Introduction
The introduction of allogeneic hematopoietic cell transplantation (allo-HCT) as a standard method of treatment for several malignant and non-malignant hematological diseases has created an excellent platform upon which to study human immunology and cell senescence. Since only a small percentage of the donor stem cells pool is collected and infused into the donor to engraft and reconstitute hematopoiesis, the cells are exposed to immense proliferative stress.
However, successful allo-HCT requires also that two important immunological barriers be overcome: host versus graft and graft versus host. Graft-versus-host reaction results from the exposure of lymphoid donor cells to the recipient antigens which induce donor lymphocyte activation and proliferation. Partially in patients with malignant diseases, this reaction is responsible for HCT’s success in eradicating the residual malignant cells (graft-versus-leukemia reaction). However, it may also lead to undesirable complications such as graft-versus-host disease (GvHD) resembling autoimmune diseases affecting several host organs. To prevent and control symptoms of graft versus host reaction, immunosuppressive agents disrupting lymphocyte proliferation (such as methotrexate and calcineurin inhibitors) are routinely administered after transplantation. A key role in GvHD is played by donor T cell lymphocytes but also B-lymphocytes [1, 2]. Involved donor lymphocytes undergo an additional intensive proliferation which may contribute to the accelerated telomere shortening in donor lymphocytes.
All of the above lead to the immense proliferative activity of the cells, including lymphocytes in allo-HCT recipients. We hypothesized that this could lead not only to accelerated telomeric shortening but also to immunophenotypic changes characteristic of natural aging. Healthy human ageing process includes in its characteristics the phenomenon of ‘inflammaging’. It may be defined as chronic, low-grade inflammation, without the presence of infection. In biochemical evaluation it presents with increased concentrations of proinflammatory cytokines due to antigenic stimulation over a lifespan of an individual [2].
It is also well known that the concentration of some proinflammatory cytokines [such as tumor necrosis factor α (TNF-α), interleukin (IL)-6] increases, whereas others decrease (such as IL-10) during the course of chronic GvHD [3–5].
We reported recently our observations regarding the changes in immunophenotype and shortened telomeres in CD8+ lymphocyte subpopulation in long-term allo-HCT recipients compared to their respective donors [6]. Here, we present data on the proinflammatory cytokine profile of the same population of patients, i.e. long-term recipients of allo-HCT and their respective donors, to determine whether allo-HCT led to the changes in the proinflammatory cytokines. Moreover, we compared the immunophenotype of the recipients grouped according to their infection and cGvHD status.
Material and methods
The content of the materials and methods section were adapted from Czarnogórski et al. 2022 [6].
Patients
The study consist of 20 allo-HCT recipient-donor pairs. The span from the transplantation was more than 12 years ago. The study was conducted at University Clinical Center, Medical University of Gdansk. From all participants full venous blood sample was collected (50 mL).
GvHD and infectious status assessment
Patients were stratified according to their history of chronic GvHD status (yes vs. no) and infectious complications according to an infection risk status score developed for the purpose of this study [6].
Peripheral blood mononuclear cells and lymphocyte isolation
Perpheral blood mononuclear cells collection was performed from full venous blood with Ficoll-Hypaque centrifugation technique. Following lymphocyte isolation was performed by immunomagnetic separation. The lymphocyte subpopulations were TCD4+, TCD8+, B-lymphocytes and natural killers (NK) cells. The quality of collected material was assessed according to validated protocols [7, 8].
Proinflammatory cytokine concentrations
Proinflammatory cytokines concentrations (IL-1B, IL-2, IL-4, IL-6, IL-10, TNF-α and IL-17F) were assessed with flow cytometry. The results which did not reach the reference were excluded from the study.
Immunophenotyping
Immunophenotyping was performed according to protocol used by Czarnogórski et al. [6].
Statistical analysis
The statistical analysis was performed by STATISTICA 12.0 and with Microsoft Exel, detailed analysis was described according to Czarnogórski et al. [6]. The W Shapiro-Wilk test, and the Leven’s (Brown-Forsythe) test were used. The significance of differences between the two groups (independent samples model) was tested by Student’s t-test or by U Mann-Whitney. The significance of differences between more than two groups was verified using the Kruskal-Wallis test. In the case of receiving statistically significant differences between groups, the Dunn test was performed. A p value <0.05 was considered significant.
Results
Patient characteristics
The time from Tx to full venous blood cytometric analysis was at least 12 years with range 12–25 years (median 17.4 years). The population studied consisted of 12 males and 8 females. The prevalence of chronic graft versus host disease among recipients was 40%. Infection risk status was assessed according to Czarnogórski et al. [6]: 12 low risk recipients and 8 high risk recipients.
