MCP-3 as a prognostic biomarker for severe fever with thrombocytopenia syndrome: a longitudinal cytokine profile study

Introduction Severe fever with thrombocytopenia syndrome (SFTS) is characterized by a high mortality rate and is associated with immune dysregulation. Cytokine storms may play an important role in adverse disease regression, this study aimed to assess the validity of MCP-3 in predicting adverse outcomes in SFTS patients and to investigate the longitudinal cytokine profile in SFTS patients. Methods The prospective study was conducted at Yantai Qishan Hospital from May to November 2022. We collected clinical data and serial blood samples during hospitalization, patients with SFTS were divided into survival and non-survival groups based on the clinical prognosis. Results The levels of serum 48 cytokines were measured using Luminex assays. Compared to healthy controls, SFTS patients exhibited higher levels of most cytokines. The non-survival group had significantly higher levels of 32 cytokines compared to the survival group. Among these cytokines, MCP-3 was ranked as the most significant variable by the random forest (RF) model in predicting the poor prognosis of SFTS patients. Additionally, we validated the predictive effects of MCP-3 through receiver operating characteristic (ROC) curve analysis with an AUC of 0.882 (95% CI, 0.787-0.978, P <0.001), and the clinical applicability of MCP-3 was assessed favorably based on decision curve analysis (DCA). The Spearman correlation analysis indicated that the level of MCP-3 was positively correlated with ALT, AST, LDH, α-HBDH, APTT, D-dimer, and viral load (P<0.01). Discussion For the first time, our study identified and validated that MCP-3 could serve as a meaningful biomarker for predicting the fatal outcome of SFTS patients. The longitudinal cytokine profile analyzed that abnormally increased cytokines were associated with the poor prognosis of SFTS patients. Our study provides new insights into exploring the pathogenesis of cytokines with organ damage and leading to adverse effects.


Introduction
Severe fever with thrombocytopenia syndrome (SFTS) is an acute tick-borne disease resulting from SFTS virus (SFTSV) infection (1).Reports indicate that SFTSV can also be transmitted among family members through close contact (2), involving exposure to blood and aerosols.Some patients were infected through close contact with sick domestic cats infected with SFTSV (3,4).Since its first report in 2009, SFTSV has been spreading across several countries and regions, including Japan, South Korea, Taiwan, Vietnam, and Thailand (5)(6)(7)(8)(9).As of 2019, 13824 laboratory-confirmed cases have been reported across 25 provinces in China (10).Despite a decrease from 30% in the early stages due to improved understanding, the case fatality rate remains high at 6.1%-21.8%(11,12), several studies showed the efficiency of favipiravir in treating SFTS patients (13,14).Timely recognition and assessment of patients with severe conditions, providing sufficient and comprehensive supportive measures, are crucial for improving outcomes in individuals with SFTS.Therefore, accurately identifying critically ill patients at an early stage is of utmost importance in clinical practice.
Currently, the mechanism underlying the severity of SFTS is not well understood.Nevertheless, multiple studies have suggested a close association between the poor prognosis of SFTS patients and cytokine storm (15,16).Numerous studies have explored the risk factors associated with adverse outcomes in SFTS patients, including clinical symptoms, signs, and laboratory parameters (17).However, only a limited number have delved into the role of cytokines in predicting a poor prognosis.
Monocyte chemoattractant protein-3 (MCP-3) is a chemokine encoded by the C-C motif chemokine ligand 7 (CCL7) gene (18).It is mainly expressed in monocytes, fibroblasts, and T cells.MCP-3 functions by attracting monocytes and eosinophils, but not neutrophils (19).Additionally, it enhances the anti-tumor activity of monocytes and binds to CC motif chemokine receptor (CCR) 1, CCR2, and CCR3, thereby influencing immune cell function (20).Previous studies have shown the robust performance of MCP-3 in identifying disease severity and predicting poor prognosis in various infectious and non-infectious diseases.For example, Sun L et al. successfully differentiated between mild and severe asthma patients using MCP-3 (21).Findings by Yang indicated a significant correlation between high serum MCP-3 concentrations and the severity of COVID-19 patients (22).Although the role of MCP-3 in predicting an unfavorable prognosis for SFTS patients remains unexplored, previous research on SFTS has indicated the crucial significance of MCP-3 in prognosticating a fatal outcome in SFTS patients.For instance, studies suggest that the MCP-3 binding protein CCR2 is the receptor for SFTSV to enter the host (23).Other studies have demonstrated that monocytes, one of the primary target cells of SFTSV, are closely associated with severe disease in patients (24).Additionally, eosinophils, one of the central chemotactic cells of MCP-3, have been identified as an independent risk factor for adverse outcomes in patients with SFTS (25).Similarly, research has shown increased intrathecal expression of CCL7 in patients with tick-borne encephalitis (26).
It is reasonable to suspect that MCP-3 plays a significant role in the cytokine storm triggered by SFTSV infection.Furthermore, the concentration of MCP-3 closely correlates with the severity of SFTS disease, serving as a reliable indicator for predicting the prognosis of SFTS patients.To validate this hypothesis, we conducted a study using the Luminex technique to assess 48 cytokines in 78 SFTS patients with varying clinical outcomes.We also monitored the dynamic changes in these 48 factors as the disease progressed.Our study provides initial evidence of the valuable predictive and prognostic role of MCP-3 in SFTS disease.

