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Basic and translational research
Extended report
The interferon type I signature is present in systemic sclerosis before overt fibrosis and might contribute to its pathogenesis through high BAFF gene expression and high collagen synthesis
  1. Zana Brkic1,
  2. Lenny van Bon2,3,
  3. Marta Cossu3,4,
  4. Cornelia G van Helden-Meeuwsen1,
  5. Madelon C Vonk3,
  6. Hanneke Knaapen3,
  7. Wim van den Berg3,
  8. Virgil A Dalm1,
  9. Paul L Van Daele1,
  10. Adriana Severino4,
  11. Naomi I Maria1,
  12. Samara Guillen1,
  13. Willem A Dik1,
  14. Lorenzo Beretta4,
  15. Marjan A Versnel1,
  16. Timothy Radstake2
  1. 1Department of Immunology, Erasmus Medical Center, Rotterdam, The Netherlands
  2. 2Department of Rheumatology, Clinical Immunology and Laboratory of Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands
  3. 3Department of Rheumatology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
  4. 4Referral Center for Systemic Autoimmune Diseases, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy
  1. Correspondence to Professor Timothy Radstake, Department of Rheumatology & Clinical Immunology, Laboratory of Translational Immunology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3485 CX, The Netherlands; Tradstake73{at}gmail.com

Abstract

Background Interferon (IFN) signature has been reported in definite systemic sclerosis (SSc) but it has not been characterised in early SSc (EaSSc). We aim at characterising IFN type I signature in SSc before overt skin fibrosis develops.

Methods The expression of 11 IFN type I inducible genes was tested in whole-blood samples from 30 healthy controls (HCs), 12 subjects with primary Raynaud's phenomenon (RP), 19 patients with EaSSc, 7 patients with definite SSc without cutaneous fibrosis, 21 limited cutaneous SSc and 10 diffuse cutaneous SSc subjects. The correlation between IFN activity in monocytes, B cell activating factor (BAFF) mRNA expression and type III procollagen N-terminal propeptide (PIIINP) serum levels was tested.

Results In all the SSc groups, higher IFN scores were observed compared with HC. An IFN score ≥7.09 discriminated HCs from patients with SSc (sensitivity=0.7, specificity=0.88, area under receiving operating characteristic (AUROC)=0.82); the prevalence of an elevated IFN score was: HC=3.3%; RP=33.3%, EaSSc=78.9%, definite SSc=100%, limited cutaneous SSc=42.9%, diffuse cutaneous SSc=70.0%. In monocytes an IFN score ≥4.12 distinguished HCs from patients with fibrotic SSc (sensitivity=0.62, specificity=0.85, AUROC=0.76). Compared with IFN-negative subjects, IFN-positive subjects had higher monocyte BAFF mRNA levels (19.7±5.2 vs 15.20±4.0, p=2.1×10−5) and serum PIIINP levels (median=6.0 (IQR 5.4–8.9) vs median=3.9 (IQR 3.3–4.7), p=0.0004).

Conclusions An IFN type I signature is observed in patients with SSc from the earliest phases of the disease, even before overt skin fibrosis. The presence of IFN type I signature in monocytes is correlated with BAFF mRNA expression and serum PIIINP levels, supporting a contribution in the pathogenesis and progression of SSc.

