close

Вход

Забыли?

вход по аккаунту

?

Effect of interactions of glutathione S-transferase T1 M1 and P1 and HMOX1 gene promoter polymorphisms with heavy smoking on the risk of rheumatoid arthritis.

код для вставкиСкачать
ARTHRITIS & RHEUMATISM
Vol. 62, No. 11, November 2010, pp 3196–3210
DOI 10.1002/art.27639
© 2010, American College of Rheumatology
Effect of Interactions of Glutathione S-Transferase T1, M1, and
P1 and HMOX1 Gene Promoter Polymorphisms With Heavy
Smoking on the Risk of Rheumatoid Arthritis
Brendan T. Keenan,1 Lori B. Chibnik,2 Jing Cui,1 Bo Ding,3 Leonid Padyukov,3
Henrik Kallberg,3 Camilla Bengtsson,3 Lars Klareskog,4 Lars Alfredsson,3 and
Elizabeth W. Karlson1
variates. 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 ⴝ
0.05) and additive (AP ⴝ 0.53, P ⴝ 0.0005) interactions
between the GSTT1-null polymorphism and smoking
and multiplicative interactions (P ⴝ 0.05) between
HMOX1 and smoking were observed. For the risk of
seropositive RA, multiplicative (P ⴝ 0.01) and additive
(AP ⴝ 0.62, P < 0.0001) interactions between GSTT1null and smoking and additive interactions (AP ⴝ 0.41,
P ⴝ 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 ⴝ
0.04) and additive interactions (AP ⴝ 0.32, P ⴝ 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.
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 ⴝ 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 coThe Nurses’ Health Study is supported by NIH grants CA87969, CA-49449, CA-67262, CA-50385, AR-049880-06, AR-47782,
and AR-0524-01. The Epidemiological Investigation of Rheumatoid
Arthritis study was supported by grants from the Swedish Medical
Research Council, the Swedish Council for Working Life and Social
Research, King Gustaf V’s 80-Year Foundation, the Swedish Rheumatism Foundation, the Stockholm County Council, and AFA Insurance, Stockholm, Sweden.
1
Brendan T. Keenan, BA, Jing Cui, MD, PhD, Elizabeth W.
Karlson, MD: Harvard Medical School and Brigham and Women’s
Hospital, Boston, Massachusetts; 2Lori B. Chibnik, PhD, MPH: Harvard Medical School and Brigham and Women’s Hospital, Boston, and
Broad Institute, Cambridge, Massachusetts; 3Bo Ding, PhD, Leonid
Padyukov, MD, PhD, Henrik Kallberg, PhD, Camilla Bengtsson, PhD,
Lars Alfredsson, PhD: Karolinska Institutet, Stockholm, Sweden;
4
Lars Klareskog, MD, PhD: Karolinska Institutet and Karolinska
Hospital, Stockholm, Sweden.
Address correspondence and reprint requests to Brendan T.
Keenan, BA, Department of Medicine, Division of Rheumatology,
Immunology and Allergy, Section of Clinical Sciences, Brigham and
Women’s Hospital, 75 Francis Street, Boston, MA 02115. E-mail:
bkeenan1@partners.org.
Submitted for publication February 23, 2010; accepted in
revised form June 24, 2010.
