Abstract

Objective

   To investigate the gene expression profile in patients with Sjögren's
   syndrome that is characterized by different clinical phenotypes.

Methods

   RNA from peripheral blood mononuclear cells was purified in 8 patients
   with glandular features (GFs) and widespread pain (WP) and 11 with
   extraglandular manifestations (EGMs) and then was analyzed by
   hybridization on a human gene chip exploring more than 40,000 human
   genes. Differentially expressed genes (DEGs) in the two subgroups (ie,
   those with false discovery rate–corrected P values ≤ 0.01) with respect
   to 20 healthy controls have been submitted to functional classification
   using a Gene Ontology database and were mapped to define the networks
   of protein to protein interactions (PPIs).

Results

   The enriched pathway analyses of DEGs and of the highly interconnected
   modules identified in the PPI networks showed that the pathological
   processes characterizing the two subgroups were substantially
   different. The predominant pathways in patients with EGMs are related
   to T‐ and B‐cell activation, Toll‐like receptor, interferon signaling,
   and apoptosis. Conversely, pathological processes related to pain
   transmission and modulation are preferentially operative in patients
   with GFs and WP. These data suggest that a neuroinflammatory pathway
   driven by cytokines and chemokines may play a central role in
   triggering WP features in this phenotype of patients.

Conclusion

   The present study supports the hypothesis that different biological
   pathways are operative in patients with primary Sjögren's syndrome with
   different clinical phenotypes. A better knowledge of these specific
   processes might help in tailoring more effective target therapies.

Introduction

   Primary Sjögren's syndrome (pSS) is a chronic autoimmune disorder whose
   typical manifestations are oral and ocular dryness. However, the
   clinical spectrum of pSS may vary from signs and symptoms consequent to
   the isolated involvement of the salivary and lachrymal glands, or
   sometimes of the other exocrine glands, up to manifestations related to
   the involvement of different organs or systems [38]1. Extraglandular
   manifestations (EGMs) are present in around 60% of patients and are
   usually distinguished in two types. The first one is characterized by
   lymphocytic infiltrates around the epithelial tissues of parenchymal
   organs, such as the lungs, kidneys, and liver. The second type is
   marked by autoantibodies or immune complex deposition in small vessels
   that may lead to the development of porpora, glomerulonephritis and
   peripheral neuropathy [39]1.

   The fact that pSS can present such a wide variability of clinical
   features suggests that different pathogenetic mechanisms may be present
   in different patients. This hypothesis is supported by the finding that
   a) the number and organization of mononuclear cells as well as T‐ and
   B‐cell ratio in the infiltrates of target tissues, b) gammaglobulins
   and antibody levels in the serum, and c) cytokine expression in both
   peripheral blood and glands can be different in patients with the
   disease limited to exocrine gland aggression or characterized by EGMs
   [40]2. Even the impact of fatigue, which represents one of the major
   contributors to the impaired quality of life in patients with pSS, is
   variable in different subsets of patients [41]3. Severe fatigue has
   been described in approximately one‐third of patients and found to be
   closely associated with widespread pain (WP), anxiety, depression, and
   impaired sleep patterns [42]3. Unexpectedly, the levels of some
   proinflammatory cytokines that have been found to characterize this
   disease are inversely related to patient‐reported levels of fatigue
   [43]4. In addition, some data suggest that WP, which is closely related
   to fatigue, is predominant in patients with a disease limited to
   glandular features (GFs) [44]5.

   Because the presence of EGMs, hypergammaglobulinemia, cryoglobulinemia,
   hypocomplementemia, lymphopenia, and the germinal center–like
   organization of mononuclear infiltrates in the salivary glands are
   commonly ascribed to B‐cell hyperactivity and are also predictors for
   the development of lymphoproliferation [45]6, targeting B cells has
   been postulated to be an effective therapeutic approach in patients
   with pSS. Therefore, treatment with rituximab, an anti‐CD20 B‐cell
   surface molecule inducing B‐cell depletion in peripheral blood [46]7,
   has been tested in patients with pSS. Although preliminary open label
   and controlled pilot trials on rituximab therapy for pSS have shown
   improvement in selected subjective and objective parameters, two large
   randomized control trials [47]8, [48]9 failed to reach the primary end
   points that were mainly represented by improvement of fatigue and sicca
   complaints. In contrast with these poor results, it has been clearly
   shown that rituximab therapy is effective in reducing the level of some
   serological markers of the disease, such as immunoglobulin M–rheumatoid
   factor, gammaglobulins, and B‐cell number also in glandular infiltrates
   [49]10. Different hypotheses have been raised to explain these negative
   results. However, it is likely that rituximab ineffectiveness could be
   mainly ascribed to the differences in the biological pathways that are
   operative in different subsets of patients with pSS [50]10. Thus, a
   better knowledge of the genotypic patterns driving the phenotypic
   differentiation of patients may lead to identify the target therapy
   with the highest probability of success in improving the clinical
   condition and the quality of life of patients with pSS.

