Abstract
Objective
To evaluate the association between cigarette smoking and the odds of IgG4-related disease (IgG4-RD).
Methods
We performed a case–control study of patients with IgG4-RD compared in a 1:5 ratio with age-, race- and sex-matched controls. We included cases evaluated at the Massachusetts General Hospital, a hospital within the Mass General Brigham (MGB) System. Controls were identified from the MGB Biobank. Smoking status at the date of IgG4-RD diagnosis or corresponding index date was determined. Conditional logistic regression was used to estimate the association between cigarette smoking and the odds of having IgG4-RD.
Results
There were 234 IgG4-RD cases and 1170 controls. The mean age (59 years), sex (62% male) and race (75% white) were well balanced. IgG4-RD cases were more likely to be current smokers compared with controls [25 (11%) vs 70 (6%); odds ratio (OR) 1.79 (95% CI 1.08, 2.95)]. This association was strongest among female cases [13 (14%) vs 19 (4%);, OR 3.79 (95% CI 1.71, 8.39)] and those with retroperitoneal fibrosis [RPF; 13 (28%) vs 13 (6%);, OR 6.93 (95% CI 2.78, 17.26)] or normal IgG4 concentrations [21 (21%) vs 21 (4%); OR 6.22 (95% CI 3.09, 12.49)]. When RPF cases were excluded, there was no longer an association between current smoking and the odds of having IgG4-RD [12 (6%) vs 57 (6%); OR 0.95 (95% CI 0.49, 1.86)].
Conclusion
Being a current smoker is associated with greater odds of having IgG4-RD, especially among women and those with RPF or normal IgG4 concentrations. Current smoking is the first recognized modifiable risk factor for IgG4-RD.
Keywords: IgG4-RD, epidemiology, risk factors, tobacco
Rheumatology key messages
IgG4-related disease (IgG4-RD) causes fibroinflammatory lesions at nearly any site, but risk factors are unknown.
Smoking is associated with IgG4-RD in females and those with RPF or normal IgG4 concentrations.
Smoking is the first modifiable risk factor to be identified in IgG4-RD.
Introduction
IgG4-related disease (IgG4-RD) is an immune-mediated, chronic fibroinflammatory condition characterized by tumefactive lesions that can involve nearly any anatomical site; it is frequently associated with an elevated serum IgG4 concentration [1]. Storiform fibrosis is a histopathologic hallmark of the disease thought to be driven by cytotoxic T lymphocytes, activated B lymphocytes and activated macrophages [2–8]. While there have been significant advances in understanding the immunologic mechanisms of IgG4-RD [9], risk factors for the disease are poorly understood [10].
Retroperitoneal fibrosis (RPF), classically manifesting as a soft tissue mass encasing the anterolateral portion of the abdominal aorta, is considered a typical feature of IgG4-RD [11–14]. Although previous reports have suggested that cigarette smoking is a risk factor for the development of idiopathic RPF [15–17], these studies were done prior to more widespread recognition of IgG4-RD. A causative role of cigarette smoking as a trigger for autoimmunity has been explored in the context of other autoantigen-directed B cell–mediated diseases such as seropositive RA and ANCA-associated vasculitis [18, 19]. Moreover, extensive correlative data have suggested various direct and indirect effects of cigarette smoking on the immune response as it relates to inflammation and fibrosis, two key features of IgG4-RD [17, 20, 21]. We hypothesized that cigarette smoking may be associated with IgG4-RD, regardless of organ involvement.
No previous study has evaluated an association between cigarette smoking and the odds of having IgG4-RD. Identifying such an association would improve our understanding of its pathogenesis and define a modifiable risk factor for IgG4-RD. We performed a case–control study to evaluate whether cigarette smoking is associated with greater odds of having IgG4-RD.
