- Academic Editor
Background: Systemic lupus erythematosus (SLE)-related hematological
disorders have different pathogenic mechanisms involving immune dysregulation as
well as microangiopathy. The current study aimed to assess the relationship
between pro- and anti-inflammatory cytokines and SLE-related hematological
abnormalities for Saudi Patients. Methods: The current cross-sectional
study including 140 participants was performed at the Prince Mohammad bin
Abdulaziz Hospital (PMAH), Riyadh, Saudi Arabia. Two blood samples were collected
from each of the study participants for evaluation of the haematological indices
including complete blood count (CBC), erythrocyte sedimentation rate (ESR), and
cytokine profile (i.e., tumour necrosis factor-alpha (TNF-
Cytokines are considered the most important secretions of the immune system that participate in a variety of cellular, inflammatory, and pathogenic processes in human disease. Cytokines that are produced in large amounts and gain across to the circulation act in a hormonal fashion and have drastic effects on other cells. Therefore, the excessive or insufficient production of certain cytokines may contribute to the pathogenicity of certain diseases [1]. An imbalance between pro- and anti-inflammatory cytokines is a well-known characteristic of SLE. Current evidence indicates that cytokine levels are related to systemic lupus erythematosus (SLE). High levels of proinflammatory cytokines may lead to an exacerbation of inflammatory response, apoptosis, and production of autoantibodies that initiate and sustain SLE disease activity [2].
SLE involves immune dysregulation and the production of autoantibodies caused by abnormalities in the activation of the innate and adaptive immune system, the occurrence, severity, and prognosis of which are highly impacted by ethnicity [3]. Certain characteristics of SLE demand the need for further study, including its incidence ratio across genders being 9:1 female to male, and its propensity to occur during the early reproductive years among women, both of which add crucial value to the study of human reproductive immunology [4]. Further studies have also highlighted that female patients present a malar rash, photosensitivity, arthritis, and oral ulcers, while male patients present more often with serositis and renal and immunological disorders. This difference indicates sex-specific features in the pathology of SLE [5].
Women account for more than 80% of SLE cases, making it an autoimmune disease with a hereditary predisposition. SLE can have an impact on the kidney, heart, joints, and central nervous system, among other internal organs [6]. Additionally, lymphopenia, leucopenia, thrombocytopenia, and complement deficiencies (C1q, C2, and C4) are blood abnormalities commonly seen in SLE patients [7]. The main causes of SLE are autoantibodies and immune complex deposition, increased apoptosis, and inadequate apoptotic cell clearance resulting in the production of excessive amounts of autoantibodies. Dysregulated cytokine production, which also contributes to tissue inflammation and organ damage, exacerbates immunological dysfunction. When T and B cells are stimulated, they release a variety of cytokines and autoantibodies that enhance the symptoms of the illness [8].
The haematological manifestation of SLE includes leucopenia, lymphopenia,
thrombocytopenia, myelofibrosis, and autoimmune haemolytic anaemia; studying
these symptoms is important at different disease stages to assess if the
occurrence is due to manifestation of SLE, treatment consequences, or another
type of blood cell dyscrasia [9, 10, 11, 12]. There is also a growing body of evidence
highlighting the role of cytokines in SLE pathogenesis, including interleukin-6
(IL-6), interleukin-17 (IL-17), interleukin-18 (IL-18), type I interferons, and
tumour necrosis factor-alpha (TNF-
A cross-sectional study was conducted on 140 participants above 18 years of age from Saudi Arabia, including 100 SLE patients whose selection was consecutive (diagnosed positive by a rheumatologist) and 40 healthy controls were diagnosed as free from any inflammatory parameters and autoimmune diseases by the rheumatologist. This study was performed over an 11-month period at Prince Mohammad bin Abdulaziz Hospital (PMAH), Riyadh, Saudi Arabia. All study participants signed informed consent. The present study received approval from the Institutional Review Board (IRB) at King Saud University (Research Project No: E-19-3701). Data was collected from patient’s case notes and hospital electronic records. Individuals with other autoimmune conditions, as well as SLE patients with other autoimmune diseases or leukemia, were excluded from this study. SLE patients with hematological abnormalities such as anemia, thrombocytopenia, thrombocytosis, leukopenia, neutropenia, and lymphopenia were also included.
A total of 100 adult patients over the age of 18 with SLE disease were included, regardless of their age at diagnosis. All patients in this study were diagnosed by a rheumatologist as having SLE. All patients with chronic diseases or any bleeding disorders like females with menorrhagia were excluded from the study.