   With the above considerations in mind, we planned the present study to
   specifically investigate the gene expression profile in patients with
   pSS with different phenotypical characteristics. To do so, we decided
   to select patients situated at the extremities of the clinical spectrum
   of the disease (ie, patients with disease limited to the involvement of
   salivary and lachrymal glands and only complaining of sicca symptoms
   and WP) and, on the opposite side, patients who, together with sicca
   manifestations, presented with systemic EGMs, such as small joint
   arthritis, vasculitis, lung or kidney involvement, peripheral
   neuropathy, and lymphoproliferative lesions.

Patients and Methods

Patient selection

   Patients classified as having pSS according with the American College
   of Rheumatology (ACR)‐European League against Rheumatism (EULAR)
   criteria were enrolled in this study [51]11. We selected patients whose
   disease was limited to glandular involvement and therefore who only
   complain of GFs and WP as well as—on the other extreme—patients who
   were characterized by the presence of a wide spectrum of EGMs. An
   accurate workup was completed in all of the patients to accurately
   define their clinical and serological profile. Namely, each EGM was
   defined according to the European SS Disease Activity Index (ESSDAI)
   nomenclature [52]12, and the cumulative ESSDAI score for systemic
   activity was calculated. Furthermore, the presence of pain and fatigue
   was scored using the Likert scale adopted for these domains in the
   European SS Patient Reported Index (ESSPRI) [53]13. Furthermore, we
   classified patients as having WP according to ACR definition. Following
   these criteria, WP is defined as the presence of pain in at least three
   sites in the left and right sides of the body, above and below the
   waist, and in the axial skeleton, present for at least 3 months [54]14.
   For each enrolled patient, a clinical examination was performed to
   check the presence and number of fibromyalgia‐associated tender points
   [55]14.

Gene expression analysis

   An analysis of gene expression profiles was performed in pSS patients
   with only GFs as well as in pSS patients with EGMs and in 20 age‐ and
   sex‐matched healthy donors.

   Blood samples were collected in Vacutainer K2EDTA tubes, and peripheral
   blood mononuclear cells (PBMCs) were isolated upon stratification on
   Lympholyte, a miRNeasy mini kit, following the manufacturer's
   instructions (Qiagen).

   cDNA preparation, sample hybridization, and scanning were entrusted to
   the Cogentech Affymetrix microarray unit (Campus IFOM IEO), and the
   whole procedure was performed as described in the Affymetrix protocols
   (Affymetrix).

   Sample hybridization was performed on Human Clariom D gene chip (Thermo
   Fisher Scientific), which interrogates more than 40 000 human genes
   that are approximately represented by more than 120 000 probe sets.

   Signal intensities of each probe set were analyzed using the
   Transcriptome Analysis Console (TAC) 4.0 software (Applied Biosystem).
   Background subtraction, normalization, and log‐transformation of signal
   intensities were performed with The Signal Space Transformation–Robust
   Multi‐Array Average algorithm.

   The relative gene expression levels of each transcript were validated
   using the relative one‐way analysis of variance (ANOVA) (P ≤ 0.01) with
   multiple testing correction.

   Transcripts that displayed an expression level at least 1.5‐fold
   different in the test sample versus control sample (P ≤ 0.01) were
   submitted to functional classification using the Gene Ontology (GO)
   annotations and pathways, and biological process enrichments in
   differentially expressed genes (DEGs) were analyzed by using Panther
   expression analysis tools ([56]http://pantherdb.org/) [57]1. Calculated
   by the binomial statistical test, P values ≤ 0.05 were considered as
   significant enrichment [58]15.

Validation of the microarray results by real‐time polymerase chain reaction

   The significantly different expression of genes observed in microarray
   assay was validated by testing some selected genes with real‐time
   polymerase chain reaction (RT‐PCR) in patients and healthy controls.
   The method adopted for this validation procedure is detailed in the
   Supplementary [59]Methods section [60]16, [61]17, [62]18.

Protein‐protein interaction, network construction, and network clustering

   DEGs in test samples versus healthy controls that met the
   above‐mentioned criteria were also mapped to the Search Tool for the
   Retrieval of Interacting Genes (STRING) database to analyze
   protein‐protein interaction (PPI) pairs between the protein products of
   modulated genes, which were validated by experimental studies [63]19. A
   PPI network was designed, and a score of ≥0.7 was selected for each PPI
   pair.

   The STRING database (version 10.5; [64]http://string-db.org/) covers
   experimental interactions in more than 1000 fully sequenced organisms.