Methods
IgG4-RD cases
The Massachusetts General Hospital (MGH) Center for IgG4-RD, a part of the Division of Rheumatology, Allergy, and Immunology, maintains a prospective registry of all patients evaluated in the centre. MGH is a hospital within the Mass General Brigham (MGB, formerly Partners) HealthCare System. Cases were classified into three groups (definite, probable and atypical IgG4-RD) using the 2019 ACR/EULAR classification criteria for IgG4-RD [14]. These classification criteria have a specificity of 97.8% and sensitivity of 82.0%. Definite cases fulfilled these criteria. Patients who were considered probable fulfilled two parts of the ACR/EULAR classification criteria (i.e. had clinical involvement of a typical organ and were rigorously evaluated to ensure that they did not meet any exclusion criteria) but did not reach the threshold of 20 inclusion points according to the criteria (frequently retroperitoneal fibrosis in a typical pattern because no biopsy could be safely obtained or the biopsy was not informative). Patients who were considered atypical met the previously established pathological and immunostaining criteria for diagnosing IgG4-RD but presented with involvement of an atypical organ (e.g. breast, prostate) that was not considered in the ACR/EULAR classification criteria; they did not fulfil any of the ACR/EULAR classification criteria exclusion criteria [2]. We included all patients seen between 2 January 2010 and 31 October 2018 who completed a detailed smoking questionnaire. The smoking questionnaire was derived from that used by the National Health and Nutrition Examination Survey (NHANES) [22].
Data pertaining to demographics, IgG4-RD manifestations and laboratory results were extracted from the registry and electronic health record. As in prior reports by our group, age at IgG4-RD onset (index date) refers to the age at which the patient first developed symptoms ultimately attributed to IgG4-RD or the time at which the disease was first diagnosed (whichever was earlier) [23]. Serum IgG4 concentrations obtained during periods of active disease prior to any treatment or while flaring when off of treatment were stratified as normal or elevated using a cut-off value of 135 mg/dl. Some of the clinical and laboratory features of cases included in this study have been reported previously [10, 23–26] but their smoking histories had not been investigated and the analyses pertaining to smoking reported herein are novel.
Control subjects
Control subjects were identified from the MGB HealthCare System Biobank, a large sample and clinical data collection program that recruits patients from inpatient and outpatient sites throughout the MGB system [27]. The biobank specifically recruits patients from a variety of settings (e.g. inpatient, primary care, specialty care) to enrol patients reflecting the diversity of patients and diseases managed at MGB and has been used for similar studies in the past [19]. Patients who had completed a smoking questionnaire (similar to the NHANES questionnaire and one administered to cases) and were enrolled in the Partners Biobank between 1 January 2010 and 4 May 2018 were considered eligible to be controls (N = 30 536). Each case was matched to five randomly selected controls based on year of birth (±2 years, given secular trends in smoking according to birth year cohort), sex and race.
Smoking ascertainment
Cases and controls were designated as current, former or never smokers based on criteria used by the NHANES [22]. Current smokers were defined as participants who endorsed actively smoking any quantity of tobacco on a regular basis at the index date. The index date for controls was the corresponding date ascertained as the index date for their respective control, as described above. Former smokers were patients who endorsed having smoked ≥100 cigarettes in their lifetime but who were not actively smoking at the index date. Never smokers were participants who denied ever smoking cigarettes regularly or who smoked <100 total cigarettes. Total cigarette exposure, in pack-years, was calculated by multiplying the number of years the patient smoked by the packs smoked per day. Patients were divided into groups based on total cigarette exposure: never smokers (0 pack-years), >0–<20 pack-years, ≥20–<40 pack-years and ≥40 pack-years.
Statistical analysis
Categorical variables are reported as number (%). Continuous variables are reported as mean (s.d.) or median [interquartile range (IQR)] depending on their distribution. In the main analysis we included definite, probable and atypical cases and compared the proportion of cases and controls with a history of cigarette smoking using conditional logistic regression to estimate odds ratios (ORs) and 95% CIs. We also examined this association after stratifying by sex, serum IgG4 concentration and organ manifestation since subgroups of IgG4-RD have been previously distinguished by these characteristics [23, 28]. Because IgG4-related RPF can be difficult to distinguish from idiopathic RPF, we performed a sensitivity analysis with only the subgroup of RPF patients who fulfilled the 2019 ACR/EULAR IgG4-RD classification criteria [14]. We also examined the association between being a current smoker and the odds of having IgG4-RD in the subgroup of patients with normal serum IgG4 concentrations after excluding patients with RPF since prior studies have found that RPF patients are more likely to have normal serum IgG4 concentrations than other IgG4-RD subgroups [28]. For all analyses, two-sided P-values <0.05 were considered significant. SAS version 9.4 (SAS Institute, Cary, NC, USA) was used for all statistical analyses.
