Cross-Disease Innate Gene Signature: Emerging Diversity and Abundance in RA Comparing to SLE and Ssc
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Hindawi Journal of Immunology Research Volume 2019, Article ID 3575803, 10 pages https://doi.org/10.1155/2019/3575803 Research Article Cross-Disease Innate Gene Signature: Emerging Diversity and Abundance in RA Comparing to SLE and SSc Anna Petrackova,1 Pavel Horak,2 Martin Radvansky,3 Martina Skacelova,2 Regina Fillerova,1 Milos Kudelka,3 Andrea Smrzova,2 Frantisek Mrazek,1 and Eva Kriegova 1 1Department of Immunology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital, Olomouc, Czech Republic 2Department of Internal Medicine III-Nephrology, Rheumatology and Endocrinology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital, Olomouc, Czech Republic 3Faculty of Electrical Engineering and Computer Science, Department of Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic Correspondence should be addressed to Eva Kriegova; [email protected] Received 3 April 2019; Accepted 12 June 2019; Published 16 July 2019 Academic Editor: Darius Widera Copyright © 2019 Anna Petrackova et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Overactivation of the innate immune system together with the impaired downstream pathway of type I interferon-responding genes is a hallmark of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc). To date, limited data on the cross-disease innate gene signature exists among those diseases. We compared therefore an innate gene signature of Toll-like receptors (TLRs), seven key members of the interleukin (IL)1/IL1R family, and CXCL8/IL8 in peripheral blood mononuclear cells from well-defined patients with active stages of RA (n =36, DAS28 ≥ 3 2), SLE (n =28, SLEDAI > 6), and SSc (n =22, revised EUSTAR index > 2 25). Emerging diversity and abundance of the innate signature in RA patients were detected: RA was characterized by the upregulation of TLR3, TLR5, IL1RAP/IL1R3, IL18R1, and SIGIRR/IL1R8 when compared to SSc (Pcorr <002) and of TLR2, TLR5, and SIGIRR/IL1R8 when compared to SLE (Pcorr <002). Applying the association rule analysis, six rules (combinations and expression of genes describing disease) were identified for RA (most frequently included high TLR3 and/or IL1RAP/IL1R3) and three rules for SLE (low IL1RN and IL18R1) and SSc (low TLR5 and IL18R1). This first cross-disease study identified emerging heterogeneity in the innate signature of RA patients with many upregulated innate genes compared to that of SLE and SSc. 1. Introduction Although the emerging role of the innate immunity in the pathogenesis of RA, SLE, and SSc has been demonstrated, Rheumatoid arthritis (RA), systemic lupus erythematosus there is no data on the cross-disease innate gene signature (SLE), and systemic sclerosis (SSc) are systemic autoimmune as well as its heterogeneity among those diseases yet. Numer- diseases characterized by overactivation of the innate ous studies on individual innate immunity members in RA, immune system together with impaired downstream path- SLE, and SSc showed the crucial role of Toll-like receptors way of type I interferon- (IFN-) responding genes (IFN sig- (TLRs) and IL1 family [5, 6]. Notable examples of common nature). Nevertheless, a certain heterogeneity in the IFN innate pathways are (i) the involvement of the adapter pro- signature among those diseases has been recognized, and tein MyD88 which is required for signal transduction by some patients even lack its presence [1–4]. TLRs and receptors of the IL1 family, (ii) the activation of 2 Journal of Immunology Research Table 1: Demographic and clinical characteristics of enrolled patients. RA (n =36) SLE (n =28) SSc (n =22) Female/male 26/10 24/4 15/7 Age (years) mean (min-max) 57.5 (39-80) 40.1 (19-67) 58.0 (38-77) Duration of the disease (years) mean (min-max) 18.1 (9-50) 10.0 (1-20) 5.4 (0-21) Medications (% (n)) Steroids 89 (32) 82 (23) 96 (21) NSAIDs 78 (28) 14 (4) 0 (0) Methotrexate 83 (30) 14 (4) 9 (2) ∗ Other DMARDs 36 (13) 100 (28) 73 (16) Biologics 39 (14) 0 (0) 0 (0) Relative white blood count (%) Lymphocytes (mean (95% CI)) 24.9 (20.5-29.3) 22.9 (18.5-27.3) 21.4 (17.5-25.4) Neutrophils (mean (95% CI)) 62.9 (57.9-67.9) 67.1 (61.6-72.6) 67.3 (62.5-72.2) Monocytes (mean (95% CI)) 8.9 (7.9-9.9) 8.5 (7.1-9.9) 9.2 (7.9-10.4) NSAIDs: nonsteroidal anti-inflammatory drugs; DMARDs: disease-modifying antirheumatic drugs; CI: confidence interval. ∗Other DMARDs taken were hydroxychloroquine (RA/SLE/SSc; n = 3/26/0), leflunomide (8/0/0), sulfasalazine (2/0/0), azathioprine (0/8/12), mycophenolate mofetil (0/6/0), cyclophosphamide (0/3/3), and cyclosporine (0/1/1). the type I IFN, and (iii) the presence of endogenous TLR criteria for SSc, respectively [15]. To exclude heterogeneity ligands [7]. Besides shared innate pathways, disease-specific due to the activity and