   High‐flow areas of the network (modules), characterized by the presence
   of highly connected proteins, were identified by a modular analysis
   employing the CFinder software tool, based on the Clique Percolation
   Method [65]20. The topological analysis of the built networks was
   performed with the Cytoscape software [66]21.

Ethical statement

   The protocol for the present study was prepared in accordance with the
   guidelines of the 1975 Declaration of Helsinki and the recommendations
   of local ethical committee of University of Verona for this kind of
   study. Written, informed consent was obtained from all the enrolled
   patients and controls.

Results

Patient population

   Eight patients with disease expression limited to GFs and 11 patients
   characterized by EGMs constituted the two selected subgroups of
   patients.

   The main demographic, clinical, and histologic findings of the patients
   are summarized in Table [67]1.

Table 1.

   Main demographic, clinical, serological, and histologic features of
   patients with primary primary Sjögren's syndrome enrolled in the study.
   Patients 1, 2, 4, 8, 12, 13, 15, and 16 were those randomly selected
   from the two phenotypically different groups for the analysis of gene
   expression profile
   Patient Number Gender Age (y) Disease Duration (y) Sicca Symptoms
   WP[68]^a ESSDAI Count ESSPRI Fatigue Score ESSPRI Pain Score Specific
   EGMs Serological Abnormalities Focus Score[69]^b
   1 M 75 3 no no 55 8 2 VP, IP, PN, My, LE ReC, Cryo, ANA, Ro, La 5
   2 F 53 6 yes no 19 6 3 AI, VP, PN ReC, ANA, Ro 3
   3 F 50 4 yes no 11 5 2 AI, VP, LP, LE ReC, ANA, Ro, La 1
   4 F 59 7 yes no 17 7 2 VP, My ReC, ANA, Ro, La 3
   5 F 52 1 yes no 17 3 4 AI, VP, LP ReC, Cryo, ANA, Ro, La 1
   6 F 53 1 yes no 29 10 2 AI, VP, ReC, ANA, Ro 1
   7 F 80 15 yes no 7 7 3 AI, VP ReC, ANA, Ro, La 4
   8 F 49 3 yes no 13 4 0 AI, VP ReC, Cryo, ANA, Ro, La 1
   9 F 31 1 yes no 7 2 0 AI, LP ANA 1
   10 F 76 11 yes no 47 5 2 AI, VP, IP, LE ReC, Cryo, ANA, Ro, La 4
   11 F 55 4 yes no 13 6 4 AI, VP, LP ReC, ANA, Ro, La 3
   12 F 56 9 yes yes 0 6 5 None ANA, Ro, La 3
   13 F 61 10 yes yes 1 4 6 LP (transient) Ro 2
   14 F 70 11 yes yes 0 3 4 None ANA, Ro 3
   15 F 76 13 yes yes 0 6 8 None ANA 2
   16 F 71 12 yes yes 0 6 8 None ANA, Ro, La 4
   17 F 58 2 yes yes 0 5 7 None ANA 1
   18 F 45 1 yes yes 0 3 8 None ANA, Ro 1
   19 F 46 8 yes yes 0 10 10 None Ana, Ro 2
   [70]Open in a new tab

   Abbreviation: ANA, antinuclear antibodies; Cryo, cryoglobulins; EGM,
   extraglandular manifestation; IP, interstitial pneumonia; La, anti‐La
   antibodies; LE, lymph node enlargement; LP, leukopenia; My, myositis;
   PN, peripheral neuropathy; ReC, reduced complement; Ro: anti‐Ro
   antibodies; VP, vasculitic purpura.
   ^a

   Widespread pain
   ^b

   Focus score is the number of infiltrates of at least 50 mononuclear
   cells observed in 4 mm^2 of salivary glandular tissue from lip biopsy.
   The tender point count in patients with WP ranged from 8 to 14 out of
   the 18 classical points considered in the classification criteria for
   fibromyalgia [71]14.

   For the gene expression analysis, RNAs isolated from the PBMCs of four
   randomly selected patients from each subgroup (patients 1, 2, 4, and 8;
   and 12, 13, 15, and 16) were obtained. RNAs from the remaining patients
   of the two subgroups were used for the validation analysis using
   RT‐PCR.

Gene expression analysis

   In comparison with 20 healthy controls (volunteers), the DEGs were 2012
   and 1679 in patients with GFs and EGMs, respectively. The complete
   lists of DEGs in the two subgroups, with the statistical difference
   compared with healthy controls and identification codes, are reported
   in Supplementary Tables [72]1 and [73]2.

   The significantly different expression of some genes observed in
   microarray assay was confirmed using the RT‐PCR method. The results of
   this validation test are reported in Supplementary Figure [74]1.

   Selectively modulated genes in the two groups were 1021 and 573 in
   patients with GFs and EGMs, respectively. The lists of these genes are
   reported in Supplementary Table [75]3.