Proinflammatory cytokine concentrations
Surprisingly, we have found no statistically significant differences in the concentrations of the cytokines: TNF-α, IL-6, IL-10 (Table I). The results of assessment of IL-17F, IL-1β, IL-4, IL-2 concentrations were out of range, therefore they could not be included into analysis.
Parameter |
R |
D |
p value |
IL-6 [ng/L]: |
N = 20 |
N = 20 |
0.5792* |
|
0.99 (1.17) |
1.61 (2.37) |
|
|
0.38–5.42 |
0.07–9.53 |
|
|
0.58 |
0.72 |
|
|
0.44–1.54 |
0.50–2.72 |
|
IL-10 [ng/L]: |
N = 19 |
N = 18 |
0.5333* |
|
0.58 (0.69) |
0.72 (0.71) |
|
|
0.01–3.20 |
0.15–3.04 |
|
|
0.42 |
0.52 |
|
|
0.25–0.91 |
0.36–1.07 |
|
TNF-α [ng/L]: |
N = 18 |
N = 19 |
0.3234* |
|
0.77 (1.53) |
0.83 (1.91) |
|
|
0.01–6.78 |
0.02–8.51 |
|
|
0.33 |
0.22 |
|
|
0.01–1.54 |
–0.09–1.75 |
Neither we have found any differences between recipients when grouped according to infection risk status (Table II).
Parameter |
Low risk |
Intermediate/ |
p value |
IL-6 [ng/L]: |
N = 12 |
N = 8 |
0.3159* |
|
1.19 (1.49) |
0.69 (0.20) |
|
|
0.38–5.42 |
0.48–1.10 |
|
|
0.52 |
0.61 |
|
|
0.24–2.14 |
0.52–0.86 |
|
IL-10 [ng/L]: |
N = 11 |
N = 8 |
0.9671* |
|
0.68 (0.88) |
0.45 (0.27) |
|
|
0.01–3.20 |
0.11–0.87 |
|
|
0.48 |
0.39 |
|
|
0.09–1.27 |
0.23–0.67 |
|
TNF-α [ng/L]: |
N = 12 |
N = 6 |
0.1898* |
|
1.02 (1.85) |
0.28 (0.20) |
|
|
0.09–6.78 |
0.01–0.62 |
|
|
0.37 |
0.28 |
|
|
–0.15–2.19 |
0.07–0.49 |
Immunophenotype of allo-HCT recpients grouped according to chronic GvHD history
The analysis of immunophenotype of the allo-HCT recipients grouped according to cGvHD history showed no significant differences (see Supplementary Table 1), with the exception of a few parameters such as Treg Helios-Eomes+, B1 PD1+, B2 PD1+ and C19 PD1+. Lymphocytes B in recipients of allo-HCT who did not develop cGvHD had greater expression of PD-1 (Table III).
Parameter |
cGvHD |
Without cGvHD |
p value |
Treg Helios–Eomes: |
0.0227 |
||
|
4.1 (1.3) |
8.7 (4.8) |
|
|
2.4–5.4 |
4.2–19.1 |
|
|
4.6 |
7.2 |
|
|
2.7–5.5 |
5.2–12.1 |
|
B1 PD1: |
0.0147 |
||
|
4.0 (2.7) |
10.4 (5.5) |
|
|
0.2–8.7 |
3.6–18.7 |
|
|
3.7 |
9.7 |
|
|
1.2–6.9 |
6.4–14.3 |
|
B2 PD1: |
0.0448 |
||
|
0.7 (0.7) |
1.8 (1.8) |
|
|
0.1–2.1 |
0.6–6.2 |
|
|
0.5 |
1.1 |
|
CD19 PD1: |
0.0147 |
||
|
1.2 (0.9) |
3.3 (2.3) |
|
|
0.2–2.9 |
1.2–8.9 |
|
|
0.9 |
3.0 |
|
|
0.2–2.2 |
1.6–4.9 |
Discussion
In this study, we tried to answer the question of whether allo-HCT accelerates the aging of the hematopoietic system by determining the differences in cytokine profile between long-term allo-HCT survivors and their respective donors of allo-HCT.
Studying donor-recipient pairs creates a unique model in which donor cells remaining in the donor could be compared to the donor cells infused into respective recipients. We were particularly interested in the features of postulated ‘inflammaging’. We also compared the same cytokine profile of the recipients when grouped according to infectious status (low vs intermediate/high) (see Czarnogórski et al. [6]). We hypothesized that allo-HCT recipients should have higher concentrations of proinflammatory cytokines as a robust indicator of aging. We also hypothesized that low-risk recipients according to their infection status would have increased concentrations of the same cytokines as an adaptation for fighting the infections.
