Application of complement C3 in diagnosis and development of HLH and prediction and prognostic analysis of response to treatment

Abstract

The invention belongs to the technical field of biological medicine, and discloses application of complement C3 in diagnosis and development of HLH, treatment response prediction and prognosis analysis. The invention particularly relates to application of a complement C3 in diagnostic analysis of HLH and application of the complement C3 in construction of a prediction model for developing from part of HLH to HLH, and further provides a prediction model for early death of HLH patients and application of the prediction model. The disclosure finds that the complement C3 can be used for diagnostic analysis of HLH, can also be used for predicting the risk of developing from part of HLH to HLH, and can also be used for predicting the risk of early death of HLH patients.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical technology, and in particular relates to the application of complement C3 in the diagnosis, development, prediction of treatment response and prognosis analysis of HLH. Background Art

[0002] Hemophagocytic lymphohistiocytosis (HLH), also known as hemophagocytic syndrome (HPS), is a life-threatening hyperinflammatory response syndrome characterized by abnormal activation and proliferation of inflammatory cells and the release of excessive cytokines caused by this immune dysfunction. HLH can be divided into primary (genetic) and secondary (reactive) forms according to the presence or absence of corresponding molecular defects. Secondary factors include infection, tumors, rheumatic immune diseases, drugs and other related causes. In adults, viral infection, especially Epstein-Barr virus (EBV) infection, is the most common secondary factor of HLH. Tumor patients, especially hematological tumors (HM) such as non-Hodgkin's lymphoma, are also susceptible to HLH. In addition, rheumatic immune system diseases (RH) also play an important role in the secondary factors of HLH in adults. The clinical manifestations of HLH include persistent fever, cytopenia, hepatosplenomegaly, liver dysfunction, reduced or absent natural killer (NK) cell activity, and hyperplasia of tissue phagocytic cells.

[0003] Although HLH is primarily considered a genetic disease that affects children, recent studies have shown that it can occur at any age. However, to date, most clinical guidelines, prospective studies, and clinical trials have focused on pediatric patients. The HLH-2004 diagnostic criteria, although originally developed for pediatric patients, are still the most commonly used criteria in adult patients. The HLH-2004 diagnostic criteria include eight items, and HLH can be diagnosed when at least five items are met. In clinical practice, it is often observed that adult patients meet some of the HLH-2004 criteria due to secondary causes but are not diagnosed with HLH. For example, the HLH-2004 diagnostic criteria have eight items, and 5 of them must be met to confirm HLH. If less than 5 items are met, that is, the criteria are partially met (only 1 to 4 criteria are met), which may indicate a partial HLH state. Therefore, our goals include identifying factors that promote the progression of partial HLH patients to HLH. In terms of prognosis, the mortality rate of adult HLH ranges from 20% to 88%, mainly due to refractory HLH, secondary infections, and progression of underlying secondary diseases. Many studies have reported that death in HLH occurs mainly during induction therapy, especially within the first 8 weeks, with a high mortality rate. To date, the prognostic factors associated with early death in adult patients with HLH remain uncertain. Summary of the invention

[0004] In view of the above problems, the present invention provides the application of complement C3 in the diagnosis, development, prediction of treatment response and prognosis analysis of HLH, mainly to solve the problem that the development of HLH cannot be effectively analyzed and predicted.

[0005] In order to solve the above problems, the present invention adopts the following technical solutions:

[0006] The first aspect of the present invention relates to the use of complement C3 in the diagnostic analysis of HLH disease risk.

[0007] In specific applications, the application methods include:

[0008] 1) The use of preparations for detecting complement C3 levels in the preparation of products for analyzing the risk of HLH. When the complement C3 level is abnormally low, it indicates an increased risk of HLH, providing a basis for clinical judgment of the disease;