   When the DEGs in the two subtypes underwent GO functional
   classification, it was evident that in both groups the large majority
   of DEGs belonged to the same biological processes. The modulated genes
   can be grouped into five main pathological processes: those related to
   apoptosis, immune and inflammatory response, Toll‐like receptor (TLR)
   signaling and type‐I interferon (IFN) signaling. Some less substantial
   differences between the subgroups were present in the relative
   proportions of genes referring to the main functional categories
   (Figure [76]1). Supplementary Tables [77]4 and [78]5 show a selection
   of genes included in the main biological processes in the two groups.

Figure 1.

   Figure 1
   [79]Open in a new tab

   Biological processes activated in the two subgroups of patients with
   primary Sjögren's syndrome, according to Gene Ontology functional
   classifications of differentially expressed genes. The proportions of
   genes belonging to each biological process are represented in the pie
   charts and slightly differ in the two subgroups.

   However, looking at the genes selectively modulated in the two
   subgroups and at their GO definition, we found that a limited series of
   genes involved in the sensory perception pathway were exclusively
   modulated in the group of patients with only GFs. Table [80]2 shows a
   selection of the above‐mentioned genes. Notably, the most strongly
   overexpressed gene in this list was that which codifies for IFN‐γ.

Table 2.

   Overexpressed genes in patients with glandular features and widespread
   pain, which are members of the “sensory perception” gene set, according
   to the Gene Ontology definition (GO: 0007600)
   Gene Symbol Gene Descriptors Function[81]^a Fold Change P value
   IFNG Interferon, gamma Proinflammatory cytokine 10.35 0.0009
   TRIM26 Tripartite motif containing 26 Transcription factor 2.38 0.0021
   TRIM25 Tripartite motif containing 25 Transcription factor 2.18 0.0057
   EDN1 Endothelin 1 Inducer of pain perception 3.41 0.009
   PML Promyelocytic leukemia protein Regulator of synapsis strength 2.58
   0.003
   ANPEP Alanyl (membrane) aminopeptidase Inducer of nociceptive pain 9.02
   0.0026
   TNFRSF1A Tumor necrosis factor receptor superfamily, member 1A Receptor
   of proinflammatory cytokine 2.09 0.0088
   P2RY1 Purinergic receptor P2Y, G‐protein coupled, 1 Receptor involved
   in synaptic transmission 2.1 0.0079
   P2RX4 Purinergic receptor P2X, 4 Receptor involved in synaptic
   transmission 3.52 <0.0001
   ADRB1 Adrenoceptor beta 1 Receptor involved in perception of pain 1.86
   0.009
   GPR75 G protein–coupled receptor 75 Chemokine receptor component 2.13
   0.0044
   GPR132 G protein–coupled receptor 132 Nociceptive receptor component
   2.87 0.0032
   GPR137B G protein–coupled receptor 137B Sensory receptor component 3.08
   0.0006
   GPR37L1 G protein–coupled receptor 37 like 1 Endothelin receptor
   component 1.98 0.0025
   ADCY5 Adenylate cyclase 5 Nociception inducer (via cAMP) 1.89 0.0027
   GNG5 Guanine nucleotide binding protein (G protein), Chemokine receptor
   component γ5 2.2 0.0018
   RGS16 Regulator of G‐protein signaling 16 Modulator of chemokine
   receptor 2.78 0.0018
   GNG2 Guanine nucleotide binding protein (G protein), Chemokine receptor
   component γ2 2.03 0.005
   LIF Leukemia inhibitory factor Interleukin‐6 family cytokine 2.24
   0.0046
   NFKB1 Nuclear factor of kappa light polypeptide gene enhancer in
   B‐cells 1 Transcription factor 4.84 0.0046
   FOSL1 FOS‐like antigen 1 Postsynaptic stimulation product 3.78 0.0004
   CSNK1E casein kinase 1, epsilon Inducer of neuropathic pain 2.24 0.0062
   GRINA Glutamate receptor, ionotropic, N‐methyl D‐aspartate‐associated
   protein 1 Postsynaptic receptor sensible to glutamate release 2.21
   0.0044
   [82]Open in a new tab
   ^a

   Function that the listed genes may have in the context of sensory
   perception.

   Pathway enrichment analyses showed that almost completely different
   signaling networks were preferentially enriched in patients with GFs
   and WP in comparison with patients with EGMs. In this latter subgroup
   of patients, the B‐cell activation and TLR signaling pathways were
   strongly enriched together with the pathways related to 5
   hydroxytryptamine (5HT)‐4 receptor signaling and angiotensin II (Ang
   II) receptor signaling (Table [83]2). Conversely, the most enriched
   pathways in the subgroup of patients with GFs and WP were those related
   to beta‐adrenergic and Notch signaling, 5HT‐1 receptor, and
   corticotropin releasing factor (CRF) receptor signaling (Table [84]3).

