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Clinical Immunology (2010) xx, xxx–xxx

YCLIM-06690; No. of pages: 12; 4C:

Analyses of T cell phenotype and function reveal analtered T cell homeostasis in systemic sclerosisCorrelations with disease severity and phenotypes

Antonello Giovannetti a,⁎, Edoardo Rosato a, Cristina Renzi b,Angela Maselli c, Lucrezia Gambardella c, Anna Maria Giammarioli c,Paolo Palange d, Patrizia Paoletti d, Simonetta Pisarri a,Felice Salsano a, Walter Malorni c,e, Marina Pierdominici f

a Department of Clinical Medicine, Division of Clinical Immunology and Allergy, Sapienza University, Rome, Italyb Epidemiology Unit, Istituto Dermopatico dell'Immacolata, Rome, Italyc Department of Therapeutic Research and Medicines Evaluation, Istituto Superiore di Sanità, Rome, Italyd Department of Clinical Medicine, Pulmonary Lung Function Unit, Sapienza University, Rome, Italye San Raffaele Institute, Sulmona, L'Aquila, Italyf Department of Cell Biology and Neurosciences, Istituto Superiore di Sanità, Rome, Italy

Received 21 December 2009; accepted with revision 2 June 2010

⁎ Corresponding author. Departmentof Clinical Immunology and Allergy,dell'Università 37, 00185 Rome, Italy.

E-mail address: antonello.giovanne(A. Giovannetti).

1521-6616/$ - see front matter © 201doi:10.1016/j.clim.2010.06.004

Please cite this article as: A. Giovasystemic sclerosis, Clin. Immunol. (2

KEYWORDSSystemic sclerosis;Lymphocytes;Apoptosis;Thymus;Cell proliferation;Tregs;DLCO

Abstract We investigated in systemic sclerosis (SSc) patients the T cell homeostasis and itsrelationship with the clinical course of the disease. Distribution of peripheral T cell subsets,thymic output, lymphocyte proliferation and apoptosis were analyzed by flow cytometry orELISA. Age inappropriate levels of naive CD4+ T cells and thymic output were observed.Proliferation of CD4+ T cells, lymphocyte apoptosis and CD4+ regulatory T (Treg) cell frequencywere significantly higher than those observed in controls and significantly correlated with clinicalphenotypes and clinical progression parameters i.e., diffusing capacity of the lung for carbonmonoxide (DLCO) and disease activity. These data indicate that the evaluation of the T cellhomeostasis can represent a valuable prognostic tool for SSc patients and it is useful to

distinguish between limited and diffuse phenotypes. A therapeutic intervention targeted atreversing T cell homeostasis abnormalities would therefore potentially be helpful in counter-acting disease progression.© 2010 Elsevier Inc. All rights reserved.

of Clinical Medicine, DivisionSapienza University, Viale

Fax +39 0649387143.tti@uniroma1.it

0 Elsevier Inc. All rights reserv

nnetti, et al., Analyses of T c010), doi:10.1016/j.clim.2010

ed.

ell.06.

Introduction

Systemic sclerosis (SSc) is a multisystem autoimmune diseaseof unknown aetiology affecting predominantly women. It ischaracterized by endothelial dysfunction and excessive

phenotype and function reveal an altered T cell homeostasis in004

Table 1 Clinical characteristics of the study sample.

Patients Diseasesubset

Autoantibodies Diseaseduration(years)

DAS DLCO(%)

# 1 Diffuse ANA 6 7 60.7# 2 Limited ANA 1 3 85# 3 Limited Scl-70 1 3 98.7# 4 Limited ANA 5 2 86# 5 Diffuse Scl-70 2 4 32# 6 Diffuse Scl-70 11 3.5 82.6# 7 Limited Scl-70 12 3 93.1# 8 Diffuse Scl70 2 4 30.7# 9 Diffuse ANA 13 5 66.9# 10 Limited ANA 2 2 88.6# 11 Diffuse ANA 3 4 45# 12 Limited ACA 2 1.5 67.6# 13 Diffuse Scl-70 3 5 46.9# 14 Diffuse ANA 3 5 48# 15 Limited ANA 2 3 71.7# 16 Limited ACA 6 4 47.8# 17 Limited ACA 20 4 98.9# 18 Diffuse ANA 2 6 35.9# 19 Diffuse Scl-70 2 7 32# 20 Limited ACA 8 3 79.2# 21 Limited Scl-70 1 3 109# 22 Limited ACA 1 2 62.2# 23 Diffuse ANA 10 4 60# 24 Limited ACA 7 3.5 49.6# 25 Diffuse ANA 5 3 63.1# 26 Limited ACA 6 2 69.2# 27 Limited ACA 21 3 58.1# 28 Limited ACA 10 2 62.1# 29 Diffuse Scl-70 15 7 40# 30 Limited Scl-70 22 2.5 107.7# 31 Limited ACA 9 3 58.9# 32 Limited ACA 4 3 93.1# 33 Limited ACA 10 3 94.3# 34 Diffuse Scl-70 14 3.5 69.3# 35 Diffuse Scl-70 16 7 57.3

ANA, antinuclear antibody; ACA, anticentromere antibody; Scl-70, anti topoisomerase I antibody; DAS, disease activity score[19,20]; DLCO, carbon monoxide lung diffusion capacity.