Results
We identified 234 IgG4-RD cases that were age-, sex- and race-matched to 1170 controls (Table 1). The mean age for cases and controls was 59.3 years; the majority of patients were male (72%) and white (75%) in both groups. A variety of manifestations of IgG4-RD were represented in the cohort, including head and neck disease [136 (58%)], pancreato-hepatobiliary disease [84 (36%)], RPF [46 (20%)] and fibrosing thyroid disease [6 (3%)]. Serum IgG4 concentrations at the baseline visit were ≥135 mg/dl in 133 (57%) cases. Among cases, 173 (74%) had definite disease, 42 (18%) had probable disease and 19 (8%) had atypical disease. Of those with probable disease, 38 had eight or more inclusion points, which has ≥85% specificity for IgG4-RD in the ACR/EULAR classification criteria. The remaining four patients with probable disease had typical pachymeningitis (two patients), biliary disease (one patient) and pancreatic disease with encasement of the large vessels (one patient).
Table 1.
Demographics of cases and controls
| Characteristics | Cases | Controls |
|---|---|---|
| n | 234 | 1170 |
| Male, n (%) | 144 (62) | 720 (62) |
| Age, years, mean (s.d.) | 59.3 (13.6) | 59.3 (13.5) |
| White, n (%) | 176 (75) | 880 (75) |
| IgG4 classification, n (%) | ||
| Meets full classification criteria | 172 (74) | — |
| Probable | 43 (18) | — |
| Atypical | 19 (8) | — |
| Selected features of IgG4-RD, n (%) | ||
| Number of organs | 2.7 (2.0) | — |
| Head, eyes, ears, nose and throat | 136 (58) | — |
| Orbital | 25 (11) | — |
| Lacrimal | 63 (27) | — |
| Salivary | 103 (44) | — |
| Thyroid | 6 (3) | — |
| Pulmonary | 42 (18) | — |
| Renal | 56 (24) | — |
| Pancreato-hepatobiliary | 84 (36) | — |
| Retroperitoneal fibrosis | 46 (20) | — |
Table 2 includes the smoking statuses of IgG4-RD cases and controls. Overall, there was a greater proportion of current smokers among IgG4-RD cases [25 (11%)] than controls [70 (6%)]. Compared with controls, IgG4-RD cases had 1.8-fold greater odds of being current smokers than never smokers [OR 1.79 (95% CI 1.08, 2.95), P = 0.02]. After stratifying by sex, this association was observed among female cases [OR 3.79 (95% CI 1.71, 8.39), P = 0.001] but not among male cases [OR 1.12 (95% CI 0.57, 2.19), P = 0.8]. A similar association was observed among white [OR 1.87 (95% CI 1.05, 3.34), P = 0.037] and non-white cases [OR 1.57 (95% CI 0.58, 4.24), P = 0.4], although it was no longer statistically significant among non-white cases.
Table 2.
