Abstract Background and Aims Immune cellular responses are implicated in all clinical aspects of kidney transplantation. There is little data regarding the additional value of regular monitoring of immune cells subsets expression in kidney transplant recipients (KTRs). The aim of our prospective study was a longitudinal follow-up analysis of monocytes subpopulations, natural killer (NK) cells and lymphocytes subsets including regulatory T cells (Tregs) in the circulation of KTRs and potential clinical correlations. Method 48 stable KTRs were initially enrolled. All KTRs were under immunosuppressive regimen with corticosteroids, mycophenolate mofetil or mycophenolate acid and calcineurin inhibitors (CNIs). Exclusion criteria were history or development during follow-up of acute rejection, cardiovascular disease, malignancy and active or chronic infections. Patients were followed for 12 months. The peripheral blood immune cell subsets CD14++CD16-, CD14++CD16+ and CD14+CD16++ absolute values and percentages out of total monocytes and NK cells (CD3+CD16+56+), CD3-CD19+ B lymphocytes, CD3+ CD4+ T cells, CD3+CD8+ T cells and Tregs (CD4+CD25+ FoxP3+) absolute values and percentages out of total lymphocytes were measured by flow cytometry at baseline (T0) and after 12 months (T1). Clinical and laboratory parameters were recorded at T0 and T1. Delta (Δ) eGFR and Δ spot urine protein to creatinine ratio (ΔUPCR) were defined as their respective differences between T1 and T0. Likewise, Delta (Δ) of immune cells subtypes or laboratory indices was defined as their respective difference between T1 and T0. Results 35 KTRs (mean age 53 ± 9.28 years, 71% males, mean transplant vintage 96 ± 66 months, 63% on Tacrolimus and 37% on Cyclosporine) were included in the final analysis. Significant differences were observed between T0 and T1 in monocytes number (653 ± 244 and 538 ± 197/μL respectively, p = 0.001), monocytes percentage (7.6 ± 2.9 and 6.6 ± 2.2% respectively, p = 0.006) as well as in the number of classical CD14++CD16- monocytes (534 ± 225 and 452 ± 185/μL respectively, p = 0.04). The rest immune cells subsets did not show any significant differences between T0 and T1. Mean eGFR declined from 58 ± 17 at T0 to 53 ± 18 ml/min/1.73 m2 at T1 (p = 0.004). No significant changes were observed between T0 and T1 in median UPCR [0.16 (IRQ, 0.09-0.56) at T0 and 0.16 (IQR, 0.10-0.70) gr protein/gr creatine at T1, p = 0.489], in median CRP [4.0 (IQR, 3-7) at T0 and 5 (IQR, 2.5-7.5) mg/L) at T1, p = 0.919], in mean ESR (20 ± 14 at T0 and 22 ± 19 mm/hour at T1, p = 0.381) or other parameters, including CNIs blood levels. ΔeGFR was correlated with the T0 percentage of monocytes (rho = 0.359, p = 0.037), the T0 number and T0 percentage of CD14++CD16+ monocytes (rho= 0.502, p = 0.003 and rho = 0.438, p = 0.008 respectively). On the other hand, a borderline inverse correlation was observed between ΔeGFR and ΔCD14++CD16+ monocytes number (rho = −0.339, p = 0.05). Additional correlates of ΔeGFR included serum albumin at T0 (rho = 0.395, p = 0.021) and Δuric acid (rho = 0.567, p = 0.000). At stepwise linear regression analysis, CD14++CD16+ monocytes (β = 0.338, p = 0.04) and Δuric acid (β = 0.477, p = 0.006) remained independent significant correlates of ΔeGFR. ΔUPCR was significantly correlated with the percentage of B-lymphocytes (rho = 0.385, p = 0.027) and CD4+ T-cells (rho = 0.352, p = 0.044) at T0, and inversely correlated with the T0 percentage of T-lymphocytes (rho = −0.402, p = 0.02) and CD8+ T cells (rho = −0.603, p = 0.000) as well as with Δhemoglobin (rho = −0.385, p = 0.027). At stepwise linear regression analysis, only the CD8+ T cells percentage at T0 remained independently correlated to ΔUPCR (β = –0.379, p = 0.03). Conclusion The results of our study indicate that intermediate CD14++CD16+ monocytes are associated with annual eGFR change whereas CD8+ T cells negatively correlate with the annual trend of proteinuria change in KTRs. Further research is needed to clarify underlying pathophysiological mechanisms for these findings. Finally, future studies including larger cohorts and with longer follow-up are required to specify the potential utility of immune subpopulations monitoring as potential prognostic biomarkers in KTRs.
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