Exposure to certain environmental factors within
genetically predisposed individuals is thought to be an
underlying cause of the development of rheumatoid
3196
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
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 ␣- and ␤-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,
3197
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
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 con-
3198
firmed 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 ⱕ10 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
KEENAN ET AL
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 con-
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
3199
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*
NHS
Characteristic
Age at match, mean ⫾ SD years
Ever cigarette smoker
Heavy cigarette smoker†
Parous
Breastfeeding ⱖ12 months‡
Age at menarche ⬍12 years
Irregular menstrual cycles
Body mass index, mean ⫾ SD kg/m2
RA feature
Age at diagnosis, mean ⫾ SD years
Seropositive
Rheumatoid nodules
Radiographic changes
Gene frequency
GSTT1
Present
Null
GSTM1
Present
Null
GSTP1
AA
AG
GG
HMOX1
AA
AT
TT
HLA–SE
No SE
Any SE
EIRA
RA cases (n ⫽ 549)
Controls (n ⫽ 549)
RA cases (n ⫽ 1,771)
Controls (n ⫽ 1,107)
55.4 ⫾ 8.0
335 (61.7)
248 (46.0)
505 (93.2)
78 (14.4)
160 (29.1)
88 (16.0)
25.9 ⫾ 4.9
55.4 ⫾ 8.0
304 (55.5)
187 (34.4)
513 (94.3)
103 (18.9)
152 (27.7)
70 (12.8)
25.9 ⫾ 5.0
51.5 ⫾ 12.3
1,175 (66.7)
803 (45.3)
–
–
–
–
25.3 ⫾ 4.3
52.9 ⫾ 11.5
672 (61.0)
377 (34.1)
–
–
–
–
25.8 ⫾ 7.0
56.9 ⫾ 10.3
325 (59.2)
71 (12.9)
161 (29.3)
–
–
–
–
51.4 ⫾ 12.5
1,123 (63.4)
–
–
–
–
–
–
434 (81.3)
100 (18.7)
445 (82.9)
92 (17.1)
1,481 (83.6)
252 (14.2)
878 (79.3)
150 (13.6)
278 (52.2)
255 (47.8)
247 (47.2)
276 (52.8)
–
–
–
–
231 (44.0)
219 (41.7)
75 (14.3)
218 (41.1)
245 (46.1)
68 (12.8)
–
–
–
–
–
–
168 (31.5)
258 (48.4)
107 (20.1)
164 (31.5)
255 (49.0)
101 (19.4)
433 (27.9)
759 (49.0)
358 (23.1)
239 (25.7)
475 (51.0)
217 (23.3)
265 (48.8)
278 (51.2)
337 (62.3)
204 (37.7)
432 (26.0)
1,230 (74.0)
467 (47.7)
512 (52.3)
* 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.
sideration 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 ACPApositive 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
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
3200
KEENAN ET AL
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 status
All RA‡
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
GSTM1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
GSTP1
AA
ⱕ10 pack-years
⬎10 pack-years
AG/GG
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
Seropositive RA§
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
GSTM1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
GSTP1
AA
ⱕ10 pack-years
⬎10 pack-years
AG/GG
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
Seronegative RA§
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
No. cases/no.
controls
OR (95% CI)
AP (95% CI)†
240/285
186/157
1.0 (referent)
1.34 (1.01 to 1.77)
0.53 (0.23 to 0.82)
44/63
55/27
0.83 (0.54 to 1.28)
2.47 (1.48 to 4.12)
148/165
127/81
1.0 (referent)
1.76 (1.23 to 2.52)
138/176
111/97
0.93 (0.68 to 1.26)
1.30 (0.91 to 1.86)
108/140
121/75
1.0 (referent)
1.81 (1.25 to 2.62)
170/206
118/105
0.96 (0.70 to 1.30)
1.30 (0.91 to 1.85)
88/99
75/65
1.0 (referent)
1.39 (0.92 to 2.11)
194/245
166/106
0.93 (0.67 to 1.28)
1.85 (1.29 to 2.65)
137/285
111/157
1.0 (referent)
1.35 (0.98 to 1.85)
21/63
38/27
0.68 (0.40 to 1.16)
2.70 (1.58 to 4.61)
89/165
78/81
1.0 (referent)
1.74 (1.17 to 2.58)
72/176
70/97
0.80 (0.55 to 1.15)
1.36 (0.91 to 2.02)
59/140
1.0 (referent)
74/75
1.99 (1.30 to 3.03)
98/206
75/105
1.00 (0.69 to 1.44)
1.46 (0.97 to 2.19)
52/99
44/65
1.0 (referent)
1.29 (0.79 to 2.09)
104/245
107/106
0.79 (0.55 to 1.15)
1.82 (1.22 to 2.72)
103/285
75/157
1.0 (referent)
1.28 (0.90 to 1.83)
Additive
P
Multiplicative
P
0.0005
0.05
⫺0.30 (⫺0.86 to 0.27)
0.31
0.67
⫺0.36 (⫺0.96 to 0.24)
0.24
0.18
0.29 (⫺0.06 to 0.63)
0.10
0.05
0.62 (0.35 to 0.89)
⬍0.0001
0.01
⫺0.13 (⫺0.72 to 0.45)
0.66
0.96
⫺0.36 (⫺1.01 to 0.29)
0.28
0.16
0.41 (0.04 to 0.78)
0.03
0.06
0.25 (⫺0.34 to 0.84)
0.40
0.51
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
3201
Table 2. (Cont’d)
RA risk, polymorphism,
smoking status
Null
ⱕ10 pack-years
⬎10 pack-years
GSTM1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
GSTP1
AA
ⱕ10 pack-years
⬎10 pack-years
AG/GG
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
No. cases/no.
