Abstract
Immune thrombocytopenia (ITP) is an autoimmune disorder characterized by increased platelet destruction and impaired platelet production. The role of T-cell subsets and platelet surface markers in ITP pathogenesis remains incompletely understood. To evaluate T-cell subpopulations and platelet surface marker expression in patients with chronic ITP compared with healthy controls using flow cytometry. This prospective case-control study included 26 chronic ITP patients and 25 healthy controls from the Hematology Department of Mersin University Hospital. Flow cytometric analysis was performed to assess CD3+, CD4+, CD8+, CD25+, CD45RA+, CD62L−, and platelet surface markers including CD41, CD42, and CD61. Statistical analyses were performed using SPSS version 22. ITP patients demonstrated significantly lower platelet counts (97,038 ± 64,596 vs. 256,920 ± 48,873/µL, p < 0.001) and higher mean platelet volume values (11.67 ± 1.46 vs. 10.46 ± 0.77 fL, p = 0.001) compared with healthy controls. CD45RA+/CD4 + ratios were significantly lower in ITP patients (10.52 ± 5.88 vs. 14.45 ± 7.21%, p = 0.038). CD62L− expression was also decreased in the ITP group (51.50 ± 12.16 vs. 60.68 ± 8.40%, p = 0.003). Among platelet surface markers, CD41 and CD61 expressions were significantly reduced in ITP patients compared with controls (p < 0.001 for both). Although CD42 expression did not differ significantly between the overall groups, subgroup analysis demonstrated significantly lower CD42 expression in patients with platelet counts below 30,000/µL (p < 0.001). This study demonstrates alterations in T-cell differentiation markers and platelet surface glycoproteins in patients with chronic ITP. Reduced CD45RA+/CD4 + ratios, altered CD62L expression, and decreased CD41 and CD61 levels suggest ongoing immune dysregulation and abnormal platelet biology in these patients. Further longitudinal and functional studies are needed to clarify the mechanistic and clinical significance of these findings.
Keywords: Immune thrombocytopenia, Flow cytometry, T-lymphocytes, CD45RA, CD62L, Platelet glycoproteins
Introduction
Immune thrombocytopenia (ITP) is an acquired autoimmune disorder characterized by isolated thrombocytopenia (platelet count < 100 × 10⁹/L) in the absence of other causes of thrombocytopenia [1]. The pathogenesis of ITP involves complex immune dysregulation affecting both cellular and humoral immunity, leading to increased platelet destruction and impaired platelet production [2, 3].
Recent advances in understanding ITP pathophysiology have revealed the crucial role of T-cell subsets in disease development and progression. T helper (Th) cells, cytotoxic T cells, and regulatory T cells (Tregs) play pivotal roles in maintaining immune homeostasis and tolerance [4]. Disruption of the balance between effector and regulatory T-cell populations has been implicated in various autoimmune diseases, including ITP [5, 6].
Studies have demonstrated that ITP patients exhibit alterations in T-cell subpopulations, particularly in the distribution of naive, memory, and effector T cells [7]. CD45RA and CD62L are important markers for T-cell differentiation and activation status. CD45RA is expressed on naive T cells and terminal effector memory T cells (TEMRA), while CD62L (L-selectin) is a lymph node homing receptor expressed on naive and central memory T cells [8, 9]. The loss of CD62L expression is associated with T-cell activation and differentiation into effector cells [10].
The role of cytotoxic CD8 + T cells in ITP has gained increasing attention. Recent evidence suggests that terminally differentiated effector memory CD8 + T cells (CD45RA+CD62L-) are expanded in ITP patients and may contribute to platelet destruction through direct cytotoxic mechanisms [11]. These TEMRA cells show enhanced cytotoxic function and persist over time, particularly in patients with refractory disease [12].
CD25, the α-chain of the interleukin-2 receptor, is expressed on activated T cells and regulatory T cells. CD4 + CD25+ regulatory T cells play a crucial role in maintaining immune tolerance and preventing autoimmune responses [13]. Deficiency or dysfunction of Tregs has been reported in ITP patients, contributing to the breakdown of self-tolerance against platelet antigens [14, 15].
Platelet surface glycoproteins, including CD41 (GPIIb), CD42 (GPIb), and CD61 (GPIIIa), are major targets of autoantibodies in ITP and serve as important markers for platelet identification and function assessment [16, 17]. Flow cytometric analysis of these markers provides valuable insights into platelet biology and the extent of platelet destruction in ITP patients [18].
Despite significant progress in understanding ITP pathogenesis, the precise mechanisms underlying immune dysregulation remain incompletely understood. Furthermore, there is a need for better biomarkers to predict treatment response and disease course. Flow cytometry offers a powerful tool for comprehensive immunophenotyping and has become increasingly important in ITP research and clinical management [19, 20].
This study aimed to comprehensively evaluate T-cell subpopulations and platelet surface marker expression in ITP patients compared to healthy controls using flow cytometry, with the goal of identifying potential biomarkers and therapeutic targets for improved disease management.