Physiologically, the proinflammatory cytokine profile of older people is characterized by increased concentrations of the aforementioned cytokines (IL-1B, IL-2, IL-4, TNF-α, IL-6, IL-10, IL-15, IL-17, IL-18). These concentrations however do not exceed the upper reference range. Hence, inflammaging is defined as the process of chronic, sterile, low-grade inflammation.
There is no data on inflammaging in a population of allo-HCT survivors compared to their respective recipients serving as controls. We did not find any statistically significant differences in IL-6, IL-10 and TNF-α concentrations, either between main groups (recipients vs. donors) nor between recipients grouped according to infection risk status. Our data did not confirm our initial hypothesis that allo-HCT accelerates the inflammaging-resembling process.
We also did not find any differences between low and intermediate/high risk recipients stratified by their infection status, which could imply that infectious risk is not directly connected to the efficacy of one’s innate immune response. It would imply that allogeneic hematopoietic cells transplantation by itself does not impact the inflammaging [9]. However, the issue remains controversial since chronic low-grade inflammation (inflammaging) is a well-established risk factor for developing neoplasia [10, 11] which could be debatable in the population of our allo-HCT survivors since they were diagnosed with hematological malignancies in their 20 s and 30 s. On the other hand, there is ample data on the reduction of relapse risk after allo-HCT in patients who developed chronic GvHD that is in fact a chronic inflammation [12]. Moreover, it is difficult to differentiate if heightened concentrations of proinflammatory cytokines after allo-HCT result from chronic GvHD [13] or possibly are an adaptation for fighting the infection. There is some data correlating the occurrence of inflammaging and immune exhaustion in some hematological malignancies, such as plasmocytic myeloma [14]. Thus, it is challenging to determine whether the inflammaging features are due to older age or to the neoplasia itself.
Surprisingly, the incidence of chronic GvHD also did not impact any studied parameters, especially immunophenotype with the exception of B-cells expressing PD-1 which serves as the programmed death ligand-1 (PD-L1) receptor and plays a role in modulating immune response [15]. We also found no differences in T-cells expressing PD-1. An increased percentage of B-cells presenting PD-1 in recipients without chronic GvHD in anamnesis is difficult to interpret. Those differences in receptor expression in antigen-presenting cells (APCs) such as B-cells seem to be insignificant or accidental. The lack of differences in long-term (12 years+ from Tx) recipients of allo-HCT when grouped according to cGvHD history may suggest that the immune system tends to stabilize in the years following Tx. Many factors might explain such notion, that is immune suppression used, history of chronic degenerative diseases, GvHD resolution and small number of participants. Our study has several limitations. Firstly, it was performed in long-term survivors who were able to fight infections successfully and whose cGvHD status became stable. Secondly, the results are affected by the small population (20 pairs) and unfortunately the results of some cytokines assays were out of range, which might be related to laboratory errors. Unfortunately, we were unable to repeat tests with out-of-range results due to sample destruction during an electricity outage. Nevertheless, our results may suggest that allo-HCT does not accelerate the aging of the hematopoietic system despite a clear reduction of telomere shortening in specific cell populations and some immunophenotypic differences reported by us [6].
Authors’ contributions
All authors revised manuscript and read and approved final manuscript. MCC and JMZ wrote manuscript. MCC, PT, JMW, MD, JMZ were responsible for study design. MCC, AP, AS, JMZ, EZ, MB, MD, AH took part in patient recruitment and clinical data acquisition. MCC, IO, JMW, JMZ, MM and KRD performed laboratory and clinical data analysis. MC, JS, MM, MZ, JMW and PT performed laboratory work.
Conflict of interest
The authors declare no conflict of interest.
Financial support
Grants from the National Science Centre, Poland (No. 2018/31/N/NZ3/01035 awarded to MCC and 2019/03/X/NZ3/01848 awarded to MD).
Ethics
This study was approved by the Ethics Committee at the Medical University of Gdańsk — NKBBN/394-594/2019 and NKBBN/394-45/2020. Each participant signed an informed consent form.
