Foot ulceration is one of the most debilitating complications associated with diabetes, but its cause remains poorly understood. Several studies have been undertaken to understand healing kinetics or find possible therapies to enhance healing. However, few studies have been directed at understanding the immunological alterations that could influence wound healing in diabetes. In this study, we analysed the T-cell receptor (TCR) repertoire diversity in TCR-αβ+ T cells. We also analysed the distribution and phenotype of T cells obtained from the peripheral blood of healthy controls and diabetic individuals with or without foot ulcers. Our results showed that diabetic individuals, especially those with foot ulcers, have a significantly lower naive T-cell number and a poorer TCR-Vβ repertoire diversity. We also showed that the reduced TCR-Vβ repertoire diversity in diabetic individuals was mainly owing to the accumulation of effector T cells, the major source of tumour necrosis factor-α production, which was even more pronounced in patients with acute foot ulceration. Moreover, the expression of several inflammatory chemokine receptors was significantly reduced in diabetic patients. In conclusion, effector T-cell accumulation and TCR repertoire diversity reduction appear to precede the development of foot ulcers. This finding may open new immunological therapeutic possibilities and provide a new prognostic tool in diabetic wound care.
The prevalence of diabetes is increasing at alarming rates worldwide and is greatly affected by the concurrent overweight and obesity epidemic caused by poor diet, lack of physical activity and genetic predisposition. Lower limb amputation, one of the major causes of diabetes-associated morbidity and mortality, is a consequence of diabetic foot ulceration (DFU).1 In contrast to normal wounds that progress through the phases of wound healing, the wounds in chronic diabetics become stalled in different phases, and healing does not occur in a synchronised fashion. This healing defect is due to diabetes-associated neuropathy, microangiopathy and immune function impairment.2 Because our understanding of how the immune response is impaired in diabetic patients is still incomplete, DFU treatments have mainly relied on lower limb amputation,3 with some occasional new strategies providing very limited results.4, 5, 6 Although prevention is essential for DFU care,7 its impact is also limited because we are still unable to predict the onset of DFU. Indeed, despite the identification of various risk factors for DFU,8, 9, 10 a reliable marker is urgently needed to identify the individuals at risk or in the early stages of DFU. To develop better therapeutic strategies or to better predict the appearance of DFU, we must first understand why the immunological response is compromised during foot infections in some diabetic individuals and how this defect leads to chronic wounds that fail to heal.
Diabetic patients present a systemic pro-inflammatory environment with increased levels of interleukin (IL)-1, tumour necrosis factor (TNF)-α and IL-6, and regulated on activation, normal T-cell expressed and secreted (RANTES).11, 12 This pro-inflammatory environment is not only present in the blood but also extends to various other tissues such as the skin,13 and significantly contributes to the microvascular and macrovascular complications associated with diabetes.14, 15, 16, 17 To elucidate the effect of insulin resistance on inflammation, a recent study using a mouse model of high-fat-diet-induced glucose intolerance revealed that insulin resistance, by impairing inflammation and collagen fibre organisation, increased wound healing time.18 In fact, hyperglycaemia alone was able to activate nuclear factor-κB,19 which impairs leukocyte activation20 and migration.21 Conversely, pro-inflammatory cytokines such as IL-6 and TNF-α were shown to regulate resistin expression in humans, worsening insulin resistance in diabetic patients.22 Despite the chronic inflammation observed in diabetic patients,11 the diabetic immune system is unable to mount the effective immune response required for bacterial control and tissue regeneration.23
Results from some DFU models also suggest that the impaired wound healing in diabetics would not only originate from an excess of pro-inflammatory cytokines but also from a deficit of anti-inflammatory and healing-associated cytokines like transforming growth factor-β and IL-10.24 Because these antagonistic cytokines usually inhibit each other’s action, the distinction between the cause and the effect is unclear. In fact, the fine balance between inflammation and pathogen tolerance is mainly regulated by T-cells. These cells also control the adaptive response through cell–cell interactions or through cytokines. In animal models, CD4+ T cells depletion negatively impacts wound healing, whereas CD8+ T-cell depletion has a positive impact.25 Despite the possible differences between the murine and human T-cell responses, a decrease in the number of CD4+ T cells was also observed in diabetic individuals.26
Various studies have demonstrated that infections that cause a strong T-cell stimulation may provoke a deleterious effect on the T-cell receptor (TCR) repertoire diversity, and therefore extensively affect the immune response to subsequent infections by different pathogens.27, 28, 29, 30, 31 This effect is mainly attributed to the competition for cytokines that mediate the survival of naive cells, such as IL-2, thereby imposing a limiting factor on the total T-cell count.32 Moreover, other studies have also shown that the accumulation of small effects caused by encounters with regular pathogens can result in a significant effect on the TCR repertoire diversity of aged individuals.33, 34 Nevertheless, using a transgenic murine model, it was also established that a fair amount of plasticity exists in the TCR repertoire, mainly because of the cross-reactivity phenomenon that can compensate for a reduction in diversity.35 However, this effect may not be sufficient to fully overcome the decrease in diversity, which likely limits the defence capacity against natural pathogens.