Materials and methods
This prospective case-control study was conducted at the Hematology Department of Mersin University Faculty of Medicine Hospital between November 1, 2022, and October 1, 2023. The study protocol received approval from the Mersin University Ethics Committee (approval number: 2023/744, dated November 1, 2023). Adherence to ethical guidelines was maintained throughout the study, ensuring compliance with the 1964 Declaration of Helsinki and its subsequent revisions. All participants provided voluntary informed consent before their inclusion.
The study population consisted of 26 patients with chronic Immune Thrombocytopenia (ITP) and 25 healthy volunteers who served as a control group. Patients in the ITP group were diagnosed according to established criteria and were in the chronic phase of the disease, defined as a duration of more than 12 months. Inclusion criteria for all participants required an age between 18 and 80 years and presentation to the clinic between November 1, 2022, and October 1, 2023. The ITP group specifically included patients with a confirmed ITP diagnosis, while the control group consisted of healthy individuals without ITP or thrombocytopenia. Participants were excluded if they were pregnant, had hematologic or oncologic malignancies, or presented with any conditions known to cause secondary thrombocytopenia.
Blood samples were collected in EDTA-containing tubes and were processed within 2 h of collection. All flow cytometric analyses were performed on the same day the samples were collected. Flow cytometric analysis was performed using a Beckman Coulter Navios-USA device. Data were recorded and analyzed using Kaluza software (Treestar, Ashland, OR, USA).
Surface staining protocol (CD45, CD3, CD4, CD8, CD45RA)
For the surface staining of specified markers, antibodies were pipetted according to kit procedures, and 100 µL of the sample was added to each tube. These samples were incubated for 15 min at room temperature in the dark. Following incubation, the tubes were vortexed, 1 mL of lysis solution was added, and the samples were incubated again in the dark before analysis.
CD4/CD25 staining
For CD4/CD25 analysis, lymphocytes were first isolated using Ficoll. Surface staining antibodies were then added, and the samples were incubated for 15 min at room temperature in the dark. After incubation, a washing solution was added, and the samples were centrifuged at 1300 rpm for 5 min. Subsequently, 500 µL of CellFix solution was added for a 10-minute incubation, followed by the addition of 500 µL of permeabilizing solution for another 10-minute incubation in the dark. Intracellular staining antibodies were then added and incubated for 30 min at room temperature in the dark. After a final wash, the samples were analyzed.
Platelet staining protocol (CD41, CD42, CD61, CD62L)
The platelet staining protocol involved adding 100 µL of patient blood to each tube, which was then diluted with 900 µL of Isoflow. Antibodies were added, the samples were vortexed, and after a 15-minute incubation at room temperature in the dark, they were analyzed by flow cytometry.
The performance of the flow cytometer was evaluated daily using a “flow checks” control solution. System accuracy was assessed monthly through the UK NEQAS external quality assessment program.
Demographic data, platelet counts, and various flow cytometric parameters (CD3+, CD4+, CD8+, CD25+, CD45RA+, CD62L-, CD41, CD42, CD61, CD107a) were recorded for all participants. For the ITP patient group, treatment history and splenectomy status were also documented.
Statistical analysis
All statistical analyses were conducted using IBM SPSS version 22 (SPSS Inc., Chicago, IL, USA). The Shapiro–Wilk test was used to assess the normality of data distribution. Continuous variables were expressed as mean ± standard deviation (SD) and median (minimum–maximum) values, while categorical variables were presented as numbers (n) and percentages (%). For comparisons between two groups, the independent samples t-test or Mann–Whitney U test was used, as appropriate. For comparisons among multiple groups, one-way ANOVA followed by Bonferroni post-hoc analysis or Kruskal–Wallis analysis followed by Mann–Whitney U tests was performed, as appropriate. A p-value of less than 0.05 was considered statistically significant.
Results
The study included 26 chronic ITP patients (16 female, 10 male) and 25 healthy controls (18 female, 7 male). The mean age of the ITP patients (46.15 ± 13.20 years) was statistically significantly higher than that of the control group (36.72 ± 10.21 years) (p = 0.001). However, there was no significant difference in gender distribution between the groups (16 F/10 M vs. 18 F/7 M, p = 0.525). Lymphocyte percentages were found to be similar in the ITP patient group (31.98 ± 8.16%) and the control group (31.18 ± 7.31%), with no statistically significant difference observed between them (p = 0.711) (Table 1).
Table 1.