Study design and patients
This prospective study was performed from May to November 2022 at Yantai Qishan Hospital and included patients diagnosed with SFTS who were admitted to the hospital during this period and met the inclusion and exclusion criteria.The diagnostic criteria for SFTS were positive real-time fluorescent polymerase chain reaction (RT-PCR) for SFTS virus RNA during hospitalization.The exclusion criteria were: (1) Patients with other viral infections; (2) Previous leukemia, idiopathic thrombocytopenic purpura, and other blood system diseases; (3) Previous autoimmune diseases.In total, 78 patients meeting the enrollment criteria were included in the final analysis, of whom 18 had a fatal outcome.The endpoints observed in this study were defined as discharge or death (the complete study schematic chart is shown in Figure 1).The Ethics Committee of the lead center, Beijing Ditan Hospital, Capital Medical University, approved this study, which strictly adhered to the principles of the Declaration of Helsinki.Patients were informed and signed the informed consent.

Data collection
Patient information, encompassing baseline demographics, clinical characteristics, and laboratory parameters, was extracted from medical records upon admission.Acute phase means within 7 days post-symptom onset (24,27).We acquired serial peripheral blood samples from 78 SFTS patients 12 hours after admission and every other day during their hospitalization.These serum samples were promptly centrifuged and stored in a freezer at -80°C until further analysis.Besides, six volunteers were selected as healthy controls and matched for gender and age (Supplementary Table 1).

Definition
Skin change is defined as at least one of the signs: skin color changes, skin eruption, or the development of nodules.Neurological abnormalities encompass changes in consciousness and signs such as involuntary movements, nerve reflexes, and muscle tension.

Statistical analyses
Normal distribution data were presented as mean ± standard deviation and compared between groups using the independentsamples t-test.Abnormally distributed data were presented as median with interquartile range (IQR) and compared between groups using the Mann-Whitney U test.Categorical variables were expressed as percentage and analyzed using the c2 test.The RF algorithm was employed to screen for important variables, and the predictive accuracy of prognostics was assessed using a receiver operating characteristic (ROC) curve analysis.Correlations between variables were evaluated using the Spearman correlation test.Linear mixed models were utilized for continuous outcomes and estimated marginal means (EMMs) with a 95% confidence interval (CI) were calculated.Statistical analyses were conducted using SPSS software (version 26.0), and figures were generated using the R programming language (version 4.3.1).All tests were two-sided, and P < 0.05 was considered statistically significant.