Therefore, the pro-inflammatory environment and the recurrent wound infections in diabetic patients may have an effect on the TCR repertoire diversity and on the distribution of T-cell populations. However, we still have to understand with precision how it affects the outcome of wound healing in diabetics. To address this question, we studied the TCR-αβ+ T-cell subpopulations present in the blood of diabetic patients with or without DFU to analyse their distribution and TCR repertoire diversity.
MATERIALS AND METHODS
Peripheral blood (PB) samples from 22 healthy adult controls and 41 diabetic patients, including 21 without DFU, 10 with acute DFU (<3 months from diagnosis36) and 10 with chronic DFU (>3 months from diagnosis36), were collected using ethylenediamine tetraacetic acid (EDTA)-K3 tubes for immunophenotyping. The sample characterisation data and relevant clinical information are summarised in Table 1. In addition, larger PB samples from 6 healthy individuals, including 4 females and 2 males aged between 35 and 47 years (average 41 years), were collected into EDTA-K3 tubes for T-cell sorting and in vitro culture experiments. In addition, a small PB sample was collected into sodium heparin tubes for cytokine production assays.
All diabetic patients and controls enrolled in the study had no previous history of neoplastic malignancies or autoimmune disorders and, at the time of sample collection, had no other clinically detectable infection than the foot infection in the case of DFU patients. A history of previous foot ulcerations was considered as an exclusion criterion for all groups except for the chronic DFU group.
TCR-β diversity assessment
Deoxyribonucleic acid (DNA) was extracted from the sorted populations using the Sigma GenElute Mammalian Genomic DNA Miniprep Kit (Sigma-Aldrich, St Louis, MO, USA) according to the manufacturer’s protocol. The extracted DNA was quantified using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).
Polymerase chain reaction (PCR) amplification was performed using 100 ng of DNA for each sample, as described in the Biomed II protocol,37 using the TCR-β Gene Clonality Assay (InVivo Scribe Technologies, San Diego, CA, USA). Briefly, three multiplex PCRs were performed, each amplifying different zones of the TCR-β locus. The first and second PCRs were designed for the detection of rearrangements between the Vβ and Jβ regions, including forward primers for the following Vβ families: Vβ2, Vβ4, Vβ5, Vβ6, Vβ7, Vβ8, Vβ9, Vβ10, Vβ11, Vβ12, Vβ13, Vβ14, Vβ15, Vβ16, Vβ17, Vβ18, Vβ19, Vβ20, Vβ21, Vβ22, Vβ23 and Vβ24. The reverse primers used in the first PCR targeted Jβ1.1, Jβ1.2, Jβ1.3, Jβ1.4, Jβ1.5, Jβ1.6, Jβ2.2, Jβ2.6 and Jβ2.7, and, for the second, Jβ2.1, Jβ2.3, Jβ2.4 and Jβ2.5. The Vβ primers covered ~90% of all the Vβ gene segments.