2 A. Giovannetti et al.

extracellular matrix deposition in the skin and other visceralorgans [1,2]. The extent of skin and internal organinvolvement, and the severity and course of the diseasemay vary greatly among SSc patients. This heterogeneity haslong induced clinicians to subdivide patients into subsets,although the wide spectrum of clinical and laboratoryfeatures is impossible to encompass adequately in any onemodel [3]. A widely used classification system is the two-subset scheme proposed by LeRoy et al. [4]. The first one ischaracterized by a diffuse skin fibrosis with a severeinvolvement of internal organs and the second is character-ized by a limited cutaneous involvement. Antibodies totopoisomerase I (Scl-70) and RNA polymerase are typicallyseen in patients with diffuse disease while anticentromereantibodies (ACA) associate with limited SSc.

Very few is to date the information as concerns theaetiology and the pathogenetic mechanisms of sclerodermaand this hindered the identification of effective interven-tions in SSc. For instance, it is still unclear whether earlyevents leading to SSc are primarily characterized byalterations of the vascular compartment or inflammatoryresponses due to perturbation of the immune system [5,6].Recent studies suggest a hierarchical predominant role ofthe T cell-mediated immune response in inducing SSc.Evidences for T cell involvement in SSc include the presenceof an early infiltrate of activated T cells in skin, before anyevidence of fibrosis [7]. Moreover infiltrating T cells exhibitrestricted T cell receptor β-chain variable region reper-toires suggesting oligoclonal expansion of T cell populationsin response to unknown antigen(s) [8]. Other in favour of aT cell involvement are the increase of CD4+ T cells areincreased in the circulation of SSc patients, as well as thedecrease whereas γ/δ and natural killer T cells aredecreased [9,10]. Finally, an increased frequency ofcirculating Th17 cells and a compromised function of Tregulatory cells (Tregs) have recently been described[11,12].

Several attempts have been made to correlate the T cellabnormalities with the clinical features of the disease,although there are no predictive factors established yet. Infact, up to date, only limited information is available. Inparticular, partially conflicting results have been detectedbecause of the different methods used and the differentcriteria for patient selection (i.e. disease stage, clinical form,duration, and treatment), which impair a comparative analysisof immune cellular involvement in different reports. Addi-tionally, a feature which significantly complicates the analysisof T cell phenotype and function is the considerable flexibilityin the size and composition of the T cell pool. Assessing totalT cell numbers misses the subtleties of the T cell's differen-

Figure 1 Peripheral distribution of T cell subsets in SSc patients anand CD3+CD8+ peripheral T cell subsets. Data were expressed as tpopulation, as detailed in Materials and methods section, and were reall SSc patients, respectively) displaying medians, 25th and 75th percnumber of Tregs was calculated as the frequency of FoxP3+CD25high icontrol values. (B and C) Distribution of naive and CD31+ thymicnaivepatients (filled circles). (D) Distribution of CD31+ thymicnaive CD4+ T cCD31+ thymic naive CD4+ T cell analysis was performed on total lymphnaive CD4+), and CD31+ (R3) T cells. Dot plots from one representaperidinin-chlorophyll protein complex; APC, allophycocyanin.

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06

tiation state: naive, effector and memory T cells appear tohave distinct lifespans and requirements for their mainte-nance. Consequently, the proportion of these subsets variesdepending on the status of the individuals (including age,recent infections, clinical history, etc.). Maintaining T cell

d age-matched controls. (A) Flow cytometry analysis of CD3+CD4+

he percentage of each subset within the CD4+ or CD8+ T cellpresented as box plots (white and grey box plots for controls andentiles as boxes, and 10th and 90th percentiles as whiskers. Then the CD4+ population. *, Pb0.05, significance as compared withCD4+ T cells during aging in controls (open circles) and all SSc

ells during aging in all SSc patient groups under investigation. (E)ocytes after sequential gating for CD4+ (R1), CD45RA+CD62L+ (R2,tive SSc patient (# 30) are shown. FSC, forward scatter; PerCP,

phenotype and function reveal an altered T cell homeostasis in.004

3

homeostasis requires a fine balance between influx of newT cells from thymus, efflux by consumption and death, and selfreplication within the existing pool of lymphocytes [13]. Lossof T cell homeostasis can result in several disease statesincluding autoimmune disorders [14].

The ability of SSc patients to produce T cells and tomaintain T cell homeostasis has been scarcely explored. In

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.

this regard, the results of studies investigating the rate ofspontaneous lymphocyte apoptosis in SSc are highlyconflicting, as are the findings on the lymphocyte expres-sion of apoptosis-related molecules [15–17]. Therefore, acomprehensive evaluation of the T cell homeostasis hasbeen carried out in the present study in SSc patients withdifferent disease phenotypes in order to identify new

phenotype and function reveal an altered T cell homeostasis in004

4 A. Giovannetti et al.

Please cite this article as: A. Giovannetti, et al., Analyses of T cell phenotype and function reveal an altered T cell homeostasis insystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.004

Table 2 Apoptosis and apoptosis-related molecules.

ctrs(mean±SD)

SSc patients(mean±SD)

p-value ⁎⁎

Ex vivo spontaneousapoptosis (%)

6±2 8±4 0.018

In vitro spontaneousapoptosis (%)

10±2 13±5 0.013

In vitro CH11-inducedapoptosis(fold increase ⁎)

3.4±0.8 3.3±0.8 N0.05

CD4+ CD95+ (%) 51±15 49±14 N0.05CD8+ CD95+ (%) 58±20 65±20 N0.05sFas (ng/ml) 0.99±0.29 1.43±0.43 0.026sFasL (ng/ml) 55±18 52±15 N0.05CD4+ Bcl-2+ (MFI) 115±27 153±43 0.018CD8+ Bcl-2+ (MFI) 142±46 133±41 N0.05

ctrs, controls; MFI, mean fluorescence intensity.⁎ Fold increase as compared to untreated cells.⁎⁎ Two-tailed Mann–Whitney U test.