controls
OR (95% CI)
23/63
17/27
1.04 (0.61 to 1.76)
1.76 (0.92 to 3.38)
59/165
49/81
1.0 (referent)
1.73 (1.09 to 2.72)
66/176
41/97
1.10 (0.74 to 1.64)
1.17 (0.73 to 1.86)
49/140
47/75
1.0 (referent)
1.59 (0.99 to 2.55)
72/206
43/105
0.91 (0.61 to 1.37)
1.05 (0.66 to 1.66)
36/99
31/65
1.0 (referent)
1.45 (0.83 to 2.51)
90/245
59/106
1.13 (0.74 to 1.71)
1.64 (1.03 to 2.63)
AP (95% CI)†
Additive
P
Multiplicative
P
⫺0.56 (⫺1.43 to 0.30)
0.20
0.17
⫺0.44 (⫺1.28 to 0.41)
0.31
0.25
0.04 (⫺0.51 to 0.60)
0.88
0.75
* 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.
alleles, HMOX1 alleles, or GSTT1 and GSTM1 deletions between cases and controls.
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 pre-
sented 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.
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).
3202
KEENAN ET AL
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 status
All RA‡
GSTT1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
GSTM1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
GSTP1
AA
Never smoker
Ever smoker
AG/GG
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
Seropositive RA§
GSTT1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
GSTM1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
GSTP1
AA
Never smoker
Ever smoker
AG/GG
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
Seronegative RA§
GSTT1
Present
Never smoker
Ever smoker
No. cases/no.
controls
OR (95% CI)
AP (95% CI)†
Additive
P
Multiplicative
P
173/191
260/253
1.0 (referent)
1.05 (0.80 to 1.38)
0.44 (0.06 to 0.83)
0.02
0.14
32/46
64/46
0.77 (0.46 to 1.30)
1.48 (0.96 to 2.29)
102/113
176/134
1.0 (referent)
1.48 (1.05 to 2.08)
⫺0.48 (⫺1.06 to 0.10)
0.10
0.22
104/117
146/159
1.06 (0.74 to 1.54)
1.04 (0.73 to 1.47)
77/97
152/121
1.0 (referent)
1.28 (0.89 to 1.84)
⫺0.23 (⫺0.77 to 0.31)
0.41
0.26
124/140
166/173
0.96 (0.67 to 1.38)
1.01 (0.71 to 1.44)
63/71
102/92
1.0 (referent)
1.35 (0.90 to 2.03)
0.04 (⫺0.37 to 0.45)
0.84
0.56
139/168
223/188
1.02 (0.71 to 1.46)
1.43 (1.00 to 2.05)
97/191
154/253
1.0 (referent)
1.06 (0.78 to 1.44)
0.53 (0.15 to 0.91)
0.01
0.08
16/46
40/46
0.66 (0.35 to 1.22)
1.53 (0.94 to 2.48)
63/113
105/134
1.0 (referent)
1.36 (0.93 to 1.99)
⫺0.21 (⫺0.82 to 0.40)
0.51
0.61
53/117
89/159
0.85 (0.55 to 1.31)
1.01 (0.68 to 1.48)
44/97
88/121
1.0 (referent)
1.27 (0.84 to 1.92)
⫺0.11 (⫺0.69 to 0.46)
0.70
0.36
70/140
103/173
0.91 (0.59 to 1.39)
1.05 (0.71 to 1.57)
40/71
55/92
1.0 (referent)
1.05 (0.66 to 1.68)
0.37 (⫺0.08 to 0.81)
0.10
0.14
72/168
140/188
0.74 (0.48 to 1.14)
1.25 (0.84 to 1.85)
76/191
106/253
1.0 (referent)
1.06 (0.74 to 1.50)
0.24 (⫺0.38 to 0.86)
0.45
0.46
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
3203
Table 3. (Cont’d)
RA risk, polymorphism,
smoking status
Null
Never smoker
Ever smoker
GSTM1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
GSTP1
AA
Never smoker
Ever smoker
AG/GG
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
No. cases/no.
