Abstract
Objectives
Pulmonary manifestations in RA are common comorbidities. Interstitial lung disease (ILD), both idiopathic and in RA, has been associated with several genetic variants. We assessed pulmonary fibrosis (PF) in an inception cohort of RA patients in relation to genetic variants and disease-related factors.
Methods
A total of 1466 early RA patients were consecutively included and followed prospectively from the index date until death or 31 December 2016. Clinical and laboratory data and treatment were continuously registered according to the Swedish Rheumatology Quality Register. DNA was available from 1184 patients and 571 151 genome-wide single-nucleotide polymorphisms (SNPs) were analysed. Thirteen identified genetic variants were extracted. At follow-up, the patients answered a questionnaire regarding disease progression and lung involvement that was validated by reviewing medical records and analysing radiological examinations.
Results
The prevalence of PF was 5.6% and the annualized incidence rate was 5.0/1000 (95% CI 3.80, 6.54). Four SNPs were associated with PF in RA: rs35705950 [MUC5B; OR 2.5 (95% CI 1.5, 4.0), adjusted P-value = 0.00016, q-value = 0.0021]; rs111521887 [TOLLIP; OR 1.9 (95% CI 1.3, 2.8), adjusted P-value = 0.0014, q-value = 0.0092]; rs2609255 [FAM13A; OR 1.7 (95% CI 1.1, 2.5), adjusted P-value = 0.013, q-value = 0.055] and rs2736100 [TERT; OR 1.5 (95% CI 1.0, 2.2), adjusted P-value = 0.046, q-value = 0.15]. Older age and RF positivity were associated with increased risk, while MTX treatment was associated with a lower risk of PF.
Conclusions
Development of PF in an inception cohort of RA patients was associated with 4 of 12 ILD risk genes. RA-related factors except for age at diagnosis and RF positivity were of limited importance in PF development.
Keywords: rheumatoid arthritis, pulmonary fibrosis, rs35705950 (MUC5B), rs111521887 (TOLLIP), rs2609255 (FAM13A), rs2736100 (TERT)
Rheumatology key messages.
Development of pulmonary fibrosis in rheumatoid arthritis is associated with certain risk genes.
Rheumatoid arthritis–related factors are of limited importance in the development of fibrosis.
Methotrexate was not associated with increased risk of pulmonary fibrosis.
Introduction
The lungs are a frequently involved organ in RA [1, 2]. Pulmonary involvement has been proposed as a locus of the initiation of RA and later in the disease course as a comorbidity secondary to RA or as a result of treatment complications [3, 4]. Interstitial lung disease (ILD) in RA shares several characteristics with idiopathic pulmonary fibrosis (IPF), with a progressive course and poor survival [5–8]. In particular, RA-ILD predominantly shares the imaging and pathological phenotypes of the usual interstitial pneumonia (UIP) type [6].
A strong genetic basis for IPF has been demonstrated in studies of familial aggregations [9] and in genome-wide association studies (GWASs) in the general population. The most consistent finding is of a common variant (rs35705950) in the promoter of the MUC5B (mucin 5B) gene [10–13], but several other genes involving host defence, cell–cell adhesion, signalling and telomere maintenance have been associated with IPF [10–12, 14, 15]. The association between the MUC5B promoter variant and ILD in RA patients has been confirmed with similar point estimates for risk as for IPF in the general population [16]. In addition, a study using exome sequencing has identified 13 heterozygous mutations in the coding regions of TERT, RTET1, PAR and SFTPC as associated with ILD in RA [17].
Predictive factors for the development of PF in RA have been reported to be similar to those for IPF and ILD in general, e.g. male sex, age and tobacco smoking [18], in addition to RA-related factors such as positive RF and/or ACPAs and disease activity [19–21].
In this study we aimed to evaluate the development of PF in relation to the previously identified gene loci for IPF in our inception cohort of patients with early RA followed prospectively within the catchment area of northern Sweden. The impact of disease-related factors was also evaluated in relation to PF.
Materials and methods
Subjects and collection of clinical data
An inception cohort of patients diagnosed with early RA according to the American College of Rheumatology Classification Criteria [22] were analysed in this study. The patients with early RA (symptomatic <12 months before diagnosis) were consecutively included in the study at the time of RA diagnosis (index date) between 1 January 1996 and 31 December 2016 at any of the five rheumatology clinics in northern Sweden. They were simultaneously included in the Swedish Rheumatology Quality Register (SRQ) [23]. Clinical data, e.g. the 28-joint DAS (DAS28) [24] and starting and ongoing pharmacological treatment, were registered. These data were systematically recorded at baseline and at 6, 12, 18 and 24 months after diagnosis and thereafter at all clinical visits. Data on smoking habits were collected at inclusion (the index date) and previous and current smoking was registered as smoking ever vs non-smoking. BMI (in m/kg2) was also recorded.
ACPAs were analysed in plasma samples collected at baseline (the index date) and preserved at −80° C until analysed using the anti-CCP2 test (Euro Diagnostica, Malmö, Sweden), as previously described [25]. RF was assessed at baseline using routine laboratory methods.
Radiographs of the lungs were obtained at baseline as part of the clinical routine in 95% of the cases. Thereafter, radiological examinations were performed in patients presenting any symptoms of cough, dyspnoea or chest pain and before initiating biologic DMARDs (bDMARDs). If there was any sign of pathology on the routine plain X-rays, clinically suspected pulmonary involvement or other clinical indication of ILD, high-resolution CT (HRCT) was performed. At the index date, 83 (7%) of the RA patients had a pulmonary diagnosis: asthma in 55 (4.7%), chronic obstructive pulmonary disease (COPD) in 22 (1.9%), both diagnoses in 3 and a diagnosis of bronchiectasis, chronic bronchitis or pleura plaque in 3.