Demographic and clinical characteristics
| Parameter | ITP Patients (n = 26) | Controls (n = 25) | p-value |
|---|---|---|---|
| Age (years) | 46.15 ± 13.20 | 36.72 ± 10.21 | 0.001 |
| Gender (F/M) | 16/10 | 18/7 | 0.525 |
| Lymphocyte % | 31.98 ± 8.16 | 31.18 ± 7.31 | 0.711 |
In the comparative analysis of hematologic and flow cytometric parameters between ITP patients and healthy controls, platelet counts in ITP patients (97,038 ± 64,596/µL) were found to be significantly lower than in the control group (256,920 ± 48,873/µL) (p < 0.001). Conversely, the mean platelet volume (MPV) was significantly higher in ITP patients (11.67 ± 1.46 fL) compared to controls (10.46 ± 0.77 fL) (p = 0.001). Analysis of T-cell subsets revealed no statistically significant differences between the groups for total CD3 + T-cell percentage (72.02 ± 10.03% vs. 74.88 ± 7.64%, p = 0.260), the CD4+/CD3 + ratio (38.87 ± 8.21% vs. 42.63 ± 8.14%, p = 0.107), or the CD8+/CD3 + ratio (31.49 ± 10.25% vs. 28.51 ± 6.24%, p = 0.220). Similarly, the CD25+/CD4 + ratio, reflecting regulatory T-cells, did not differ significantly between groups (p = 0.204). However, among T-cell differentiation and activation markers, the CD45RA+/CD4 + ratio was significantly lower in ITP patients (10.52 ± 5.88%) compared to controls (14.45 ± 7.21%) (p = 0.038), and CD62L- expression was significantly decreased in ITP patients (51.50 ± 12.16%) versus controls (60.68 ± 8.40%) (p = 0.003). In the analysis of platelet surface markers, platelet percentage was significantly lower in ITP patients compared with healthy controls (1.85 ± 1.13% vs. 4.16 ± 1.01%, p < 0.001). Among platelet surface markers, both CD41 and CD61 expressions were significantly reduced in ITP patients compared with healthy controls (p < 0.001 for both), whereas CD42 expression did not differ significantly between groups. Finally, the CD62L-/platelet ratio, an indicator of activated platelet-T cell interactions, was significantly higher in ITP patients (0.78 ± 1.29) than in controls (0.24 ± 0.21) (p = 0.044) (Table 2).
Table 2.
Hematologic parameters and flow cytometric analysis in ITP patients vs. controls
| Parameter | Group | N | Mean ± SD | Min-Max | p-value |
|---|---|---|---|---|---|
| Age (years) | ITP | 26 | 46.15 ± 13.20 | 24.00–72.00 | 0.001 |
| Control | 25 | 36.72 ± 10.21 | 23.00–64.00 | ||
| Lymphocyte % | ITP | 26 | 31.98 ± 8.16 | 19.53–57.71 | 0.711 |
| Control | 25 | 31.18 ± 7.31 | 11.11–42.78 | ||
| Platelet Count | ITP | 26 | 97,038.46 ± 64,596.27 | 3,000-275,000 | < 0.001 |
| Control | 25 | 256,920.00 ± 48,873.07 | 156,000-357,000 | ||
| MPV (fL) | ITP | 18 | 11.67 ± 1.46 | 9.90–14.30 | 0.001 |
| Control | 25 | 10.46 ± 0.77 | 9.10–12.00 | ||
| CD3+ (%) | ITP | 26 | 72.02 ± 10.03 | 43.85–85.24 | 0.260 |
| Control | 25 | 74.88 ± 7.64 | 46.12–87.57 | ||
| CD4+/CD3+ (%) | ITP | 26 | 38.87 ± 8.21 | 24.11–50.60 | 0.107 |
| Control | 25 | 42.63 ± 8.14 | 28.06–58.54 | ||
| CD8+/CD3+ (%) | ITP | 26 | 31.49 ± 10.25 | 11.69–55.36 | 0.220 |
| Control | 25 | 28.51 ± 6.24 | 15.11–40.21 | ||
| CD25+/CD4+ (%) | ITP | 26 | 1.81 ± 0.75 | 0.60–3.32 | 0.204 |
| Control | 25 | 2.11 ± 0.87 | 0.80–4.37 | ||
| CD45RA+ (%) | ITP | 26 | 55.25 ± 8.93 | 33.64–74.32 | 0.812 |
| Control | 25 | 55.85 ± 9.16 | 37.41–69.83 | ||
| CD45RA+/CD4+ (%) | ITP | 26 | 10.52 ± 5.88 | 3.04–22.90 | 0.038 |
| Control | 25 | 14.45 ± 7.21 | 5.11–30.31 | ||
| CD62L- (%) | ITP | 26 | 51.50 ± 12.16 | 30.57–83.85 | 0.003 |
| Control | 25 | 60.68 ± 8.40 | 39.49–72.57 | ||
| Platelet % (%) | ITP | 26 | 1.85 ± 1.13 | 0.26–4.88 | < 0.001 |