A total of 40 healthy adult volunteers from among the hospital staff, over 18 years old, with normal complete blood count (CBC), and without SLE were included as healthy controls. Individuals with other autoimmune diseases or any inflammatory signs were excluded.
Two samples of blood were collected from each of the study participants in an ethylene diamine tetra-acetic acid (EDTA) vacutainer for analysis of complete blood count (CBC) and erythrocyte sedimentation rate (ESR). The second sample collected in a red top vacutainer was utilized for cytokine profiling and analysis.
The haematological assay involving CBC was performed using an automated blood
cell counter analyser (Alinity hq, Abbott Laboratories, Chicago, IL, USA). A
six-part differential count analysis was obtained for each sample along with an
indication for nucleated red blood cells (NRBCs). ESR was measured using a Test-1
analyser (Alifax, Padua, Italy). Cytokine profiling was done via enzyme
immunoassay (EIA) for the quantitative determination of human TNF-
Statistical analysis was done using the statistical package of social sciences
(SPSS) software, v25 (IBM Corp., Armonk, NY, USA). Qualitative data were assessed
with frequency, while quantitative data were assessed using the mean and standard
deviation, and the significance was calculated as a p-value to compare
cytokine profile and haematological indices between SLE patients and healthy
controls. The Pearson’s correlation coefficient was used to evaluate the
correlation between haematological parameters and cytokines (IL-6, IL10, and
TNF-
The study included a total of 140 Saudi participants, including 100 diagnosed SLE patients and 40 healthy controls, all participants above 18 years (Table 1).
Hematological paramitas | Healthy controls | Reference range | SLE patients |
(N = 40) | (N = 100) | ||
Age | 33.3 Y | - | 39.4 Y |
WBC | 6.3 × 10 |
4.5–11.0 × 10 |
5.70 × 10 |
RBC | 4.5 × 10 |
4.3–5.9 × 10 |
4.43 × 10 |
Haemoglobin | 8.25 mmol/L | 7.4–9.9 mmol/L | 7.48 mmol/L |
HCT | 38.8% | 38.3% to 48.6% | 37.812% |
MCV | 86.3 fL | 80–100 fL | 85.76 fL |
MCH | 28.9 mol/cell | 0.39–0.54 mol/cell | 27.27 mol/cell |
MCHC | 33 mmol Hb/L | 4.81–5.58 mmol Hb/L | 31.80 mmol Hb/L |
RDW | 12.2% | 12% to 15% | 14.13% |
PLT | 278 billion/L | 135–317 billion/L | 271.16 billion/L |
MPV | 8.7 fL | 8.9–11.8 fL | 8.76 fL |
Neutrophil | 4.6 × 10 |
1.5–10.0 10 |
3.34 10 |
Lymphocyte | 1.7 × 10 |
1.2–4.0 10 |
1.79 10 |
ESR | 3.25 mm/hr | 1–13 mm/hr | 37.5 mm/hr |
SLE, systemic lupus erythematosus; WBC, white blood cell; RBC, red blood cells; HCT, Hematocrit; MCV, mean corpuscular volume; MCH, mean corpuscular haemoglobin; MCHC, mean corpuscular haemoglobin concentration; RDW, red blood distribution width; MPV, mean platelet volume; ESR, erythrocyte sedimentation rate.
Females were found to be the majority in both the study cohorts, comprising 88% among SLE cases and 85% among the healthy controls. The cohort distribution is outlined in Table 2.