  • Autoimmune Diseases
  • Systemic Sclerosis
  • Inflammation
  • Cytokines

http://dx.doi.org/10.1136/annrheumdis-2015-207392

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    Introduction

    Systemic sclerosis (SSc) is a complex autoimmune disease with extensive fibrosis, vascular alterations and immune activation among its principal features.1 With an incidence of 1–2 cases per 100 000 it is considered a rare disease in which chronic oxidative stress and inflammation lead to organ failure ending up in severe fibrosis of skin and internal organs. Ultimately, these disease hallmarks culminate in profound decline in the quality of life and premature death. Raynaud's phenomenon (RP) is the first manifestation of SSc in 95% of cases and can precede the onset of SSc by years. The presence of RP, specific autoantibodies and typical features at the nailfold videocapillaroscopy (NVC) even in the absence of other additional clinical or laboratory features, allows identification of a specific group of patients termed patients with early SSc (EaSSc),2 who are considered to have a high chance to develop SSc.3 ,4 The American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) Scleroderma Classification Criteria Committee proposed new criteria to identify patients with definite SSc even when overt skin or lung fibrosis may not be present.5 This allows the identification of a new group of patients with definite SSc that does not show the prototypical cutaneous involvement that clinically allows the identification of two major subsets of SSc, that is, limited cutaneous SSc (lcSSc) and the diffuse cutaneous SSc (dcSSc).6 It is now clear that in most cases, the natural history of SSc can be viewed as a continuum where the disease develops from RP, to a very early disease stage where only NVC and/or autoantibody alterations are present (EaSSc), to a state where the first definite SSc manifestation can be observed and eventually progress to a full blown disease with cutaneous and visceral fibrotic features. Estimates in EaSSc case-series showed that the risk of progression to a definite SSc according to the ACR/EULAR 2013 criteria is about 60% and 80% at 5 years and 10 years from referral, respectively.5 It is currently unknown to what extent the different stages of the disease differ from each other in terms of immunological abnormalities. Yet, focusing on the study of early disease stages could provide new prognostic tools and a novel therapeutic window of opportunity to prevent the onset of fibrosis and end-stage organ failure.

    Potential candidates for the understanding of the immunological properties of early SSc are type I interferons (IFNs). Studies on genetic risk factors for SSc revealed that genes involved in the IFN type I signalling pathway such as STAT4 and IRF5 are associated with a significant risk of SSc occurrence.7–10 Furthermore, a substantial part of patients with SSc displays IFN type I activation either in the affected skin or in immune cells isolated from the circulation.11–13 Clinically, the expression of the IFN type I induced genes Siglec-1 (CD169) and IFI44 in skin biopsies correlated with the modified Rodnan skin score (mRSS), that is still considered the only available marker of disease progression.14 It is widely accepted that plasmacytoid dendritic cells (pDCs) are the main source of type I IFNs. Upon activation of toll-like receptors (TLRs) by the so-called danger signals, pDCs start to secrete marked amounts of type I IFN and SSc pDCs produce increased levels of type I IFN after TLR9 stimulation.15 This release of type I IFN is reflected by the IFN type I induced gene expression pattern, the so-called IFN type I signature, observed in multiple systemic autoimmune diseases.16 ,17

    One of the most studied cell types affected by type I IFN are monocytes. Monocytes stimulated by type I IFN differentiate into activated DCs and macrophages and, in combination with other triggers, direct the immune system into potentially harmful conditions like autoimmune diseases. Previously we found a monocyte IFN type I signature in 55% of patients with primary Sjögren's syndrome (pSS) compared with 4.5% of healthy controls (HCs).18 One of the genes that strongly correlated with the presence of the IFN type I signature was B cell activating factor (BAFF) of the tumour necrosis factor family.18 Interestingly, BAFF serum levels were found to correlate with the extent of skin fibrosis in patients with SSc.19

    Overall, disentangling the IFN type I activity in different phases of disease and its role in the pathogenesis of SSc is highly justified. In this study we analysed for the first time the prevalence of the IFN type I signature in individuals with primary RP and EaSSc along with patients with definite SSc. We then further investigated the presence of IFN type I signature in monocytes from two independent cohorts of patients with lcSSc and dcSSc, focusing on the relationship between IFN type I and other important parameters of SSc pathogenesis such as BAFF expression and collagen synthesis.

    Patients and methods

    Patient collection

    A two-stage study was conducted; as a first step, whole-blood analysis was conducted on HCs and patients with SSc at different disease stages including patients with EaSSc,2 patients with definite SSc without cutaneous fibrotic features and fibrotic SSc subjects; as a second step, monocytes isolated from a different cohort were used from HCs and patients with SSc with overt skin fibrosis.