In 2016 the patients completed a questionnaire regarding disease progression and the incidence of lung involvement, e.g. self-reported symptoms of cough, dyspnoea or chest pain. The answers to the questionnaires were validated by reviewing the patients’ medical records and analysing the radiological examinations of the lungs. In this study of the originally recruited RA patients with DNA collected at baseline, 1184 were eligible, although 66 patients (5.6%) declined to participate by not answering the questionnaires. Consequently they were excluded and their hospital records were not examined, resulting in 1118 patients remaining for the analysis of PF. Since their inclusion in the study, 157 patients have died and therefore did not answer the questionnaire. For these individuals, medical records were reviewed and the radiological examinations were analysed. The results of the X-rays and HRCT examinations were reassessed at the end of the follow-up by an experienced pulmonologist. The diagnosis of PF was based on the results of HRCT, with the exception of five patients for whom the PF diagnosis was based on the routine plain X-ray examinations. The HRCT findings defined as PF were reticular pattern, honeycombing or traction bronchiectasis of variable degree and with ground-glass in a few cases [26]. In this study, no further diagnostic evaluation was performed to identify and separate between UIP and non-specific interstitial pneumonia.
Pharmacological treatment was registered at the index date, after 24 months and as ever-used treatment during the study period regarding corticosteroids and conventional synthetic DMARDs (csDMARDS; MTX, SSZ, chloroquine, LEF, AZA, ciclosporin, MMF and oral or injectable gold salts). Treatment with bDMARDs (abatacept, adalimumab, anakinra, etanercept, infliximab, rituximab, tocilizumab) was recorded as prescribed during the initial 24 months and as after 24 months if ever prescribed during the study period.
Genotyping
At inclusion, blood samples was collected and stored at −80°C for analyses (n = 1184). Controls [n = 1456; 68.1% females, mean age 51.7 years (s.d. 9.3)] for the GWAS were recruited from the Medical Biobank of Northern Sweden, a population-based biobank comprising a screening program for cardiovascular risk factors and prevention of comorbidity [27].
GWAS genotyping of DNA samples from cases and controls was performed using the Global Screen Assay (GSA; Illumina, San Diego, CA, USA) to analyse 571 151 genome-wide single-nucleotide polymorphisms (SNPs) at deCode Genetics (Reykjavík, Iceland). The genetic variations in the HLA region defined from 29.6 to 33.27 Mb in chromosome 6 were imputed using a European reference panel consisting of 5225 European individuals in the Type 1 Diabetes Genetic Consortium [28, 29]. An HLA-shared epitope was defined as 0401/0404/0405/0408 or 0101. Information for the following selected gene variants (n = 13) at 12 loci was extracted from the genotype data set: rs35705950 (MUC5B), rs2736100 (TERT), rs111521887 and rs5743890 (TOLLIP), rs2076295 (DSP), rs7887 (EHMT2), rs2034650 (IVD), rs2609255 (FAM13A), rs4727443 (LOC100128334/LOC105375423), rs11191865 (OBFC1), rs1278769 (ATP11A), rs6793295 (LRRC34) and rs12610495 (DPP9), according to previous publications [16].
Pulmonary examinations
The HRCT examinations were performed during the 20 year study period at five different radiology centres, leading to modifications in the methods. The GE Medical Systems Light Speed Plus and GE Medical Revolution System (GE Healthcare, Chicago, IL, USA) were used with the following parameters: axial mode collimator total/single width (1.25/0.625 mm), rotation time 0.5 or 0.7 s, pitch/scan options at 120/140 KV; and 1.25 mm thick section at 10 mm intervals and helical mode collimator total/single width 20–40/0.625 mm, rotation time 0.5 s and 2.5–5.0 mm thick sections at 1.25–5.0 mm intervals were reconstructed with an X-ray tube current of 180–280 mAs.
Statistical analysis
Statistical analysis was performed using R software version 3.5.0 (R Foundation for Statistical Computing, Vienna, Austria) [30] and SPSS 25.0 (IBM, Armonk, NY, USA). Descriptive data were summarized and presented as proportions, means and medians as appropriate. Frequencies were compared using the chi-squared test and for continuous data the Student’s t test and non-parametric tests were used. Associations between PF and possible predictors including genetic markers were analysed using logistic regression analysis and are presented as the odds ratio (OR) with the 95% CI. All multivariable models were adjusted for sex, smoking habits and age at DNA sampling (controls) or age at RA onset if not stated otherwise. The models were further adjusted for ACPA, RF, HLA-shared epitope and disease activity at the index date and during the first 24 months summarized by the calculated area under the curve for DAS28 (DAS-AUC24), as presented in the tables. A crude P-value is presented for the simple model based on the same subsets of samples as the multiple variable models for which the adjusted P-value is presented. The significance level was set at P < 0.05. A q-value is presented, i.e. a P-value adjusted for multiple testing according to the Benjamini–Hochberg false discovery rate (FDR) method; <10% was regarded as acceptable and hence the significance threshold was q = 0.10.
For missing data, imputations have been performed: age at sampling for controls (n = 34) and smoking habits for cases and controls (n = 75) and, for the RA patients, BMI (n = 197). Imputation was performed using linear/logistic regression based on age, sex, smoking and RA status (RA or control). All other data were complete except for missing data for MTX (n = 102).
Results
Of the early RA patients included in our inception cohort, 60 (5.6%) had PF at the time of diagnosis or developed PF during follow-up. In two of the cases the diagnosis of PF was settled prior to the diagnosis of RA, at 5 and 7 months, respectively. In nine additional cases the diagnosis was confirmed at the same time RA was diagnosed or within 4 months of the RA diagnosis. The degree of radiological changes diagnosed as PF varied from mild to severe. The total time at risk for the patients was 10 340 person-years and the annualized incidence rate was 5.0/1000 (95% CI 3.80, 6.54) for PF. Twenty-seven patients diagnosed with PF died during the study. Demographic and clinical data of the patients stratified for PF are presented in Table 1.
Table 1.