Variable | SLE patients | Healthy controls | p-value |
(N = 100) | (N = 40) | ||
Females | 88% | 85% | N/A |
TNF- |
5.72 |
1.74 |
0.001 |
IL-6 | 28.81 |
1.79 |
0.001 |
IL-10 | 25.55 |
1.61 |
0.009 |
RBC | 4.44 |
4.57 |
0.207 |
Haemoglobin | 12.06 |
13.32 |
0.001 |
HCT | 37.81 |
38.66 |
0.373 |
ESR | 37.39 |
3.25 |
0.001 |
TNF-
Haematological abnormalities were detected among 63% of SLE patients, and
anaemia was found to be the most common with 52% prevalence. Further, platelet
abnormalities, including thrombocytopenia, were found in 8% of the patients, and
thrombocytosis was observed among 7%. Leukopenia was found in 17%, leucocytosis
in 4%, neutropenia in 20%, and lymphopenia in 14% of SLE cases. Haemoglobin
levels were found to be significantly lower among SLE cases compared to the
healthy controls (p
The levels of cytokines studied, including TNF-
A significant correlation was found between levels of the cytokine
TNF-
SLE patients | Healthy controls | ||||
Variables | Reference range | Pearson correlation | p-value | Pearson correlation | p-value |
WBC | 4.5–11.0 × 10 |
–0.148 | 0.143 | 0.070 | 0.668 |
RBC | 4.3–5.9 × 10 |
–0.453 | 0.120 | 0.462 | |
Haemoglobin | 2.09–2.71 mol/L | –0.715 | 0.120 | 0.461 | |
HCT | 38.3% to 48.6% | –0.688 | –0.171 | 0.291 | |
MCV | 80–100 fL | –0.330 | 0.001 | 0.051 | 0.754 |
MCH | 0.39–0.54 mol/cell | –0.361 | –0.077 | 0.636 | |
MCHC | 4.81–5.58 mmol Hb/L | –0.219 | 0.029 | –0.067 | 0.681 |
RDW | 12% to 15% | 0.334 | 0.001 | –0.224 | 0.165 |
PLT | 135–317 billion/L | 0.320 | 0.001 | 0.088 | 0.590 |
MPV | 8.9–11.8 fL | 0.016 | 0.875 | 0.019 | 0.905 |
Neutrophil | 1.5–10.0 10 |
–0.050 | 0.630 | 0.045 | 0.783 |
Lymphocyte | 1.2–4.0 10 |
–0.201 | 0.050 | 0.275 | 0.086 |
ESR | 1–13 mm/hr | 0.685 | 0.328 | 0.039 |
A further correlation analysis between IL-6 and haematological parameters identified negative correlations with RBC, haemoglobin, HCT, MCV, MCH, and MCHC. A positive correlation was detected between platelet count and ESR. These correlations are detailed in Table 4.
SLE patients | Healthy controls | ||||
Variables | Reference range | Pearson correlation | p-value | Pearson correlation | p-value |
WBC | 4.5–11.0 × 10 |
–0.033 | 0.743 | –0.053 | 0.745 |
RBC | 4.3–5.9 × 10 |
–0.219 | 0.029 | 0.001 | 0.993 |
Haemoglobin | 2.09–2.71 mol/L | –0.538 | –0.016 | 0.922 | |
HCT | 38.3% to 48.6% | –0.535 | 0.068 | 0.678 | |
MCV | 80–100 fL | –0.417 | 0.035 | 0.829 | |
MCH | 0.39–0.54 mol/cell | –0.457 | 0.140 | 0.390 | |
MCHC | 4.81–5.58 mmol Hb/L | –0.310 | 0.002 | 0.068 | 0.677 |
RDW | 12% to 15% | 0.096 | 0.341 | –0.110 | 0.499 |
PLT | 135–317 billion/L | 0.225 | 0.024 | 0.066 | 0.688 |
MPV | 8.9–11.8 fL | –0.027 | 0.790 | –0.130 | 0.423 |
Neutrophil | 1.5–10.0 10 |
0.024 | 0.813 | 0.016 | 0.920 |
Lymphocyte | 1.2–4.0 10 |
–0.104 | 0.315 | –0.002 | 0.991 |
ESR | 1–13 mm/hr | 0.522 | –0.165 | 0.308 |
Correlation analysis between IL-10 and haematological indices among SLE cases
identified a negative correlation with haemoglobin (p = 0.040) and a
positive correlation with platelet count (p = 0.001), RDW (p
SLE patients | Healthy controls | ||||
Variables | Reference range | Pearson correlation | p-value | Pearson correlation | p-value |
WBC | 4.5–11.0 × 10 |
–0.067 | 0.510 | 0.042 | 0.799 |
RBC | 4.3–5.9 × 10 |
–0.114 | 0.260 | 0.046 | 0.778 |
Haemoglobin | 2.09–2.71 mol/L | –0.206 | 0.040 | –0.139 | 0.393 |
HCT | 38.3% to 48.6% | –0.191 | 0.057 | –0.191 | 0.238 |
MCV | 80–100 fL | –0.118 | 0.244 | 0.163 | 0.314 |
MCH | 0.39–0.54 mol/cell | –0.132 | 0.191 | 0.009 | 0.958 |
MCHC | 4.81–5.58 mmol Hb/L | –0.109 | 0.279 | 0.062 | 0.702 |
RDW | 12% to 15% | 0.391 | –0.267 | 0.096 | |
PLT | 135–317 billion/L | 0.337 | 0.001 | 0.009 | 0.956 |
MPV | 8.9–11.8 fL | –0.136 | 0.177 | 0.056 | 0.731 |
Neutrophil | 1.5–10.0 10 |
–0.042 | 0.686 | 0.200 | 0.215 |
Lymphocyte | 1.2–4.0 10 |
–0.156 | 0.129 | 0.081 | 0.621 |
ESR | 1–13 mm/hr | 0.237 | 0.029 | –0.129 | 0.427 |
The relationship between levels of cytokines and haematological parameters was
assessed using a stepwise multiple regression model in which haematological
indices were taken as explanatory variables and cytokines as dependent variables.