inactivity of the diseases, only cases molecular and cellular mechanisms exist. In SLE, recent evi- with active phenotypes of the disease classified according to dence has suggested a close relationship between the endoso- common activity scores (Disease Activity Score in 28 joints mal TLR activation and the disease onset [8, 9] with an (DAS28), SLE Disease Activity Index (SLEDAI), and revised essential role of endosomal TLRs in the generation of anti- European Scleroderma Trials and Research group (EUSTAR) nuclear antibodies and type I IFNs [10]. In RA, abundant acti- index) were included: RA (n =36, DAS28 ≥ 3 2), SLE (n =28, vation of individual members of TLR and IL1 families was SLEDAI > 6), and SSc (n =22, revised EUSTAR index > 2 25). already evidenced with a proposed role for exogenous TLR The demographic and clinical features, used medication, ligands in the disease onset (i.e., Proteus infection of urinary duration of disease, and relative white blood count are tract, Epstein-Barr virus, and parvovirus B19) and for endog- described in Table 1. Distribution of lymphocyte, neutrophil, enous ligands in self-sustaining of the inflammatory loop and monocyte counts did not differ between studied patient’s [5, 11]. In SSc, signaling via TLR is increasingly recognized groups (P >005). The healthy control cohort consisted of 77 as a key player driving the persistent fibrotic response and is subjects (mean age 51 yrs, min-max 24-90 yrs, female/male linked to the activity of TGF-β; however, the pathological role 58/19) out of which were formed three age-/gender-matched of TLRs and their ligands in SSc still remains unclear [12]. groups for each disease: 63 controls for RA (mean age 56 yrs, We undertook this study to elucidate the underlying dif- min-max 41-90 yrs, female/male 45/18), 33 controls for SLE ferences in the innate immunity signature across three major (40, 24-50, 27/6, respectively), and 48 controls for SSc (58, autoimmune disorders using multivariate analysis. This first 48-90, 34/14, respectively). In all healthy subjects, presence cross-disease analysis of the innate gene expression signature of inflammatory autoimmune diseases in first or second of 10 TLRs, 7 key members of the IL1/IL1R family, and degree relatives, recent vaccination, infection, and usage of interleukin 8 (CXCL8) in peripheral blood mononuclear immunosuppressive drugs were excluded by questionnaire. cells (PBMC) from patients with active SLE, RA, and SSc The patients and control subjects provided written revealed emerging diversity and abundance in RA compared informed consent about the usage of peripheral blood for to SLE and SSc. Our study contributes to further understand- the purpose of this study, which was approved by the ing of the innate signature underlying the immunopathology ethics committee of the University Hospital and Palacký of major autoimmune diseases, with special emphases to University Olomouc. discriminate shared and disease-specific expression patterns. 2.2. Sample Processing and Real-Time Reverse Transcription- 2. Materials and Methods Polymerase Chain Reaction (qRT-PCR). The PBMC were iso- lated from the peripheral blood collected in K3EDTA tubes 2.1. Study Subjects. The study cohort consisted of 86 Cauca- by Ficoll density gradient centrifugation (Sigma-Aldrich, sian patients with autoimmune diseases from a single rheuma- Germany) and stored in TRI Reagent (Sigma-Aldrich, Ger- ° tology center in Olomouc, Moravia region of Czech Republic. many) at −80 C until analysis. Total RNA was extracted All enrolled RA/SLE/SSc patients met the 2010 ACR/EULAR using a Direct-zol RNA kit (Zymo Research, USA) according classification criteria for RA [13], the ACR classification cri- to the manufacturer’s recommendations. After reverse tran- teria for SLE [14], and the 2013 ACR/EULAR classification scription with a Transcriptor First Strand cDNA Synthesis Journal of Immunology Research 3 TLR5 SIGIRR TLR2 0.25 0.4 0.7 P = 0.02 P = 0.02 P = 0.009 corr 0.3 corr 0.20 corr 0.6 0.2 0.15 0.5 0.15 0.08 0.4 0.10 0.06 0.3 0.04 0.2 0.05 mRNA relative expression relative mRNA mRNA relative expression relative mRNA 0.02 expression relative mRNA 0.1 0.00 0.0 0.00 RA SLE RA SLE RA SLE (a) IL1RAP TLR5 IL18R1 0.4 P = 3 × 10-6 P = 0.0001 P = 0.0001 0.10 corr corr corr 0.2 0.03 0.05 0.10 0.020 0.08 0.02 0.015 0.06 0.010 0.04 0.01 mRNA relative expression relative mRNA 0.005 expression relative mRNA 0.02 expression relative mRNA 0.000 0.00 0.00 RA SSc RA SSc RA SSc SIGIRR TLR3 0.020 P = 0.003 0.7 corr Pcorr = 0.007 0.6 0.016 0.5 0.012 0.4 0.3 0.008 0.2 0.004 mRNA relative expression relative mRNA 0.1 expression relative mRNA 0.0 0.000 RA SSc RA SSc (b) IL1R1 0.03 P corr = 0.005 0.012 0.009 0.006 0.003 mRNA relative expression relative mRNA 0.000 SSc SLE (c) Figure 1: Relative mRNA expression levels of genes differentially expressed in (a) RA vs.