Demographic and clinical data of the included patients with early RA stratified for development of PF
| Characteristics | Early RA with PF (n = 60) | Early RA without PF (n = 1058) |
|---|---|---|
| Age at RA diagnosis, mean (s.d.), years | 64.8 (10.3)*** | 57.4 (14.1) |
| Age at ILD diagnosis, mean (s.d.), years | 73.9 (9.6) | – |
| Females, n (%) | 37 (61.7) | 720 (70.7) |
| Ever-smoker, n (%) | 43/59 (72.9) | 623/1009 (61.7) |
| Current smoker, n (%) | 11/58 (19.0) | 203/1043 (19.5) |
| ACPA positive, n (%) | 43 (80.0) | 705 (69.2) |
| ACPA, median (IQR) | 203.0 (547.4) | 98.2 (415.0) |
| RF positive, n (%) | 53 (88.3)** | 739 (72.5) |
| HLA-shared epitope positive, n (%) | 23 (63.9) | 371 (58.7) |
| Follow-up time from RA diagnosis until 31 December 2016 or death, mean (s.d.), years | 8.7 (4.8) | 9.5 (5.0) |
| BMI, mean (s.d.), kg2/cm | 27.0 (3.7)a | 26.4 (4.5)a |
| DAS28 on index date, mean (s.d.) | 4.8 (1.4) | 4.8 (1.4) |
| DAS28-AUC24, mean (s.d.) | 90.0 (18.8)* | 82.7 (21.5) |
| Death during study period, n (%) | 27 (45.0)*** | 130 (12.3) |
| Treatment at index date, n/N (%) | ||
| Glucocorticoids | 25/45 (55.6) | 454/775 (58.6) |
| MTX | 38/57 (66.7) | 735/859 (85.6)*** |
| csDMARDs ever during follow-up, n/N (%) | 57/58 (98.3) | 1004/1024 (98.0) |
| MTX ever during follow-up, n/N (%) | 39/59 (66.1) | 860/960 (89.6)*** |
| bDMARDs within 24 months, n/N (%) | 12/60 (20.0)* | 113/1050 (10.8) |
| bDMARDs during follow-up, n/N (%) | 23/37 (38.3) | 295/1050 (28.1) |
| Duration of RA at time of PF diagnosis, mean (minimum–maximum), years | 5.4 (−0.58–15.6) | – |
| HRCT, n (%) | 55/60 (91.7) | – |
| VC, mean (95% CI), %b | 88.2 (79.9, 96.5) | – |
| TLC, mean (95% CI), %b | 81.3 (74.5, 88.2) | |
| DLCO, mean (95% CI), %b | 61.1 (52.6, 69.7) | – |
Data available in 50 patient with PF and 849 patients without PF.
Performed in 25 cases synchronous to radiology.
VC: vital capacity; TLC: total lung capacity; DLCO: diffusion capacity of the lungs for carbon monoxide. *P<0.05, **P<0.01, ***P<0.001.
Associations with SNPs
RA patients with PF vs population controls
In the genetic association analysis, the SNPs rs35705950 (MUC5B) and rs111521887 (TOLLIP) were significantly associated with RA with PF, compared with population controls [for rs35705950: OR 4.4 (95% CI 1.9, 11.0), adjusted P-value = 0.00069, q-value = 0.009; for rs111521887: OR 2.4 (95% CI 1.2, 4.5), adjusted P-value = 0.0083, q-value = 0.054; Table 2a].
Table 2.
Association between selected SNPs and RA with PF (n = 60) and population controls (n = 1292) and in RA patients with and without PF (in simple logistic regression analyses adjusted for sex, smoking habits and age at DNA sampling or age at RA onset, respectively) analysed for each SNP separately
| rs Identifier | Risk allele | RA-PF vs controls |
RA-PF vs RA without PF |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MAF (RA/C) | OR (95% CI) | Crude P-value | OR (95% CI) | Adjusted P-value | q-Value | MAF | OR (95% CI) | Crude P-value (ILD/no ILD) | OR (95% CI) | Adjusted P-value | q-Value | ||
| rs35705950 | T | 0.26/0.12 | 2.39 (1.48, 3.76) | 0.00021 | 4.41 (1.88, 10.66) | 0.00069 | 0.009 | 0.26/0.11 | 2.57 (1.58, 4.10) | 8.9e-05 | 2.52 (1.54, 4.04) | 0.00016 | 0.0021 |
| rs111521887 | G | 0.33/0.19 | 2.09 (1.40, 3.08) | 0.00025 | 2.35 (1.25, 4.48) | 0.0083 | 0.054 | 0.33/0.20 | 1.91 (1.28, 2.80) | 0.0011 | 1.89 (1.27, 2.78) | 0.0014 | 0.0092 |
| rs2609255 | G | 0.33/0.24 | 1.58 (1.07, 2.30) | 0.018 | 1.34 (0.72, 2.49) | 0.35 | 0.65 | 0.33/0.23 | 1.69 (1.13, 2.50) | 0.0096 | 1.67 (1.11, 2.49) | 0.013 | 0.055 |
| rs7887 | T | 0.47/0.37 | 1.55 (1.07, 2.23) | 0.019 | 1.54 (0.85, 2.79) | 0.15 | 0.43 | 0.47/0.42 | 1.23 (0.85, 1.79) | 0.27 | 1.21 (0.83, 1.77) | 0.32 | 0.59 |
| rs2736100 | A | 0.61/0.55 | 1.25 (0.86, 1.83) | 0.24 | 1.60 (0.91, 2.93) | 0.11 | 0.43 | 0.61/0.53 | 1.39 (0.96, 2.03) | 0.085 | 1.47 (1.01, 2.15) | 0.046 | 0.15 |
| rs12610495 | G | 0.43/0.38 | 1.23 (0.84, 1.77) | 0.28 | 0.98 (0.51, 1.83) | 0.94 | 0.94 | 0.43/0.36 | 1.35 (0.92, 1.96) | 0.12 | 1.31 (0.89, 1.92) | 0.16 | 0.42 |
