To examine the associations of cigarette smoking with rheumatoid arthritis (RA) in African Americans, and to determine whether this association is impacted by the HLA–DRB1 shared epitope (SE).
To examine the associations of cigarette smoking with rheumatoid arthritis (RA) in African Americans, and to determine whether this association is impacted by the HLA–DRB1 shared epitope (SE).
Smoking status, cumulative smoking exposure, and SE status were determined in African American patients with RA and African American healthy controls. Associations of smoking with RA were examined using age- and sex-adjusted logistic regression analyses. Additive and multiplicative SE–smoking interactions were examined.
After adjustment for age and sex, ever smoking (odds ratio [OR] 1.45, 95% confidence interval [95% CI] 1.07, 1.97) and current smoking (OR 1.56, 95% CI 1.07, 2.26), relative to never smoking, were more common in African American patients with RA (n = 605) than in controls (n = 255). The association of smoking with RA was limited to those with a cumulative exposure exceeding 10 pack-years, associations that were evident both in autoantibody-positive and in autoantibody-negative disease. There was evidence of a significant additive interaction between SE status and heavy smoking (≥10 pack-years) in relation to RA risk (attributable proportion [AP] due to interaction 0.58, P = 0.007), with similar results for the additive interaction between SE status and ever smoking (AP 0.47, P = 0.006). There was no evidence of multiplicative interactions.
Among African Americans, cigarette smoking is associated not only with the risk of autoantibody-positive RA but also with the risk of autoantibody-negative disease. The risk of RA attributable to smoking is limited to African Americans with more than 10 pack-years of exposure and is more pronounced among individuals positive for the HLA–DRB1 SE.
Since initial reports published more than 20 years ago (1), cigarette smoking has repeatedly been shown to be associated with rheumatoid arthritis (RA) susceptibility (2–10), a risk most pronounced among heavy smokers (2, 11). Studies in populations of European ancestry have shown that the relationship of smoking to the risk of RA appears to be impacted by the presence of HLA–DRB1 shared epitope (SE)–containing alleles (7, 12, 13), but the mechanisms underpinning this interaction have yet to be fully defined. The associations of cigarette smoking with disease risk in populations of European ancestry also appear to be limited to those in whom seropositive RA develops, as characterized by the presence of either rheumatoid factor (RF) or anti–cyclic citrullinated peptide (anti-CCP) antibodies in the serum (2, 6).
Prior studies examining the association of cigarette smoking with RA risk have almost exclusively involved populations of European ancestry. The lack of such studies among African Americans represents an important gap in our knowledge. Although smoking is less frequent in African Americans than in individuals of European ancestry (14), the incidence of smoking appears to be increasing in this population (15), and concomitant rates of smoking cessation in African Americans are consistently lower compared with those in Caucasians (16). It is unknown whether smoking contributes to RA risk in African Americans and whether this risk is impacted by the presence of the HLA–DRB1 SE, a genetic risk factor that is less prevalent in African Americans with RA than in individuals of European ancestry with RA (17). To address these knowledge gaps, we conducted a case–control study to examine the association of cigarette smoking with RA among African Americans, to assess the impact of cumulative exposure to smoking, and to define the extent to which this association is affected by HLA–DRB1 SE positivity.
Patients with RA and healthy controls were subjects in the Consortium for the Longitudinal Evaluations of African Americans with Early Rheumatoid Arthritis (CLEAR) (18–20). All cases of RA satisfied the American College of Rheumatology (formerly, the American Rheumatism Association) classification criteria (21), and all study subjects self-reported race as African American. Additional information regarding African American heritage (race/ethnicity of parents, grandparents) was not collected. This study included cases and controls from both the CLEAR I study (RA patients with ≤2 years' disease duration from the time of symptom onset) and the CLEAR II study (RA patients with any disease duration).