5

pathogenetic pathways, prognostic tools and possible the-rapeutic targets.

Materials and methods

SSc patients and controls

Thirty-five consecutive outpatients (30 women, 5 men) froma cohort of more than 200 patients, aged 22–80 years (mean56±14) fulfilling the American College of Rheumatologycriteria for SSc [18] were enrolled for the study, with theirinformed consent and institutional approval. Patients wereclassified as having limited cutaneous SSc (lcSSc, n=20) ordiffuse cutaneous SSc (dcSSc, n=15) on the basis of thecriteria of LeRoy et al. [4]. For all SSc patients, diseaseactivity was assessed using the activity indexes of theEuropean Scleroderma Study Group (disease activity score,DAS) [19,20]. According to these criteria, the disease wasconsidered active if the sum of the scores of detected itemswas ≥3 (patients with active disease, n=17; with inactivedisease, n=18). Exclusion criteria were previous or concom-itant treatments with immunosuppressive drugs. Patientswho were receiving steroids (n=5, prednisone≤5 mg/day)discontinued the treatment 30 days before immunologicalassays. Table 1 shows the clinical and laboratory character-istics of each patient. Twenty-nine healthy subjects matchedfor age and sex made up a control group.

Figure 2 Analysis of Ki-67-expressing CD4+ T cells, apoptosis andcontrols. (A) Ki-67 antigen expression measured in total, naive (CD45memory (CD45RO+CD27−, TEM ) T cells [49] from whole SSc patierepresentative patient (# 15, bottom) and control (top) are shown.lymphocytes using forward scatter vs. side scatter parameters afterCD4+ TEM cells), and Ki-67+ (R2). (C) Ki-67 antigen expression in totafrom SSc patient subsets (gray bars) and controls (white bars). (D) Peand Bcl-2 expression in CD4+ T cells from SSc patient subsets (grapercentage of annexin V positive cells. In all figures *, pb0.05, sign

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.

Carbon monoxide diffusion capacity (DLCO) analysis

DLCO was measured by the single breath method, accordingto the American Thoracic Society standards [21] with a DLCOanalyzer (Cosmed, Rome, Italy).

Cell culture and stimulation

Peripheral bloodmononuclear cells (PBMC)were isolated by aFicoll–Hypaque density-gradient separation (Lympholyte-H;Cedarlane Laboratories, Hornby, Ontario, Canada) andcultured in RPMI-1640 medium (GIBCO BRL, Grand Island, NY)with 10% FBS (Euroclone, Pero, Italy), 2 mM glutamine(Sigma, St Louis, MO) and 50 μg/ml gentamycin (Sigma).Spontaneous apoptosis was measured immediately afterseparation (ex vivo apoptosis) and after 48 h of culture (invitro apoptosis). For CH11-induced apoptosis, PBMC wereactivated with 1 μg/ml PHA (Sigma) for 72 h and thenmaintained in recombinant human IL-2 (60 IU/ml; PeproTechInc., Rocky Hill, NJ) as previously described [22]. An anti-human Fas IgM mAb (clone CH11; Upstate Biotechnology,Lake Placid, NY) was then added for 24 h to activated PBMC ata concentration of 0.5 μg/ml.

Flow cytometry analyses

Surface and intracellular phenotyping of freshly isolatedPBMC were performed with quadruple combinations ofmonoclonal antibodies (mAbs) as described before [22,23].The distribution of naive and memory CD4+ and CD8+ T cellswas evaluated by using mAbs directed towards the CD45RAand CD62L molecules. The naive subset was defined asCD45RA+CD62L+ while the remaining cells comprised thememory subsets (CD45RA−CD62L+, central memory subset,TCM; CD45RA−CD62L− and CD45RA+CD62L−, effector memorysubset, TEM) [24]. Intracellular staining of CD4+CD25+ cellsfor FoxP3 (Tregs) was performed using intracellular fixationand staining procedures according to the manufacturer'sprotocols (BioLegend, San Diego, CA). Recent thymicemigrants (RTE, thymicnaive CD4+ T cells) were defined asCD31+ naive CD4+ T cells, and postthymically expanded naiveCD4+ T cells (centralnaive CD4+ T cells) as CD31− naive CD4+

T cells [25]. For CD4+ and CD8+ lymphocyte subsets, datawere expressed as the percentage of each subset within theCD4+ or CD8+ population considered as 100%. CD31+ thymicna-ive CD4+ T cell analysis was performed by sequential gatingfor CD4+ (R1), CD45RA+CD62L+ (R2, naive CD4+), and CD31+