    For whole-blood analysis subjects were enrolled at the Referral Center for Systemic Autoimmune Diseases, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy. Overall, 12 subjects with primary RP, 19 patients with EaSSc following the LeRoy and Medsger criteria2 and 38 patients with definite SSc according to the ACR/EULAR 2013 classification criteria,5 were included. Patients with definite SSc were further subdivided based on the extent of skin involvement6 into lcSSc (n=21), dcSSc (n=10) and non-cutaneous SSc (ncSSc) (n=7) subsets. Thirty age-matched and sex-matched HCs were also included; characteristics of patients and controls are summarised in table 1.

    View this table:
    Table 1

    Clinical and demographic characteristics of the patients included for whole-blood analysis

    For monocyte cell analysis, 58 patients with definite SSc with fibrotic skin features were considered. Of those, 28 patients with SSc referred to the Department of Rheumatology, Radboud University Nijmegen Medical Center, the Netherlands and 30 patients with SSc to the Department of Immunology, Erasmus Medical Center, Rotterdam, the Netherlands. As above, these patients were stratified as lcSSc (n=42) and dcSSc (n=16).6

    The presence of SSc-specific autoantibodies, namely antitopoisomerase I (ATA), anticentromere (ACA) and anti-RNA polymerase III (RNAP), was tested according to local laboratory standards. None of the patients had chronic hepatitis C infection or overlap syndromes with other autoimmune diseases that may influence IFN signature. Pulmonary fibrosis was defined as the presence of lung fibrosis on high-resolution CT scan (at least 5% of the whole parenchyma) combined with a restrictive pulmonary function pattern (forced vital capacity or diffusing capacity for carbon monoxide <80% of the predicted). Pulmonary artery hypertension was diagnosed by right heart catheterisation and considered present when the mean pulmonary artery pressure was greater than 25 mm Hg at rest in the presence of a normal wedge pressure.

    As a comparator group, 27 HCs were also included. Characteristics of patients and controls that underwent monocyte cells analysis are summarised in table 2.

    View this table:
    Table 2

    Clinical and demographic characteristics of the patients included for monocyte cell analysis

    Blood samples were obtained with informed consent.

    Whole blood collection

    Blood was collected in PaxGene tubes (PreAnalytix, Hombrechtikon, Switzerland) according to manufacturer's protocol and stored at −80°C. Total RNA was purified according to manufacturer's instructions using the RNA blood extraction kit (PreAnalytix, Hombrechtikon, Switzerland).

    Blood collection and isolation of monocytes

    Blood was collected in clotting tubes for serum preparation (stored at −80°C) and in sodium-heparin tubes for peripheral blood mononuclear cell (PBMC) preparation as described in detail elsewhere.20 CD14 positive monocytes were isolated from frozen PBMCs by magnetic cell sorting system (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer's recommendations. The purity of monocytes was >90% (determined by morphological screening after trypan blue staining and fluorescence-activated cell sorting (FACS)). As reported elsewhere positive immune cells did not influence gene expression profiles.21 Total RNA was isolated from purified monocytes using RNAeasy columns according to the manufacturer's instructions (Qiagen, USA) and as previously described.22

    Real-time quantitative PCR

    The expression levels of 11 IFN type I inducible genes (IFI27, IFI44L, IFIT3, IFITM1, SERPING1, IFIT1, IFIT2, LY6E, IFI44, XAF3 and MXA) was assessed.18 These genes were previously selected from microarray analysis of monocytes of pSS.18

    RNA was reverse-transcribed to cDNA using a high-capacity cDNA reverse transcription kit and real-time quantitative PCR analysis was performed using predesigned primer/probe sets (Applied Biosystems, Foster City, California, USA). For calculation of relative expression, all samples were normalised against expression of the household gene ABL (Abelson murine leukaemia viral oncogene homologue 1).23 Fold change values were determined from normalised CT values using 2¯ΔΔCT method (User Bulletin, Applied Biosystems, Foster City, California).