Baseline demographic, laboratory, and clinical characteristics
We enrolled 78 patients with confirmed SFTS in our study.Based on clinical outcomes, they were categorized into a survival group (n=60) and a non-survival group (n=18), resulting in a fatality rate of 23.1% (18/78).Table 1 presents the baseline demographics, clinical characteristics, and laboratory parameters at admission for both survival and non-survival groups.All SFTS patients had an average age of 65.89 ± 11.19 years.Among these patients, the survivors had an average age of 64.92 ± 11.76 years, while the non-survivors had higher average age of 69.11 ± 8.54 years.Out of the total 78 patients, 37 (47.4%) were male, including 27 (45.0%) in the survival group and 10 (55.6%) in the non-survival group.There was no significant difference in age or gender between the two groups (P > 0.05).In comparison to the survival group (925.5, 404.25-2773.25), the non-survival group (3858, 1746.5-4921)exhibited a higher viral load, demonstrating significant differences (P < 0.05).In terms of laboratory examination, we observed that alanine aminotransaminase (ALT), aspartate aminotransferase (AST), direct bilirubin (DBIL), blood urea nitrogen (BUN), creatinine (CREA), creatine kinase (CK), creatine kinase isoenzyme MB (CK-MB), a-hydroxybutyrate dehydrogenase (a-HBDH), lactate dehydrogenase (LDH), K + , Na + , procalcitonin (PCT), activated partial thromboplastin time (APTT), thrombin time (TT), and D-dimer levels were significantly higher in the non-survival group compared to the survival group (P < 0.05).All patients showed a decrease in white blood cell (WBC) counts, lymphocytes (LYM), and platelet (PLT) counts, while there was no significant difference between the two groups (P > 0.05).

MCP-3 serves as a crucial biomarker in predicting the prognosis of SFTS patients B A
The importance of variables ranked by random forest.characterized by MCP-3 levels higher than the cutoff value.The fatality rate of the high-risk group (65.2%) was significantly higher than that of the low-risk group (5.5%) (P < 0.001) (Figure 4B).We further employed the Kaplan-Meier (KM) analysis method to estimate cumulative survival.The results revealed that SFTS patients in the high-risk group, also known as MCP-3 high group, exhibited lower cumulative survival than those in the lowrisk group (P < 0.001) (Figure 4C).Furthermore, the clinical utility of MCP-3 in predicting adverse outcomes in patients with SFTS in the acute phase was evaluated through a decision curve analysis (DCA).As shown in Figure 4D, at threshold probabilities between 0.1 and 0.7, the clinical benefit of MCP-3 was markedly superior to that of complete intervention or no intervention at all.

Longitudinal cytokine profiles of SFTS patients with different clinical outcomes
In this study, MCP-3 levels exhibited a rapid increase, reaching a maximum, followed by a decrease and stabilization at higher levels until death in non-survivors.These levels consistently surpassed those in survivors and healthy controls.A similar trend was observed for IL-1a, IL-1Ra, IL-4, IL-10, IL-17, LIF, IFN-g, GM-CSF, M-CSF, SCGF-b, basic FGF, HGF, MCP-1, Eotaxin, MIG, and IP-10.The levels of IL-6, IL-16, IL-18, IFN-a2, HGF, MCP-1, MCP-3, Eotaxin, CTACK, MIG, and MIF were significantly elevated in non-survivors, whereas they remained relatively stable in survivors, comparable to healthy controls.Cytokines such as IL-6, IL-16, IFN-a2, HGF, MCP-1, MCP-3, Eotaxin, MIG, and MIF exhibited similar levels when comparing HCs and survivors.Additionally, we noted lower levels of IL-9, TNF-b, PDGF-BB, and RANTES in non-survivors compared to survivors during hospitalization.Unlike other cytokines, the concentrations of them tended to increase during the late course of the disease in survivors (Figure 6).