African American control subjects were enrolled based on age, sex, and geographic residence and were recruited predominantly from lists of telephone numbers from individuals residing in the same mailing zip codes as those of the patients with RA. These lists were obtained from the Genesys/Marketing Systems Group (http://www.m-s-g.com/default.htm). Telephone numbers were selected from census tracts that had high percentages of African Americans identified near the sites at which patients were enrolled. Controls were selected within an age range of ±10 years based on the mean age of the RA patients at each site, and the female-to-male ratio was 3:1 based on the anticipated sex distribution among RA patients. Potential control subjects were contacted by telephone so that interviewers could determine their eligibility and interest, and lists of suitable control subjects were then distributed to the sites to arrange study visits.
RA patients and controls were enrolled through 1 of 5 sites: the University of Alabama at Birmingham (Birmingham, AL), Emory University (Atlanta, GA), Medical University of South Carolina (Charleston, SC), the University of North Carolina (Chapel Hill, NC), and Washington University (St. Louis, MO). The study was approved by the Institutional Review Board at each participating center, and all study subjects provided informed written consent prior to participation. Subjects for whom data on either smoking status or cumulative smoking exposure were missing were excluded from the analysis (11 RA cases and 7 controls excluded), leaving 605 RA patients and 255 healthy controls evaluable for this analysis.
Information regarding smoking status (current, former, never) was collected at the time of enrollment, and among ever smokers, pack-years of smoking served as the measure of cumulative exposure. Never smoking was defined as having smoked fewer than 100 cigarettes in the subject's lifetime. Former smokers included individuals who had smoked ≥100 cigarettes over the subject's lifetime but who had quit smoking any time prior to study enrollment. Based on recent reports examining the association of heavy smoking with RA risk among women of European ancestry (11), ever smokers were further categorized based on the magnitude of cumulative exposure (<10 pack-years and ≥10 pack-years). Information specific to “second-hand” or other environmental smoking exposures was not collected as part of this study.
Autoantibody measurements, including anti-CCP antibodies and RF, were performed as previously reported, using commercially available enzyme-linked immunosorbent assay kits (18). Anti-CCP antibodies (IgG) (Diastat; Axis-Shield Diagnostics) were measured in arbitrary units (AU) per ml and were considered to be positive at a cut-off value of ≥5 AU/ml (18). RF (IgM) (Inova Diagnostics) was measured in international units (IU) per ml and was considered positive at concentrations of ≥9.5 IU/ml (18).
High-resolution HLA–DRB1 genotyping was performed as previously described, with a previous report showing a higher frequency of SE-containing alleles in African American RA patients compared with African American controls (22). HLA–DRB1 SE status was not available for 13 patients (2% of all patients) and 5 controls (2% of all controls); these subjects were excluded from analyses that included SE status.
To examine potential ancestral differences between patients and controls, DNA samples from a subset of RA patients (n = 561) and controls (n = 231) from the CLEAR Registry were genotyped using a custom Illumina chip with 3,317 AIMs, performed in the laboratory of Dr. Peter Gregersen as part of the International MHC and Autoimmunity Genetics Network (23). The proportion attributable to European ancestry in each participant was calculated as a percentage on the basis of the AIM genotypes, using the software package Structure (version 2.3.1) (24). Simulations were run on the assumption of 2 founding populations, 10,000 burn-ins, and 1,000 subsequent replicates, to generate the estimates.
Subject characteristics (RA patients versus controls), including the percentage of European ancestry, were compared using descriptive statistics, the chi-square test for dichotomous variables, and Student's t-test for continuous variables. Associations of smoking (current and former versus never) with case status were examined using unconditional logistic regression, adjusting for age and sex, given the differences in these characteristics between patients and controls. To account for effects of cumulative exposure, we examined the associations of heavy smoking (≥10 pack-years) with RA risk relative to that in individuals reporting never smoking combined with individuals reporting <10 pack-years of smoking. In additional analyses, we examined the aforementioned smoking variables with the risk of autoantibody-positive and -negative disease, examining associations with anti-CCP antibody–positive and RF-positive disease in separate models. Given the small proportion of healthy controls positive for anti-CCP antibodies or RF, all controls (n = 255) were included in analyses examining associations of smoking with autoantibody-positive and -negative RA.