The association of cigarette smoking and risk of IgG4-RD
| Smoking status | Cases | Controls | OR (95% CI) |
|---|---|---|---|
| Overall, n (%) | 234 | 1170 | |
| Never smoker | 136 (58) | 666 (57) | 1.00 (Ref) |
| Former smoker | 73 (31) | 434 (37) | 0.80 (0.58, 1.11) |
| Current smoker | 25 (11) | 70 (6) | 1.79 (1.08, 2.95) |
| Male, n (%) | 144 | 720 | |
| Never smoker | 86 (60) | 402 (56) | 1.00 (Ref) |
| Former smoker | 46 (32) | 267 (37) | 0.79 (0.53, 1.18) |
| Current smoker | 12 (8) | 51 (7) | 1.12 (0.57, 2.19) |
| Female, n (%) | 90 | 450 | |
| Never smoker | 50 (56) | 264 (59) | 1.00 (Ref) |
| Former smoker | 27 (30) | 167 (37) | 0.85 (0.5, 1.44) |
| Current smoker | 13 (14) | 19 (4) | 3.79 (1.71, 8.39) |
| RPF, n (%) | 46 | 230 | |
| Never smoker | 17 (37) | 129 (56) | 1.00 (Ref) |
| Former smoker | 16 (35) | 88 (38) | 1.27 (0.60, 2.68) |
| Current smoker | 13 (28) | 13 (6) | 6.93 (2.78, 17.26) |
| Non-RPF, n (%) | 188 | 940 | |
| Never smoker | 119 (63) | 537 (57) | 1.00 (Ref) |
| Former smoker | 57 (30) | 346 (37) | 0.72 (0.51, 1.04) |
| Current smoker | 12 (6) | 57 (6) | 0.95 (0.49, 1.86) |
| IgG4 <135 mg/dl | 101 | 505 | |
| Never smoker | 46 (46) | 282 (56) | 1.00 (Ref) |
| Former smoker | 34 (34) | 202 (40) | 0.99 (0.60, 1.63) |
| Current smoker | 21 (21) | 21 (4) | 6.22 (3.09, 12.49) |
| IgG4 >135 mg/dl | 133 | 665 | |
| Never smoker | 90 (68) | 384 (58) | 1.00 (Ref) |
| Former smoker | 39 (29) | 232 (35) | 0.70 (0.46, 1.08) |
| Current smoker | 4 (3) | 49 (7) | 0.34 (0.12, 0.98) |
The association between being a current smoker and the odds of IgG4-RD was especially strong among the subgroups of cases with RPF as well as those with a normal serum IgG4 concentrations (Table 2). RPF cases (n = 46) were more often current smokers [13 (28%)] than controls [13 (6%)], corresponding to nearly 7-fold higher odds of being current smokers than controls [OR 6.93 (95% CI 2.78, 17.26), P < 0.001]. Among those with RPF, there was a trend towards an association between current smoking and odds of IgG4-RD increasing with greater cigarette exposure (Fig. 1a; P for trend = 0.066). When limiting the analysis to only cases with RPF (n = 27) who met the 2019 ACR/EULAR classification criteria, the association between current smoking the greater odds of IgG4-RD was attenuated but the trend remained [15% vs 8%; OR 2.07 (95% CI 0.6, 7.18), P = 0.25]. In contrast to our observations among patients with RPF, there was not an association between current smoking and the odds of having IgG4-RD among cases without RPF (n = 188) when compared with controls [6% vs 6%; OR 0.95 (95% CI 0.49, 1.86), P = 0.9].
Fig. 1.
The association between pack-years of smoking and the odds of having (a) IgG4-RD with RPF and (b) IgG4-RD with a normal serum IgG4 concentration
Among cases with a normal serum IgG4 concentration (n = 101), IgG4-RD cases were more likely to be current smokers than controls [21 (21%) vs 21 (4%)]. In this subgroup, being a current smoker was associated with 6-fold higher odds of having IgG4-RD [6.22 (95% CI 3.09, 12.49), P < 0.001] and there was a strong trend towards a greater pack-year history of smoking and the odds of having IgG4-RD (Fig. 1b; P for trend = 0.02). Of note, the majority of cases with normal serum IgG4 concentrations were female [55 (55%) vs 46 (46%)], whereas the majority of cases with elevated serum IgG4 concentrations were male [98 (74%) vs 35 (26%)]. After excluding RPF patients from the analysis of the association between normal serum IgG4 concentrations and the odds of IgG4-RD, the observed association was attenuated but the trend remained [OR 2.42 (95% CI 0.97, 6.06), P = 0.059]. In contrast, smoking had an inverse association with the odds of IgG4-RD among those with elevated serum IgG4 concentrations when comparing cases and controls [49 (7%) vs 4 (3%), respectively; OR 0.34 (95% CI 0.12, 0.98), P = 0.045].