| rs2076295 | G | 0.47/0.41 | 1.29 (0.91, 1.85) | 0.15 | 1.14 (0.64, 2.06) | 0.65 | 0.84 | 0.47/0.42 | 1.25 (0.86, 1.82) | 0.25 | 1.25 (0.86, 1.83) | 0.24 | 0.53 |
| rs5743890 | C | 0.08/0.10 | 0.85 (0.41, 1.56) | 0.62 | 0.95 (0.34, 2.45) | 0.92 | 0.94 | 0.08/0.11 | 0.75 (0.36, 1.39) | 0.40 | 0.75 (0.36, 1.40) | 0.41 | 0.66 |
| rs4727443 | C | 0.38/0.36 | 1.10 (0.76, 1.59) | 0.61 | 0.68 (0.36, 1.35) | 0.23 | 0.50 | 0.38/0.36 | 1.08 (0.74, 1.58) | 0.68 | 1.07 (0.73, 1.56) | 0.73 | 0.93 |
| rs1278769 | G | 0.22/0.21 | 1.04 (0.66, 1.60) | 0.86 | 1.21 (0.60, 2.37) | 0.59 | 0.84 | 0.22/0.24 | 0.89 (0.57, 1.46) | 0.61 | 0.93 (0.58, 1.42) | 0.73 | 0.93 |
| rs11191865 | A | 0.44/0.47 | 0.90 (0.63, 1.29) | 0.58 | 0.66 (0.36, 1.18) | 0.17 | 0.43 | 0.44/0.46 | 0.91 (0.63, 1.32) | 0.62 | 0.95 (0.65, 1.38) | 0.79 | 0.93 |
| rs6793295 | C | 0.32/0.29 | 1.12 (0.75, 1.65) | 0.56 | 1.04 (0.55, 1.93) | 0.89 | 0.94 | 0.32/031 | 1.01 (0.68, 1.49) | 0.95 | 1.04 (0.69, 1.53) | 0.86 | 0.93 |
| rs2034650 | A | 0.50/0.46 | 1.20 (0.83, 1.73) | 0.34 | 1.17 (0.65, 2.11) | 0.60 | 0.84 | 0.50/0.49 | 1.02 (0.70, 1.49) | 0.90 | 1.01 (0.69, 1.47) | 0.98 | 0.98 |
RA patients with PF vs RA patients without PF
In logistic regression analyses, the same two SNPs, rs35705950 and rs111521887, were also associated with an increased risk of PF in RA [for rs35705950: OR 2.5 (95% CI 1.5, 4.0), adjusted P-value = 0.00016, q-value = 0.0021; for rs111521887: OR 1.9 (95% CI 1.3, 2.8), adjusted P-value = 0.0014, q-value = 0.0092; Table 2b], as was SNP rs2609255 (FAM13A gene locus; OR 1.7 (95% CI 1.1, 2.5), adjusted P-value = 0.013, q-value = 0.055]. The SNP rs2736100 (TERT gene locus) was associated with the risk of PF after adjustments [OR 1.5 (95% CI 1.0, 2.2), adjusted P-value = 0.046, q-value = 0.15] (Table 2b). Further adjustments for ACPA, RF and HLA-shared epitope did not change the associations between the SNPs; rs35705950, rs111521887 and rs2609255 and the risk of RA-PF showed similar ORs and P-values (Table 3). The addition of DAS28 at the index date to the mentioned adjustments did not change the ORs or the P-values (Table 3) and additional adjustments for BMI and MTX at the index date, included separately or together, yielded similar significant associations of the SNPs with the development of PF (data not shown).
Table 3.
Association between RA with and without PF analysed in simple logistic regression analyses for each SNP with adjustments
| rs Identifier | Risk allele | RA with vs. without PF with adjustmentsa |
RA with vs. without PF with adjustmentsb |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MAF (ILD+/ILD−) | OR (95% CI) | Crude P-value | OR (95% CI) | Adjusted P-value | q-Value | MAF (ILD+/ILD−) | OR (95% CI) | Crude P-value | OR (95% CI) | Adjusted P-value | q-Value | ||
| rs35705950 | T | 0.27/0.11 | 2.81 (1.71, 4.53) | 2.8e-05 | 2.65 (1.59, 4.32) | 0.00012 | 0.0015 | 0.26/0.11 | 2.74 (1.65, 4.43) | 5.5e-05 | 2.56 (1.54, 4.21) | 0.00023 | 0.0029 |
| rs111521887 | G | 0.34/0.20 | 1.95 (1.30, 2.89) | 0.00093 | 1.90 (1.27, 2.81) | 0.0016 | 0.010 | 0.34/0.20 | 2.01 (1.34, 2.98) | 0.00060 | 1.96 (1.31, 2.92) | 0.00098 | 0.0063 |
| rs2609255 | G | 0.33/0.23 | 1.63 (1.08, 2.43) | 0.017 | 1.63 (1.07, 2.45) | 0.021 | 0.090 | 0.32/0.23 | 1.59 (1.05, 2.38) | 0.026 | 1.61 (1.05, 2.44) | 0.027 | 0.12 |
| rs2736100 | Ac | 0.60/0.53 | 1.36 (0.94, 2.00) | 0.11 | 1.42 (0.97, 2.09) | 0.076 | 0.25 | 0.60/0.53 | 1.33 (0.91, 1.95) | 0.14 | 1.38 (0.94, 2.05) | 0.10 | 0.33 |
| rs2076295 | G | 0.47/0.42 | 1.25 (0.85, 1.84) | 0.25 | 1.29 (0.88, 1.91) | 0.19 | 0.45 | 0.46/0.42 | 1.21 (0.82, 1.77) | 0.34 | 1.25 (0.84, 1.85) | 0.26 | 0.59 |
| rs12610495 | G | 0.43/0.36 | 1.33 (0.91, 1.95) | 0.14 | 1.28 (0.87, 1.88) | 0.21 | 0.45 | 0.42/0.36 | 1.28 (0.87, 1.88) | 0.21 | 1.22 (0.83, 1.80) | 0.31 | 0.59 |
| rs7887 | T | 0.48/0.42 | 1.27 (0.87, 1.86) | 0.21 | 1.18 (0.79, 1.77) | 0.42 | 0.75 | 0.48/0.42 | 1.27 (0.87, 1.86) | 0.22 | 1.18 (0.78, 1.77) | 0.44 | 0.71 |