controls
OR (95% CI)
16/46
24/46
0.95 (0.51 to 1.79)
1.33 (0.76 to 2.34)
39/113
71/134
1.0 (referent)
1.60 (1.02 to 2.50)
51/117
57/159
1.38 (0.86 to 2.23)
1.06 (0.67 to 1.68)
33/97
64/121
1.0 (referent)
1.36 (0.85 to 2.17)
54/140
63/173
1.03 (0.64 to 1.66)
0.94 (0.59 to 1.48)
23/71
47/92
1.0 (referent)
1.90 (1.09 to 3.31)
67/168
83/188
1.52 (0.91 to 2.54)
1.61 (0.98 to 2.66)
AP (95% CI)†
Additive
P
Multiplicative
P
⫺0.87 (⫺1.78 to 0.03)
0.06
0.04
⫺0.49 (⫺1.29 to 0.32)
0.23
0.15
⫺0.50 (⫺1.18 to 0.19)
0.15
0.31
* 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.
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 GSTM1null 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.
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
3204
KEENAN ET AL
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*
All RA†
Study, genetic factor,
smoking status
NHS
GSTT1-null
ⱕ10 pack-years
⬎10 pack-years
GSTT1-present
ⱕ10 pack-years
⬎10 pack-years
GSTT1-null
Never smoker
Ever smoker
GSTT1-present
Never smoker
Ever smoker
HMOX1-AT/TT
ⱕ10 pack-years
⬎10 pack-years
HMOX1-AA
ⱕ10 pack-years
⬎10 pack-years
EIRA
GSTT1-null
ⱕ10 pack-years
⬎10 pack-years
GSTT1-present
ⱕ10 pack-years
⬎10 pack-years
No. cases/no.
controls
OR (95% CI)
Seropositive RA‡
P
44/63
55/27
1.00 (referent)
3.10 (1.65 to 5.89)
0.0004
240/285
186/157
1.00 (referent)
1.36 (1.02 to 1.79)
32/46
64/46
No. cases/no.
controls
OR (95% CI)
P
21/63
38/27
1.00 (referent)
4.25 (2.04 to 8.83)
0.0001
0.03
137/285
111/157
1.00 (referent)
1.41 (1.02 to 1.96)
0.04
1.00 (referent)
1.95 (1.06 to 3.59)
0.03
16/46
40/46
1.00 (referent)
2.39 (1.14 to 5.00)
0.02
173/191
260/253
1.00 (referent)
1.09 (0.83 to 1.43)
0.55
97/191
154/253
1.00 (referent)
1.16 (0.84 to 1.60)
0.37
194/245
166/106
1.00 (referent)
1.90 (1.39 to 2.60)
⬍0.0001
104/245
107/106
1.00 (referent)
2.26 (1.58 to 3.24)
⬍0.0001
88/99
75/65
1.00 (referent)
1.24 (0.79 to 1.95)
0.35
52/99
44/65
1.00 (referent)
1.22 (0.72 to 2.08)
0.46
131/101
121/49
1.00 (referent)
2.40 (1.52 to 3.78)
0.0002
70/101
94/49
1.00 (referent)
3.48 (2.09 to 5.78)
⬍0.0001
821/568
660/310
1.00 (referent)
1.61 (1.35 to 1.93)
⬍0.0001
485/568
450/310
1.00 (referent)
1.96 (1.60 to 2.39)
⬍0.0001
* 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.
(95% CI 1.58 to 3.24) was observed in heavy smokers
with the HMOX1 risk alleles.