The third PCR was designed for the detection of rearrangements between the Dβ and Jβ regions, using forward primers for Dβ1 and Dβ2, and reverse primers for Jβ1.1, Jβ1.2, Jβ1.3, Jβ1.4, Jβ1.5, Jβ1.6, Jβ2.1, Jβ2.2, Jβ2.3, Jβ2.4, Jβ2.5, Jβ2.6 and Jβ2.7.
Amplification was performed using the phycoerythrin (PE) 9600 thermal cycler (Perkin Elmer, Applied Biosystems, Inc., Foster City, CA, USA), and product sizes were detected with the Applied Biosystems ABI 310 single-capillary electrophoresis system (Thermo Fisher Scientific) using a 47 cm × 50 μm capillary at the single-base sensitivity. The resulting data were analysed using the Peak Scanner Software v1.0 (Thermo Fisher Scientific).
The analysis of surface antigen expression on the PB T cells was consistently performed using a whole-blood direct immunofluorescence four-colour staining with the monoclonal antibodies (mAbs) indicated in Table 2.
The cells were prepared for flow cytometry as previously described.38 In brief, the blood cells were incubated for 15 min at room temperature with the antibodies after the erythrocyte lysis and cell fixation steps, which were performed using the FACS lysing solution (Becton Dickinson, East Rutherford, NJ, USA).
The flow cytometry experiments were performed on a FACSCalibur cytometer (Becton Dickinson) using the BD CellQuest software (Becton Dickinson) for sample acquisition and the BD Paint-A-Gate Pro software for data analysis (Becton Dickinson). Alternatively, we also used a Navios cytometer equipped with the Navios software for sample acquisition and the Kaluza software for data analysis (all from Beckman Coulter, Brea, CA, USA).
The different subpopulations were selected using anti-CD4 or anti-CD8 together with anti-CD27 and/or anti-CD28, and anti-CD45RO mAbs. This strategy, proposed by Appay et al.,39 allowed for a clear identification of three major blood T-cell populations: naive (CD27+ CD28+ CD45RO−), activated/memory (CD27+ CD28+ CD45RO+) and effector (CD27− CD28−).
Cell culture assays
Mononuclear cells were separated from whole blood by centrifugation using a 1.077 density gradient media (Lymphoprep, Axis Shield PoC, Oslo, Norway) and were cultured for 3 weeks at a density of ~1 × 106 cells per ml in 2 ml plates placed in a sterile environment at 37 °C under a 5% CO2 humidified atmosphere. Cells were cultured in complete medium (Roswell Park Memorial Institute medium (RPMI) 1640+10% foetal calf serum (FCS)+1 M 4-(2-hydroxyethyl)-1-piperazineethanesulphonic acid (HEPES) buffer+200 mM L-glutamine) supplemented with IL-2 (50 U/ml; all from Sigma-Aldrich). At day 0, concanavalin A (2.5 mg/ml; Sigma-Aldrich) was added to the culture medium. The complete medium+IL-2 was renewed twice a week. Cells were collected at days 0, 3, 7, 14 and 21, washed with PBS and used directly for flow cytometry analysis.
T-cell population sorting
Mononuclear cells were separated from whole blood by centrifugation using a 1.077 density gradient media (Lymphoprep, Axis Shield PoC) and then stained using a direct immunofluorescence four-colour staining technique as described above. All experiments were performed on a BD FACSAria cell sorter using the BD FACSDiva software (Becton Dickinson).
The selective gating of different T-cell populations was based on the differential expression of the CD27, CD28 and CD45RO molecules. We used an anti-CD3 in conjunction with anti-CD28, anti-CD45RO and anti-CD27 mAbs that were conjugated with allophycocyanin (APC), phycoerythrin-Cy5 tandem (PC5), PE and fluorescein (FITC), respectively. This strategy allowed for a clear separation of the three previously mentioned blood T-cell populations: naive (CD27+ CD28+ CD45RO−), activated/memory (CD27+ CD28+ CD45RO+) and effector (CD27− CD28−) with more than 99.5% purity and without contamination between each population.