[0009] 2) Complement C3 can be used as a risk marker for analyzing the progression of partial HLH to HLH. Lower C3 levels are associated with an increased risk of HLH development. When C3 levels decrease, it indicates an increased risk of further development of HLH, especially when C3 levels are lower than the critical point of 0.764 g / L (the critical point can also be re-determined based on different samples, not strictly limited to this) as in this study, indicating a significantly increased risk of progression to HLH. To a certain extent, it can even be considered that when C3 levels are lower than the critical point of 0.764 g / L, it indicates the progression from partial HLH to HLH. It can also be understood that C3 levels lower than the critical point of 0.764 g / L are a risk factor for the progression of partial HLH to HLH, which provides a basis for clinical judgment of the development of HLH disease, especially for the partial HLH population, which can be analyzed more accurately. By detecting complement C3 levels, the risk of partial HLH to HLH in some specific populations can be analyzed;

[0010] 3) Use of a preparation for detecting complement C3 levels in the preparation of products for analyzing the severity of HLH or the prognosis of HLH treatment; wherein, the complement C3 level is negatively correlated with the severity of HLH, which can also be understood as the people with C3 levels below 0.764g / L have more severe HLH severity than the people with C3 levels not less than 0.764g / L; the complement C3 level is positively correlated with the prognosis of HLH treatment, and when the C3 level is not less than 0.764g / L, the prognosis of HLH treatment is expected to be better than that of the people with C3 levels below 0.764g / L. Generally speaking, when performing severity analysis, most of them are aimed at people who have been diagnosed with HLH, and their C3 levels are analyzed to evaluate the severity of HLH disease.

[0011] Both "partial HLH" and "HLH" are generally determined by clinical criteria. When complement C3 decreases, it indicates that the disease is developing. The continuous decrease of complement C3 indicates that the condition is gradually progressing from partial HLH to HLH, and they can be complementary to each other and diagnosed as suffering from HLH. Some HLH patients meet some of the criteria of HLH-2004 due to secondary reasons, but are not diagnosed with HLH. For example, there are 8 diagnostic criteria for HLH-2004, and 5 of them must be met to confirm HLH. If less than 5 criteria are met, it means that the criteria are partially met (only 1 to 4 criteria are met). HLH patients meet at least 5 of the diagnostic criteria of HLH-2004.

[0012] For this application, some of these conditions are optional, and any one of the conditions in each paragraph can be selected separately:

[0013] Among them, the methods for detecting complement C3 levels include at least one-way immunodiffusion method, rocket immunoelectrophoresis method, flow cytometric immunoluminescence method (the method used in this study), and other methods that can detect complement C3 levels.

[0014] Among them, complement C3 levels and other indicators are generally tested and analyzed using standards consistent with clinical indicators, and are generally not limited to specific standard testing methods. In addition, the high and low standards of complement C3 levels can be set at critical values ​​according to clinical needs, or other means of analysis can be used to obtain critical values.

[0015] Among them, the level of complement C3 can be used as a reference to the clinical normal value to evaluate whether the complement C3 level is abnormally reduced or increased, and the critical value can also be specifically confirmed by analytical means. Specifically, when the complement C3 level is abnormally reduced, the severity of HLH increases, and when the complement C3 level is increased, the severity of HLH decreases. In other words, if the complement C3 level of some HLH patients is further reduced, it indicates that they may have developed into HLH. When complement C3 is used as a target for analyzing the severity of HLH or diagnosing HLH, it can be judged whether it develops from partial HLH to HLH based on the complement C3 level and the critical value. Taking the samples involved in this study as an example, the critical value was analyzed. In order to distinguish the best critical point between HLH and partial HLH patients, the critical point of C3 can be determined as 0.764g / L based on the curve and the highest Youden index. The C3 concentration is high when it is higher than the critical point, and low when it is lower than the critical point. That is, when the C3 concentration of some HLH patients is detected to be lower than 0.764g / L, it can be considered that partial HLH develops into HLH.

[0016] Among them, when complement C3 is used as a prognostic marker, when the complement C3 level is abnormally low, it indicates that the prognosis of HLH treatment is poor, and when the complement C3 level is elevated, it indicates that the prognosis of HLH treatment is good.

[0017] A second aspect of the present invention relates to a prediction model for the progression from partial HLH to HLH and its application, wherein the prediction model can Analyze the risk of progression from partial HLH to HLH.