Regression analysis between TNF-
Regression analysis between IL-6 and haematological indices identified R = 0.760
and R
Regression analysis between IL-10 and haematological indices identified R =
0.340 and R
Variable | Predictors | T | R square | F | p-value | |
A. TNF- | ||||||
TNF- |
(Constant) | 16.15 | 4.48 | 0.57 | 51.5 | |
Haemoglobin | –1.07 | –4.23 | ||||
ESR | 0.07 | 3.75 | ||||
B. IL-6 and haematological indices | ||||||
IL-6 | (Constant) | 15.67 | 4.0 | 0.58 | 7.62 | |
Haemoglobin | –21.5 | –2.1 | ||||
MCV | –11.7 | –2.8 | ||||
MCH | –34 | –2.4 | ||||
MCHC | –44.5 | –3.3 | ||||
RDW | 2.3 | 2.1 | ||||
C. IL-10 and haematological indices | ||||||
IL-10 | (Constant) | 31.5 | 1.96 | 0.12 | 5.25 | 0.007 |
Haemoglobin | –2.35 | –2.07 | ||||
ESR | 0.27 | 3.23 |
The present study assessed the impact of haematological indices and cytokine
profiles among Saudi patients with SLE. The most frequent haematological
abnormalities were detected to be anaemia, thrombocytopenia, and leukopenia. Our
study also identified significantly high levels of all three cytokines (i.e.,
TNF-
Haematological abnormalities were reported to be a common occurrence in SLE, with studies reporting the incidence rate to be about 50% due to impaired erythropoietin responses and the development of corresponding antibodies [5]. Other causes of anaemia may include nutritional deficiencies, myelofibrosis, gastrointestinal loss, infection, hypersplenism, treatment-induced illness, etc. [14]. Our study also identified anaemia as the most common haematological abnormality among SLE cases at 52%. Studies on SLE-impacted quality of life have demonstrated an increase in ESR to occur independently of the organic damage index and hence serve as a relevant and sensitive index to determine disease activity. The organ lesion index has also been shown to rise with the occurrence of adverse haematological events including anaemia, leukopenia, and thrombocytopenia, which impair quality of life. Studies thus suggest the importance of a routine assessment of quality of life in SLE to facilitate the early detection of anaemia [15].
Studies have also assessed the prognostic impact of thrombocytopenia, wherein a clinical manifestation the same as that of the first episode was recorded in addition to the classification criteria at diagnosis, immunologic profile, disease activity, and end-organ damage. The study identified 58% of SLE cases with thrombocytopenia at diagnosis, and haemorrhagic manifestations were significantly associated with the degree of thrombocytopenia. The study identified thrombocytopenia to define a subgroup of patients with higher morbidity [16]. Our study identified thrombocytopenia at a much lower frequency than that reported in 8% of cases. The difference in reported frequencies can be attributed to differences in SLE disease activity that were shown to be correlated negatively with platelet counts. This difference is also considered a prognostic factor in identifying cases with an aggressive course of disease [17].
Among the white blood cell (WBC) abnormalities, studies have reported a prevalence of leukopenia in between 22% and 41.8% of cases, lymphopenia in between 15% and 82% of cases, and neutropenia in between 20% and 40% of cases. However, studies on evidence for the risk of infection with lower WBC counts continue to be contradictory [18]. Our study identified leukopenia in 17%, leucocytosis in 4%, neutropenia in 20%, and lymphopenia in 14% of SLE cases. Factors such as the number of cases, region, race, treatment, and research method used may influence the differences in the prevalence of leukopenia, neutropenia, and lymphopenia reported among various studies [19]. The haematological findings of our study also aligned with many previous publications. Levels of haemoglobin were found to be significantly decreased among SLE cases compared to the healthy controls, which is in line with a publication by Yu et al. [20]. A significant increase in ESR and RDW was also detected among SLE cases, as previously reported, wherein an increased RDW was related to active disease status and suggested to be useful as a surrogate marker for inflammation over neutrophil and lymphocyte counts [21, 22, 23]. Our present study also did not detect a significant difference in platelet counts and MPV between SLE cases and healthy controls, while some published reports indicated higher disease activity with a lower MPV [24, 25]. Studies have also assessed individual MPV fluctuations and investigated if these variations could be associated with clinical phenotypes of SLE, finding intra-individual MPV variations to be of low magnitude and disease activity fluctuations to not impact MPV values longitudinally [26].