Cytokine-producing T-cell quantification
Previously sorted T-cell populations were cultured in a sterile environment in 15-ml tubes at a density of ~1 × 106 cells per ml for 5 h, at 37 °C under a 5% CO2 humidified atmosphere. Cells were cultured in complete medium (RPMI 1640+10% FCS+1 M HEPES buffer+200 mM L-glutamine) in the presence of brefeldin A (10 μg/ml), with (stimulated cultures) or without (un-stimulated controls) 12-O-tetradecanoylphorbol-13-acetate (PMA; 25 ng/ml) and ionomycin (1 μg/ml; all from Sigma-Aldrich).
The intracellular staining procedure was previously described in detail.40 In brief, the cells were harvested and stained for surface antigens and then fixed and permeabilised using the FIX & PERM Cell Fixation and Cell Permeabilization Kit (Life Technologies, Invitrogen, CA, USA). The cells were then stained with anti-IL-2, anti-IL-4, anti-IL-10, anti-interferon (IFN)-γ or anti-TNF-α mAbs conjugated with PE and analysed by flow cytometry.
All statistical analyses was performed using a one-way analysis of variance followed by Tukey’s honest significant difference test with a 95% confidence interval using the GraphPad prism 6.0 software (GraphPad Software Inc., La Jolla, CA, USA). Differences were considered statistically significant for P<0.05.
All samples were collected after informed consent. This study was approved by the ethical review board of the Santo António Hospital, Porto, Portugal.
TCR-β gene diversity in circulating T cells from diabetic patients
We analysed the size of various PCR products that expanded parts of the TCR gene, encompassing the Vβ, Dβ and Jβ regions. The diversity in the PCR product sizes directly correlates with the V(D)J recombination diversity which, in turn, correlates with the T-cell clonal diversity, as previously described.37 The blood TCR-αβ+ T cells from non-diabetic individuals (controls; n=10; Figure 1a) presented a Gaussian distribution of the PCR product sizes, indicating that the TCR-αβ+ T cells from these individuals are clonally diverse. In contrast, the blood TCR-αβ+ T cells from diabetic individuals with acute DFU (n=10; Figure 1c) and from diabetic patients with chronic DFU (n=10; Figure 1d) clearly showed multiple clonal expansions represented by the presence of multiple peaks deviating from the Gaussian distribution.
The diabetic patients without DFU (n=10; Figure 1b) showed no large clonal expansions but presented an intermediate phenotype between those of the controls and DFU patients. Indeed, small expansions were observed in 8 of the 10 diabetic patients analysed. However, all these patients displayed a significant decrease in the polyclonal background height (as shown in Figure 1b), which indirectly correlates with a reduction in the TCR-β repertoire diversity.37
In addition, we analysed the TCR-β repertoire diversity of diabetic patients who had previous episodes of DFU but had no active foot ulceration at the time of sample collection (n=3). In all cases, large TCR-β expansions were observed (data not shown).
Collectively, these results indicate that the TCR-β repertoire is less diverse in diabetic patients, especially in those with active foot ulcerations, and that this phenomenon persists after the DFU has healed.
Effect of the decreased circulating pool of naive T cells on inflammation
Because clonal expansion is a consequence of T-cell activation, we determined whether the various T-cell activation-related populations were contributing differently to the diminished TCR-β gene diversity observed in diabetic patients with DFU. We first quantified the relative representation of the most relevant T-cell activation-related populations in the PB of diabetic patients and controls, and then analysed the TCR-β gene rearrangement diversity in each population.
Three major T-cell populations were identified in the PB of controls and diabetic patients, and were defined on the basis of the relative expression of the co-stimulatory molecules CD27 and CD28, and the activation-associated molecule CD45RO: naive (CD27+ CD28+ CD45RO−), activated/memory (CD27+ CD28+ CD45RO+) and effector (CD27− CD28−). The gating strategy for these three populations is represented on Figure 2a.
We observed a significant decrease in the percentage of naive CD4+ T cells (Figure 2b) between controls (n=22) and all diabetic patient groups (n=41). This reduction of the percentage of naive CD4+ T cells in patients with chronic DFU (n=10) was not as severe as in the acute DFU patients (n=10), with a similar average reduction as in diabetic patients without DFU. In the case of CD8+ T cells, a similar trend was observed (Figure 2b), although the results were statistically significant in the acute DFU patients group only.