[0018] The prediction model includes the following formula: Riskscore = 1.25*C3 + 0.95*malignant tumor + 0.17*PT-3.30; C3 is the level of serum protein C3, low C3 means C3 < 0.764g / L, low C3 is 1, non-low C3 (C3 ≥ 0.764g / L) is 0, PT is prothrombin time (common clinical unit), malignant tumor index: 1 if the disease is present, otherwise 0; Riskscore is the risk score for the development of partial HLH to HLH. Flow cytometry immunoluminescence is used as the C3 level detection method, and 0.764g / L is used as the boundary between low C3 and non-low C3. Of course, if other methods are used, this standard can also be used, or the difference between the standards can be converted.

[0019] When this model is applied, the risk level can be assessed based on the score calculated according to each indicator. When the risk score is compared with the threshold: if Riskscore>threshold, it develops from partial HLH to high HLH risk; if Riskscore=threshold, it is to be estimated (in clinical practice, it can be determined whether it is biased towards one type of risk based on the rounded result, or other definition methods can be used, which are not specifically limited here); if Riskscore<threshold, it develops from partial HLH to low HLH risk.

[0020] Hematologic malignancies and rheumatic immune system diseases are diagnosed based on clinical diagnostic criteria to determine whether the disease is present. For example, hematologic malignancies are generally hematologic malignant tumors.

[0021] When applied, this model can at least be used for risk assessment for the aforementioned "adult patients who meet some of the HLH-2004 criteria but are not diagnosed with HLH due to secondary causes are often observed" to assess the risk of this group of people developing HLH. It can also be used for other patients who meet some of the HLH criteria to develop HLH.

[0022] For the analysis model, some of these conditions are optional:

[0023] Wherein, the threshold is the optimal threshold obtained by calculating through the R software package; or, the threshold is the optimal threshold obtained by analyzing the population to be detected through the R software package (hereinafter the same). Specifically, the threshold is the optimal threshold obtained by calculating through the R software package, and the specific analysis and calculation method can adopt the existing technology. Of course, even if the optimal threshold is calculated, the critical value can also float within a certain range according to clinical requirements in practical application. Further, its specific analysis example can be carried out in a certain population, and then the risk score calculation is carried out according to the population, and then the risk of HLH development to HLH risk of the population is assessed; when it is actually applied, as long as the present model is applied, it should be regarded as within the scope of the present invention, but the setting of the threshold is not considered too much. In short, in terms of the selection of the setting of the threshold, the commonly used method for obtaining the optimal threshold is to select the threshold that maximizes the difference between the true positive rate (TPR) and the false positive rate (FPR) of the model as the optimal threshold, that is, to find the threshold that maximizes TPR-FPR, by calculating TPR and FPR under different thresholds, and then find the threshold corresponding to the maximum TPR-FPR value as a reference value.

[0024] Among them, serum protein C3 level can be a commonly used indicator in clinical practice, such as the normal value of complement C3 in clinical practice: one-way immunodiffusion method, 0.80-1.20 g / L; rocket immunoelectrophoresis method, 0.9879-1.4559 g / L; flow cytometry immunoluminescence method, 0.790-1.520 g / L. In this scheme, the above or other similar methods can be used to obtain the complement C3 level in the sample to be analyzed.

[0025] In terms of the application of the analysis model: a product that analyzes the risk of progression from partial HLH to HLH can be constructed based on the analysis model. The product can be an analysis system that receives various parameters and calculates to obtain a risk score.

[0026] A third aspect of the present invention relates to a system for predicting the risk of progression from partial HLH to HLH, the system being based on the risk of progression from partial HLH to HLH. Prediction model setup for HLH progression to HLH.

[0027] Specifically, the system for predicting the risk of progression from partial HLH to HLH includes a sample detection module, a risk assessment module, and a result comparison module.