| Control | 25 | 4.16 ± 1.01 | 2.49–6.16 | ||
| CD42 (%) | ITP | 26 | 75.76 ± 23.2 | 2.68–95.65 | 0.330 |
| Control | 25 | 94.38 ± 2.25 | 86.32–96.85 | ||
| CD41 (%) | ITP | 26 | 75.80 ± 23.12 | 3.07–95.72 | < 0.001 |
| Control | 25 | 94.42 ± 2.23 | 86.57–96.98 | ||
| CD61 (%) | ITP | 26 | 75.19 ± 23.23 | 1.92–95.22 | < 0.001 |
| Control | 25 | 94.01 ± 2.21 | 86.47–96.41 | ||
| CD107a (%) | ITP | 26 | 0.90 ± 0.62 | 0.20–2.73 | 0.257 |
| Control | 25 | 1.07 ± 0.45 | 0.39–2.42 | ||
| CD62L-/Platelet | ITP | 26 | 0.78 ± 1.29 | 0.04–6.24 | 0.044 |
| Control | 25 | 0.24 ± 0.21 | 0.02–0.68 |
ITP patients were stratified into three subgroups for analysis based on their platelet counts: <30,000/µL (n = 4), 30,000-100,000/µL (n = 11), and > 100,000/µL (n = 11). No statistically significant differences were found among these subgroups for parameters such as age, lymphocyte percentage, CD3+, CD4+/CD3+, CD8+/CD3+, CD25+/CD4+, CD45RA+, CD45RA+/CD4+, and CD62L- (p > 0.05). In contrast, the platelet percentage showed significant differences across the groups (0.51 ± 0.20%, 1.35 ± 0.40%, and 2.83 ± 0.97%, respectively; p < 0.001). CD41, CD42, and CD61 platelet surface marker expressions exhibited statistically significant differences among the platelet count groups (p < 0.001 for all). Specifically, the expressions of CD41, CD42, and CD61 were markedly lower in patients with platelet counts below 30,000/µL compared with the other two groups. The CD62L-/Platelet ratio did not show a significant difference between the groups (p = 0.460) (Table 3).
Table 3.
Analysis of ITP patients stratified by platelet count and flow cytometric parameters
| Parameter | < 30,000/µL (n = 4) | 30,000-100,000/µL (n = 11) | > 100,000/µL (n = 11) | p-value |
|---|---|---|---|---|
| Age (years) | 43.75 ± 10.05 | 48.55 ± 14.89 | 44.64 ± 13.14 | 0.743 |
| Lymphocyte % | 27.97 ± 4.07 | 31.55 ± 6.73 | 33.88 ± 10.27 | 0.468 |
| CD3+ (%) | 75.57 ± 3.36 | 74.22 ± 10.17 | 68.53 ± 10.98 | 0.320 |
| CD4+/CD3+ (%) | 39.42 ± 10.25 | 39.46 ± 8.24 | 38.07 ± 8.24 | 0.921 |
| CD8+/CD3+ (%) | 33.28 ± 7.72 | 34.11 ± 13.68 | 28.21 ± 6.10 | 0.389 |
| CD25+/CD4+ (%) | 1.61 ± 0.91 | 1.75 ± 0.75 | 1.95 ± 0.74 | 0.689 |
| CD45RA+ (%) | 61.01 ± 5.61 | 54.15 ± 6.05 | 54.24 ± 11.72 | 0.389 |
| CD45RA+/CD4+ (%) | 13.61 ± 6.86 | 10.58 ± 5.82 | 9.45 ± 5.84 | 0.551 |
| CD62L- (%) | 53.92 ± 9.61 | 52.22 ± 14.69 | 49.89 ± 10.97 | 0.835 |
| Platelet % (%) | 0.51 ± 0.20* | 1.35 ± 0.40* | 2.83 ± 0.97* | < 0.001 |
| CD42 (%) | 33.54 ± 32.12* | 76.86 ± 8.54* | 90.03 ± 4.94* | < 0.001 |
| CD41 (%) | 33.66 ± 31.91* | 76.88 ± 8.51* | 90.04 ± 4.93* | < 0.001 |
| CD61 (%) | 33.17 ± 32.32* | 76.11 ± 8.78* | 89.56 ± 4.88* | < 0.001 |
| CD107a (%) | 0.72 ± 0.58 | 1.07 ± 0.75 | 0.80 ± 0.48 | 0.489 |
| CD62L-/Platelet | 0.67 (0.18–6.24) | 0.39 (0.14–3.06) | 0.27 (0.04–1.18) | 0.460 |
*Significant difference between < 30,000/µL group and other groups (p < 0.05)
The clinical and laboratory data of the eight splenectomized patients in the study were analyzed. Of these patients, five were not receiving any active treatment, and three of these five had platelet counts exceeding 100,000/µL. It was observed that these patients, particularly those not on active treatment and with higher platelet counts, had higher CD25 + CD4+ ratios compared to patients with active disease. According to the data in the table, platelet counts for splenectomized patients ranged from 30,000/µL to 185,000/µL. The CD25+/CD4 + ratios varied widely, from a low of 0.599% in a patient receiving MMF to as high as 2.533% in an untreated patient (Table 4).
Table 4.