| rs5743890 | C | 0.09/0.11 | 0.77 (0.37, 1.43) | 0.45 | 0.78 (0.37, 1.45) | 0.46 | 0.75 | 0.08/0.11 | 0.70 (0.33, 1.33) | 0.32 | 0.70 (0.32, 1.34) | 0.32 | 0.59 |
| rs6793295 | C | 0.33/0.31 | 1.06 (0.71, 1.57) | 0.76 | 1.11 (0.73, 1.65) | 0.61 | 0.89 | 0.33/0.32 | 1.09 (0.72, 1.61) | 0.69 | 1.13 (0.75, 1.68) | 0.56 | 0.82 |
| rs11191865 | A | 0.44/0.46 | 0.90 (0.62, 1.32) | 0.60 | 0.93 (0.63, 1.37) | 0.73 | 0.95 | 0.44/0.46 | 0.90 (0.61, 1.32) | 0.60 | 0.93 (0.63, 1.38) | 0.73 | 0.87 |
| rs1278769 | G | 0.22/0.24 | 0.93 (0.59, 1.42) | 0.75 | 0.94 (0.59, 1.46) | 0.80 | 0.95 | 0.22/0.24 | 0.90 (0.56, 1.39) | 0.65 | 0.90 (0.56, 1.40) | 0.67 | 0.87 |
| rs2034650 | A | 0.49/0.50 | 0.98 (0.67, 1.44) | 0.93 | 0.99 (0.67, 1.46) | 0.96 | 0.97 | 0.48/0.50 | 0.95 (0.64, 1.39) | 0.77 | 0.96 (0.65, 1.42) | 0.84 | 0.91 |
| rs4727443 | C | 0.36/0.36 | 0.99 (0.67, 1.46) | 0.98 | 1.01 (0.67, 1.49) | 0.97 | 0.97 | 0.36/0.36 | 0.98 (0.66, 1.45) | 0.92 | 1.0 (0.67, 1.48) | 1.0 | 1.0 |
Only patients with no missing values are included.
Adjusted for sex, age at RA diagnosis, smoking habits, anti-CCP, RF and HLA-shared epitope.
Adjusted for sex, age at diagnosis, smoking habits, anti-CCP, RF, HLA-shared epitope and DAS28 at the index date.
PF-associated allele.
MAF: minor allele frequency.
Associations with clinical data
The patients affected with PF were significantly older at RA disease onset, were more often RF positive and had higher disease activity during the first 24 months (Table 1). PF was associated with increased risk of death, which remained significant after adjustments for age [adjusted OR 4.55 (95% CI 2.53, 8.16), P < 0.001]. Seven of the 11 patients with early diagnosis of PF (within 4 months from the index date) were already being treated with MTX from the index date. Overall, patients selected for MTX treatment were significantly younger, with a mean age of 56.3 years (s.d. 13.4) vs 59.5 (16.1) for those not treated with MTX (P < 0.001). This was also evident among those with or developing PF; those selected for MTX treatment were significantly younger, with a mean age of 63.7 years (s.d. 8.9) vs 67.3 (13.2) for those not treated. However, significantly more patients diagnosed with PF had received bDMARDs already within the first 24 months of disease (20% vs 10.8%; P < 0.05), irrespective of the time point of the PF diagnosis.
In simple logistic regression analysis, age at onset and positive RF were associated with increased risk of PF, and in multiple variable analysis these factors remained significantly associated with the risk of PF (Table 4). MTX exposure from the index date was associated with a decreased risk of PF [OR 0.21 (95% CI 0.12, 0.39), P = 6.0 × 10−7), irrespective of smoking and age, while the other variables were associated with increased risk (Table 4). Frequencies of csDMARD treatment during the first 24 months or after 24 months were similar, irrespective of the presence of PF (Table 1).
Table 4.
Associations between PF and covariates in simple and multivariable analyses
| Variables | Simple variable analysis |
Multivariable analysis |
||
|---|---|---|---|---|
| OR (95% CI) | P-value | OR (95% CI) | P-value | |
| Sex | 0.64 (0.35, 1.24) | 0.17 | 0.86 (0.44, 1.74) | 0.67 |
| Age at RA onset | 1.10 (1.03, 1.09) | 2.9e-05 | 1.10 (1.03, 1.09) | 0.0001 |
| Smoking +/−a | 1.80 (0.92, 3.60) | 0.099 | 1.50 (0.77, 3.21) | 0.25 |
| ACPA +/− | 1.40 (0.70, 3.01) | 0.37 | 1.20 (0.52, 2.81) | 0.73 |
| RF +/− | 2.70 (1.10, 7.80) | 0.042 | 3.0 (1.10, 9.58) | 0.045 |
| HLA-shared epitope +/−b | 0.97 (0.51, 2.00) | 0.94 | 0.88 (0.44, 1.89) | 0.74 |
| MTX started at index date | 0.27 (0.14, 0.51) | 4.3e-05 | 0.30 (0.16, 0.60) | 0.00048 |
| BMIc | 1.0 (0.95, 1.08) | 0.64 | 1.00 (0.95, 1.10) | 0.54 |
| DAS28 at index date | 0.99 (0.80, 1.22) | 0.92 | 0.91 (0.72, 1.14) | 0.39 |
Smoking refers to ever being a smoker.
HLA-shared epitope includes 0401/0404/0405/0408/0101.
Missing values were imputed.