    Radioimmunoassay for quantitative N-terminal propeptide III

    For quantitative assessment of intact N-terminal propeptide of type III procollagen (PIIINP), a radioimmunoassay kit was used according to manufacturer's protocol (UniQ, Orion Diagnostica, Espoo, Finland); frozen sera (stored at −80°C), collected at the time of patient inclusion were analysed. Measurement range: 1.0–50 µg/L, detection limit: ±0.3 µg/L, defined as twice the SD of the zero-binding value.

    Data analysis

    To reduce data complexity, the expression levels of the 11 IFN I genes were submitted to unsupervised principal component analysis (PCA) via the IBM SPSS V.20.0 software. The subset of genes that explained 0.95 of the total variance of the data was assessed and a total score summing the individual IFN gene expression values was obtained and used for further statistical considerations (see below). Given that the expression of IFN type I inducible genes is not normally distributed, log transformations of expression values was performed and IFN scores calculated as described for pSS and SLE.18 ,24 MeanHC and SDHC of each gene in the HC-groups were used to standardise expression levels.

    The distribution of IFN scores in the different groups was compared via analysis of variance (ANOVA) with Tukey's honest significant difference (HSD) post hoc correction after verifying that data were normally distributed via the Shapiro-Wilk test and homogenously distributed around the mean (skewness between −2.5 and 2.5). A cut-off for the monocyte IFN scores to differentiate HCs and patients with SSc was calculated via receiver operating characteristic (ROC) analysis; the optimal cut-off was chosen as the one that maximised the J statistic (Youden index). For whole-blood IFN scores, having verified that these were equally distributed between HCs and patients with primary RP (see Results below), a cut-off was similarly calculated to differentiate between HCs and RP (class=0) and SSc (class=1) subjects. The distribution of clinical variables in the groups of patients was compared by means of Pearson's χ2 test or Fischer's exact test, in case of categorical data, or by means of Student's t test, in case of continuous data; Mann-Whitney U test was used when the normality assumption was not met. A nominal α level equal to 0.05 after correction for multiple tests according to Bonferroni, was used. Correlations among continuous variables were performed via Pearson's r.

    Normally distributed data are presented as mean±SD, median and IQRs are used elsewhere.

    Results

    The IFN type I signature is present at the earliest phases of the disease, even before overt skin fibrosis

    PCA sorted out six genes (IF127, IF144L, IFIT1, IFIT2, IFIT3 and Serping1) that explained >95% of the total variance among the different stages of the disease. The IFN score was significantly increased in patients in every stage of the disease compared with HCs. Figure 1 depicts the distribution of IFN scores according to the different groups along with the results of pairwise comparisons. The mean±SD values for the IFN scores were as follows: HCs, 0.406±4.502; RP, 4.829±10.057; EaSSc, 12.775±9.969; ncSSc, 26.365±13.856; lcSSc, 9.151±10.085; dcSSc, 12.04±9.906. Higher IFN scores were observed when comparing patients with non-fibrotic SSc (EaSSc+ncSSc, n=26) with fibrotic SSc (lcSSc+dcSSc, n=31): 16.43±12.47 vs 10.08±9.95, p=0.037.

    Figure 1
    Figure 1

    Prevalence of IFN type I signature in whole blood in the earliest phases of disease and patients with systemic sclerosis (SSc). Distribution of IFN scores in healthy control (HC), Raynaud's phenomenon (RP), early SSc (EaSSc), non-cutaneous SSc (ncSSc), limited cutaneous SSc (lcSSc) and diffuse cutaneous SSc (dcSSc). Interferon (IFN) type I positive cases are depicted in red. One-way analysis of variance (ANOVA) was performed followed by Tukey's honest significant difference (HSD) to perform pairwise comparisons. *p values <0.05 vs HC; **p values <0.01 vs HC; ***p values <0.001 vs HC.