To explore the potential interactions between smoking and the HLA–DRB1 SE, additional models stratified by SE status (presence of 0 versus 1 or 2 alleles) were examined. A potential dose effect of the SE was not examined, given the low proportion of African American patients with RA homozygous for the HLA–DRB1 SE. Analyses stratified by SE status and examining the risk of autoantibody-positive and -negative RA were considered exploratory. For stratified analyses involving small sample sizes, we also examined the associations of smoking with disease risk using Firth's penalized likelihood approach, which is an alternative method of addressing issues of small sample sizes and the resulting bias in parameter estimates (25, 26).
SE–smoking interactions were examined in 2 ways. First, we evaluated evidence of departure from additivity using methods previously described by Rothman and colleagues (27). This method has been used in other major epidemiologic studies in RA examining additive interactions of the HLA–DRB1 SE and smoking (2, 6, 11, 28). Using the methods detailed by Andersson et al (29), we calculated the attributable proportion (AP) due to interaction as the primary measure of additive interaction (an AP value of 0 corresponds to no interaction, while an AP value of 1.0 corresponds to complete additive interaction). Secondary measures of additive interaction included the relative excess risk due to interaction (RERI) and the synergy index (SI) (29). The 95% confidence intervals (95% CIs) were calculated for the AP, RERI, and SI using the method described by Hosmer and Lemeshow (30). A P value less than 0.05 for the AP was considered to represent statistically significant additive interaction. Multiplicative interaction was then assessed by modeling the SE–smoking product term in age- and sex-adjusted logistic regression models. To optimize study power, the analyses of interactions were limited to dichotomous variables (SE-positive versus SE-negative, ever versus never smoking, and ≥10 pack-years versus never/<10 pack-years) and to two-way interactions.
We calculated minimal detectable odds ratios (ORs) for the main effects of ever smoking and heavy smoking, with 80% power to detect an effect using a statistical threshold of α = 0.05 (1-sided), assuming that 10% of the variability in multivariate analyses would be explained by covariates. Based on the number of patients and controls available and the smoking exposures observed, the study was powered to detect a minimal detectable OR of 1.45 for the association with ever smoking, with similar power for the association with heavy smoking. Based on the assumption that the presence of 1 risk factor in isolation (SE or smoking) would have an OR of 2.0, we had 78% power to detect an SI of 2.55 for the interaction between SE and ever smoking and 60% power to detect an SI of 2.88 for the interaction between SE and heavy smoking. All analyses were conducted using SAS, version 9.2 (SAS Institute).
There were 605 RA patients and 255 healthy controls included in the analysis. The characteristics of the patients and controls are shown in Table 1. There were more women among RA patients than among controls (84% versus 76%; P = 0.004). Patients with RA were slightly older than control subjects (mean age 54 years versus 52 years; P = 0.048) and were much more likely than control subjects to have at least 1 HLA–DRB1 SE–containing allele (40% versus 23%; P = 0.0001). Only 5% of African American patients with RA were homozygous for the HLA–DRB1 SE. Among the patients with RA, the mean ± SD disease duration was 6.3 ± 8.7 years (1.0 ± 0.6 years in CLEAR I and 11.2 ± 9.9 years in CLEAR II), and most of the patients were positive for anti-CCP antibodies (67%) or RF (76%). The levels of European admixture based on AIM genotyping did not differ between RA patients (mean ± SD 14 ± 13%) and controls (mean ± SD 13 ± 11%) (P = 0.59).
|RA patients (n = 605)||Controls (n = 255)||P|
|Age, mean ± SD years||54 ± 13||52 ± 13||0.048|
|Disease duration at baseline, mean ± SD years†||6.3 ± 9||–||–|
|SE positive (1 or 2 copies)||40||23||0.0001|
|Anti-CCP antibody positive||67||4||<0.0001|
|Cumulative smoking exposure|
|Never or <10 pack-years||72||85|
|Ever, ≥10 pack-years||28||15||<0.0001|
Smoking status and the frequency of heavy smoking (defined as ≥10 pack-years) among RA patients and controls are shown in Table 1. Compared with healthy control subjects, patients with RA were slightly more likely to report a status of former or current smoking and less likely to be never smokers (global P = 0.055). Among those reporting a history of ever smoking, heavy smoking was much more common in RA patients (54% of ever smokers) than in controls (35% of ever smokers).