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
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
3205
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 status
All RA
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
ACPA-positive RA
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
ACPA-negative RA
GSTT1
Present
ⱕ10 pack-years
⬎10 pack-years
Null
ⱕ10 pack-years
⬎10 pack-years
HMOX1
AA
ⱕ10 pack-years
⬎10 pack-years
AT/TT
ⱕ10 pack-years
⬎10 pack-years
No. cases/no.
controls
OR (95% CI)†
821/568
660/310
1.0 (referent)
1.66 (1.40 to 1.97)
131/101
121/49
0.90 (0.68 to 1.19)
1.92 (1.36 to 2.73)
265/169
189/82
1.0 (referent)
1.37 (0.90 to 2.10)
628/474
541/264
0.73 (0.55 to 0.99)
1.32 (0.96 to 1.83)
485/568
450/310
1.0 (referent)
1.99 (1.65 to 2.40)
70/101
94/49
0.80 (0.58 to 1.11)
2.64 (1.82 to 3.81)
143/169
124/82
1.0 (referent)
1.72 (1.06 to 2.79)
338/474
375/264
0.70 (0.50 to 1.00)
1.76 (1.21 to 2.56)
336/568
210/310
1.0 (referent)
1.23 (0.98 to 1.53)
61/101
27/49
1.02 (0.72 to 1.43)
0.98 (0.60 to 1.62)
122/169
65/82
1.0 (referent)
1.09 (0.65 to 1.80)
290/474
166/264
0.77 (0.55 to 1.09)
0.93 (0.63 to 1.37)
Additive
P
Multiplicative
P
0.19 (⫺0.14 to 0.51)
0.25
0.21
0.17 (⫺0.27 to 0.60)
0.46
0.27
0.32 (0.04 to 0.60)
0.02
0.04
0.19 (⫺0.25 to 0.64)
0.40
0.19
⫺0.26 (⫺1.00 to 0.48)
0.49
0.56
0.08 (⫺0.55 to 0.71)
0.80
0.72
AP (95% CI)‡
* 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.
smoking, but no significant interactions were observed
(Table 6).
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 ACPApositive RA, in which we observed a 3.48-times in-
creased risk (95% CI 2.09 to 5.78) in heavy smokers with
GSTT1-null.
DISCUSSION
Interest in the associations of GST and HMOX1
genes with RA risk stems from the role of the genes in
3206
KEENAN ET AL
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 status
All RA
GSTT1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
ACPA-positive RA
GSTT1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
ACPA-negative RA
GSTT1
Present
Never smoker
Ever smoker
Null
Never smoker
Ever smoker
HMOX1
AA
Never smoker
Ever smoker
AT/TT
Never smoker
Ever smoker
No. cases/no.
controls
OR (95% CI)†
AP (95% CI)‡
Additive
P
Multiplicative
P
476/345
940/529
1.0 (referent)
1.29 (1.08 to 1.53)
⫺0.11 (⫺0.56 to 0.34)
0.66
0.62
75/51
163/97
1.07 (0.73 to 1.56)
1.22 (0.91 to 1.62)
142/99
196/139
1.0 (referent)
1.45 (1.05 to 2.01)
⫺0.14 (⫺0.51 to 0.22)
0.44
0.54
363/264
749/424
0.96 (0.71 to 1.30)
1.23 (0.93 to 1.63)
261/345
625/529
1.0 (referent)
1.56 (1.28 to 1.90)
0.08 (⫺0.30 to 0.46)
0.66
0.67
35/51
117/97
0.91 (0.57 to 1.44)
1.59 (1.17 to 2.18)
70/99
196/139
1.0 (referent)
1.99 (1.37 to 2.90)
⫺0.21 (⫺0.58 to 0.16)
0.27
0.33
198/264
510/424
1.06 (0.74 to 1.52)
1.70 (1.22 to 2.37)
215/345
315/529
1.0 (referent)
0.96 (0.77 to 1.19)
⫺0.60 (⫺1.52 to 0.33)
0.21
0.13
40/51
46/97
1.26 (0.80 to 1.97)
0.76 (0.52 to 1.12)
72/99
93/139
1.0 (referent)
0.92 (0.62 to 1.37)
⫺0.01 (⫺0.57 to 0.56)
0.98
0.93
165/264
239/424
0.86 (0.60 to 1.23)
0.78 (0.55 to 1.09)
* 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.