We also observed a significant increase in the percentage of activated/memory CD4+ T cells (Figure 2c) between controls and diabetic individuals. This tendency was not observed in the case of CD8+ T cells, in which no difference was observed.
In the case of effector T cells, we found a significant increase in the percentage of both CD4+ and CD8+ cells between diabetic patients with acute DFU and other diabetic patients or controls (Figure 2d). Although not statistically significant, we also observed a tendency towards an increase in the number of both CD4+ and CD8+ effector T cells in diabetic individuals without DFU compared with controls. Moreover, the diabetic patients without DFU showing the highest percentages of effector T cells (both CD4+ and CD8+) were also the ones showing the greatest reduction in their TCR-β repertoire diversity.
Interestingly, no difference was found in the effector T-cell percentages between diabetic patients with chronic DFU and both the diabetic patients without DFU and control groups (Figure 2d).
Effect of diabetes and foot ulceration on T cell chemokine receptor expression
Because both the chemokine environment11 and the immune cell migration capacity21 are altered in diabetic patients, we also investigated the expression of particular skin homing (CCR4), early inflammatory/Th1-specific (CCR5 and CXCR3) and late inflammatory (CXCR1) chemokine receptors (CHRs) on these T-cell populations.
In both the control and diabetic patient groups (n=6 in each group), the presence of CCR4 was almost restricted to the activated/memory T cells (P<0.01; Figure 3), with a higher expression level in the CD4+ subset. There was no significant difference in CCR4 expression between diabetic patients and controls.
CCR5 and CXCR3 were preferentially expressed in the activated/memory and effector T-cell populations, especially in the latter, in both diabetic patients and controls. Nonetheless, compared with controls, CCR5 and CXCR3 expression was significantly diminished in the effector T cells from the diabetic patients (P<0.0001) for both the CD4+ and CD8+ subsets. In addition, there was a significant decrease in the CCR5 expression level (P<0.001) in diabetic patients with chronic DFU when compared with the acute and non-DFU patients.
In contrast with the expression of the early inflammatory CHRs CCR5 and CXCR3 observed in all T-cell populations, the expression of the late inflammatory CHR CXCR1 was only detected in the CD4+ or CD8+ effector T cells, with a consistently higher expression level in the CD8+ cells. Interestingly, almost no CXCR1 expression was observed in the effector T cells from diabetic individuals with or without foot ulceration (P<0.0001).
Furthermore, we analysed the effect of excessive stimulation on the CHR expression levels of T cells in vitro to mimic the excessive inflammatory conditions observed in diabetic patients. Therefore, we stimulated mononuclear cells from non-diabetic individuals (controls; n=6) with concanavalin A in the presence of IL-2 and cultured these cells for 3 weeks. The expression of the previously analysed CHRs (CCR4, CCR5, CXCR1 and CXCR3) was monitored on days 0, 3, 7, 14 and 21 (Figure 4).
Under these conditions, the percentage of T cells expressing CCR4 and CXCR3 increased consistently during the 3 weeks of culture, although this increase was not statistically significant. Conversely, the expression of CXCR1 and CCR5 decreased during the 21 days of culture, a change that was significant only for CCR5 expression (P<0.01).
The T-cell activation profile limits TCR clonal diversity
We showed that diabetic patients with acute or chronic DFU display a skewed TCR-Vβ repertoire (Figure 1). In order to evaluate whether this is a cell-intrinsic mechanism associated with the differentiation of T cells into effector cells, we used the same methodology as before to analyse the TCR-β gene rearrangement diversity in sorted naive, activated/memory and effector T-cell populations from the PB of six healthy adult individuals. We also analysed the TCR-Vβ family representation at the protein level by flow cytometry.
We observed that both the naive (Figure 5a) and activated/memory T-cell pools (Figure 5b) expressed a wide range of TCR-Vβ families, which correlates with a high level of diversity in the TCR-Vβ family repertoire. In contrast, the effector population displayed a clear tendency towards the overexpression of certain TCR-Vβ families (different within individuals), with the concomitant absence of others (Figure 5c).