Table 3.

   Enriched pathways in the two subgroups of patients obtained by Panther
   analysis
   Pathways enriched in patients with EGMs P Value
   B‐cell activation ([85]P00010) 1.49E‐02
   Toll receptor signaling pathway ([86]P00054) 2.67E‐02
   5HT‐4 type receptor mediated signaling pathway ([87]P04376) 3.40E‐02
   Angiotensin II‐stimulated signaling through G proteins and
   beta‐arrestin ([88]P05911) 4.54E‐02
 Pathways enriched in patients with GFs and WP                          P Value
 Beta adrenergic receptor signaling pathway ([89]P04377)                1.42E‐02
 Notch signaling pathway ([90]P00045)                                   3.70E‐02
 5HT1 type receptor mediated signaling pathway ([91]P04373)             4.67E‐02
 Corticotropin releasing factor receptor signaling pathway ([92]P04380)
   4.89E‐02
   [93]Open in a new tab

   Abbreviation: EGM, extraglandular manifestation; GF, glandular feature;
   WP, widespread pain.

   PPI analysis of DEGs allowed the identification of two networks that
   represented all the functional interactions among modulated genes in
   the two subgroups of patients. Also, with this kind of analysis,
   relevant differences could be observed in the number of genes,
   composition, density of edges (Figure [94]2A and B) in the PPI network
   of DEGs in patients with GFs and WP in comparison with that derived in
   patients with EGMs.

Figure 2.

   Figure 2
   [95]Open in a new tab

   Protein‐to‐protein interaction networks of differentially expressed
   genes in patients with primary Sjögren's syndrome characterized by the
   presence of extraglandular manifestations (EGMs) (A) and with disease
   expression limited to glandular features (GFs) and widespread pain (WP)
   (B).

   The network obtained from PPI analysis of DEGs in patients with GFs and
   WP included 585 codifying genes and 2166 pairs of interactions (edges)
   (Figure [96]2A). This PPI network was then submitted to cluster
   analysis to identify the more highly interconnected nodes or modules
   (M) that are more probably involved in determining the typical feature
   characteristics of different subsets of patients. This modular analysis
   showed the presence of 13 modules that were submitted to pathway
   enrichment analysis. In particular, we observed that several genes
   involved in pain perception and in nociceptive signal transduction were
   present in M0 and M2 (Figure [97]3A). M0 was characterized by the
   presence of genes codifying for endothelin 1 precursor (EDN1),
   G‐protein subunit γ 2 and 5 (GNG2; GNG5), lysophosphatidic acid
   receptor 2 and 5 (LPAR2; LPAR5), which were also present in M2. In
   addition, genes codifying for C‐C chemokine receptor 5 (CCR5), taste
   type 2 receptor 3 (TAS2R3), and adenylate cyclase 5 (ADCY5) entered in
   the composition of this module. Besides the genes shared with M0, M2
   also included cysteinyl leukotriene receptor 1 (CYSLTR1), P2Y
   purinoreceptor 1 (P2RY1), and G‐coupled receptor 132 (GPR132).

Figure 3.

   Figure 3
   [98]Open in a new tab

   Highly interconnected modules obtained by cluster analysis of the
   protein‐to‐protein interaction networks in patients with glandular
   features and widespread pain (A), and in patients with extraglandular
   manifestations (B). The enrichment analysis of these modules allows
   recognition of the pathways represented in each module (listed in the
   lower part of the figure). For the definition and function of the genes
   present in the modules, see the Results section of the text.

   The enrichment analysis applied to M0 and M2 showed that, among the
   pathways represented in these modules, there are those related to
   G‐proteins, beta adrenergic receptors, 5HT receptors, muscarinic
   receptors, gamma‐aminobutyric acid (GABA) receptor, CRF receptor
   signaling, and to proinflammatory cytokine‐chemokine signaling
   (Figure [99]3A).

   In contrast with M0 and M2, M11 contained genes encoding for
   anaphase‐promoting complex subunit 5 and 16 (ANAPC5; ANAPC16) and for
   histone H2B type 1‐B proteins (HIST1H2‐BB, ‐BJ, and ‐BL),
   CCAT/enhancer‐binding protein beta (CEBPB), and nuclear factor
   NF‐kappa‐B subunit 1 (NFKB1). The analysis for enriched pathways
   demonstrates that these genes are involved in apoptosis and in immune
   response, namely in B‐ and T‐cell activation and TLR signaling
   (Figure [100]3A).