Parameter |
p value |
Parameter |
p value |
Parameter |
p value |
B1 |
0.1193 |
NK CD39 |
0.5508 |
B1 PD1 |
0.0147 |
B2 |
0.0973 |
NK CD56 dim |
0.2548 |
B2 |
0.2123 |
CD19 |
0.6511 |
NK CD56 high |
0.2548 |
B2 Fas |
0.9567 |
CD3 |
0.9599 |
NK Eomes |
0.9567 |
B2 PD1 |
0.0448 |
DNT |
0.4808 |
NK Perforin |
0.7042 |
CD19 |
0.9567 |
NK |
0.7595 |
NKT like |
1.00 |
CD19 Fas |
0.9567 |
NK CD56 dim |
0.9512 |
Q1 |
0.5508 |
CD19 PD1 |
0.0147 |
NK CD56 high |
0.4624 |
Q1 CD39 |
0.8708 |
CD4 CD27+CD28– |
0.3290 |
NKT like |
0.0662 |
Q1 Eomes |
0.3566 |
CD4 CD27+CD28+ |
0.2123 |
T CD4 |
0.7250 |
Q1 IL10 |
0.5508 |
CD4 CD27–CD28– |
0.4808 |
T CD8 |
0.9567 |
Q1 Perforin |
0.0827 |
CD4 CD27–CD28+ |
0.7042 |
B1 |
0.0927 |
Q2 |
0.9567 |
CD4 CD28 |
0.3566 |
B1 CD39 |
0.4159 |
Q2 CD39 |
0.3028 |
CD4 CD57 |
0.3028 |
B1 Eomes |
0.3566 |
Q2 Eomes |
0.7863 |
CD4 FasL |
0.8283 |
B1 IL10 |
0.1752 |
Q2 IL10 |
0.1585 |
CD4 PD-1 |
0.6255 |
B2 |
0.0927 |
Q2 Perforin |
0.1752 |
CD8 CD27+CD28– |
0.7683 |
B2 CD39 |
0.7449 |
Q3 |
0.3290 |
CD8 CD27+CD28+ |
0.1949 |
B2 Eomes |
0.0577 |
Q3 CD39 |
0.7042 |
CD8 CD27–CD28– |
0.6800 |
B2 IL10 |
0.6255 |
Q3 Eomes |
0.2123 |
CD8 CD27–CD28+ |
0.5959 |
CD19 |
0.4808 |
Q3 IL10 |
0.1931 |
CD8 CD28 |
0.7683 |
CD19 CD39 |
0.4159 |
Q3 Perforin |
0.8708 |
CD8 CD57 |
0.6800 |
CD19 Eomes |
0.0448 |
RTE |
0.1158 |
CD8 PD-1 |
0.3165 |
CD19 IL10 |
0.4477 |
T CD4 |
0.7863 |
DNT |
0.3566 |
CD3 |
0.6255 |
T CD8 |
0.7863 |
Memory B |
0.0735 |
CD4 CD39 |
0.4808 |
Treg FoxP3 |
0.9567 |
NK |
0.2123 |
CD4 CM |
0.3028 |
Treg FoxP3 CD39 |
0.6255 |
NK CD27 |
0.7449 |
CD4 EM |
0.7042 |
Treg FoxP3 Eomes |
0.9136 |
NK CD28 |
0.8708 |
CD4 Eomes |
1.00 |
Treg FoxP3 IL10 |
0.0735 |
NK CD56 dim |
0.2123 |
CD4 IL10 |
0.5508 |
Treg FoxP3 Perforin |
0.2548 |
NK CD56 high |
0.5508 |
CD4 Naive |
0.9567 |
Treg Helios– |
0.6255 |
NK CD57 |
0.3566 |
CD4 Perforin |
0.0577 |
Treg Helios– CD39 |
0.3566 |
NK PD-1 |
0.6255 |
CD4 Temra |
0.7863 |
Treg Helios– Eomes |
0.0227 |
NKT like |
0.9567 |
CD8 CD39 |
0.8137 |
Treg Helios– IL10 |
0.1752 |
Q1 |
0.8708 |
CD8 CM |
0.3768 |
Treg Helios– Perforin |
0.2548 |
Q1 CD27 |
0.9567 |
CD8 EM |
0.0875 |
Treg Helios+ |
0.7042 |
Q1 CD28 |
0.1431 |
CD8 Eomes |
0.2159 |
Treg Helios+ CD39 |
0.7042 |
Q1 CD57 |
0.2123 |
CD8 Naive |
0.2629 |
Treg Helios+ Eomes |
0.0577 |
Q1 FasL |
0.7863 |
CD8 Perforin |
0.3768 |
Treg Helios+ IL10 |
0.0927 |
Q1 PD-1 |
