates for GSTT1, GSTM1, and GSTP1 and their roles in detoxification and toxification (13–16).

Results of previous studies on interactions between GSTM1 polymorphisms and smoking in RA have been inconsistent (3, 24, 26). Mattey et al observed that ever smokers with the GSTM1-null polymorphism were at higher risk for a more severe disease outcome, but Bohanec Grabar et al did not observe a significant interaction between GSTM1 and ever smoking in relation to RA disease activity (24, 26). Criswell et al observed a significant interaction between GSTM1 and exposure to tobacco smoke in the risk of RA (OR 2.10, 95% CI 1.13 to 3.89), which suggests that smoking is a stronger risk factor among individuals with GSTM1 present (3). After correction for multiple comparisons, we observed no significant associations with GSTM1 in the risk of RA.

This is also the first study to examine the effect of possible interactions between HMOX1 and heavy smoking on RA risk. We observed interactions between HMOX1 and heavy smoking for both the risk of all RA and the risk of seropositive RA in the NHS sample. Our results suggest that among individuals carrying at least 1 HMOX1 risk allele, heavy smoking was associated with a 1.9-times increased risk of all RA and a 2.3-times increased risk of seropositive RA, compared with never or light smokers. However, this result was not significant after correction for multiple comparisons and we did not observe significant associations in the replication analyses in the EIRA cohort. More research is needed to determine the validity of this association.

A number of studies have shown gene–environment interactions between HLA and smoking in the risk of seropositive RA (3, 6, 9–12). Thus, it is important to consider the impact that HLA may have on our results. We examined possible gene–gene interactions between HLA and our polymorphisms of interest and found no significant associations (results not shown).

Limitations of this study include the inability to determine heterozygous deletions for GSTM1 and GSTT1 polymorphisms, and the lack of information on the anti-CCP status in the NHS cohort. The fact that data on the anti-CCP status were lacking is due to the absence of plasma samples in almost half of our patients with RA, and the fact that many of the cases were diagnosed prior to the widespread use of the anti-CCP test. However, RF status was available from medical record reviews, and other gene–environment interactions are similar for RF- and anti-CCP–seropositive phenotypes in RA (9, 10). Our rates of seropositive RA in this study (59% anti-CCP+ and/or RF+) are similar to those reported in a large US registry study that recruited patients from rheumatology practices across the US (48). Furthermore, we only had data on incident RA, and therefore could not study disease severity phenotypes.

The NHS cohorts are comprised primarily of middle-to-older–age Caucasian women with high education levels. This lack of diversity in the population may raise concerns about the generalizability of our results, and these interactions should be studied in other cohorts. However, the restriction of our genetic analyses to Caucasian women limits the potential for population stratification, and thus may also be viewed as a strength. While limiting our analyses to self-reported Caucasian ancestry does not remove all concerns about population stratification, prior research has examined the potential for this bias extensively within the NHS and found no evidence of significant population stratification (49, 50).

Other strengths of this study include the prospective nature of the information collected, including detailed information on smoking status, and the access to a large, independent case–control sample for replication. Our sample size makes this one of the largest studies examining the effects of GST and HMOX1 genes on RA risk. Despite this large sample, the power to detect a significant interaction was still limited. Based on the observed ORs for the association of RA risk with specific genes (OR 1.1) and heavy smoking (OR 1.8), we had, at most, 24% power and 40% power to detect a significant gene × environment interaction (OR of 1.5) in the NHS and EIRA study, respectively. This should be considered when interpreting negative results.

In summary, we observed significant multiplicative and strong additive interactions between the GSTT1-null polymorphism and heavy smoking, with the strongest associations seen in the risk of seropositive RA. In replication analyses, we found that the interaction between GSTT1-null and heavy smoking that was observed in relation to the risk of seropositive RA could be replicated in a study assessing the risk of ACPA-positive RA. This suggests that we have identified a truly novel association with the risk of seropositive RA. Although we observed significant interactions between the HMOX1 risk alleles and heavy smoking in the risk of RA in the NHS, these results could not be replicated. No significant interactions were seen in relation to the risk of seronegative RA, supporting the hypothesis that different risk factors and different pathways may exist between the seropositive and seronegative RA phenotypes.

Our results add new evidence to the hypothesis that gene–environment interactions play a significant role in the complex etiology of RA. Additional research is needed to examine the validity of these interactions and to study the potential biologic pathways involved. Future studies should focus on how to incorporate these findings, in addition to the findings on other risk factors previously identified, into larger models that can be used for RA prediction.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Mr. Keenan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Keenan, Chibnik, Bengtsson, Klareskog, Alfredsson, Karlson.

Acquisition of data. Keenan, Chibnik, Cui, Ding, Padyukov, Kallberg, Bengtsson, Alfredsson, Karlson.

Analysis and interpretation of data. Keenan, Chibnik, Cui, Ding, Padyukov, Kallberg, Klareskog, Alfredsson, Karlson.

Acknowledgements

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES

The authors wish to thank the participants, investigators, and study staff of the NHS, headquartered at the Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School in Boston, Massachusetts. We also would like to thank the EIRA study in Sweden for their contributions.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. Acknowledgements
  8. REFERENCES