Effects of two immunosuppression regimens on T-lymphocyte subsets in elderly kidney transplant recipients.

Background: Despite the growing number of elderly kidney transplant (Ktx) recipients, few studies have examined the effects of immunosuppression on their lymphocyte profiles. Methods: We evaluated the early conversion from mycophenolate sodium (MPS) to everolimus (EVL) after rabbit antithymocyte globulin (rATG) 2 mg/kg induction in elderly kidney recipients. Three groups of KTx patients were compared: (a) Young (n=20, 36 ± 7 y) receiving standard immunosuppression (Group A1) (prednisone, tacrolimus, and MPS), (b) Elderly (n=35, 65 ± 3 y) receiving standard immunosuppression (Group B1), and (c) Elderly (n=16, 65 ± 3 y) with early (mean 30 d) conversion from MPS to EVL (Group B2). Naive, memory, and regulatory peripheral blood TCD4+ lymphocytes were quantified at 0, 30, and 365 d. Results: Results are reported as [mean(p25-p75)]. Young recipients had higher lymphocyte counts at baseline [2,100(1,630-2,400) vs. 1,310 (1,000-1,600)/mm3, p<0.0001] maintained higher counts within 365 d [1,850(1,590-2,120) vs. 1,130(460-1,325)/mm3, p=0.018 and vs. 1,410(805-1,895)/mm3, p=0.268]. Elderly recipients showed a decrease in lymphocytes within 30 d [1,310(1,000-1,600) vs. 910(700-1,198)/mm3, p=0.0012] with recovery within 365 d. The same pattern was observed in total lymphocytes and TCD4+ counts. Rabbit antithymocyte globulin induced a reduction in central memory T-cell percentages at 30 d in both young recipients [6.2(3.77-10.8) vs. 5.32(2.49-7.28)% of CD4+, p=0.036] and in elderly recipients [8.17(5.28-12.88) vs. 6.74(4.36-11)% of CD4+, p=0.05] on standard immunosuppression, returning to baseline at 365 d in elderly recipients but not in young recipients. Regulatory T CD39+ cells (Treg) percentages decreased at 30 d in elderly recipients [2.1(1.23-3.51) vs. 1.69(0.8-2.66)% of CD4+, p=0.0028] and in young recipients [1.29(0.45-1.85) vs. 0.84(0.18-1.82)% of CD4+, p=0.0038], returning to baseline at 365 d in elderly recipients [2.1(1.23-3.51) vs. 2.042(0.88-2.42)% of CD4+], but not in young recipients [1.29(0.45-1.85) vs. 0.86(0.7-1.34) % of CD4+]. The elderly everolimus conversion group did not show significant changes in cell profile over time or compared to elderly recipients with standard immunosuppression. Conclusion: Aging favored the maintenance of Treg during the late transplantation period despite ongoing immunosuppression. Lymphocyte depletion due to rATG was more prominent in elderly recipients and affected memory subsets with a temporary reduction in central memory T cells. However, conversion to everolimus did not impact Treg profile. Reducing the dose of rATG in elderly recipients seems necessary for the expected lymphocyte changes with EVL to occur. Clinical trial registration: nEverOld Trial, identifier NTC01631058.

Propolis anti-inflammatory effects on MAGE-1 and retinoic acid-treated dendritic cells and on Th1 and T regulatory cells.

Background: Propolis exhibits huge potential in the pharmaceutical industry. In the present study, its effects were investigated on dendritic cells (DCs) stimulated with a tumor antigen (MAGE-1) and retinoic acid (RA) and on T lymphocytes to observe a possible differential activation of T lymphocytes, driving preferentially to Th1 or Treg cells. Methods: Cell viability, lymphocyte proliferation, gene expression (T-bet and FoxP3), and cytokine production by DCs (TNF-α, IL-10, IL-6 and IL-1ß) and lymphocytes (IFN-γ and TGF-ß) were analyzed. Results: MAGE-1 and RA alone or in combination with propolis inhibited TNF-α production and induced a higher lymphoproliferation compared to control, while MAGE-1 + propolis induced IL-6 production. Propolis in combination with RA induced FoxP3 expression. MAGE-1 induced IFN-γ production while propolis inhibited it, returning to basal levels. RA inhibited TGF-ß production, what was counteracted by propolis. Conclusion: Propolis affected immunological parameters inhibiting pro-inflammatory cytokines and favoring the regulatory profile, opening perspectives for the control of inflammatory conditions.

Propolis anti-inflammatory effects on MAGE-1 and retinoic acid-treated dendritic cells and on Th1 and T regulatory cells

Background: Propolis exhibits huge potential in the pharmaceutical industry. In the present study, its effects were investigated on dendritic cells (DCs) stimulated with a tumor antigen (MAGE-1) and retinoic acid (RA) and on T lymphocytes to observe a possible differential activation of T lymphocytes, driving preferentially to Th1 or Treg cells. Methods: Cell viability, lymphocyte proliferation, gene expression (T-bet and FoxP3), and cytokine production by DCs (TNF-α, IL-10, IL-6 and IL-1ß) and lymphocytes (IFN-γ and TGF-ß) were analyzed. Results: MAGE-1 and RA alone or in combination with propolis inhibited TNF-α production and induced a higher lymphoproliferation compared to control, while MAGE1 + propolis induced IL-6 production. Propolis in combination with RA induced FoxP3 expression. MAGE-1 induced IFN-γ production while propolis inhibited it, returning to basal levels. RA inhibited TGF-ß production, what was counteracted by propolis. Conclusion: Propolis affected immunological parameters inhibiting pro-inflammatory cytokines and favoring the regulatory profile, opening perspectives for the control of inflammatory conditions.(AU)

Continuous Modeling of T CD4 Lymphocyte Activation and Function.