(R3) T cells (Fig. 1E). Ki-67-expressing CD4+ T cell analysiswas performed by sequential gating for CD4+, CD45RO+CD27−

(R1, CD4+ TEM cells), and Ki-67+ (R2) (Fig. 2B). Apoptosis was

apoptosis-related molecules in SSc patients and age-matchedRO−CD27high), CD27+ memory (CD45RO+ CD27+, TCM), and CD27−

nts (gray bars) and controls (white bars). (B) Plots from oneKi-67-expressing CD4+ TEM cell analysis was performed on totalsequential gating for CD4+ (data not shown), CD45RO+CD27− (R1,l (left), naive (middle), and effector memory (right) CD4+ T cellsrcentage of ex vivo and in vitro apoptosis, level of sFas (ng/ml)y bars) and controls (white bars). Apoptosis was expressed asificance as compared with control values.

phenotype and function reveal an altered T cell homeostasis in004

6 A. Giovannetti et al.

quantified using FITC-conjugated annexin V/propidium io-dide apoptosis detection kit (Marine Biological Laboratory,Woods Hole, MA) according to the manufacturer's protocol.Reduced glutathione (GSH) was evaluated in lymphocytes aspreviously described [26]. Analyses were done with aFACSCalibur flow cytometer and the Cell Quest Pro software(BD Immunocytometry Systems, San Jose, CA).

Enzyme-linked immunosorbent assay (ELISA)

Serum soluble Fas (sFas) and Fas ligand (sFasL) concentra-tions were determined by commercially available ELISA kitsfollowing the manufacturer's instructions (R&D Systems,Minneapolis, MN).

Statistical analysis

Numerical data were expressed as mean±SD. Regardingcontinuous variables the two-tailed Mann–WhitneyU test andthe Spearman's rank correlation analyses were performed.We examined the association between clinical SSc subsets(i.e. lcSSc and dcSSc), DAS, DLCO and each immunologicalparameter investigated in the present study. We dichoto-mized the variables DLCO and DAS in the categories poor vs.good. The category poor corresponds to the lower tertile forDLCO (i.e.b60%) and to the upper tertile for DAS (i.e.≥3); thecategory good includes all other values.

Laboratory parameters were also divided into tertiles dueto the non-normality of their distribution. The cut-offs for thelower, intermediate and upper tertiles of the laboratoryparameters shown in Table 3 were: ex vivo apoptosis, b8, 8–10, N10; in vitro apoptosis, b12, 12–14, N14; CD4+ Ki-67+

Figure 3 Regulation of naive CD4+ T cells frequency by the counsignificant correlation for naive CD4+ T cells and cell proliferation (lcorrelation was also found between the sFas molecule and both th(right). Apoptosis was expressed as percentage of annexin V positive

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06

cell frequency, b0.09, 0.09–0.18, N0.18; naive CD4+ Ki-67+

cell frequency, b0.04, 0.04–0.05, N0.05; CD4+ TCM Ki-67+ cellfrequency, b0.12, 0.11–0.18, N0.18; CD4+ TEM cell frequency,b7, 7–12, N12; Treg frequency, b5.5, 5.5–7.5, N7.5; CD4+/Bcl-2+ cell expression, b123, 123–170, N170; sFasL b48, 48–67, N67. Groups were compared using the Fisher's exact testfor categorical variables. Test for trend was used whereappropriate. Mantel–Haenszel odds ratios (MH-OR) with 95%confidence interval (CI) were calculated for the univariateassociation between laboratory parameters categorized intotertiles and the binary outcome variables lcSSc and dcSScphenotypes, DAS and DLCO. Statistical significance was setat pb0.05. The computer package STATA 9 (Stata Corp,College Station, TX) was used for statistical analyses.

Results

Altered T cell subset composition in SSc patients

According with the main aim of the present study, i.e. theevaluation of the T cell homeostasis in patients with SSc andits relationship with the different clinical phenotypes, wefirst investigated the peripheral distribution of the main Tcell subpopulations by four-colour flow cytometry. As shownin Fig. 1A, a great interindividual variability was observed inboth controls and patients. This was probably related to thelarge age range of the subjects under investigation, fromyoung adults to elderly persons. Notwithstanding, significantdifferences could be demonstrated between SSc patientsand controls. Particularly, a significant increase was ob-served for CD4+ T cells (51±9% vs. 47±6%, p=0.041) andTregs (6.7±2.2% vs. 4.5±1.5%, pb0.0001) whereas CD4+ TEM

teracting mechanisms of cell proliferation and apoptosis. (A) Aeft) and ex vivo apoptosis (right) was detected. (B) A significante distribution of naive CD4+ T cells (left) and ex vivo apoptosiscells.

phenotype and function reveal an altered T cell homeostasis in.004

7

cells and CD4+ HLA-DR+ T cells were significantly decreased(10±6% vs. 14±7 %, p=0.027 and 5±3% vs. 7±3%, p=0.015,respectively). These initial observations were of particularinterest because at variance with previously reported dataindicating an increased T cell activation in SSc patients. In lightof the abovementioned “plastic” nature of the T cell pool,this apparent discrepancy could be explained by demographic(e.g. age) as well as clinical differences among the studypopulations (e.g. the relative distribution of patients withlimited and diffuse form or with active or quiescent disease,with an early or late disease).