    After cut point analysis, a positive IFN score defined as values ≥7.09 was able to discriminate between HCs and patients with a sensitivity of 0.667, a specificity of 0.881 and area under receiving operating characteristic (AUROC) of 0.823. The prevalence of subjects with positive IFN scores according to the disease status was: HC, 3.3%; RP, 33.3%; EaSSc, 78.9%; ncSSc, 100%; lcSSc, 42.9%; dcSSc, 70.0% (χ2=41.789, 5° of freedom (df), p=6.2×10−8).

    No correlation was found between IFN scores and the age at onset of RP, disease duration or the age at blood drain. Neither is there a correlation between ATA or RNAP positivity and the IFN score. In patients with non-fibrotic SSc IFN scores were higher in the 17 ACA+ patients compared with the 9 ACA− patients (IFN scores=20.84±12.26 vs 8.11±5.11; p=0.01); no differences were observed as far as patients with fibrotic SSc were concerned (IFN scores=8.85±9.44 vs 10.86±10.45 in 12 ACA+ vs 19 ACA− patients; p=not significant (NS)). Therapy was not relevant in predicting IFN responses and IFN scores were equally distributed between patients receiving (n=12) and patients not receiving (n=57) immunosuppressant (IFN scores=14.34±9.83 vs 10.97±11.97; p=NS).

    Monocytes of patients with fibrotic SSc have higher IFN type I signature than controls

    PCA identified a subset of five genes (IFI44L, IFIT3, IFITM1, IFIT1 and MXA) to explain 96% of the total variance of the 11 IFN type I inducible genes within the fibrotic SSc cohort. In figure 2 the distribution of monocyte IFN scores according to the different groups along with the significant pairwise comparisons is shown. The mean±SD values for the monocytes IFN scores were as follows: HCs, 0±4.088; lcSSc, 4.993±6.583; dcSSc, 7.36±6.291.

    Figure 2
    Figure 2

    Prevalence of interferon (IFN) type I signature in monocytes of patients with systemic sclerosis (SSc). (A) Heat map showing gene expression of five IFN type I inducible genes in monocytes of patients with limited cutaneous SSc (lcSSc, n=42), diffuse cutaneous SSc (dcSSc, n=16) and healthy controls (HCs) (n=27). On the left the HCs are depicted and on the right the patients with SSc are depicted and subdivided into lcSSc and dcSSc. Red colour indicates high gene expression and cases are depicted according to ascending IFN scores. (B) Distribution of IFN scores in patients with lcSSc and dcSSc and HCs. IFN type I positive cases are depicted in red. One-way analysis of variance (ANOVA) was performed followed by Tukey's honest significant difference (HSD) to perform pairwise comparisons. ***p values <0.001.

    After cut point analysis, a positive IFN score defined as values ≥4.124 was able to discriminate between patients and controls with a sensitivity of 0.621 and a specificity of 0.852 (AUROC 0.76). The prevalence of subjects with positive IFN scores according to the disease status was: HC, 14.8%; lcSSc, 59.5%; dcSSc, 68.8% (χ2=16.91, 5 df, p=2.1×10−4). Overall the experiments conducted on patients with fibrosis confirm at the cellular level the results observed in whole blood, where IFN type I genes are overexpressed in patients with lcSSc and dcSSc compared with HCs.

    No significant differences were observed between patients with lcSSc and dcSSc or when autoantibodies or the other clinical parameters were taken into account. Remarkably, all patients positive for anti-RNAP antibodies (n=4) had a positive IFN score, yet the number of RNAP positive patients was too low to draw any relevant conclusions. Therapy did not influence IFN signature and IFN scores were equally distributed between patients receiving (n=17) and not receiving (n=41) immunosuppressant (IFN scores=6.62±7.65 vs 5.24±6.07; p=NS).