Clinical characteristics of the eight splenectomized ITP patients
| Treatment Status of the Cases | Platelet Count (/µL) | CD4+/CD3+ (%) | CD25+/CD4+ (%) |
|---|---|---|---|
| No treatment | 105,000 | 24.381 | 1.397 |
| No treatment | 95,000 | 46.365 | 2.194 |
| No treatment | 58,000 | 48.069 | 2.196 |
| MMF | 30,000 | 24.11 | 0.599 |
| No treatment | 110,000 | 45.75 | 2.533 |
| Eltrombopag | 185,000 | 30.759 | 0.808 |
| Eltrombopag | 59,000 | 30.404 | 1.626 |
| No treatment | 115,000 | 34.403 | 1.202 |
MMF: mycophenolate mofetil
The diagnosis years, treatment histories, and responses of the ITP patients were examined in detail. The treatment histories reveal the use of various agents, including steroids, IVIG, and eltrombopag. A total of fifteen patients had received eltrombopag, with six continuing the therapy at the time of the study. Twenty-four patients had received steroid treatment at some point in their disease course, with three achieving sustained remission without requiring additional therapy. Among five patients who received IVIG after steroid treatment, four achieved remission and showed higher CD25 + CD4+ ratios. The data highlight a wide range of diagnosis years, from 1995 to 2022, and diverse treatment combinations, underscoring the heterogeneous nature of ITP and the variability in treatment responses. For instance, one patient diagnosed in 2004 who received IVIG in 2021 had a platelet count of 139,000/µL, whereas another diagnosed in 2010 on ongoing eltrombopag therapy had a platelet count of 3,000/µL (Table 5).
Table 5.
Treatment history and response in ITP patients
| Diagnosis Year | Treatment History | Splenectomy | Platelet Count (/µL) | CD4+/CD3+ (%) | CD25+/CD4+ (%) |
|---|---|---|---|---|---|
| 2004 | 2021 IVIG | No | 139,000 | 38.74 | 2.243 |
| 2016 | 2017 Eltrombopag | No | 57,000 | 36.13 | 3.317 |
| 2007 | 2012 IVIG | No | 164,000 | 35.241 | 2.647 |
| 2018 | 2018 Eltrombopag | No | 275,000 | 46.708 | 2.513 |
| 2016 | 2016 Eltrombopag | No | 81,000 | 32.197 | 1.946 |
| 2009 | Steroids 10 years ago | Yes | 105,000 | 24.381 | 1.397 |
| 2018 | 2023 Eltrombopag | Yes | 95,000 | 46.365 | 2.194 |
| 2017 | 2022 IVIG | No | 75,000 | 49.84 | 2.202 |
| 2011 | 2020 Eltrombopag (ongoing) | No | 117,000 | 49.022 | 2.526 |
| 2022 | 2023 Eltrombopag | No | 25,000 | 45.777 | 1.396 |
| 2008 | 2008 Steroids | No | 228,000 | 34.141 | 2.685 |
| 1995 | 1995 Steroids-Danazol | Yes | 58,000 | 48.069 | 2.196 |
| 2021 | 2022 Eltrombopag (ongoing) | No | 54,000 | 28.702 | 1.362 |
| 2006 | 2023 MMF (ongoing) | Yes | 30,000 | 24.11 | 0.599 |
| 2010 | 2023 Eltrombopag, RTX 2015 | Yes | 110,000 | 45.75 | 2.533 |
| 2015 | 2019 Eltrombopag (ongoing) | No | 81,000 | 31.581 | 1.719 |
| 2010 | 2019 Eltrombopag (ongoing) | No | 3,000 | 44.303 | 2.789 |
| 2015 | No treatment | No | 61,000 | 41.032 | 0.721 |
| 2009 | 2009 Steroids | No | 70,000 | 50.599 | 0.722 |
| 2019 | 2019 Eltrombopag (ongoing) | No | 67,000 | 39.136 | 1.207 |
| 2020 | 2023 IVIG-Eltrombopag | No | 3,000 | 43.483 | 1.662 |
| 2021 | 2022 Eltrombopag | No | 122,000 | 31.445 | 0.86 |
| 2011 | 2022 Eltrombopag (ongoing) | Yes | 185,000 | 30.759 | 0.808 |
| 2006 | Eltrombopag 6 months (ongoing) | Yes | 59,000 | 30.404 | 1.626 |
| 2003 | No treatment | Yes | 115,000 | 34.403 | 1.202 |
| 2014 | 2016 IVIG | No | 144,000 | 48.224 | 2.087 |
This table compares basic hematological and T-cell subpopulation parameters between the ITP patients and the control group, reaffirming the findings previously presented in Table 2. According to the data, ITP patients have statistically significantly lower platelet counts (97,038.46 ± 64,596.27 vs. 256,920.00 ± 48,873.07) and higher MPV values (11.67 ± 1.46 vs. 10.46 ± 0.77) compared to controls. While no significant difference was found in the total CD3 + T-cell percentage (72.02 ± 10.03 vs. 74.88 ± 7.64), a trend towards a lower CD4+/CD3 + ratio (38.87 ± 8.21 vs. 42.63 ± 8.14) and a slight trend towards a higher CD8+/CD3 + ratio (31.49 ± 10.25 vs. 28.51 ± 6.24) were observed in ITP patients, though these differences did not reach statistical significance (Table 6).