Since in normal individuals the age is one of the mainfactors influencing the T cell subset composition (a phenom-enon named “immunosenescence”), we next explored indetail this cause of heterogeneity in order to unveil furtherdifferences between patients and controls.

When the datawere plotted against the age value,wewereable to demonstrate, as expected, a significant negativecorrelation in controls for naive CD4+ (r=−0.56 and p=0.001,Fig. 1B) and CD8+ T cells (r=−0.88 and pb0.0001, data notshown). Interestingly, in SSc patients the frequency ofperipheral naive CD4+ T cells did not correlate with age(Fig. 1B, r=0.07 and p=0.664).

Looking at Fig. 1B, it may be observed that this findingwas mainly due to the elevated naive CD4+ T cell frequenciesdisplayed by elderly patients.

Given the essential role of thymus inmaintaining the pool ofnaive T cells,wenext evaluated the thymic activity. One of thebest ways to assess RTE is the direct analysis of T cell receptorcircle (TREC)withinCD4+ T cells. However, a number of studieshave demonstrated a strong correlation between TREC andCD31+ CD4+ T lymphocytes in healthy persons [25,27,28]. Thecorrelation between the TREC content and CD31+ expressionhas also been described by us and other authors in differentimmunological conditions including common variable immu-nodeficiency [23,29,30] and multiple sclerosis [31]. Thereforewe evaluated the thymic activity by measuring the expressionof the CD31 molecule that allows distinguishing true RTE(thymicnaive CD4+ T cells) from postthymically expanded naiveCD4+ T cells (centralnaive CD4+ T cells) [25]. Altogether, SScpatients showed values of CD31+ thymicnaive CD4+ T cells notsignificantly different from those observed in age-matchedcontrols (60±12% vs. 58±15%, p=0.672). However, in SScpatients this physiological decline was undetectable (r=−0.33and p=0.062), whereas in control samples the percentage ofCD31+ thymicnaive CD4+ T cells significantly declined with age(r 0.86 and pb0.0001) (Fig. 1C). Once more, the significantdifference observed between patients and controls wasapparently due to a “subset” of older patients showing highvalues of CD31+ thymicnaive CD4+ T cells.

At this point, in order to better characterize patientsshowing abnormal distributions of CD31+ thymicnaive CD4+

T cells, we plotted data according to the main subsetsactually used to classify SSc patients. Interestingly, whereaslinear regression lines similar to those found in controls wereobserved in SSc patients belonging to the diffuse (r=−0.88and pb0.0001) and active (r=−0.81 and p=0.0001) subsets,not-significant regression equations were detected inpatients belonging to limited (r=−0.2 and p=0.484) andinactive (r=−0.15 and p=0.556) SS forms (Fig. 1D).

These data indicate that, with aging, the physiologicalloss of thymic cells could be slowed down in SSc patients

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.

classified as having both the inactive and limited forms ofthe disease, but not in patients with the diffuse and activedisease. Since a disrupted equilibrium between cellularproliferation and apoptosis may underlie this abnormality,we next evaluated these two parameters in lymphocytesfrom SSc patients.

Increased lymphocyte proliferation and apoptosis inSSc patients

Proliferation of CD4+ T lymphocytes was evaluated bymeasuring the Ki-67 nuclear antigen expression known tobe associated with ribosomal RNA transcription and it may benecessary for cellular proliferation [32]. As shown in Fig. 2Aand B the percentage of Ki-67 expression was significantlyhigher in SSc patients in comparison with that observed incontrol samples for total CD4+ T cells (1.4±0.9% vs. 0.7±0.3%, p=0.010), for naive CD4+ T cells (0.4±0.2% vs. 0.3±0.1%, p=0.038), and for CD4+ TEM cells (3.4±3.1% vs. 1.3±0.7%, p=0.002). By contrast, proliferation of CD4+ TCM cellswas similar in samples from patients with scleroderma andhealthy subjects.

When these data were stratified according to the dif-ferent clinical subsets, we found that the significant increasein CD4+, naive CD4+ and CD4+ TEM cell proliferation wasmainly due to patients belonging to the diffuse and activesubsets.

Spontaneous and Fas-induced apoptosis as well as apo-ptosis-related molecules (CD95, sFas sFasL, Bcl-2) were alsoevaluated (Table 2). In addition, since the redox state oflymphocytes was considered of importance in cell demise,GSH content, known to counteract cell death [33] wasassessed. An increased level of both ex vivo and in vitrospontaneous apoptosis was detected in SSc patients ascompared to controls (8±4% vs. 6±2%, p=0.018 and 13±5%vs. 10±2%, p=0.013, respectively). Significant differences werealso found for sFas (1.43±0.43 ng/ml vs. 0.99±0.29 ng/ml,p=0.026) and Bcl-2 expression in CD4+ T cells (mean fluores-cence intensity, MFI, 153±43, vs. 115±27, p=0.018). Also in thisinstance patients with diffuse and active disease showeddistinctive tracts in comparison to patients with limited andinactive disease: they displayed highest values of apoptosisand Bcl-2 expression (Fig. 2D). Regarding the GSH content,no significant differences could be demonstrated betweenpatients and controls (data not shown).