0.3566 |
CD8 Temra |
0.953 |
Treg Helios+ Perforin |
0.6255 |
Q2 |
0.9567 |
DNT |
0.4159 |
B1 |
0.2123 |
Q2 CD27 |
0.7449 |
NK |
0.2123 |
B1 Fas |
0.8708 |
Q2 CD28 |
0.5508 |
Q2 CD57 |
0.0735 |
CD3 |
0.9567 |
Treg FoxP3 CXCR5 |
0.1431 |
Q2 FasL |
0.4159 |
CD4 CD152 |
0.6255 |
Treg FoxP3 TIGIT |
0.7863 |
Q2 PD-1 |
0.9567 |
CD4 CXCR4 |
0.7042 |
Treg Helios– |
0.4808 |
Q3 |
0.1158 |
CD4 CXCR5 |
0.1431 |
Treg Helios– CCR5 |
0.5508 |
Q3 CD27 |
0.3566 |
CD4 TIGIT |
0.4477 |
Treg Helios– CD152 |
0.7042 |
Q3 CD28 |
0.7449 |
CD8 CXCR4 |
0.7683 |
Treg Helios– CXCR4 |
0.4159 |
Q3 CD57 |
0.0057 |
CD8 CXCR5 |
0.1116 |
Treg Helios– CXCR5 |
0.6255 |
Q3 FasL |
0.1431 |
CD8 TIGIT |
0.5169 |
Treg Helios– TIGIT |
0.7042 |
Q3 PD-1 |
0.0577 |
DNT |
0.4159 |
Treg Helios+ |
0.5508 |
T CD4 |
0.7042 |
NK |
0.2123 |
Treg Helios+ CCR5 |
0.8708 |
T CD8 |
0.6255 |
NK CCR5 |
0.4477 |
Treg Helios+ CD152 |
0.7042 |
Treg FoxP3 |
0.9567 |
NK CD56 dim |
0.2123 |
Treg Helios+ CXCR4 |
0.6255 |
Treg FoxP3 CD27 |
0.1037 |
NK CD56 high |
0.4159 |
Treg Helios+ CXCR5 |
0.4808 |
Treg FoxP3 CD28 |
0.7042 |
NK CXCR4 |
0.2548 |
Treg Helios+ TIGIT |
0.8708 |
Treg FoxP3 CD57 |
0.0735 |
NK CXCR5 |
0.3566 |
||
Treg FoxP3 FasL |
0.1931 |
NK TIGIT |
0.4808 |
||
Treg FoxP3 PD-1 |
0.4808 |
NKT like |
0.9567 |
||
Treg Helios– |
0.0735 |
Q1 |
0.5508 |
||
Treg Helios– CD27 |
0.9567 |
Q1 CCR5 |
0.4159 |
||
Treg Helios– CD28 |
0.3028 |
Q1 CD152 |
0.5876 |
||
Treg Helios– CD57 |
0.0577 |
Q1 CXCR4 |
0.8708 |
||
Treg Helios– FasL |
0.2781 |
Q1 CXCR5 |
0.1431 |
||
Treg Helios– PD-1 |
0.4808 |
Q1 TIGIT |
0.3028 |
||
Treg Helios+ |
0.7863 |
Q2 |
0.8708 |
||
Treg Helios+ CD27 |
0.1585 |
Q2 CCR5 |
0.9567 |
||
Treg Helios+ CD28 |
0.8708 |
Q2 CD152 |
0.3028 |
||
Treg Helios+ CD57 |
0.0079 |
Q2 CXCR4 |
0.4477 |
||
Treg Helios+ FasL |
0.3028 |
Q2 CXCR5 |
0.9567 |
||
Treg Helios+ PD-1 |
0.7863 |
Q2 TIGIT |
0.2548 |
||
B1 |
0.0927 |
Q3 |
0.4159 |
||
B1 CCR5 |
0.3566 |
Q3 CCR5 |
0.7863 |
||
B1 CD152 |
0.0735 |
Q3 CD152 |
0.6255 |
||
B1 CXCR5 |
0.2548 |
Q3 CXCR4 |
0.7042 |
||
B2 |
0.0577 |
Q3 CXCR5 |
0.4808 |
||
B2 CCR5 |
0.7449 |
Q3 TIGIT |
0.6644 |
||
B2 CD152 |
0.3028 |
T CD4 |
0.8708 |
||
B2 CXCR5 |
0.4477 |
T CD8 |
0.8708 |
||
CD19 |
0.4159 |
Treg FoxP3 |
0.9567 |
||
CD19 CCR5 |
0.4159 |
Treg FoxP3 CCR5 |
0.7042 |
||
CD19 CD152 |
0.1752 |
Treg FoxP3 CD152 |
0.7042 |
||
CD19 CXCR5 |
0.7042 |
Treg FoxP3 CXCR4 |
1.00 |