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 packyears) in the NHS cohort, although only the interactions
between GSTT1-null and heavy smoking remained sig-
nificant 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
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
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 GSTT1null who were heavy smokers. When we examined the
effect of GSTT1-null among groups defined by smoking
levels of ⱕ10, 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
3207
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
3208
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 ACPApositive RA. This suggests that we have identified a truly
novel association with the risk of seropositive RA.
KEENAN ET AL
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.
ACKNOWLEDGMENTS
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.
AUTHOR CONTRIBUTIONS
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.
REFERENCES
1. Gabriel SE, Crowson CS, O’Fallon WM. The epidemiology of
rheumatoid arthritis in Rochester, Minnesota, 1955–1985. Arthritis Rheum 1999;42:415–20.
2. Costenbader KH, Feskanich D, Mandl LA, Karlson EW. Smoking
intensity, duration, and cessation, and the risk of rheumatoid
arthritis in women. Am J Med 2006;119:503–11.
3. Criswell LA, Merlino LA, Cerhan JR, Mikuls TR, Mudano AS,
Burma M, et al. Cigarette smoking and the risk of rheumatoid
arthritis among postmenopausal women: results from the Iowa
Women’s Health Study. Am J Med 2002;112:465–71.
4. Stolt P, Bengtsson C, Nordmark B, Lindblad S, Lundberg I,
Klareskog L, et al. Quantification of the influence of cigarette
smoking on rheumatoid arthritis: results from a population based
case-control study, using incident cases. Ann Rheum Dis 2003;62:
835–41.
5. Karlson EW, Lee IM, Cook NR, Manson JE, Buring JE, Hennek-
INTERACTIONS OF GST/HMOX1 POLYMORPHISMS AND SMOKING IN RA RISK
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
ens CH. A retrospective cohort study of cigarette smoking and risk
of rheumatoid arthritis in female health professionals. Arthritis
Rheum 1999;42:910–7.
Karlson EW, Chang SC, Cui J, Chibnik LB, Fraser PA, De Vivo I,
et al. Gene-environment interaction between HLA-DRB1 shared
epitope and heavy cigarette smoking in predicting incident RA.
Ann Rheum Dis 2010;69:54–60.
Gregersen PK, Silver J, Winchester RJ. The shared epitope
hypothesis: an approach to understanding the molecular genetics
of susceptibility to rheumatoid arthritis. Arthritis Rheum 1987;30:
1205–13.
Fernando MM, Stevens CR, Walsh EC, De Jager PL, Goyette P,
Plenge RM, et al. Defining the role of the MHC in autoimmunity:
a review and pooled analysis. PLoS Genet 2008;4:e1000024.
Klareskog L, Stolt P, Lundberg K, Kallberg H, Bengtsson C,
Grunewald J, et al, and the Epidemiological Investigation of
Arthritis Study Group. A new model for an etiology of rheumatoid arthritis: smoking may trigger HLA–DR (shared
epitope)–restricted immune reactions to autoantigens modified
by citrullination. Arthritis Rheum 2006;54:38–46.
Padyukov L, Silva C, Stolt P, Alfredsson L, Klareskog L, for the
Epidemiological Investigation of Arthritis Study Group. A
gene–environment interaction between smoking and shared
epitope genes in HLA–DR provides a high risk of seropositive
rheumatoid arthritis. Arthritis Rheum 2004;50:3085–92.
Pedersen M, Jacobsen S, Garred P, Madsen HO, Klarlund M,
Svejgaard A, et al. Strong combined gene–environment effects in
anti–cyclic citrullinated peptide–positive rheumatoid arthritis: a
nationwide case–control study in Denmark. Arthritis Rheum
2007;56:1446–53.
Kallberg H, Padyukov L, Plenge RM, Ronnelid J, Gregersen PK,
van der Helm-van Mil AH, et al, for the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) Study Group. Gene-gene
and gene-environment interactions involving HLA-DRB1,
PTPN22, and smoking in two subsets of rheumatoid arthritis. Am J
Hum Genet 2007;80:867–75.
Landi S. Mammalian class theta GST and differential susceptibility to carcinogens: a review. Mutat Res 2000;463:247–83.
Hayes JD, Strange RC. Glutathione S-transferase polymorphisms
and their biological consequences. Pharmacology 2000;61:154–66.