Finally, we were able to demonstrate a tight regulation ofnaive CD4+ T cells frequency by the counteracting mechan-isms of cell proliferation and apoptosis, so confirming thatapoptosis and proliferation may be compensatory mechan-isms [34]. In fact, as shown in Fig. 3A, the distribution ofnaive CD4+ T cells resulted significantly related to bothcell proliferation (r=−0.4; p=0.035), and ex vivo apoptosis(r=−0.4; p=0.029). A significant association was also foundbetween the sFas molecule and both the distribution of naiveCD4+ T cells (r=0.4; p=0.025) and ex vivo apoptosis (r=−0.5;p=0.002), Fig. 3B. This finding was in good agreement withthe view that sFas can block apoptosis induced by FasL assuggested by in vitro experiments [35].

In conclusion, our data confirm at the T cell level the deepdichotomy existing between the diffuse and the limitedsubsets. In addition, they also suggest that in patients with

phenotype and function reveal an altered T cell homeostasis in004

Table 3 Association between DLCO, DAS, lcSSc and dcSSc phenotypes, and laboratory parameters.

DLCO

A Good Poor Total p-value ⁎ MH-OR (95% CI) # p-value §

n (%) n (%) n=35

Ex vivo apoptosis Low 13 86.7 2 13.3 15 0.004 2.76 (1.1–6.8) 0.028Intermediate 7 53.9 6 46.2 13High 3 42.9 4 57.1 7

In vitro apoptosis Low 11 84.6 2 15.4 13 0.002 3.85 (1.7–8.7) 0.001Intermediate 9 81.8 2 18.2 11High 2 18.2 9 81.8 11

CD4+ Bcl-2+ Low 9 81.8 2 18.2 11 0.015 3.14 (1.3–7.4) 0.009Intermediate 9 81.8 2 18.2 11High 3 27.3 8 72.7 11

CD4+ Ki-67+ Low 11 78.6 3 21.4 14 0.024 2.78 (1.2–6.2) 0.012Intermediate 7 77.8 2 22.2 9High 3 27.3 8 72.7 11

naive CD4+ Ki-67+ Low 11 84.6 2 15.4 13 0.058 2.7 (1.2–6.1) 0.017Intermediate 6 60 4 40 10High 4 36.4 7 63.6 11

CD4+ TCM Ki-67+ Low 10 90.9 1 9.1 11 0.036 3.14 (1.3–7.4) 0.009Intermediate 7 63.6 4 36.4 11High 4 36.4 7 63.6 11

Tregs Low 12 92.3 1 7.7 13 0.015 3.3 (1.4–7.5) 0.005Intermediate 6 60 4 40 10High 4 36.4 7 63.6 11

DAS

B 1–4 ≥5 Total p-value ⁎ MH-OR (95% CI) # p-value §

n (%) n (%) n=35

Ex vivo apoptosis Low 12 100.0 0 0.0 12 0.010 4.71 (1.6–13.8) 0.005Intermediate 12 75.0 4 25.0 16High 3 42.9 4 57.1 7

In vitro apoptosis Low 12 92.3 1 7.7 13 0.013 3.52 (1.4–9.0) 0.009Intermediate 10 90.9 1 9.1 11High 5 45.5 6 54.6 11

CD4+ Ki-67+ Low 13 92.3 1 7.1 14 0.103 2.78 (1.1–7.4) 0.039Intermediate 9 75.0 3 25.0 12High 5 55.6 4 44.4 9

naive CD4+ Ki-67+ Low 13 100.0 0 0.0 13 0.014 3.44 (1.4–8.7) 0.009Intermediate 7 70.0 3 30.0 10High 6 54.6 5 45.5 11

CD4+ TCM Ki-67+ Low 11 100.0 0 0.0 11 0.043 3.74 (1.4–10.2) 0.010Intermediate 9 81.8 2 18.2 11High 6 54.6 5 45.5 11

Tregs Low 12 92.3 1 7.7 13 0.003 3.84 (1.4 to10.2) 0.007Intermediate 10 100.0 0 0.0 10High 5 45.5 6 54.6 11

sFasL Low 12 100.0 0 0.0 12 0.031 3.34 (1.3–8.5) 0.012Intermediate 7 70.0 3 30.0 10High 6 54.6 5 45.5 11

SSc subsets

C lcSSc dcSSc Total p-value ⁎ MH-OR (95% CI) # p-value §

n (%) n (%) n=35

Ex vivo apoptosis Low 11 91.7 1 8.3 12 0.006 3.79 (1.5–9.4) 0.004Intermediate 7 43.8 9 56.3 16High 2 28.6 5 71.4 7

8 A. Giovannetti et al.

Please cite this article as: A. Giovannetti, et al., Analyses of T cell phenotype and function reveal an altered T cell homeostasis insystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.004

Table 3 (continued)

SSc subsets

C lcSSc dcSSc Total p-value ⁎ MH-OR (95% CI) # p-value §

n (%) n (%) n=35

CD4+ TEM Low 9 75.0 3 25.0 12 0.008 3.03 (1.3–6.9) 0.008Intermediate 9 75.0 3 25.0 12High 2 18.2 9 81.8 11

CD4+ Ki-67+ Low 9 64.3 5 35.7 14 0.044 2.09 (0.9–4.8) 0.08Intermediate 9 75.0 3 25.0 12High 2 22.2 7 77.8 9

Tregs Low 10 76.9 3 23.1 13 0.157 2.25 (1.0–5.0) 0.048Intermediate 6 60.0 4 40.0 10High 4 36.4 7 63.6 11

Poor DLCO corresponds to the lower tertile (i.e. b60) and good DLCO corresponds to the intermediate and upper tertiles. n, number ofpatients (total number may vary due to missing values).⁎ Fisher's exact test.# MH-OR (95% CI) for a unit increase in laboratory parameters going from low to intermediate to high levels.§ Test for trend.