Associations between clinical data and SNPs
Including the three SNPs most strongly associated with RA-PF (rs35705950, rs111521887 and rs2609255) in separate multiple variable analyses including the demographic data yielded similar risk ratios for the SNPs for PF. Age, RF positivity and MTX exposure from the index date remained significantly associated with the risk of PF (Table 5). Comparing patients who were carriers of the minor alleles of all three SNPs vs those without minor alleles yielded a similar risk for the combination of the three SNPs [OR 2.1 (95% CI 1.4, 3.3), P = 0.00049] as did each SNP separately. The other factors (age at RA diagnosis, RF positivity and MTX) remained significant risk factors of the same magnitude in the simple and multiple variable analyses (data not shown).
Table 5.
Logistic regression analyses with PF as the outcome with the top three SNPs included (rs2609255, rs111521887 and rs35705950) and covariates included as adjustments in previous analyses in multivariable regression models and registered at the index date
| Variables | rs 2609255 |
rs111521887 |
rs35705950 |
|||
|---|---|---|---|---|---|---|
| OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | |
| SNP | 2.04 (1.22, 3.39) | 0.0057 | 2.19 (1.34, 3.55) | 0.0015 | 2.67 (1.38, 5.02) | 0.0026 |
| Sex, female/male | 0.80 (0.39, 1.69) | 0.54 | 0.80 (0.39, 1.69) | 0.55 | 0.49 (0.22, 1.09) | 0.075 |
| Age at RA diagnosis | 1.05 (1.02, 1.08) | 0.0030 | 1.05 (1.02, 1.09) | 0.0017 | 1.05 (1.01, 1.09) | 0.0097 |
| Ever-smoker, +/− | 2.31 (1.02, 5.92) | 0.058 | 2.30 (1.02, 5.89) | 0.060 | 3.21 (1.17, 11.41) | 0.040 |
| BMI, kg2/ma | 1.03 (0.95, 1.11) | 0.45 | 1.04 (0.96, 1.12) | 0.32 | 1.05 (0.95, 1.15) | 0.29 |
| DAS28 | 0.90 (0.71, 1.16) | 0.42 | 0.93 (0.73, 1.19) | 0.54 | 0.84 (0.64, 1.11) | 0.23 |
| MTX | 0.39 (0.19, 0.87) | 0.016 | 0.38 (0.18, 0.84) | 0.013 | 0.46 (0.18, 1.27) | 0.11 |
| ACPA +/− | 1.16 (0.48, 3.09) | 0.76 | 1.30 (0.53, 3.54) | 0.59 | 1.57 (0.51, 6.03) | 0.47 |
| RF +/− | 2.78 (0.94, 10.36) | 0.088 | 2.62 (0.88, 9.84) | 0.11 | 4.05 (1.03, 27.30) | 0.080 |
| HLA-shared epitopeb | 0.95 (0.44, 2.22) | 0.91 | 0.81 (0.38, 1.87) | 0.61 | 0.90 (0.36, 2.45) | 0.82 |
Missing values for BMI are imputed.
HLA-shared epitope includes 0401/0404/0405/0408/0101.
Discussion
In this rather small exploratory study of an unselected inception cohort of patients with early RA, associations were found with PF risk gene variants. The PF risk conferred by the MUC5B promoter variant rs35705950 was the strongest in our analysis and of the same magnitude in our cohort as in others [16]. Moreover, 3 of the 12 additional genetic loci previously associated with PF in RA were confirmed in our study, including the TERT locus when fully adjusted [10, 11, 14]. The remaining nine loci were not associated with PF in RA in our study, possibly due to the limited size of the cohort. We also adjusted for several clinical variables, which was not performed fully in other studies. This study conclusively confirms both a shared genetic predisposition for IPF and RA-associated PF and an RA-specific genetic susceptibility to PF.
Eleven (18.3%) of the RA patients were diagnosed with PF along with the diagnosis of RA, which is a slightly lower frequency than has been found in similar studies, which were 24.7% and 25%, respectively [15, 31]. The reported prevalence in our unselected inception cohort was fairly low, despite the fact that in most cases the diagnosis of PF was based on the results of HRCT, which is a favourable method of detecting fibrosis [32]. The annualized incidence was 5.0/1000 person-years, which is in line with another report of 4.1/1000 person-years [15], although we have focussed on the presence of PF in screening for lung involvement while the other study included ILD [15].
In previously performed studies on IPF as well as in RA-related PF, older age at disease onset, male sex and smoking were predisposing factors [18, 19]. Interestingly, we found that only older age and the presence of RF promoted the development of fibrosis. Male sex and being an ever-smoker were numerically greater in the cases with fibrosis but did not reach statistical significance in simple or multiple variable analyses, concordant with the findings reported for another inception cohort [15]. However, the frequency of being an ever-smoker was, overall, high in our population irrespective of the presence of lung fibrosis, while the frequency of current smokers had decreased to 19% and was similar in both patient groups irrespective of fibrosis. ACPAs were numerically, but not significantly, more frequently positive among the RA patients with fibrosis. This finding is not as convincing as those of a number of studies that reported increased frequencies of ACPAs in RA patients with ILD [5, 19, 21] but is in line with another [33]. In this study focussed on the development of PF, we did not include the development of other lung manifestations, which could explain the lack of a significant association with ACPAs. The frequency of ACPA positivity among patients having or receiving the PF diagnosis when RA was diagnosed was 82%, similar to that in the whole PF group (80%). Taken together, a putative association between the presence of ACPAs and the development of RA-PF remains controversial and larger studies with well-defined cohorts are needed in order to support or reject a common pathogenic mechanism between the two.
Patients with PF had higher disease activity over time, measured as DAS28-AUC24, as previously reported [34, 35]. The DAS28 at the index date was similar among patients, irrespective of PF. Further, adjustments for DAS28 in multivariable analyses did not affect the increased risk of PF conveyed by the SNPs. Patients who developed PF were more often treated with bDMARDs already within the first 24 months after the diagnosis of RA, irrespective of diagnosed PF. This suggests, indirectly, that they had a higher disease activity. Also, only 4 of the 12 cases treated with bDMARDs within the first 24 months were diagnosed with PF during that period. csDMARDs were used to the same extent as for those without fibrosis—in 98% of the cases—although to a significantly lesser extent with MTX from baseline.