Strange RC, Jones PW, Fryer AA. Glutathione S-transferase:
genetics and role in toxicology. Toxicol Lett 2000;112–113:357–63.
Strange RC, Spiteri MA, Ramachandran S, Fryer AA. Glutathione-S-transferase family of enzymes. Mutat Res 2001;482:21–6.
Carlsten C, Sagoo GS, Frodsham AJ, Burke W, Higgins JP.
Glutathione S-transferase M1 (GSTM1) polymorphisms and lung
cancer: a literature-based systematic HuGE review and meta-analysis. Am J Epidemiol 2008;167:759–74.
Cote ML, Chen W, Smith DW, Benhamou S, Bouchardy C,
Butkiewicz D, et al. Meta- and pooled analysis of GSTP1 polymorphism and lung cancer: a HuGE-GSEC review. Am J Epidemiol 2009;169:802–14.
Raimondi S, Paracchini V, Autrup H, Barros-Dios JM, Benhamou
S, Boffetta P, et al. Meta- and pooled analysis of GSTT1 and lung
cancer: a HuGE-GSEC review. Am J Epidemiol 2006;164:
1027–42.
Ali-Osman F, Akande O, Antoun G, Mao JX, Buolamwini J.
Molecular cloning, characterization, and expression in Escherichia
coli of full-length cDNAs of three human glutathione S-transferase Pi gene variants: evidence for differential catalytic activity
of the encoded proteins. J Biol Chem 1997;272:10004–12.
Zimniak P, Nanduri B, Pikula S, Bandorowicz-Pikula J, Singhal
SS, Srivastava SK, et al. Naturally occurring human glutathione
S-transferase GSTP1-1 isoforms with isoleucine and valine in
position 104 differ in enzymic properties. Eur J Biochem 1994;
224:893–9.
Engel LS, Taioli E, Pfeiffer R, Garcia-Closas M, Marcus PM, Lan
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
3209
Q, et al. Pooled analysis and meta-analysis of glutathione
S-transferase M1 and bladder cancer: a HuGE review. Am J
Epidemiol 2002;156:95–109.
Rebbeck TR. Molecular epidemiology of the human glutathione
S-transferase genotypes GSTM1 and GSTT1 in cancer susceptibility. Cancer Epidemiol Biomarkers Prev 1997;6:733–43.
Bohanec Grabar P, Logar D, Tomsic M, Rozman B, Dolzan V.
Genetic polymorphisms of glutathione S-transferases and disease
activity of rheumatoid arthritis. Clin Exp Rheumatol 2009;27:
229–36.
Mattey DL, Hassell AB, Plant M, Dawes PT, Ollier WR, Jones
PW, et al. Association of polymorphism in glutathione S-transferase loci with susceptibility and outcome in rheumatoid arthritis:
comparison with the shared epitope. Ann Rheum Dis 1999;58:
164–8.
Mattey DL, Hutchinson D, Dawes PT, Nixon NB, Clarke S, Fisher
J, et al. Smoking and disease severity in rheumatoid arthritis:
association with polymorphism at the glutathione S-transferase
M1 locus. Arthritis Rheum 2002;46:640–6.
Yun BR, El-Sohemy A, Cornelis MC, Bae SC. Glutathione
S-transferase M1, T1, and P1 genotypes and rheumatoid arthritis.
J Rheumatol 2005;32:992–7.
Otterbein LE, Soares MP, Yamashita K, Bach FH. Heme oxygenase-1: unleashing the protective properties of heme. Trends Immunol 2003;24:449–55.
Maines MD. Heme oxygenase: function, multiplicity, regulatory
mechanisms, and clinical applications. FASEB J 1988;2:2557–68.
Chang YC, Lai CC, Lin LF, Ni WF, Tsai CH. The up-regulation of
heme oxygenase-1 expression in human gingival fibroblasts stimulated with nicotine. J Periodontal Res 2005;40:252–7.
Exner M, Minar E, Wagner O, Schillinger M. The role of heme
oxygenase-1 promoter polymorphisms in human disease. Free
Radic Biol Med 2004;37:1097–104.
Wagener FA, Volk HD, Willis D, Abraham NG, Soares MP,
Adema GJ, et al. Different faces of the heme-heme oxygenase
system in inflammation. Pharmacol Rev 2003;55:551–71.