After the estimates were adjusted for age and sex, patients with RA were much more likely than controls to report a status of current smoking relative to never smoking (OR 1.56, 95% CI 1.07, 2.26), and there was a nonsignificant trend toward higher rates of former smoking among RA patients (Table 2). As anticipated, the association of ever smoking with overall RA, relative to never smoking (OR 1.45, 95% CI 1.07, 1.97), was in the intermediate range when compared with the associations of current and former smoking with RA.
|No. patients/no. controls||All RA||Anti-CCP positive||Anti-CCP negative||RF positive||RF negative|
|Former||153/55||1.34 (0.91, 1.97)||1.42 (0.94, 2.14)||1.19 (0.73, 1.94)||1.44 (0.96, 2.16)||1.07 (0.63, 1.82)|
|Current||163/58||1.56 (1.07, 2.26)||1.57 (1.05, 2.34)||1.47 (0.92, 2.35)||1.66 (1.12, 2.44)||1.31 (0.77, 2.21)|
|Ever||316/113||1.45 (1.07, 1.97)||1.49 (1.07, 2.08)||1.32 (0.90, 1.96)||1.55 (1.12, 2.14)||1.18 (0.77, 1.81)|
|<10 pack-years||145/74||1.00 (0.71, 1.43)||1.05 (0.72, 1.55)||0.94 (0.59, 1.49)||1.08 (0.75, 1.57)||0.81 (0.49, 1.36)|
|≥10 pack-years||171/39||2.37 (1.56, 3.60)||2.40 (1.54, 3.74)||2.11 (1.27, 3.51)||2.51 (1.63, 3.87)||1.93 (1.11, 3.35)|
|Never or <10 pack-years||434/216||Referent||Referent||Referent||Referent||Referent|
|Ever (≥10 pack-years)||171/39||2.37 (1.60, 3.52)||2.35 (1.55, 3.58)||2.16 (1.33, 3.50)||2.43 (1.62, 3.66)||2.07 (1.23, 3.50)|
Associations of smoking status with anti-CCP antibody–positive versus anti-CCP antibody–negative RA and with RF-positive versus RF-negative RA are shown in Table 2. The association of smoking with overall RA was greatest among heavy smokers relative to never smokers (OR 2.37, 95% CI 1.56, 3.60), and this association was significant for both autoantibody-positive and -negative disease (Table 2), whether based on anti-CCP antibody status or on RF status. In contrast, there were no associations of lower cumulative smoking exposure (<10 pack-years) with RA (Table 2).
Because the analyses revealed that lower cumulative smoking exposure (<10 pack-years) was not associated with an increased risk of RA (relative to never smoking), the never smokers and ever smokers with <10 pack-years of exposure were combined in the subsequent analyses in which associations of cumulative smoking exposure were examined. Compared with the combined group of never smokers and those reporting <10 pack-years of exposure, a history of heavy smoking was significantly associated with the development of both anti-CCP antibody–positive RA (OR 2.35, 95% CI 1.55, 3.58) and anti-CCP antibody–negative RA (OR 2.16, 95% CI 1.33, 3.50), with similar results corresponding to both RF-positive and RF-negative RA (Table 2). Age- and sex-adjusted associations of heavy smoking with overall RA were examined separately by cohort, which showed that the associations were significant in both the CLEAR I cohort (OR 2.15, 95% CI 1.23, 3.75) and the CLEAR II cohort (OR 2.48, 95% CI 1.39, 4.42) (results not shown).