   From the PPI analysis of genes modulated only in the subgroup of
   patients with EGMs, we obtained a PPI network connecting 440 genes
   (Figure [101]2B), and from this network, four hyperconnected modules
   were extracted. The pathway enrichment analysis of the four modules
   showed that no pathways were significantly enriched in M0 and M2,
   whereas in M1 and M3 we observed the enrichment of signaling pathways
   related to apoptosis, T‐ and B‐cell activation, TLR and IFN‐γ
   signaling, as well as co‐stimulatory and proinflammatory cytokine
   signaling (Figure B). The complete list of the genes in the modules
   derived from PPI network analysis in the two subgroups of patients and
   the related enriched pathways are reported in Supplementary Tables
   [102]6 and [103]7.

Discussion

   We report here the results of gene expression analysis carried out in
   two strongly differentiated subsets of patients with pSS: those with
   disease limited to GFs, who also complained of WP, and those who
   presented with a variety of EGMs.

   DEGs were functionally classified and submitted to a pathway enrichment
   analysis to find the most crucial signaling network that could be
   operative in the two subgroups.

   The number and type of DEGs were different in the two subtypes of
   patients. Furthermore, patients with disease limited to GFs had a
   higher number of DEGs. This may indicate that this kind of patient
   could have a wider spectrum of pathological pathways.

   In both subgroups, most of the modulated genes belonged to the same few
   biological processes that are known to be peculiarly activated in pSS
   [104]22. However, only in the GFs group were genes involved in sensory
   and pain perception modulated.

   We then performed a cluster analysis of the PPI networks to detect
   areas with the highest levels of interconnections among modulated genes
   (modules) and their associated pathways, which could be the drivers of
   the most important pathological mechanisms that are operative in the
   two subsets of patients.

   As in the present study, the few previous studies in this field of gene
   expression analysis in pSS patients was performed using PBMCs [105]23,
   [106]24. Although these studies were not completely comparable because
   of differences in adopted gene platforms, oligonucleotide probe sets,
   applied analytical software and statistical analysis, they unanimously
   demonstrated the central role of IFN type I and its induced genes in
   the pathogenesis of pSS [107]23, [108]24 as well as the association of
   this gene signature with the presence of anti‐Ro/La antibodies [109]23.
   In PBMC, pathways also related to T‐ and B‐cell activation via their
   respective receptor signaling appeared to be overexpressed [110]23,
   [111]24. However, in previous studies, in contrast with the present
   one, no preliminary phenotypical characterization and distinction was
   made in the studied cohorts to analyze possible correlations between
   genotypic and phenotypic patterns.

   Although some locally activated pathways are certainly important to
   explain the biological processes specifically operative in target
   tissues, it has been largely demonstrated that the analysis of gene
   signature in PBMCs can be considered the mirror of the main mechanisms
   that may drive the pathogenesis of some systemic autoimmune diseases,
   such as rheumatoid arthritis and systemic lupus [112]25, [113]26, but
   also of other organ‐specific immune‐mediated disorders, such as
   multiple sclerosis [114]27. The fact that a transcription profile
   similar to that found in PBMCs has been observed in salivary tissue of
   patients with pSS [115]24 and, more recently, in cells isolated from
   synovial tissue of patients with psoriatic arthritis [116]28, seems to
   further support this assumption.

   When the analysis of the most enriched pathways was performed in the
   present study, the results we obtained indicate that the predominant
   signaling networks in the two subsets of patients were different.
   Because the methods to define biological processes and enriched
   pathways in gene expression analysis are different, to obtain not
   completely concordant results from the application of these procedures
   is only apparently contradictory. Two sets of genes can be part of the
   same biological process, according to the GO classification system, but
   can be assigned to different signaling pathways when enrichment
   analysis is applied.

   The most enriched pathways that characterized patients with GFs and WP
   are linked to pain perception and modulation processes (beta‐adrenergic
   receptor, CRF, and 5HT receptors signaling) [117]29, [118]30, [119]31.
   The activation in PBMCs of some signaling pathways that are commonly
   believed to be peculiar of neuroendocrine system, but not of cells
   belonging to the immune system, is not surprising. Some studies have
   shown that a specific gene signature is present in PBMCs in
   non immunoe‐related conditions [120]32 and in neuropsychiatric
   disorders [121]33. This is considered the direct consequence of the
   continuous biological cross talk between the neuroendocrine system and
   innate immune cell population that induces a reciprocal regulation
   [122]34.

   Notch signaling is another pathway we found to be enriched in patients
   with GFs and WP. The evolutionary conserved Notch signaling is a
   ubiquitous pathway that is involved in many biological processes in
   adulthood. It has been shown that Notch signaling is involved in many
   inflammatory conditions [123]35. Probably via the TLR signal, Notch
   signaling is activated in macrophages and dendritic cells and thus
   induces these cells to proliferate and produce inflammatory cytokines,
   such as TNF‐α and IL‐1β. Thus, Notch signaling plays multiple roles in
   both innate immune response and inflammation. Furthermore, Notch
   signaling has an important role in synaptic plasticity and inflammation
   in the central nervous system (CNS). It seems to have an important role
   in the development of neuropathic pain as demonstrated by the fact that
   the intrathecal administration of a Notch signaling inhibitor may
   prevent the development of neuropathic pain [124]36.