Kikuchi A, Yamaya M, Suzuki S, Yasuda H, Kubo H, Nakayama
K, et al. Association of susceptibility to the development of lung
adenocarcinoma with the heme oxygenase-1 gene promoter polymorphism. Hum Genet 2005;116:354–60.
Kobayashi H, Takeno M, Saito T, Takeda Y, Kirino Y, Noyori K,
et al. Regulatory role of heme oxygenase 1 in inflammation of
rheumatoid arthritis. Arthritis Rheum 2006;54:1132–42.
Rueda B, Oliver J, Robledo G, Lopez-Nevot MA, Balsa A,
Pascual-Salcedo D, et al. HO-1 promoter polymorphism associated with rheumatoid arthritis. Arthritis Rheum 2007;56:3953–8.
Wagener FA, Toonen EJ, Wigman L, Fransen J, Creemers MC,
Radstake TR, et al. HMOX1 promoter polymorphism modulates
the relationship between disease activity and joint damage in
rheumatoid arthritis. Arthritis Rheum 2008;58:3388–93.
Hankinson SE, Colditz GA, Hunter DJ, Manson JE, Willett WC,
Stampfer MJ, et al. Reproductive factors and family history of
breast cancer in relation to plasma estrogen and prolactin levels in
postmenopausal women in the Nurses’ Health Study (United
States). Cancer Causes Control 1995;6:217–24.
Karlson EW, Sanchez-Guerrero J, Wright EA, Lew RA, Daltroy
LH, Katz JN, et al. A connective tissue disease screening questionnaire for population studies. Ann Epidemiol 1995;5:297–302.
Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF,
Cooper NS, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis.
Arthritis Rheum 1988;31:315–24.
Karlson EW, Mandl LA, Hankinson SE, Grodstein F. Do breastfeeding and other reproductive factors influence future risk of
rheumatoid arthritis? Results from the Nurses’ Health Study.
Arthritis Rheum 2004;50:3458–67.
3210
41. Covault J, Abreu C, Kranzler H, Oncken C. Quantitative real-time
PCR for gene dosage determinations in microdeletion genotypes.
Biotechniques 2003;35:594–6, 598.
42. Rothman KJ. Causes. Am J Epidemiol 1976;104:587–92.
43. Lundberg M, Fredlund P, Hallqvist J, Diderichsen F. A SAS
program calculating three measures of interaction with confidence
intervals. Epidemiology 1996;7:655–6.
44. Andersson T, Alfredsson L, Kallberg H, Zdravkovic S, Ahlbom A.
Calculating measures of biological interaction. Eur J Epidemiol
2005;20:575–9.
45. Hosmer DW, Lemeshow S. Confidence interval estimation of
interaction. Epidemiology 1992;3:452–6.
46. Li Y, Abecasis G. Mach 1.0: rapid haplotype reconstruction and
missing genotype inference. Am J Hum Genet 2006;S79:2290.
47. Meyer DJ. Significance of an unusually low Km for glutathione in
KEENAN ET AL
glutathione transferases of the alpha, mu and pi classes. Xenobiotica 1993;23:823–34.
48. Finckh A, Choi HK, Wolfe F. Progression of radiographic joint
damage in different eras: trends towards milder disease in rheumatoid arthritis are attributable to improved treatment. Ann
Rheum Dis 2006;65:1192–7.
49. Costenbader KH, Chang SC, De Vivo I, Plenge R, Karlson EW.
Genetic polymorphisms in PTPN22, PADI-4, and CTLA-4 and
risk for rheumatoid arthritis in two longitudinal cohort studies:
evidence of gene-environment interactions with heavy cigarette
smoking. Arthritis Res Ther 2008;10:R52.
50. Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, Hankinson
SE, et al. A genome-wide association study identifies alleles in
FGFR2 associated with risk of sporadic postmenopausal breast
cancer. Nat Genet 2007;39:870–4.
Документ
Категория
Без категории
Просмотров
2
Размер файла
109 Кб
Теги
interactions, smoking, glutathione, effect, promote, polymorphism, arthritis, hmox1, heavy, genes, risk, rheumatoid, transferase
1/--страниц
Пожаловаться на содержимое документа