Age- and sex-adjusted associations between heavy smoking and RA stratified by HLA–DRB1 SE status are shown in Figure 1. Because of the lower frequency of SE positivity among patients and controls combined (35% of total participants being SE positive), coupled with the small number of controls with heavy smoking exposure (n = 39), confidence intervals were universally wider for analyses limited to SE-positive individuals compared with analyses limited to SE-negative individuals. Among African Americans with 1 or 2 SE alleles, heavy smoking was associated with a more than 4-fold increased risk of RA (OR 4.44, 95% CI 1.58, 12.51). Among African Americans who were SE-negative, the association of heavy smoking with RA risk was less striking, although it remained statistically significant (OR 2.22, 95% CI 1.43, 3.45). Associations of heavy smoking with anti-CCP antibody–positive and –negative RA, stratified by SE status, were similar to the estimates observed for overall disease risk (Figure 1), as were the results based on RF-positive and -negative disease (results not shown). Results of these stratified analyses were not changed after application of Firth's penalized likelihood approach (25, 26) to account for small sample sizes (results not shown).
There was evidence of significant additive interaction of HLA–DRB1 SE status with heavy smoking in relation to the overall risk of RA (AP 0.58, 95% CI 0.16, 0.99; P = 0.007), an interaction that was less striking, but still significant, in the association with ever smoking (AP 0.47, 95% CI 0.14, 0.80; P = 0.006) (Table 3). The corresponding measures of interaction, the SI and RERI, are also shown in Table 3. There was no evidence of multiplicative interaction between the presence of the HLA–DRB1 SE and heavy smoking (P = 0.38) or ever smoking (P = 0.17) in relation to overall disease risk.
|Ever smoking–SE||≥10 pack-years–SE|
|AP (95% CI)†||0.47 (0.14, 0.80)||0.58 (0.16, 0.99)|
|Relative excess risk due to interaction (95% CI)||2.04 (−0.36, 4.43)||4.86 (−3.08, 12.80)|
|Synergy index (95% CI)||2.55 (0.99, 6.60)||2.88 (0.92, 9.04)|
|P, product term||0.17||0.38|
|Anti-CCP antibody–positive RA|
|AP (95% CI)†||0.53 (0.22, 0.83)||0.63 (0.25, 1.00)|
|Relative excess risk due to interaction (95% CI)||3.16 (−0.22, 6.54)||7.16 (−3.76, 18.08)|
|Synergy index (95% CI)||2.70 (1.13, 6.45)||3.17 (1.04, 9.62)|
|P, product term||0.13||0.36|
|Anti-CCP antibody–negative RA|
|AP (95% CI)†||0.04 (−0.77, 0.86)||0.24 (−0.69, 1.17)|
|Relative excess risk due to interaction (95% CI)||0.08 (−1.39, 1.54)||0.81 (−3.17, 4.80)|
|Synergy index (95% CI)||1.11 (0.15, 8.38)||1.52 (0.26, 9.04)|
|P, product term||0.96||0.87|
The APs corresponding to HLA–DRB1–smoking interactions for anti-CCP antibody–positive RA and anti-CCP antibody–negative RA are shown in Table 3, and similar results were observed for measures of interaction corresponding to RF-positive and RF-negative RA (results not shown). Additive interactions between the HLA–DRB1 SE and smoking were stronger among patients with seropositive RA when compared with patients with seronegative RA. Results of these analyses were not changed when the percentage of European admixture based on AIM genotyping was included as a covariate in the models (results not shown).
To our knowledge, this is the first study to show an association of cigarette smoking with RA in African Americans. We found that this association is most striking in heavy smokers and those with HLA–DRB1 SE–containing alleles. Among African Americans with a cumulative smoking history exceeding 10 pack-years, the risk of RA is increased by more than 2-fold, and this risk is increased to more than 4-fold in the presence of SE alleles. In contrast, the risk of RA among ever smokers with a cumulative exposure of fewer than 10 pack-years appears to be negligible. Assuming that the smoking behaviors reported by control subjects in this study (15% reported a smoking history of more than 10 pack-years) reflect those of African Americans nationally, the attributable risk of RA due to heavy smoking exposure in this population may be as high as 16%. Stated in another way, our results suggest that ∼1 in 6 new cases of RA occurring in African Americans could be prevented through smoking cessation or by limiting cumulative smoking exposure in this population to <10 pack-years. In light of reports suggesting that smoking is on the rise among African Americans (15), our results suggest that RA incidence and disease burden may increase in this population over the next decades.