Table 6.
Comparison of CD4 + and CD8 + T-cell levels between groups
| Parameter | Group | N | Mean ± SD | Min-Max |
|---|---|---|---|---|
| Platelet Count (/µL) | ITP | 26 | 97,038.46 ± 64,596.27 | 3,000-275,000 |
| Control | 25 | 256,920.00 ± 48,873.07 | 156,000-357,000 | |
| MPV (fL) | ITP | 18 | 11.67 ± 1.46 | 9.90–14.30 |
| Control | 25 | 10.46 ± 0.77 | 9.10–12.00 | |
| CD3+ (%) | ITP | 26 | 72.02 ± 10.03 | 43.85–85.24 |
| Control | 25 | 74.88 ± 7.64 | 46.12–87.57 | |
| CD4+/CD3+ (%) | ITP | 26 | 38.87 ± 8.21 | 24.11–50.60 |
| Control | 25 | 42.63 ± 8.14 | 28.06–58.54 | |
| CD8+/CD3+ (%) | ITP | 26 | 31.49 ± 10.25 | 11.69–55.36 |
| Control | 25 | 28.51 ± 6.24 | 15.11–40.21 |
Discussion
This study provides comprehensive flow cytometric analysis of T-cell subsets and platelet surface markers in chronic ITP patients, revealing several important findings that contribute to our understanding of ITP pathogenesis and potential therapeutic targets.
The significantly lower CD45RA+/CD4 + ratios in ITP patients suggest altered T-cell differentiation patterns, with a shift away from naive T-cell populations. This finding is consistent with chronic immune activation and ongoing autoimmune processes in ITP patients [21]. CD62L shedding is generally associated with T-cell activation and differentiation toward effector phenotypes. Therefore, the lower proportion of CD62L− cells observed in our ITP cohort may initially appear counterintuitive in the context of chronic immune activation. One possible explanation is that chronic antigenic stimulation in ITP may lead to redistribution of activated effector cells from peripheral blood to lymphoid or inflammatory tissues, while circulating T cells retain a relatively less differentiated phenotype. Alternatively, ongoing immunomodulatory treatments may have influenced T-cell activation profiles [22].
Our observation of reduced CD61 expression on platelets in ITP patients aligns with previous studies demonstrating platelet surface glycoprotein alterations in autoimmune thrombocytopenia [23, 24]. This reduction may reflect either direct antibody-mediated effects or compensatory mechanisms in response to chronic platelet destruction.
The correlation between platelet count and CD41, CD42, and CD61 expression supports the concept that platelet surface glycoprotein expression serves as a marker of disease severity and platelet turnover. Although CD42 expression did not differ significantly between the overall ITP and control groups, subgroup analysis demonstrated significantly lower CD42 expression in patients with severe thrombocytopenia (< 30,000/µL). This finding may indicate that CD42 alterations become more prominent in advanced disease states characterized by increased platelet destruction and immune-mediated platelet consumption.
The higher CD62L-/platelet ratio in ITP patients indicates increased interactions between activated T cells and platelets, supporting the emerging concept of T-cell-mediated platelet destruction in ITP [25]. This finding is particularly relevant given recent evidence for the role of cytotoxic CD8 + T cells in ITP pathogenesis [11, 12].
Interestingly, patients in remission or those with successful treatment responses showed higher CD25 + CD4+ ratios, suggesting improved regulatory T-cell function or activation. This observation supports the therapeutic potential of treatments that enhance regulatory T-cell function in ITP patients [26, 27]. CD25 expression alone cannot definitively identify regulatory T cells, as activated conventional T cells may also express CD25. Therefore, the CD25+/CD4 + population evaluated in this study should be interpreted as a surrogate marker rather than a definitive Treg population in the absence of additional markers such as FOXP3 or CD127.
The lack of significant differences in overall CD3+, CD4+, and CD8 + populations suggests that the pathogenic changes in ITP are more subtle and involve specific functional subsets rather than gross alterations in T-cell numbers. This emphasizes the importance of detailed immunophenotyping for understanding autoimmune diseases.
Our findings have several clinical implications. First, the flow cytometric parameters we identified, particularly CD45RA+/CD4 + ratios and CD61 expression, may serve as biomarkers for disease monitoring and treatment response assessment. Second, the differential expression patterns across platelet count subgroups suggest that these markers could help stratify patients for different therapeutic approaches.
The observation that patients in remission show improved CD25 + CD4+ ratios supports the potential use of this parameter as a treatment response marker. This could be particularly valuable for monitoring the effectiveness of immunosuppressive therapies and predicting long-term outcomes.