T CD4+ cells are central to the adaptive immune response against pathogens. Their activation is induced by the engagement of the T-cell receptor by antigens, and of co-stimulatory receptors by molecules also expressed on antigen presenting cells. Then, a complex network of intracellular events reinforce, diversify and regulate the initial signals, including dynamic metabolic processes that strongly influence both the activation state and the differentiation to effector cell phenotypes. The regulation of cell metabolism is controlled by the nutrient sensor adenosine monophosphate-activated protein kinase (AMPK), which drives the balance between oxidative phosphorylation (OXPHOS) and glycolysis. Herein, we put forward a 51-node continuous mathematical model that describes the temporal evolution of the early events of activation, integrating a circuit of metabolic regulation into the main routes of signaling. The model simulates the induction of anergy due to defective co-stimulation, the CTLA-4 checkpoint blockade, and the differentiation to effector phenotypes induced by external cytokines. It also describes the adjustment of the OXPHOS-glycolysis equilibrium by the action of AMPK as the effector function of the T cell develops. The development of a transient phase of increased OXPHOS before induction of a sustained glycolytic phase during differentiation to the Th1, Th2 and Th17 phenotypes is shown. In contrast, during Treg differentiation, glycolysis is subsequently reduced as cell metabolism is predominantly polarized towards OXPHOS. These observations are in agreement with experimental data suggesting that OXPHOS produces an ATP reservoir before glycolysis boosts the production of metabolites needed for protein synthesis, cell function, and growth.

Trypanosoma cruzi Induces B Cells That Regulate the CD4+ T Cell Response.

Trypanosoma cruzi infection induces a polyclonal B cell proliferative response characterized by maturation to plasma cells, excessive generation of germinal centers, and secretion of parasite-unrelated antibodies. Although traditionally reduced to the humoral response, several infectious and non-infectious models revealed that B lymphocytes could regulate and play crucial roles in cellular responses. Here, we analyze the trypomastigote-induced effect on B cells, their effects on CD4+ T cells, and their correlation with in vivo findings. The trypomastigotes were able to induce the proliferation and the production of IL-10 or IL-6 of naïve B cells in co-culture experiments. Also, we found that IL-10-producing B220lo cells were elicited in vivo. We also found up-regulated expression of FasL and PD-L1, proteins involved in apoptosis induction and inhibition of TCR signaling, and of BAFF and APRIL mRNAs, two B-cell growth factors. Interestingly, it was observed that IL-21, which plays a critical role in regulatory B cell differentiation, was significantly increased in B220+/IL-21+ in in vivo infections. This is striking since the secretion of IL-21 is associated with T helper follicular cells. Furthermore, trypomastigote-stimulated B-cell conditioned medium dramatically reduced the proliferation and increased the apoptotic rate on CD3/CD28 activated CD4+ T cells, suggesting the development of effective regulatory B cells. In this condition, CD4+ T cells showed a marked decrease in proliferation and viability with marginal IL-2 or IFNγ secretion, which is counterproductive with an efficient immune response against T. cruzi. Altogether, our results show that B lymphocytes stimulated with trypomastigotes adopt a particular phenotype that exerts a strong regulation of this T cell compartment by inducing apoptosis, arresting cell division, and affecting the developing of a proinflammatory response.

An Integrative Network Modeling Approach to T CD4 Cell Activation.

The adaptive immune response is initiated by the interaction of the T cell antigen receptor/CD3 complex (TCR) with a cognate peptide bound to a MHC molecule. This interaction, along with the activity of co-stimulatory molecules and cytokines in the microenvironment, enables cells to proliferate and produce soluble factors that stimulate other branches of the immune response for inactivation of infectious agents. The intracellular activation signals are reinforced, amplified and diversified by a complex network of biochemical interactions, and includes the activity of molecules that modulate the activation process and stimulate the metabolic changes necessary for fulfilling the cell energy demands. We present an approach to the analysis of the main early signaling events of T cell activation by proposing a concise 46-node hybrid Boolean model of the main steps of TCR and CD28 downstream signaling, encompassing the activity of the anergy factor Ndrg1, modulation of activation by CTLA-4, and the activity of the nutrient sensor AMPK as intrinsic players of the activation process. The model generates stable states that reflect the overcoming of activation signals and induction of anergy by the expression of Ndrg1 in the absence of co-stimulation. The model also includes the induction of CTLA-4 upon activation and its competition with CD28 for binding to the co-stimulatory CD80/86 molecules, leading to stable states that reflect the activation arrest. Furthermore, the model integrates the activity of AMPK to the general pathways driving differentiation to functional cell subsets (Th1, Th2, Th17, and Treg). Thus, the network topology incorporates basic mechanism associated to activation, regulation and induction of effector cell phenotypes. The model puts forth a conceptual framework for the integration of functionally relevant processes in the analysis of the T CD4 cell function.