    IFN type I signature is positively correlated with monocyte BAFF mRNA, PIIINP serum levels

    BAFF mRNA levels positively correlated with monocyte IFN scores (Pearson's r=0.601, p=1.2×10−9), figure 3A. Accordingly, mRNA BAFF levels were higher in IFN type I signature-positive (n=40) compared with signature-negative subjects (n=45) (19.7±5.2 vs 15.205±3.95, p=2.1×10−5), figure 3B. BAFF mRNA levels were found to be higher in patients with dcSSc compared with controls (20.022±5.7 vs 15.802±3.784, p=0.022, Tukey's HSD), while no differences were found between dcSSc and lcSSc or HC and lcSSc (mean mRNA BAFF levels in lcSSc=17.265±5.255).

    Figure 3
    Figure 3

    Interferon (IFN) type I signature is positively correlated with B cell activating factor (BAFF) mRNA and N-terminal propeptide of type III procollagen (PIIINP) serum levels and faster disease development. (A) BAFF mRNA expression in healthy controls (HCs) (n=27), patients with limited cutaneous SSc (n=42) and diffuse cutaneous SSc (n=16). (B) BAFF mRNA expression in IFN type I signature-positive (n=40) and signature-negative subjects (n=45). (C) Scatterplot of IFN scores vs serum PIIINP; PIIINP is reported in log-scale due to dispersion of data (D) PIIINP (μg/L) in serum from subjects positive (n=14) and negative (n=28) for IFN type I signature. IFN type I positive cases are depicted in red. Independent t test was used to compare means in (A and B) where horizontal lines represent means. Mann-Whitney U test was used in (C and D) where horizontal lines represent medians. ***p values <0.001. SSc, systemic sclerosis.

    We next investigated whether an indicator of de novo collagen type III synthesis, namely PIIINP, is increased in subjects positive for the IFN type I signature. PIIINP levels positively correlated with IFN scores (Spearman's r=0.573, p<0.0001), figure 3C. Subjects with positive IFN scores had higher PIIINP levels compared with IFN-negative ones (median=6.00 (IQR, 5.40–8.90) vs median=3.90 (IQR, 3.25–4.70), p=0.0004), figure 3D. We then found increased PIIINP levels in patients with SSc compared with HC (median=5.80 (IQR, 4.10–6.93) vs median=3.70 (IQR, 3.20–4.70), p=0.0005), Figure 3D, but no differences between patients with dcSSc and lcSSc (median=5.75 (IQR, 4.28–8.00) vs 5.80 (IQR, 4.03–6.95)). None of the clinical parameters correlated with BAFF mRNA or PIIINP serum levels. PIIINP and BAFF serum levels were independently correlated with IFN scores in a multivariate regression model (PIIINP, p=0.0107; BAFF, p=0.0112); the overall fit of the multivariate model was: r2=0.368 (p=5×10−6).

    Discussion

    In rheumatic disorders one of the main challenges is to identify patients as soon as possible to start treatment and prevent irreversible damage. Here we show for the first time, that an IFN type I signature is present in patients with SSc before overt fibrosis develops and since the earliest phases of the disease (EaSSc). Moreover, we did find that IFN type I signature is associated with high BAFF mRNA expression and high serum PIIINP levels. While IFN signature is a hallmark of the majority of patients, it is noteworthy to observe that patients with non-fibrotic SSc had the highest averages of IFN scores as well the highest prevalence of IFN signature among SSc subjects. This underlines the presence of inflammation and immune modifications which can be suitable for therapeutic targeting before—and thereby preventing—the onset of fibrosis, introducing a paradigm shift in the handling of SSc in its earliest identifiable phase. Prospective studies to assess the development of fibrotic features or of internal organ damage in EaSSc or ncSSc that have increased IFN scores without clinical evidence of fibrosis, may further clarify the predictive capability of IFN type I signature and its role as a biomarker of disease progression. The finding that patients with systemic lupus erythematosus and SSc share a common IFN type I signature25 and the promising results of a phase 1 trial with sifalimumab, an anti-IFNα monoclonal antibody, may offer the promise of adequate therapy in the early phase of disease in a selected subgroup of patients with SSc.