Several limitations of this study should be acknowledged. First, the relatively small sample size, particularly within the platelet count-based subgroups, especially the subgroup with platelet counts below 30,000/µL, limits the statistical robustness and generalizability of our findings. Second, the cross-sectional design precludes evaluation of temporal changes in immune phenotypes during disease progression or treatment response. Third, the significant age difference between the ITP and control groups may have influenced T-cell differentiation and activation patterns, as immunosenescence is known to affect naïve and memory T-cell distributions. In addition, the heterogeneous nature of the patient cohort with respect to disease duration, treatment history, splenectomy status, and ongoing therapies may have contributed to variability in immune phenotypes. Particularly, thrombopoietin receptor agonists such as eltrombopag may exert immunomodulatory effects beyond platelet production. Finally, our study relied primarily on phenotypic immunophenotyping without functional characterization of T-cell subsets. Given the substantial plasticity of Th17 cells and the complexity of cytokine-mediated immune regulation, phenotypic surface marker analysis alone may not fully reflect the functional immune status of ITP patients. Future studies incorporating intracellular cytokine profiling, functional T-cell assays, and longitudinal follow-up are needed to better define the relationship between immune phenotype, cytokine secretion patterns, disease activity, and treatment response.
Future studies should include larger patient cohorts with longitudinal follow-up to assess the prognostic value of these flow cytometric parameters. Functional studies examining T-cell cytokine production, proliferation, and cytotoxic activity would complement these phenotypic analyses. Additionally, correlation with treatment response and long-term outcomes would help establish the clinical utility of these biomarkers.
Investigation of other T-cell subsets, including Th17 cells and tissue-resident memory T cells, may provide further insights into ITP pathogenesis. Investigation of Th17 plasticity and cytokine-producing T-cell subsets may provide further insights into the immunopathogenesis of chronic ITP and treatment response heterogeneity. Advanced techniques such as mass cytometry and single-cell RNA sequencing could offer more detailed characterization of immune cell populations in ITP patients.
Conclusion
This study demonstrates alterations in T-cell differentiation markers and platelet surface glycoproteins in patients with chronic ITP. Reduced CD45RA+/CD4 + ratios, altered CD62L expression, and decreased CD41 and CD61 levels, together with severity-associated alterations in CD42 expression, suggest ongoing immune dysregulation and abnormal platelet biology in these patients. Although these findings may contribute to understanding ITP immunopathogenesis, the absence of functional immune analyses limits mechanistic interpretation. Further longitudinal and functional studies are needed to validate these markers and clarify their potential clinical utility as biomarkers or therapeutic targets.
Author contributions
All authors contributed to the study conception and design. P.A. and M.K. followed the patients. C.G. and M.B.Y.C. performed the laboratory studies. Material preparation, data collection and analysis were performed by M.K., P.A., and M.B.Y.C. The first draft of the manuscript was written by M.K. and P.A., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
None.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study protocol received approval from the Clinical Research Ethics Committee of Mersin University Medical Faculty (approval number: 2023/744, dated November 1, 2023). Adherence to ethical guidelines was maintained throughout the study, ensuring compliance with the 1964 Declaration of Helsinki and its subsequent revisions. All participants provided voluntary informed consent before their inclusion.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Clinical trial number
Not applicable.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Neunert C, Terrell DR, Arnold DM et al (2019) American Society of Hematology 2019 guidelines for immune thrombocytopenia. Blood Adv 3(23):3829–3866 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bu S, Liu M, Yang L et al (2025) The function of T cells in immune thrombocytopenia. Front Immunol 16:1499014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Yue Z, Xie F, Wang R, Wang X, Li H (2025) Lienal polypeptide decreases immune thrombocytopenia in a mouse model by upregulating cytokine production and increasing the levels of CD4+, CD8+, and T regulatory cells. J Interferon Cytokine Res [DOI] [PubMed]
- 4.Žibřidová K, Souček O, Krčmová LK et al (2024) Lymphocyte subpopulations: a potential predictor of a response in patients with immune thrombocytopenia. Hematology 29(1):2304486 [DOI] [PubMed] [Google Scholar]