9

the limited form not yet identified antiapoptotic factorsmight be upregulated leading in the long run to a progressiveexpansion of the naive CD4+ subset.

Correlations between clinical andimmunological parameters

In order to ascertain if the above demonstrated immuneabnormalities could have a role in the clinical course of thedisease several of statistical evaluation were performedmatching all the immunological data available with the mainclinical parameters of SSc. Only significant results arereported below.

Spearman's rank correlation showed a significant negativecorrelation for DLCO values and apoptosis levels (ex vivoapoptosis, r=−0.36; p=0.03; in vitro apoptosis, r=−0.43;p=0.01), CD4+ Bcl-2+ cell expression (r=−0.46; p=0.008),CD4+ Ki-67+ cell frequency (r=−0.54; p=0.001), naive CD4+

Ki-67+ cell frequency (r=−0.41; p=0.016), CD4+ TCM Ki-67+

cell frequency (r=−0.48; p=0.004), and Treg distribution(r=−0.65; pb0.001).

Examining the association between DLCO and laboratoryparameters transformed into categorical variables accordingto tertiles, we found an increasing trend of poor DLCO (i.e.b60) going from the lower to the higher tertiles of thelaboratory parameters shown in Table 3A. Poor DLCO showeda particularly high prevalence among patients with labora-tory parameters in the upper tertiles.

In regard to DAS, the Spearman's rank correlation showeda significant positive correlation with CD4+ Ki-67+ cell fre-quency (r=0.37; p=0.031), naive CD4+ Ki-67+ cell frequency(r=0.35; p=0.045), CD4+ TCM Ki-67+ cell frequency (r=0.36;p=0.037), and Treg distribution (r=0.36; p=0.037). WhenDAS was dichotomized in DASN3 vs. lower levels, nosignificant association with the examined laboratory para-meters was observed. Interestingly, when DAS was dicoto-mized in DAS≥5 vs. DAS 1–4, we observed an increasing

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06.

trend of DAS≥5 with increasing levels of the laboratoryparameters shown in Table 3B.

Finally, Spearman's rank correlation showed a significantpositive correlation for the dcSSc phenotype with ex vivoapoptosis (r=0.46; p=0.005), CD4+ TEM Ki-67+ cell frequency(r=0.37; p=0.030), and GSH values (r=0.46; p=0.036).When the association between the lcSSc and dcSSc pheno-types and the laboratory parameters was examined, anincreasing trend of the dcSSc phenotype, going from thelower to the intermediate to the highest tertiles of thelaboratory parameters shown in Table 3C, was observed.

Discussion

We show here that patients with SSc, during lifespan, mayundergo a progressive expansion of the naive CD4+ T cellsubset. This appeared mainly due to a derangement offactors committed to T cell homeostasis. The combinedevaluation of thymic output, apoptosis and cell proliferationrevealed distinct immunological profiles for the different SScphenotypes. Increased levels of Tregs, T cell apoptosis andproliferation were significantly associated with a moresevere disease course and phenotype.

To our knowledge, this is the first report describing in SScpatients an age-inappropriate peripheral distribution ofnaive CD4+ T cells. Differently from that observed in normalindividuals the distribution of naive cells increased with agein SSc patients. This was also at variance with that observedin other autoimmune diseases, such as rheumatoid arthritis(RA), where the high levels of T cell activation and apoptosislead to a progressive expansion of the memory subset to thedetriment of the naive T cell pool in the long run [36]. Theanalysis of CD31 expression, a molecule used to distinguishthymicnaive from centralnaive CD4+ T cells in the peripheralblood, allowed us to unveil unusually high levels of RTE in anumber of elderly patients mainly belonging to the limitedand inactive subsets. Therefore differences exist among SSc

phenotype and function reveal an altered T cell homeostasis in004

10 A. Giovannetti et al.

patients regarding their capability to maintain the T cellhomeostasis.

An altered production of cytokines could be implicated inthe increased distribution of naive cells and thymic activityobserved in a subpopulation of SSc patients. In this regard,IL-7 might play a role. In fact, it is required for developingmature T cells in the thymus, whereas in the periphery itpromotes the survival of naive and memory T cells byupregulating the antiapoptotic molecule Bcl-2 [37,38].Interestingly, Churchman et al. [39] recently describedthat patients with RA, classically presenting with reducednaive CD4+ T cells, have low serum levels of IL-7. Therefore,studies on IL-7 production in SSc patients are required toestablish the role of this cytokine in the genesis of T cellhomeostasis abnormalities.