   The most enriched pathways in pSS patients with EGMs are those related
   to B‐cell activation and TLR signaling. This confirms the previous data
   indicating that both innate and adaptive immune response are enhanced
   in this subset of patients.

   Another pathway that appeared to be enriched in the patients with EGMs
   is that related to angiotensin II. Angiotensin II exerts
   proinflammatory and immune‐mediated actions through the interaction
   with angiotensin II receptor type 1 expressed on the surface of
   macrophages and T cells by inducing the activation of different
   kinases, such as mitogen‐activated protein kinase (MAPK) and
   extracellular signal–activated kinase (ERK), which are involved in many
   intracellular transduction signals [125]37. In this pathway, the
   arrestin system is able to influence various signaling systems and
   modulate chemokine receptor trafficking and signaling as well as
   apoptosis mechanisms [126]38. Conversely, the fact that the 5HT
   receptor signaling pathway is also enriched in this subgroup suggests
   that the activation of pain perception pathways is an important
   pathogenetic moment, even in this distinct phenotype of patients.

   The differences in gene expression in the two subgroups of pSS
   patients, with opposite phenotypic features, appear more evident when
   looking at the PPI network cluster analysis and the related enriched
   pathway analysis. The most interconnected genes modulated in patients
   with EGMs belong to pathways involved in innate (apoptosis, TLR and IFN
   signaling, proinflammatory cytokines) and adaptive (T‐ and B‐cell
   activation and cooperation) immune responses, which are largely
   documented in many biological studies as playing fundamental roles in
   pSS [127]22.

   Conversely, by analyzing the PPI network derived from patients with GFs
   and WP, only one module (M11) was composed of genes that can be
   referred to enriched pathways involved in innate and adaptive immune
   responses, whereas M0 and M2 are dominated by components that belong to
   pathways that are involved in sensory perception and pain modulation
   mechanisms [128]39. In details, LPAR2, P2RY, beta‐adrenergic receptor,
   and CRF receptor are involved throughout different biological
   mechanisms in central and peripheral pain sensitivity, whereas 5HT
   receptor systems have a double function of descending facilitation or
   inhibition of pain, and GABA receptor plays an important role in the
   inhibition of ascending painful stimuli [129]40.

   Of particular interest are M0 and M2, in which the enriched pathway
   called “inflammation mediated by chemokines and cytokines” is
   interfaced with genes and their related pathways, which are involved in
   the process of pain perception and modulation. According to the
   enriched pathway description, CCR5, ADCY5 (present in M0), GNG2, and
   GNG5 (present in both M0 and M2) are the modulated genes that are
   components of this pathway. Notably, most of the genes present in M0
   and M2 are also included among those that, according to the GO
   definition, are members of “sensory perception” gene set
   (Table [130]2).

   GNG2 and GNG5 are the γ2 and γ5 subunits of specific heterodimeric G
   proteins and thus are essential constituents of some subtypes of G
   protein–coupled receptors (GPCRs). The GPCRs are ubiquitously
   distributed in practically all cells and systems, although the large
   majority of them have been estimated to be located in the peripheral
   nervous system (PNS) and CNS, and drive here important functions in
   nociceptive signal transmission from the periphery and modulation of
   the upcoming neuropathic signals [131]41, [132]42. The γ subunit,
   together with the β subunit, are constituents of particular GPCR
   subtypes that are specifically linked and activated by all types of
   chemokines, ie, α (C‐X‐C), β (C‐C), γ (CX3C), and δ (XC) chemokines
   [133]43, [134]44. The activation of these receptors is followed by the
   formation of the second messenger, the cyclic adenosine monophosphate
   (cAMP), which is catalyzed by ADCY. cAMP production is only the first
   step of a cascade of events, which includes activation of multiple
   kinases and transcription factors that exert differentiated effects on
   PBMCs, like T‐cell proliferation, migration, aggregation, and
   production of proinflammatory cytokines as well as B cell
   antigen–stimulated proliferation [135]45.

   Different chemokine receptors have been identified as promising
   therapeutic targets in autoimmune diseases. This approach, however,
   appears to be extremely complicated because of the redundancy of
   chemokines as well as the remarkable complexity and variety of
   chemokine receptors involved in the recruitment of multiple types of
   immune and inflammatory cells [136]46. Some interesting results
   regarding the role of chemokines in activating the autoimmunity
   process, and the possibility to consider this mechanism as a new
   potentially effective therapeutic challenge, come from animal studies,
   namely, by the demonstration that the inhibition of G protein βγ
   subunit signaling may abrogate nephritis in lupus‐prone mice [137]47.