In the case of cytokine profiling, the present study identified levels of
TNF-
The current study additionally identified a negative correlation between IL-10 levels and haemoglobin levels in SLE patients, and it also found a positive correlation between platelet counts and SLE patients. However, these findings do not match those previously reported, which instead indicated that levels of IL-10 do not correlate with haematologically active disease in SLE cases [30]. Recent studies have also indicated that IL-10 plays a dual role in SLE, wherein it inhibits pro-inflammatory effector functions and is also the main driver of the extra follicular antibody response [31]. Ethnicity has also been reported to play a role in determining the concentration of IL-10 and was found to be different between various ethnic groups. For example, Asian SLE cases were found to have more than twice the concentration of serum IL-10 compared to non-Asian cases [32].
Investigating the correlation between the proinflammatory cytokines and hematological abnormalities among SLE patients in a Saudi Arabian population provides insights into how the interplay between cytokines and hematological abnormalities may differ in this specific ethnic and geographic context. Genetic, environmental, and lifestyle factors can vary between populations, potentially leading to unique patterns in disease manifestation and progression. Additionally, conducting this research in Saudi Arabia has the potential to uncover unique insights and contribute to the global understanding of SLE and its associated hematological abnormalities. It can also have practical implications for healthcare and treatment strategies in the Saudi Arabian context.
Moreover, the hematological profiles of patients with SLE can vary among individuals and populations, including those from different ethnicities. Whether the hematological profiles of Saudi Arabian SLE patients are similar to or different from those of other ethnicities worldwide can depend on various factors, including genetic, environmental, and healthcare access factors. Nearly the same results were recorded by [27] as they examined the levels of TNF-alpha, TNF receptors, IL-6, and IL-10 in individuals with SLE. To the best of our knowledge, they addressed these factors in Egyptian patients, and it involved a limited number of patients [27, 29].
Multiple regression analysis was also performed to assess the relationship
between haematological abnormalities and increased cytokine levels. Levels of
haemoglobin and ESR were shown to be associated with both TNF-
Study limitations include the sample size, which may not be representative of the entire Saudi population; the limited number of cytokines assessed; and the lack of consideration of organ involvement in SLE disease. Additionally, our study did not differentiate between disease-oriented and treatment-causative causes of haematological abnormalities. Furthermore, treatment strategies and medications used by SLE patients in the study, and their influences were not included in this study. Additionally, data on the baseline renal, hepatic, cardiac, coagulation, and pulmonary functions were not collected, which might have affected the findings.
Our study revealed a modified cytokine pattern in Systemic Lupus Erythematosus (SLE) patients. Specifically, compared to healthy controls, we observed a substantial elevation of TNF-a, IL-6, and IL-10 levels in Saudi patients with SLE. Moreover, this increase was closely associated with the activity of SLE. Among individuals with SLE, hematological irregularities were identified as the most prevalent. In addition, the connection between cytokine patterns and hematological parameters suggests that cytokines play a significant role in the emergence of these hematological irregularities. Cytokines in their pathogenesis could potentially contribute to early diagnosis and the formulation of more targeted therapies for SLE. However, it is crucial to emphasize that additional research is needed to gain a more comprehensive understanding of how these cytokines may impact the development of anemia in SLE.
All data generated or analysed during this study are included in the published article. The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Conceptualization, FMA; methodology, FMA and MAA; formal analysis, MAA; investigation, FMA and MAA; resources, FMA; data curation, FMA and SAA; data interpretation, AFA, KHD and RS; writing—original draft preparation, FMA and MAA; writing—review and editing, FMA, MAA, SAA, AFA, KHD, and RS; supervision, FMA; funding acquisition, FMA. All authors read and approved the final manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity. All authors contributed to editorial changes in the manuscript.
The current study received approval from the Institutional Review Board (IRB) at King Saud University (Research Project No: E-19-3701). This study was also approved form IRB at Saudi Arabian Ministry of Health (IRB NO: 2019-0054M). In addition, all study participants contributed to this study were applied assigned and written informed consent.
The authors extend their appreciation to the Researchers Supporting Project number (RSP2023R506) at King Saud University, Riyadh, Saudi Arabia.
This research was funded by King Saud University, Riyadh, Saudi Arabia (RSP2023R506).
The authors declare no conflict of interest.
Publisher’s Note: IMR Press stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.