However, the absence of a significant correlation betweenthe frequency of naive CD4+ T cells and the level of CD31thymic cells argues against an exclusive role of thymus,suggesting that further, peripheral mechanisms must beinvoked to explain the increased frequencies of naive CD4+

T cells seen in SSc patients. In this regard, we found anincreased naive CD4+ T cell proliferation that might also havepathogenetic relevance. In fact, assuming that postthymicproliferation of central naive CD4+ T cells is driven by self-peptides, a positive selection and expansion of potentiallyautoreactive Th cells might occur [27]. As a result, theaccumulation of autoreactive naive CD4+ T cells, possiblytogether with predisposing genetic factors, could facilitatethe initiation of autoimmune diseases. This has been provenin mice where lymphopenia with consecutively increasedperipheral homeostatic proliferation of T cells leads to severeautoimmunity [40]. Consistent with this observation, in-creased T cell turnover has been observed in patients with RA[41] and multiple sclerosis [31].

A significant increase in the proliferation rate of the CD4+

TEM cell pool, which contains functionally differentiated Tlymphocytes [42], was also detected in SSc patients ascompared to controls, suggesting a persistent in vivoantigenic stimulation. This response might be due to afailure in one or more peripheral tolerance mechanisms. Adefective suppressive function of circulating Tregs, asrecently reported in SSc patients [12], might contribute toproliferating CD4+ TEM cell expansion [43]. An expandedpopulation of circulating CD4+ TEM cells has been demon-strated in various autoimmune diseases including Wegener'sgranulomatosis, multiple sclerosis, type 1 diabetes mellitus,juvenile idiopathic arthritis, and psoriasis [44]. CD4+ TEMcells produce high levels of cytokines with immunomodula-tory potential and profibrotic activities such as IL-4 and IL-13[42,45] and therefore they may be involved in the earlyvascular damage seen in SSc.

To date, contrasting data regarding a possible dysregula-tion of lymphocyte apoptosis and an altered expression ofapoptosis-related molecules have been reported in SSc. In aninitial paper on this topic, Stummvoll et al. [17] showednormal levels of both spontaneous and CH11-inducedapoptosis in association with increased sFasL serum levels.As opposite, Cipriani et al. [16] reported, more recently,decreased apoptosis with normal sFasL levels in patients withSSc. It is our opinion that differences in disease duration andphenotype of patients investigated in those studies should betaken into account to explain this discrepancy. Our data

Please cite this article as: A. Giovannetti, et al., Analyses of T cellsystemic sclerosis, Clin. Immunol. (2010), doi:10.1016/j.clim.2010.06

indicate that the clinical phenotype, the disease activity andthe lung involvement could represent predictive factors forthe levels of apoptosis and apoptosis-related molecules.Therefore it is tempting to speculate a therapeutic usage ofantiapoptotic agents for patients with SSc. Agents such as N-acetylcysteine, which thanks to its vasodilatory propertiesalready represents a useful drug in the clinical managementof SSc [46,47], could particularly be suitable in patients withdcSSc showing high levels of apoptosis or during the activephases of the disease.

Finally, we retain that the tight correlation between thefrequency of peripheral Tregs and clinical aspects of SScshould carefully be re-considered. Tregs are known torepresent the most pivotal players in the maintenance ofimmune tolerance and both quantitative and qualitativealterations of Tregs have been described in several autoim-mune diseases [48]. Our data are consistent with thoserecently reported by Radstake et al. [12] who showed anincreased frequency and a compromised function of Tregs inSSc. From a clinical point of view, the correlation betweenTreg frequencies and both disease severity and clinicalphenotypes represents a novelty making conceivable thepossibility of a Tregs-directed therapy. In fact, treatmentshave been identified capable to modify both number andactivity of Tregs [48]. Further studies specifically aimed todemonstrate links between Treg activity and severity of thedisease are now required in order to guide the choice towardboosting treatments.

Summarizing, the immunological scenario we propose hereassumes that alterations of the T cell homeostasis may play arole in the fate of SSc, although they do not entirely take intoaccount the vast heterogeneity of the disease. In geneticallysusceptible individuals yet unidentified factors might triggerdivergent immune responses. A first type of immune responseis characterized by high levels of Tregs, lymphocyte apoptoticsusceptibility as well as with CD4+ T cell proliferation. This isthemore aggressive immunological profile associatedwith thediffuse phenotype, lung involvement, and active disease. It isconceivable that up-regulation of molecules belonging to theFas–FasL family may play a role in the development of thisprofile. A second type of immune response is characterized bylow levels of Tregs, apoptosis and CD4+ T cell proliferation andassociates with the limited form of the disease. The low levelsof lymphocyte apoptosis in association with a sustained thymicoutputwould result in a progressive increase of naive T cells. Itshould be noted that this profile is quite different from thatobserved in other autoimmune diseases such as systemic lupuserythematosus and RA inwhich early thymic involution is foundin association with a chronic lymphocyte activation and anincreased turnover of peripheral lymphocytes [49,50].

In spite of the limitations of our study, i.e. the limitationin sample size and its cross-sectional nature, we believe thatour data may contribute to the understanding of the complexpathogenetic mechanism underlying the different forms ofSSc. However, we cannot exclude that the immunologicalabnormalities here described could be, at least in part,epiphenomena unrelated to the pathogenesis of the disease,although representing a promising progression marker.Stemming on these findings, further expanded and longitu-dinal studies are however mandatory in order to improve andvalidate these findings and translate them in the clinicalpractice.

phenotype and function reveal an altered T cell homeostasis in.004

11

Acknowledgments

This work was partially supported by C26/D grant (W.Malorni).

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