   On the other hand, there is a large amount of data demonstrating that
   the biological sequence represented by chemokine linkage to their
   specific GPCRs, ADCY catalytic action, cAMP intracellular release, and
   specific kinase activation is an essential moment in inducing
   neuropathic pain and its central processing [138]48, [139]49. A
   confirmation of this aspect comes from the observation that ADCY5
   knockout mice have a markedly reduced pain response in acute and
   chronic conditions [140]50. The main actors in the development of
   neuropathic pain and pain sensitization mechanisms are the glia cells,
   namely, the microglia cells resident in PNS and spinal cord [141]51.
   Spinal microglial cells, but also peripheral nociceptors, and afferent
   postsynaptic neurons express chemokine receptors, and the activation of
   these receptors induces the ADCY‐catalyzed cAMP production, the
   subsequent p38 MAP kinase phosphorylation leading to the production of
   proinflammatory cytokines and growth factors [142]52, [143]53, [144]54.
   It has also been shown in many experimental studies that T
   cell–released IFNγ is one of the main activators of microglia cells;
   this step is considered crucial for the induction of neuropathic pain
   [145]39. The fact that IFNγ is markedly overexpressed in patients with
   GFs and WP may suggest that this mechanism could be important even in
   inducing pain sensitization in this subset of patients.

   This complex system can be maintained and even enhanced by the ability
   of activated microglia cells to induce a similar activation of
   astrocytes, which are also important actors for the induction of
   presynaptic/postsynaptic starting of excitatory ascending stimuli.
   Because astrocytes are predominantly located in the brain, it has been
   postulated that these biological processes may also induce central pain
   sensitization [146]39.

   The data obtained in the present study using PBMCs suggest the
   possibility that specific mediators of inflammatory processes may play
   a role in activating different pathways involved in the development of
   neuropathic pain and central and peripheral sensitization. We can
   hypothesize that the same machinery of soluble mediators could become
   operative in glia and neuronal cells of both the PNS and CNS and thus
   may trigger the development of WP in pSS as well in other autoimmune
   disease where similar clinical features have been described [147]55.

   In summary, our data suggest that different pathways driven by DEGs are
   operative in patients with pSS characterized by a disease limited to
   GFs and WP as compared with patients phenotypically marked by the
   presence of EGMs. In the former subtype, the phenotypical expression of
   the disorder could be predominantly driven by mechanisms of innate
   immunity and by a cascade of inflammatory cytokines and chemokines. The
   chronic production of these proinflammatory mediators could induce pain
   sensitization and WP.

   Conversely, adaptive immune response pathways appear to dominate the
   scene in patients belonging to the other subtype of disease that is
   phenotypically characterized by EGMs. Whether these differences may be
   conditioned by differences in genetic susceptibility, as genoma‐wide
   association studies may suggest [148]56, or modulated by
   post‐transcriptional epigenetic phenomena like DNA methylation defects,
   histone modifications or microRNA‐related activity [149]57 remains to
   be clarified. Further studies are needed to confirm the present
   preliminary data and to better understand these phenomena. More
   advanced results could both open the possibility to a more precise
   stratification of patients with pSS according to the pathological
   processes activated in different phenotypic subsets and offer the
   opportunity to adopt more precisely tailored therapeutic strategies.

Author Contributions

   Drs. Vitali and Dolcino wrote the article. All authors approved the
   final version of the article to be published.

Study conception and design

   Vitali, Puccetti, Del Papa, Lunardi.

Acquisition of data

   Dolcino (gene expression analysis), Minniti, Pignataro, Maglione, Del
   Papa (clinical and serological characterization of patients).

Analysis and interpretation of data

   Vitali, Dolcino, Del Papa, Puccetti, Lunardi.

Supporting information


   [150]Click here for additional data file.^ (278.1KB, pdf)


   [151]Click here for additional data file.^ (662.7KB, docx)


   [152]Click here for additional data file.^ (101.6KB, docx)


   [153]Click here for additional data file.^ (49.2KB, docx)

   The work was supported by funds from the University of Verona and
   Genoa. The research reported in the manuscript was not supported by
   funds or other benefits coming from commercial sources.

   Claudio Vitali, MD: ‘Mater Domini’ Humanitas Hospital, Castellanza,
   Italy; ^2Marzia Dolcino, MD, Claudio Lunardi, MD: University of Verona,
   Verona, Italy; ^3Nicoletta Del Papa, MD, Antonina Minniti, MD,
   Francesca Pignataro, MD, Wanda Maglione, MD: DH Reumatologia, Gaetano
   Pini Hospital, Milan, Italy; ^4Antonio Puccetti, MD, University of
   Genoa, Genoa, Italy.

   No potential conflicts of interest relevant to this article were
   reported.

References