It is worth noting that some uncertainty remains regarding the optimal method to model gene–environment interactions (31). In contrast to prior studies that have examined smoking–SE interactions in RA risk using only additive interaction (2, 6), we have examined measures of both additive and multiplicative interaction. Multiplicative interaction refers to the inclusion of a product term in regression analyses to generate an optimal fit of the data in the statistical model. It is important to note that the absence of multiplicative interaction does not exclude the existence of important biologic or additive interactions, which, in the case of this study, show that at least 1 pathway to RA development in African Americans requires the presence of 2 risk factors (i.e., heavy smoking and the HLA–DRB1 SE).
The results presented herein are similar to those presented in a recent report from the Nurses' Health Study (NHS), a nested case–control study that included 439 women with incident RA, all of whom were of European ancestry (11). In the NHS study (11), investigators found evidence of a significant additive interaction between HLA–DRB1 and heavy smoking (>10 pack-years) in relation to overall RA risk, with an AP of 0.39 (95% CI 0.08, 0.69; P = 0.01). Although the NHS study did not yield evidence of multiplicative interaction in overall disease risk (P = 0.14), there was evidence of a significant multiplicative interaction between the HLA–DRB1 SE and heavy smoking in the development of seropositive RA (a phenotype based on RF status in some patients and anti-CCP antibody status in others) (11). The absence of multiplicative interaction in our study of African Americans may be related to the smaller number of controls and limited power in comparison with that in the larger NHS study.
Investigators in the NHS also found no evidence of additive interaction between the HLA–DRB1 SE and ever smoking status in relation to disease risk (AP 0.23, 95% CI 0.14, 0.61; P = 0.23). The additive interaction between the SE and ever smoking in our current CLEAR cohort was similarly attenuated compared with the interaction between the SE and heavy smoking, although the association was still statistically significant. Results from the NHS suggest that accounting for cumulative exposure is essential in assessing the role of cigarette smoking and gene–smoking interactions in RA. In light of our results, these conclusions can now be extended to African Americans. Failure to account for the “dose” of smoking could explain the lack of evidence of substantial SE–smoking interactions in other North American cohorts (28).
Biologic interactions between HLA–DRB1 SE alleles and smoking in relation to RA risk have been shown in several epidemiologic investigations, although the present study is the first to exclusively involve African Americans. Taken together, the findings from these studies suggest that smoking may trigger initial inflammatory events in RA that are HLA–DRB1 dependent. Previous studies, which involved populations of European ancestry, have shown that SE–smoking interactions are most evident in the development of anti-CCP antibody–positive disease. These results have been interpreted to mean that smoking either up-regulates citrullination or enhances the immunogenicity of citrullinated peptides in the context of select HLA alleles. However, our study of African Americans showed that the associations of heavy smoking with RA are similar for autoantibody-positive and -negative disease, although risk estimates were consistently higher for seropositive RA. This finding is in direct contrast to results from studies involving populations of European ancestry (2, 11), and this will require replication in separate study populations.
These results are consistent with a prior case-only analysis done in a subset of patients from the CLEAR I study, in whom no association of smoking with anti-CCP antibody positivity was found (32). In the present study of African Americans, heavy smoking was associated with a significant and >2-fold increased risk of both anti-CCP antibody–negative RA and RF-negative RA. In contrast, in a large national case–control study from Sweden, Klareskog and colleagues found no associations of smoking with the risk of anti-CCP antibody–negative RA, regardless of HLA–DRB1 SE status (2). Reasons for this apparent discrepancy are unknown, but it is possible that other genetic and/or environmental factors could mediate the effect of smoking in autoantibody-negative RA, and the prevalence of these as-yet undefined factors could vary markedly based on race/ethnicity. In addition to differences in the study populations and in data analyses accounting for or not accounting for cumulative smoking exposures, variations in study design, ascertainment of smoking status, and different methods of analysis could also serve to explain differences across published reports.