Discussion
SFTS is a newly emerging infectious disease with a high mortality rate.The World Health Organization has recognized SFTSV as one of the top-prioritized pathogens for research and development (30).Compared to healthy controls, the study observed that all SFTS patients showed increased levels of various cytokines, except for individual ones such as IL-9, TNF-b, GRO-a, and RANTES.Further analysis indicated that the non-survival group exhibited significantly higher levels of 32 cytokines than the survival group.This finding aligns with previous research, supporting the notion that the immune dysfunction-cytokine storm closely linked to the unfavorable prognosis of SFTS patients (31,32).
According to the RF algorithm model, MCP-3 has identified as a crucial factor in predicting adverse clinical outcomes in SFTS patients.In non-survivors of SFTS, MCP-3 levels rapidly increased during the acute phase, reaching the highest level.As the disease progressed, MCP-3 concentrations decreased slightly but remained higher than in non-survivors until death.Moreover, compared to healthy controls, the MCP-3 concentration in the patients in the survival group showed a slight increase, but no significant difference observed.
MCP-3 is a member of the monocyte chemotactic proteins (MCP) subgroup of CC chemokines.It was produced by various cells, including monocytes, T lymphocytes, fibroblasts, and platelets (19).MCP-3 is a highly versatile chemokine, activating a broad spectrum of leukocytes, such as natural killer cells and T lymphocytes (33).It is a chemoattractant for monocytes, eosinophils, macrophages, basophils, lymphocytes, and dendritic cells (20).studies have demonstrated the pivotal role of MCP-3 in distinguishing between infectious and non-infectious diseases.Although there is currently no relevant study on the mechanism by which MCP-3 mediates the severity of SFTS, we attempted to analyze it from two perspectives: viral infiltration and inflammatory damage.Our study found that the serum SFTSV level was significantly higher in the non-survival group than in the survival group, and the serum MCP-3 level positively correlated with the SFTSV.CCR2 is recognized as one of the primary receptors of MCP-3 (35).Recent studies have also identified CCR2 as the host receptor of SFTSV.Knocking out CCR2 has been shown to significantly reduce virus binding and infection, while increased expression of CCR2 leads to enhanced infection (23).Hence, it is plausible that MCP-3 assists CCR2 in mediating virus invasion into the host.Additionally, studies have demonstrated that in COVID-19 patients, the increase in viral load corresponds to the upregulation of critical chemokines, including CCL7, CCL2, CXCL8, and others (36, 37).
In terms of inflammation, MCP-3, as an inflammatory cytokine, plays a crucial role in maintaining a balanced level of circulating inflammatory monocytes.A deficiency in MCP-1 or MCP-3 results in approximately 40-50% decrease in monocyte recruitment during infection (38).A study by Girkin J's team demonstrated that CCL7 is the most significantly upregulated gene induced by rhinovirus infection, and inhibiting CCL7 reduces inflammation and airway hyperreactivity (AHR) (39).Additionally, children with naturally occurring viral infections release high concentrations of MCP-3 and MCP-4 into their nasal secretions (40).To examine the relationship between MCP-3 and organ damage, correlation analysis was conducted on laboratory indicators such as ALT, AST, LDH, a-HBDH, APTT, and D-dimer etc.Previous studies identified these indicators as independent risk factors for poor prognosis in SFTS patients.The findings revealed a significant positive correlation between MCP-3 and these indicators.
In this study, we found that the concentrations of TNF-b had increased in the late stage for survivors, and the related studies were rarely reported in SFTS.There was a study found that TNF-b was considerably increased in patients with COVID-19 (41).Previous studies have shown that the concentrations of RANTES in plasma tended to increase during the late course of the disease, which was consistent with our findings in the survival group (42,43), similar finding was reported in the late stage of survivors with Middle East respiratory syndrome (MERS) that RANTES marked elevation (44).Our study also suggested that the PLT levels are closely correlated with the levels of RANTES.Another study manifested that RANTES had large fluctuations after onset, and the higher virus loads suppressed the production of RANTES to a large extent (15).RANTES can recruit and activate T cells and they may play a crucial role in recovery from SFTS.
This study has certain limitations.Firstly, the sample size is limited, and the source is singular.Secondly, although we observed the role of MCP-3 in the prognosis of SFTS patients, further experiments are needed to explore its mechanism of action.Lastly, in future research, we aim to expand the sample size and sources, employing sequencing technology to investigate the mechanisms underlying the elevated MCP-3 levels and their impact on patients with severe SFTS.

Conclusions
In summary, we observed a correlation between abnormally elevated MCP-3 levels and a poor prognosis in SFTS patients.This study is the first to reveal that MCP-3 levels could serve as a meaningful biomarker for predicting the severe and fatal outcome of SFTS patients.These findings contribute to the advancement of our understanding, exploration, and management of SFTS.

FIGURE 1
FIGURE 1Workflow diagram of study design.

FIGURE 6
FIGURE 6 Dynamic evolution of serum cytokines in SFTS patients.Estimated marginal means (EMMs) and 95%CI with linear mixed-effects models for dynamic analysis of cytokines.Error bars indicate 95%CI.The dotted horizontal line within each cytokine panel represents the average value for healthy controls.

TABLE 1
Baseline demographics, clinical characteristics, and laboratory parameters of patients with SFTS.
(34)arch by Sun L's team indicates the potential utility of serum MCP-3 levels in distinguishing between patients with mild and severe asthma (21).Yang et al. examined 48 cytokines in the peripheral blood of COVID-19 patients, identifying IP-10, MCP-3, and IL-1ra as biomarkers associated with disease severity and fatal outcomes(34).