Discussion
Being a current smoker is associated with increased odds of having IgG4-RD, but this association is primarily observed among patients with RPF attributed to IgG4-RD, those with normal serum IgG4 concentrations and female patients. The observed frequencies of cigarette use in our cohort are somewhat lower than those reported in other cohorts describing patients with RPF, likely reflecting differences in the source population [29]. This is the first study to evaluate the association between cigarette smoking and the odds of having IgG4-RD.
To our knowledge, only one other study has evaluated the association between cigarette smoking and the odds of having a manifestation of IgG4-RD compared with a control population. In that study of idiopathic RPF, details of whether cases were thought to be in the spectrum of IgG4-RD or had manifestations suggestive of IgG4-RD elsewhere are not reported [17]. They found that 32% of their cohort were current smokers and 52% were former smokers, such that current smokers had 3-fold higher odds of developing RPF. A similar proportion (28%) of our IgG4-related RPF cohort was composed of current smokers. However, we found a greater effect size (6.93 vs 3.21) between the association of being a current smoker and the odds of IgG4-RD, which may reflect differences in the source of controls (e.g. they used family/friends of the subjects as controls) and the general prevalence of smoking in the USA vs Italy (e.g. low prevalence in the USA).
Our findings expand upon this prior study by examining these associations among patients with IgG4-RD. Indeed, when we restricted our analysis to those RPF cases fulfilling the ACR/EULAR classification criteria for IgG4-RD, we found a similar association. Moreover, we found that the association between being a current smoker and the odds of having IgG4-RD was particularly strong among female participants and cases with a normal serum IgG4 concentration, regardless of whether they had RPF. Our current study lacks power to determine whether smoking is a risk factor for other highly fibrotic manifestations of IgG4-RD, such as thyroiditis, which comprised just 3% of our population but is often characterized by normal serum IgG4 concentrations and dramatic fibrotic infiltrates on biopsy [30].
The associations between the odds of having IgG4-RD and being a current smoker among RPF cases and those with a normal serum IgG4 concentration suggests that there is aetiologic heterogeneity in IgG4-RD, as has been previously hypothesized [28]. Similar observations have been made in other immune-mediated conditions (e.g. RA) [31]. As such, there are likely several pathophysiologic pathways to IgG4-RD. It may be that patients who present with IgG4-RD characterized by an elevated serum IgG4 concentration develop IgG4-RD as a result of other environmental exposures or genetic risk factors that also contribute to an elevated IgG4 concentration. Given that the majority of patients with normal serum IgG4 concentrations are female, we suspect that our findings regarding the association between smoking and IgG4-RD in female but not male cases is related to differences in sex distribution among those with normal and elevated serum IgG4 concentrations [31].
The protective effect of smoking observed among those with elevated IgG4 concentrations was surprising but is similar to associations reported in IBD [32]. In IBD, current cigarette smoking is thought to increase the risk of Crohn’s disease but protect against ulcerative colitis for uncertain reasons. One potential explanation for our observation in IgG4-RD is that smoking may affect IgG4 class-switching such that smokers are unlikely to develop an IgG4-RD phenotype characterized by elevated serum IgG4 concentrations. This possibility has been previously suggested among a cohort of Black patients with periodontal disease [33], although this observation has not been further validated and there is no known mechanism to potentially explain this. The role of IgG4 antibodies in the pathogenesis of IgG4-RD is controversial, with some evidence suggesting the pathogenicity of IgG4 antibodies [34] but in the context of an understanding that unique properties of IgG4 antibodies make them a poor activator of an immune response [9].