Limitations to this study are those inherent in its case–control design. These include possible recall bias and the possibility of a “healthy responder” bias among controls. This latter concern is mitigated by the fact that the enrolled healthy controls were recruited from among individuals residing in the same census tracts as those of the patients with RA, so that these individuals were similar to the RA patients with regard to sociodemographic characteristics and other unmeasured confounders. Similarities between patients and controls were further borne out at the genetic level, with examinations of AIMs showing very similar levels of European admixture in both groups.
The case–control design also prohibits conclusions regarding the direction of the associations examined, although for all RA patients included in this study, the initial smoking exposure preceded disease onset by many years, in most cases. We also found no major differences in the risk estimates corresponding to heavy smoking between analyses limited to CLEAR I (RA patients with disease duration <2 years) and analyses limited to CLEAR II (RA patients with any disease duration), suggesting that recall bias and protopathic bias (disease onset leading to exposure) are less likely to be issues. If a protopathic bias had been operative in these findings, we would have expected to have observed much stronger associations of heavy smoking with RA in CLEAR II, a cohort that included RA patients with established disease and a much longer time interval between disease onset and study enrollment. Despite these potential limitations, this effort represents the largest study to date examining the impact of smoking and gene–smoking interactions in RA in a well-characterized African American population, a group that has been vastly understudied in RA epidemiology.
In summary, cigarette smoking is significantly associated with RA in African Americans, an association that is most pronounced in those with a cumulative smoking history exceeding 10 pack-years. Similar to prior reports describing populations of European ancestry, the risk attributed to smoking is highest in African Americans positive for HLA–DRB1 SE alleles, with evidence of a significant biologic interaction between the SE and heavy smoking in relation to the risk of RA.
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. Dr. Mikuls 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. Mikuls, Jonas, Smith, Brasington, Moreland, Bridges.
Acquisition of data. Mikuls, Thiele, Conn, Jonas, Callahan, Smith, Brasington, Moreland, Bridges.
Analysis and interpretation of data. Mikuls, Sayles, Yu, LeVan, Gould, Thiele, Smith, Moreland, Reynolds, Bridges.
The CLEAR Registry is an NIH-sponsored resource, with clinical data, DNA, and other biologic samples available to approved users. Details on obtaining data or biologic samples are available at the Web site http://www.dom.uab.edu/rheum/CLEAR%20home.htm. The CLEAR investigators are as follows: S. Louis Bridges, Jr., MD, PhD, Director, George Howard, DrPH, Co-Director, and Graciela S. Alarcón, MD, MPH (University of Alabama at Birmingham); Doyt L. Conn, MD (Emory University); Beth L. Jonas, MD and Leigh F. Callahan, PhD (University of North Carolina); Edwin A. Smith, MD (Medical University of South Carolina); Richard D. Brasington, Jr., MD (Washington University); Ted R. Mikuls, MD, MSPH (University of Nebraska); and Larry W. Moreland, MD, Co-Director (University of Pittsburgh). We gratefully acknowledge the following CLEAR Registry staff and coordinators: Stephanie Ledbetter, MS, Zenoria Causey, MS, Selena Luckett, RN, CRNC, Laticia Woodruff, RN, MSN, and Candice Miller (University of Alabama at Birmingham); Joyce Carlone, RN, RNP, Karla Caylor, BSN, RN, and Sharon Henderson, RN (Emory University); Diane Bresch, RN (University of North Carolina); Trisha Sturgill (Medical University of South Carolina); and Teresa Arb (Washington University). We also gratefully acknowledge the following physicians who enrolled patients into the CLEAR Registry: Jacob Aelion, MD (Jackson, TN), Charles Bell (Birmingham, AL), Sohrab Fallahi, MD (Montgomery, AL), Richard Jones, PhD, MD (Tuscaloosa, AL), Maura Kennedy, MD (Birmingham, AL), Adahli Estrada Massey, MD (Auburn, AL), John Morgan, MD (Birmingham, AL), Donna Paul, MD (Montgomery, AL), Runas Powers, MD (Alexander City, AL), William Shergy, MD (Huntsville, AL), Cornelius Thomas, MD (Birmingham, AL), and Ben Wang, MD (Memphis, TN).