At the gene rearrangement level, we observed that the PCR product sizes from both the naive (Figure 5d) and activated/memory (Figure 5e) subpopulations followed a Gaussian distribution, reflecting a polyclonal TCR-β gene rearrangement. Again, the effector population (Figure 5f) significantly deviated from this Gaussian distribution by displaying a significant reduction in the TCR-β gene diversity in both the Vβ-Jβ and Dβ-Jβ regions.
Because, in diabetic individuals, the T cells have an important role in the maintenance of the systemic pro-inflammatory environment41 that is partially responsible for their impaired wound healing,11 we analysed the production of key inflammatory cytokines (IL-2, IFN-γ and TNF-α) by each of the sorted T-cell populations.
The naive and activated/memory T cells from the CD4+ (Figure 6a) or CD8+ (Figure 6b) subsets were both able to secrete IL-2 upon stimulation with PMA and ionomycin. However, only a minimal IL-2 production level was observed in effector T cells. The percentage of IL-2-secreting cells was higher in the activated/memory T cell than in the naive T-cell pools (P<0.01 for CD8; P<0.05 for CD4).
In contrast, both IFN-γ and TNF-α expression levels were only detected on the activated/memory and effector T cells, with a significantly higher expression level of IFN-γ in the effector T-cell population compared with the activated/memory population (P<0.01; Figure 6).
The early studies involving murine models42, 43 unravelled a dual role of T cells in both the inflammatory and proliferation phases of wound healing. Although wound healing impairment has usually been associated with the effect of cytotoxic CD8+ T cells, the subset of T cells responsible for wound healing enhancement remained to be identified.44 Using a different approach to this problem, we analysed how diabetes, in general, and DFU, in particular, affect TCR diversity. We also analysed the relative distribution of the most representative T-cell populations.
We demonstrated, for the first time, that DFU patients show a significantly reduced blood T-cell TCR-β repertoire diversity that directly correlates with both a decrease in the naive T cell and a concomitant increase in the effector T-cell pools. Our data clearly show that effector T cells display a significantly reduced TCR-β repertoire diversity. Because T cells tend to accumulate in diabetic patients (especially in those with acute DFU), the overall TCR-β repertoire diversity is reduced in these patients. The BMI of the diabetic patients and controls was similar (data not shown), thereby excluding obesity as the cause for the restricted TCR-β repertoire diversity.
Based on our data, we cannot infer that the TCR-β diversity observed in these patients was decreased to the point where the T-cell pool would fail to recognize antigens, which could, as previously observed in aged individuals, impair the immune response to subsequent infections by different pathogens.27, 33, 34 Nevertheless, our data indicate that a reduced TCR-β diversity is present in most diabetic patients, is more severe in DFU patients and persists after DFU healing. Further experiments are needed to construct evidence-based mathematical models that could predict the effects of TCR-β restriction on the immune function. Longitudinal studies are underway to determine whether, as expected, diabetic patients with a significantly reduced TCR-β repertoire diversity are more prone to DFU.
Surprisingly, we also found that diabetic patients with chronic foot ulceration usually have a similar naive and effector T-cell pool size to those of diabetic patients without foot ulcers. However, a considerably larger cohort will be needed to understand the reasons behind this observation because the chronic DFU patient cohort was very heterogeneous compared with the acute DFU cohort. Indeed, the chronic DFU cohort comprised patients with wounds at different stages, patients who were already in remission or patients who were given different treatments.
Our results also suggest that diabetes alone does not cause a severe reduction in the TCR-β diversity, presumably because the systemic pro-inflammatory environment is not sufficient to fully drive T-cell activation and promote clonal expansion. Nevertheless, the pro-inflammatory environment observed in diabetic patients seems to enhance clonal expansion, leading to a significant decrease in the naive T-cell subset with an accumulation of T cells at various stages of activation. In fact, some diabetic individuals who do not have active or previous foot ulcerations, already have a significant increase in the percentage and number (data not shown) of effector T cells and display various large clonal expansions. This suggests that the accumulation of effector T cells and the concomitant reduction in the overall TCR-Vβ diversity represent a continuous phenomenon driven by diabetes.