Although this study was not designed to analyse the relationship between MTX treatment and PF in depth, we could clearly see that MTX exposure from the index date was associated with a significantly reduced risk of fibrosis. These findings are in line with a previous publication of a reduced incidence of RA-ILD in patients treated with MTX [31]. In another study, no supporting evidence was presented for a relationship between MTX and RA-ILD [15], and in a recent review of the literature, firm conclusions about an association between MTX and ILD could not be drawn [36]. Another recent nationwide population-based study found no increased risk of MTX treatment for RA-ILD [37]. The choice of pharmacological treatment for individual RA patients in our cohort was made by the patient’s physician in agreement with the patient, based on the Swedish national guidelines. Notably, in our study, patients diagnosed with PF were less often already being treated with MTX from baseline and also were less often treated with MTX when the fibrosis was diagnosed at a later stage during disease progression. Patients selected for MTX treatment were significantly younger than patients who started other treatments. One possible explanation for this could be that at the time of RA diagnosis, older individuals present with more comorbidities or other factors that would drive the selection of treatments towards other csDMARDs. Thus we suspect, but have not been able to show in our available data, that absolute or relative contraindications for MTX coincided with or were associated with risk factors for PF, such as older age, causing MTX to less often be the choice for patients who later developed PF.
The strength of the current study is that the cohort of RA patients was unselected and originated from a homogeneous population of northern Sweden. Almost all (95%) individuals diagnosed with early RA within the catchment area of northern Sweden and included in the SRQ were included and willing to participate in the study. Furthermore, X-rays of the lungs of the patients were routinely performed at inclusion, providing baseline information about the lungs.
A limitation of the study is that the HRCT examinations were not performed randomly or on all included patients, but for those with abnormalities on the plain X-rays or clinical indications with the development of defined symptoms. The HRCT examinations have been performed over a period of almost 20 years and methodological improvements during this time could affect the results. Consequently we refrained from further diagnostic evaluations besides PF. Another limitation is that the controls were identified within the population-based biobank of northern Sweden and we lack information about any comorbidities among the them. However, the potential prevalence of PF among the controls would reduce the contrast in the comparison with our affected cases.
From this study we can conclude that RA-related factors with the exceptions of age at diagnosis and positivity for RF have limited importance compared with the impact of ILD-associated genetic factors in the development of PF in RA. These findings would support the use of the newly introduced antifibrotic targeted therapies in the treatment of patients with RA and PF to prevent further fibrotic development.
Acknowledgements
We would like to acknowledge the staff at the departments of rheumatology at the hospitals at Sundebyn, Sundsvall Örnsköldsvik and Östersund and in particular Viktoria von Zweighberg, for holding the project together. Dr Saedis Saevarsdottir and Prof. Leonid Padyukov are gratefully acknowledged for technical work with the GWAS and imputations for the HLA region. 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. E.J. and S.R.D. were responsible for study conception and design. E.J., L.L. and S.R.D. were responsible for the acquisition of data. E.J., L.L., E.N., E.F., J.D. and S.R.D. were responsible for the analysis and interpretation of data. The study complies with the Declaration of Helsinki and the Regional Ethics Committees at Umeå University approved this study (Dnr 2017-432-32M, 2019-02039) and the patients signed an informed consent to participate.
Funding: This work was supported by grants from the Vasculitis Foundation USA, the Swedish Research Council (K2013-52X-20307-07-3 and Dnr 2018-02551), King Gustaf V’s 80-Year Fund, the Swedish Rheumatism Association and Umeå University.
Disclosure statement: None.
Data availability statement
The data underlying this article cannot be shared publicly due to the privacy of individuals that participated in the study. The data will be shared on reasonable request to the corresponding author.
References
- 1. Turesson C, O’Fallon WM, Crowson CS, Gabriel SE, Matteson EL.. Extra-articular disease manifestations in rheumatoid arthritis: incidence trends and risk factors over 46 years. Ann Rheum Dis 2003;62:722–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Cortet Perez BT, Roux N, Flipo RM. et al. Pulmonary function tests and high resolution computed tomography of the lungs in patients with rheumatoid arthritis. Ann Rheum Dis 1997;56:596–600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Hyldgaard C, Hilberg O, Becic Pedersen A. et al. A population-based cohort study of rheumatoid arthritis-associated interstitial lung disease: comorbidity and mortality. Ann Rheum Dis 2017;76:1700–6. [DOI] [PubMed] [Google Scholar]
- 4. Reynisdottir G, Olsen H, Joshua V. et al. Signs of immune activation and local inflammation are present in the bronchial tissue of patients with untreated early rheumatoid arthritis. Ann Rheum Dis 2016;75:1722–7. [DOI] [PubMed] [Google Scholar]
- 5. Kelly CA, Saravanan V, Nisar M. et al. Rheumatoid arthritis-related interstitial lung disease: associations, prognostic factors and physiological and radiological characteristics—a large multicentre UK study. Rheumatology (Oxford) 2014;53:1676–82. [DOI] [PubMed] [Google Scholar]
- 6. Kim EJ, Collard HR, King TE. Jr. Rheumatoid arthritis-associated interstitial lung disease: the relevance of histopathologic and radiographic pattern. Chest 2009;136:1397–405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Assayag D, Lubin M, Lee JS, et al. Predictors of mortality in rheumatoid arthritis-related interstitial lung disease. Respirology 2014;19:493–500. [DOI] [PubMed] [Google Scholar]