- 5.Wang Z, Lang T, Li Y, Zhang X, Abdur M, Mao M (2024) Hypermethylation of the FOXP3 gene regulates Tregs immunodysregulation in chronic idiopathic thrombocytopenic purpura. Allergol Immunopathol 52(4):30–37 [DOI] [PubMed] [Google Scholar]
- 6.Elsayh KI, Saad K, Osman NS et al (2022) Regulatory T-lymphocyte subsets in children with chronic immune thrombocytopenia after high-dose of dexamethasone. Pediatr Res 92(5):1432–1436 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Zahran AM, El-Badawy OH, Mahran H et al (2024) Detection and characterization of autoreactive memory stem T-cells in children with acute immune thrombocytopenia. Clin Experimental Med 24(1):158 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Zhang L, Zhou G-z, Feng W-y, Li D (2022) Immune status and chemokine C receptor 7 expression in primary in patients with immune thrombocytopenia. Turkish J Hematol 39(1):29 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.An H, Li T, Yang L et al (2024) Unveiling the hidden link: elevated platelets and T cell subsets in 5% of moderate COVID-19 patients 48 days post-onset. Front Cell Infect Microbiol 14:1498491 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Zhang X, Wang Y, Zhang D, Li H, Zhou Z, Yang R (2020) CD70-silenced dendritic cells induce immune tolerance in immune thrombocytopenia patients. Br J Haematol 191(3):466–475 [DOI] [PubMed] [Google Scholar]
- 11.Malik A, Sayed AA, Han P et al (2023) The role of CD8 + T-cell clones in immune thrombocytopenia. Blood J Am Soc Hematol 141(20):2417–2429 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gupta S, Shen L, Henry SP, Aghaeepour N, Narayanan P, Maecker HT (2025) Cellular immune changes during severe antisense oligonucleotide-associated thrombocytopenia in a nonhuman primate model. J Immunol 214(4):636–650 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Abd El-Ghani SE-S, Mahmoud Mohamed LA, El-Masry MR, Abdelhamid HM, Fateen M, Mohamed MS CD8 + CD25+ tregs as a predictor of glucocorticoid sensitivity in patients with immune thrombocytopenia. Expert Rev Hematol. 2025;(just-accepted) [DOI] [PubMed]
- 14.Bayegi SN, Hamidieh AA, Behfar M et al (2024) The reconstitution of T-cells after allogeneic hematopoietic stem cell transplant in a pediatric patient with congenital amegakaryocytic thrombocytopenia (CAMT). Endocrine, Metabolic & Immune Disorders-Drug Targets (Formerly Current Drug Targets-Immune. Endocr Metabolic Disorders) 24(2):265–272 [DOI] [PubMed] [Google Scholar]
- 15.Xu W, Chen S, Wang X et al (2024) Cepharanthine synergistically promotes methylprednisolone pharmacodynamics against human peripheral blood mononuclear cells possibly via regulation of P-glycoprotein/glucocorticoid receptor translocation. BMC Complement Med Ther 24(1):186 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ugurel E, Narimanfar G, Cilek N et al (2024) Platelet proteome reveals novel targets for hypercoagulation in pseudoexfoliation syndrome. Int J Mol Sci 25(3):1403 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Malinin AI, Atar D, Callahan KP, McKenzie ME, Serebruany VL (2003) Effect of a single dose aspirin on platelets in humans with multiple risk factors for coronary artery disease. Eur J Pharmacol 462(1–3):139–143 [DOI] [PubMed] [Google Scholar]
- 18.Zarif MN, Soleimani M, Abolghasemi H, Amirizade N, Arefian E, Rahimian A (2013) Megakaryocytic differentiation of CD133 + hematopoietic stem cells by down-regulation of microRNA-10a. Hematology 18(2):93–100 [DOI] [PubMed] [Google Scholar]
- 19.Cooper N, Ghanima W (2019) Immune thrombocytopenia. N Engl J Med 381(10):945–955 [DOI] [PubMed] [Google Scholar]
- 20.Provan D, Arnold DM, Bussel JB et al (2019) Updated international consensus report on the investigation and management of primary immune thrombocytopenia. Blood Adv 3(22):3780–3817 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Semple JW, Rebetz J, Kapur R (2019) Transfusion-associated circulatory overload and transfusion-related acute lung injury. Blood J Am Soc Hematol 133(17):1840–1853 [DOI] [PubMed] [Google Scholar]
- 22.McKenzie CG, Guo L, Freedman J, Semple JW (2013) Cellular immune dysfunction in immune thrombocytopenia (ITP). Br J Haematol 163(1):10–23 [DOI] [PubMed] [Google Scholar]
- 23.Audia S, Mahévas M, Samson M, Godeau B, Bonnotte B (2017) Pathogenesis of immune thrombocytopenia. Autoimmun rev 16(6):620–632 [DOI] [PubMed] [Google Scholar]
- 24.Lambert MP, Gernsheimer TB (2017) Clinical updates in adult immune thrombocytopenia. Blood J Am Soc Hematol 129(21):2829–2835 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Li S, Wang L, Zhao C, Li L, Peng J, Hou M (2007) CD8 + T cells suppress autologous megakaryocyte apoptosis in idiopathic thrombocytopenic purpura. Br J Haematol 139(4):605–611 [DOI] [PubMed] [Google Scholar]
- 26.Yu J, Heck S, Patel V et al (2008) Defective circulating CD25 regulatory T cells in patients with chronic immune thrombocytopenic purpura. Blood J Am Soc Hematol 112(4):1325–1328 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Sakakura M, Wada H, Tawara I et al (2007) Reduced Cd4 + Cd25+ T cells in patients with idiopathic thrombocytopenic purpura. Thromb Res 120(2):187–193 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.