Our findings are consistent with previous reports describing an association between cigarette smoking and fibrosis in other conditions, including hepatitis C [21] and pulmonary fibrosis [35]. One proposed mechanism to explain the association between smoking and fibrosis is that smoking leads to oxidative stress that induces fibrosis over time [17]. Indeed, RPF is often quite fibrotic when examined histopathologically and some investigators have subgrouped IgG4-RD manifestations according to the general degree of fibrosis [30]. In addition, investigators have previously hypothesized that retroperitoneal fibrosis may result from a local inflammatory response to antigens within aortic atherosclerotic plaques [36, 37]. Smoking, which is known to cause and worsen atherosclerosis, may therefore initiate the process that ultimately culminates in RPF by inducing atherosclerosis and increasing the likelihood of plaque antigen exposure to the immune system [38]. This mechanism, by which smoking might contribute to the development of RPF in IgG4-RD, warrants further investigation.
Our study has several strengths. First, both cases and controls completed standardized surveys to classify smoking status. Second, the sample size of 234 well-phenotyped IgG4-RD patients with corresponding smoking surveys is large for IgG4-RD. Third, we classified patients as having IgG4-RD using an adapted version of the recently published ACR/EULAR classification criteria for IgG4-RD [14]. Fourth, in contrast to prior studies in idiopathic RPF, our control population was sourced from a patient data repository (the MGB Biobank) representative of the population of patients seen in the MGB.
Our study has certain limitations. First, though relatively large for a sample of IgG4-RD subjects, our analysis was limited by small sample sizes of IgG4-RD subgroups, which may have limited our ability to detect significant differences. Future studies might investigate whether our observations persist across racial and ethnic groups and whether there are associations between smoking exposure and certain histopathologic findings. Second, subjects were asked to complete smoking surveys in the medical setting, which may introduce recall bias. However, both cases and controls were administered a similar survey in the context of receiving medical care so, if present, recall bias would likely be similar among cases and controls. Moreover, our primary analysis compared current smokers with never smokers to minimize the potential impact of recall bias with regard to former smoking.
In conclusion, we found a strong association between being a current smoker and the odds of having IgG4-RD manifesting as RPF or with a normal serum IgG4 concentration. Cigarette smoking is the first recognized modifiable risk factor for IgG4-RD and patients with IgG4-RD, especially those with RPF, may benefit from smoking cessation counselling. Future studies should elucidate the mechanism underlying these observations.
Acknowledgements
We thank the MGB HealthCare System Biobank for providing control health information data. This study was approved by the MGB HealthCare Institutional Review Board
Funding: This work was supported by the Rheumatology Research Foundation (Scientist Development Award to Z.S.W.) and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (K23-AR073334 and L30-AR070520 to Z.S.W.). This work was also supported by the Rheumatology Research Foundation (Scientist Development Award to C.A.P.) and the Scleroderma Foundation (New Investigator Grant to C.A.P.). This work received funding from the National Institute of Allergy and Infectious Diseases (UMI AI144295) and the Autoimmune Disease Center of Excellence: Targeting T Cells in Autoiummunity (to J.H.S., Z.S.W. and C.A.P).
Disclosure statement: Z.S.W. receives grant support from Bristol Myers Squibb for unrelated research.
Contributor Information
Rachel Wallwork, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology.
Cory A Perugino, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology.
Xiaoqing Fu, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology; Division of Rheumatology, Allergy, and Immunology, Clinical Epidemiology Program, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
Tyler Harkness, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology.
Yuqing Zhang, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology; Division of Rheumatology, Allergy, and Immunology, Clinical Epidemiology Program, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
Hyon K Choi, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology; Division of Rheumatology, Allergy, and Immunology, Clinical Epidemiology Program, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
John H Stone, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology; Division of Rheumatology, Allergy, and Immunology, Clinical Epidemiology Program, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
Zachary S Wallace, Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology; Division of Rheumatology, Allergy, and Immunology, Clinical Epidemiology Program, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
Data availability statement
Data are available upon reasonable request by any qualified researchers who engage in rigorous, independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). All data relevant to the study are included in the article.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are available upon reasonable request by any qualified researchers who engage in rigorous, independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). All data relevant to the study are included in the article.