Alternatively, our results partially explain the reason behind the self-sustaining systemic inflammatory environment in diabetics. We have shown that the effector T cells, which tend to accumulate in diabetic patients, are the major producers of the IFN-γ and TNF-α inflammatory cytokines that, in turn, enhance naive T-cell activation and differentiation.45, 46 Importantly, activated/memory T cells also contribute to the observed systemic inflammatory environment to a smaller extent by producing lower levels of IFN-γ and TNF-α. TNF-α alone has been shown to have various harmful effects on diabetic wound healing, such as the inhibition of fibroblasts and keratinocytes proliferation and migration,47, 48 the induction of apoptosis in endothelial cells and pericytes, or the increase in the expression of the FOXO1 transcription factors.49, 50 In fact, the inhibition of TNF-α in vivo significantly improves wound closure in animal models.51 Our group has already demonstrated that neurotensin, either in vitro52, 53 or when used in wound dressings,54 inhibits TNF-α expression, reduces inflammation and promotes wound healing in diabetic mice. Our results also partly explain why T-cell migration is altered independently of the presence of foot ulcerations in diabetic patients.
Although we did not observe any difference in the expression of the skin homing receptor CCR4 between the T cells from diabetic individuals and controls, the expression of the inflammatory CHRs CCR5, CXCR1 and CXCR3 was significantly altered. In non-diabetic individuals, the expression of the early inflammatory/Th1-related CHRs CCR5 and CXCR3 is observed in both activated/memory and effector T cells, whereas the expression of CXCR1 is observed only in the effector T cells. In the T cells from diabetic patients, a significant reduction in the expression of these CHRs was observed, including in patients without DFU.
The in vitro stimulation assays mimicking the pro-inflammatory environment observed in diabetes revealed a reduction in the CCR5 and CXCR1 expression levels in T cells. In contrast, a clear increase in CXCR3 expression was observed after T-cell stimulation. The internalisation of CXCR3 by IFN-γ-activated venous endothelial cells (as observed in diabetic patients) has already been described.55 Because our cultures only contained blood mononuclear cells, this effect could not be observed and might explain the differences observed between the in vitro and in vivo CXCR3 expression changes.
We do not yet understand how and why the expression of these CHRs is reduced, but, collectively with previous studies, our results lead us to speculate that overstimulation could promote their internalisation.56, 57 Nevertheless, the profound reduction in the expression of these CHRs on the T cells from diabetic patients is expected to adversely impact T-cell migration to inflamed tissues such as diabetic foot ulcers.
In conclusion, our results strongly emphasize the dysfunctional immune response observed in diabetic patients. For the first time, we have analysed the effect of diabetes on the TCR repertoire diversity in circulating TCR-αβ+ T cells and on the distribution of T-cell populations. Our results showed that diabetes has a profound impact on the circulating T-cell pool, increasing the naive/effector T-cell ratio and reducing TCR-β repertoire diversity.
Conversely, we have shown that the concomitant and continuous accumulation of both CD4+ and CD8+ effector T cells may be responsible for the abnormally high IFN-γ and TNF-α levels observed in diabetic patients, and may lead to a reduction of the inflammatory CHR expression, which could possibly affect T-cell migration into inflamed tissues.
Because the accumulation of effector T cells appears central to the DFU pathology, immunotherapeutic strategies should be devised in order to diminish T-cell activation and tissue accumulation. Moreover, the number of effector T cells and the overall TCR-β repertoire diversity may hold a prognostic value in the treatment of DFU and possibly other diabetes-associated complications.
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This work was financed by FEDER funds by the operational program Factors of Competitivity – COMPETE, by the Portuguese Foundation for Science and Technology (FCT) - EXCL/DTP-PIC/0069/2012, PEst-C/SAU/LA0001/2013 and UID/NEU/04539/2013, the EFSD European Research Programme in Microvascular Complications of Diabetes supported by Novartis, and Forum Hematológico do Norte, Portugal. Eugénia Carvalho is partly funded by the Arkansas Biosciences Institute, the major research component of the Arkansas Tobacco Settlement Proceeds Act of 2000, NIH P30AG028718, and NIH RO1 AG033761.
The authors declare no conflict of interest.
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