- 8. Solomon JJ, Chung JH, Cosgrove GP. et al. Predictors of mortality in rheumatoid arthritis-associated interstitial lung disease. Eur Respir J 2016;47:588–96. [DOI] [PubMed] [Google Scholar]
- 9. Steele MP, Speer MC, Loyd JE. et al. Clinical and pathologic features of familial interstitial pneumonia. Am J Respir Crit Care Med 2005;172:1146–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Allen RJ, Guillen-Guio B, Oldham JM. et al. Genome-wide association study of susceptibility to idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2020;201:564–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Hobbs BD, Putman RK, Araki T. et al. Overlap of genetic risk between interstitial lung abnormalities and idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2019;200:1402–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Fingerlin TE, Murphy E, Zhang W. et al. Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis. Nat Genet 2013;45:613–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Zhu QQ, Zhang XL, Zhang SM. et al. Association between the MUC5B promoter polymorphism rs35705950 and idiopathic pulmonary fibrosis: a meta-analysis and trial sequential analysis in Caucasian and Asian populations. Medicine (Baltimore) 2015;94:e1901. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Noth I, Zhang Y, Ma SF. et al. Genetic variants associated with idiopathic pulmonary fibrosis susceptibility and mortality: a genome-wide association study. Lancet Respir Med 2013;1:309–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Kuduri G, Norton S, Young A. et al. Interstitial lung disease has a poor prognosis in rheumatoid arthritis: results from an inception cohort . Rheumatology (Oxford) 2010;49:1483–9. [DOI] [PubMed] [Google Scholar]
- 16. Juge PA, Lee JS, Ebstein E. et al. MUC5B promoter variant and rheumatoid arthritis with interstitial lung disease. N Engl J Med 2018;379:2209–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Juge PA, Borie R, Kannengiesser C. et al. Shared genetic predisposition in rheumatoid arthritis-interstitial lung disease and familial pulmonary fibrosis. Eur Respir J 2017;49:1602314. 11 [DOI] [PubMed] [Google Scholar]
- 18. Raghu G, Collard HR, Egan JJ. et al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 2011;183:788–824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Johnson C. Recent advances in the pathogenesis, prediction, and management of rheumatoid arthritis-associated interstitial lung disease. Curr Opin Rheumatol 2017;29:254–9. [DOI] [PubMed] [Google Scholar]
- 20. Wang D, Zhang J, Lau J. et al. Mechanisms of lung disease development in rheumatoid arthritis. Nat Rev Rheumatol 2019;15:581–96. [DOI] [PubMed] [Google Scholar]
- 21. Giles JT, Danoff SK, Sokolove J. et al. Association of fine specificity and repertoire expansion of anticitrullinated peptide antibodies with rheumatoid arthritis associated interstitial lung disease. Ann Rheum Dis 2014;73:1487–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Arnett FC, Edworthy SM, Bloch DA. et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 1988;31:315–24. [DOI] [PubMed] [Google Scholar]
- 23.Swedish Rheumatology Quality Register. www.srq.nu/en.
- 24. Prevoo ML, van ’t Hof MA, Kuper HH. et al. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum 1995;38:44–8. [DOI] [PubMed] [Google Scholar]
- 25. Kokkonen H, Johansson M, Innala L, Jidell E, Rantapää-Dahlqvist S.. The PTPN221858C/T polymorphism is associated with anti-cyclic citrullinated peptide antibody-positive early rheumatoid arthritis in northern Sweden. Arthritis Res Ther 2007;9:R56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Raghu G, Remy-Jardin M, Myers JL. et al. Diagnosis of idiopathic pulmonary fibrosis. An official ATS/ERS/JRS/ALAT clinical practice guideline. Am J Respir Crit Care Med 2018;198:e44–e68. [DOI] [PubMed] [Google Scholar]
- 27. www.umu.se/enheten-for-biobanksforskning.
- 28. Jia X, Han H, Onengut-Gumuscu S. et al. Imputing amino acid polymorphisms in human leukocyte antigens. PLoS One 2013;8:e64683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Brown WM, Pierce J, Hilner JE. et al. Overview of the MHC fine mapping data. Diabetes Obes Metab 2009;11(Suppl 1):2–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2018.
- 31. Kiely P, Busby AD, Nikiphorou E. et al. Is incident rheumatoid arthritis interstitial lung disease associated with methotrexate treatment? Results from a multivariate analysis in the ERAS and ERAN inception cohorts. BMJ Open 2019;9:e028466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Gabbay E, Tarala R, Will R. et al. Interstitial lung disease in recent onset rheumatoid arthritis. Am J Respir Crit Care Med 1997;156:528–35. [DOI] [PubMed] [Google Scholar]
- 33. Sebastiani M, Manfredi A, Cerri S. et al. Radiologic classification of usual interstitial pneumonia in rheumatoid arthritis-related interstitial lung disease: correlations with clinical, serological and demographic features of disease. Clin Exp Rheumatol 2016;34:564–5. [PubMed] [Google Scholar]
- 34. Restrepo JF, del Rincón I, Battafarano DF. et al. Clinical and laboratory factors associated with interstitial lung disease in rheumatoid arthritis. Clin Rheumatol 2015;34:1529–36. [DOI] [PubMed] [Google Scholar]
- 35. Rocha-Muñoz AD, Ponce-Guarneros M, Gamez-Nava JI. et al. Anti-cyclic citrullinated peptide antibodies and severity of interstitial lung disease in women with rheumatoid arthritis. J Immunol Res 2015;2015:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Fragoulis GE, Conway R, Nikiphorou E.. Methotrexate and interstitial lung disease: controversies and questions. A narrative review of the literature. Rheumatology (Oxford) 2019;58:1900–6. [DOI] [PubMed] [Google Scholar]
- 37. Ibfelt EH, Jacobsen RK, Iskov Kopp T. et al. Methotrexate and risk of interstitial lung disease and respiratory failure in rheumatoid arthritis: a nationwide population-based study. Rheumatology (Oxford) 2021;60:346–52. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data underlying this article cannot be shared publicly due to the privacy of individuals that participated in the study. The data will be shared on reasonable request to the corresponding author.