    In this light, the observation that IFNα is able to induce the expression of TLR3 in SSc dermal fibroblasts,26 leading to a self-perpetuating inflammatory loop, might directly link pDC activation, IFN type I and the onset of fibrotic events. In addition, IFNα2 has been reported to induce TLR3-induced production of the profibrotic cytokine interleukin (IL) 6. SSc fibroblasts showed an augmented TLR3 response to IFNα2 compared with HC fibroblasts.26 Our observation that collagen synthesis—as represented by elevated PIIINP serum levels—is increased in IFN type I signature-positive patients with SSc, is in line with these data.

    Next to the direct effect of IFN type I on fibrosis, an indirect effect through upregulated BAFF production is possible. BAFF serum levels correlate with the extent of skin fibrosis in SSc19 and we found elevated BAFF mRNA levels in monocytes of IFN type I signature positive patients with SSc. A recent report suggested BAFF being increased mainly in the early phase of the disease,27 ,28 in line with our findings on the IFN type I signature. No BAFF serum protein levels were assessed since we previously reported a lack of correlation between BAFF monocyte mRNA and BAFF serum protein,18 although monocytes are the major producers of BAFF protein. This might be caused by the fact that only the soluble BAFF protein is measured by commercial BAFF ELISAs and not the membrane bound form. In other autoimmune diseases type IFN induced BAFF is directly linked to disease pathogenesis by, for example, rescuing autoreactive B cells from deletion.29 ,30 We hypothesised that BAFF is correlated with fibrosis through the increase of PIIINP. The clear correlation warrants further research on the meaning of this plausible mechanism.

    In contrast to earlier studies,31 we did not find an association between ATA and IFN type I signature. This might be related to the limited ATA positivity in our study. However, in support of our findings Eloranta et al32 reported that ATA did not correlate with the presence of IFN type I using a functional approach. Similarly, we did not find any correlation between IFN signature and mRSS; albeit disappointing and not directly comparable, these results are in line with York et al12 who showed that the expression of another IFN type I inducible gene Siglec-1, does not correlate with the mRSS in dcSSc.12 We further pursued the question if the IFN type I signature is more frequent in dcSSc, which is denied by our data in line with earlier studies.13 ,33 Interestingly the signature is not confined to the early phase of the disease, but remains present in later stages as recently shown with an IFN type I induced chemokine profile.33 In fact, there is no clear correlation with any of the investigated clinical parameters leaving the question on what further defines IFN type I positive patients unresolved. SSc is a heterogeneous disease and the need to understand the mechanisms that characterise the first phases of the disease and/or its progression is often unmet. In the present work we show that prototypical immunological mechanisms are distinguishable from the very beginning of the disease, when SSc is not full blown yet, and we hypothesise that these mechanisms may later influence the turnover of collagen and the appraisal of skin fibrosis. At the moment it is not possible to tell whether the IFN type I signature may represent a marker of disease progression and may allow the identification of a subgroup of patients at greater risk for an unfavourable evolution. Nonetheless, the so far neglected possibility of identifying those patients and the possibility of providing an early therapeutic intervention, warrant further studies in this field.

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    Footnotes

    • Handling editor Tore K Kvien

    • ZB, LvB, MAV and TR contributed equally.

    • Twitter Follow Lenny Bon at @LennyGeurts

    • Contributors Set-up of methodology; ZB, LvB, MC, LB, MAV and TR. Gathering of data; ZB, LvB, MC, CGvH-M, MCV, HK, WvdB, VAD, PLVD, AS, NIM, SG, WAD, LB, MAV and TR. Analysis of data; ZB, LvB, MC, LB, MAV and TR. Critical reading of the manuscript; ZB, LvB, MC, CGvH-M, MCV, HK, WvdB, VAD, PLVD, AS, NIM, SG, WAD, LB, MAV and TR.

    • Funding TR was funded by the VIDI laureaat (NWO, Netherlands institute for Science), ERC starting grant (EU) and Dutch arthritis foundation.

    • Competing interests None declared.

    • Ethics approval Local ethical committees of all participating institutions.

    • Provenance and peer review Not commissioned; externally peer reviewed.