[0028] The functions of the sample detection module, risk assessment module and result comparison module are as follows: the sample detection module is used to detect and analyze the samples from the subjects to be tested, and obtain whether the subjects to be tested have malignant tumors and the serum protein C3 level and prothrombin time of the samples. The risk assessment module inputs the above data into the prediction model formula and calculates the Riskscore, Riskscore = 1.25*C3+0.95*malignant tumor+0.17*PT-3.30; where C3 is the serum protein C3 level, low C3 means C3 < 0.764g / L, low C3 is 1, non-low C3 (C3 ≥ 0.764g / L) is 0, PT is prothrombin time, malignant tumor index: 1 if the patient is ill, otherwise 0; Riskscore is the risk score of HLH with bleeding. The result comparison module compares the obtained Riskscore with the threshold to obtain the risk rating from partial HLH to HLH. If Riskscore>threshold, it develops from partial HLH to HLH high risk, if Riskscore=threshold, it is to be estimated, and if Riskscore<threshold, it develops from partial HLH to HLH low risk.

[0029] The fourth aspect of the present invention relates to a prediction model for early death of HLH patients, which can be used to predict the early death of HLH patients. risk of early death.

[0030] The prediction model includes the following formula: Riskscore = 0.53*C3+0.44*PCT; where: C3 is the serum protein C3 level, low C3 represents C3 < 0.764g / L, low C3 is 1, and non-low C3 (C3 ≥ 0.764g / L) is 0; PCT represents the procalcitonin level, high PCT represents PCT > 2ug / L, high PCT is 1, and non-high PCT (PCT ≤ 2ug / L) is 0; Riskscore is the risk score for early death in HLH patients.

[0031] When this model is applied, after calculating the score, the risk level can be evaluated according to the score value. When riskscore is compared with the threshold: if Riskscore>threshold, HLH patients have a high risk of early death; if Riskscore=threshold, it is to be estimated; if Riskscore<threshold, HLH patients have a low risk of early death.

[0032] For analytical model application, some of these conditions are optional:

[0033] Among them, a product for analyzing the early death risk of HLH patients can be constructed based on the analysis model. The product can be an analysis system that receives various parameters and calculates to obtain a risk score.

[0034] Among them, early death can be explained as death in the early stage of the disease, such as early death within 8 weeks of illness. Based on this prediction model, the risk of early death in HLH patients after illness can be analyzed, providing more references for clinical treatment.

[0035] The fifth aspect of the present invention relates to a risk prediction system for early death of HLH patients. The system is based on the early Prediction model setup for mortality.

[0036] Specifically, the risk prediction system for early death in HLH patients includes a sample detection module, a risk assessment module, and a result comparison module.

[0037] The functions of the sample detection module, risk assessment module and result comparison module are as follows: the sample detection module is used to detect and analyze the samples from the subjects to be tested, and obtain whether the subjects to be tested have rheumatic immune system diseases and the levels of serum protein C3 and procalcitonin in the samples. The risk assessment module inputs the above data into the risk prediction model formula for early death of HLH patients and calculates Riskscore, Riskscore = 0.53*C3+0.44*PCT; where C3 is the level of serum protein C3, low C3 represents C3 < 0.764g / L, low C3 is 1, non-low C3 is 0, PCT represents procalcitonin level, high PCT represents PCT > 2ug / L, high PCT is 1, non-high PCT (PCT ≤ 2ug / L) is 0; Riskscore is the risk score for early death of HLH patients. The result comparison module compares the obtained Riskscore with the threshold to obtain the early death risk rating of HLH patients. If Riskscore>threshold, the HLH patient has a high risk of early death, if Riskscore=threshold, it is to be estimated, and if Riskscore<threshold, the HLH patient has a low risk of early death.

[0038] In the present disclosure, C3 is identified as a valuable predictive and prognostic biomarker in adult HLH, and low C3 levels are associated with increased HLH disease severity and poor prognosis. It is specifically clarified that complement C3 can be used for the diagnosis and analysis of HLH, and can also be used to construct an analytical model to predict the risk of progression from partial HLH to HLH, and can also be used to construct an analytical model to predict the risk of early death in HLH patients, providing a risk prediction scheme for whether a partial HLH population will develop into HLH, and also providing an effective means for the risk of early death in HLH patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 : Flowchart for selection of patients included in the study.

[0040] Figure 2: The predictive value of C3 in the progression from partial HLH to HLH. (A) The distribution of different triggering factors in the pre-HLH ​​and HLH groups, the pre-HLH ​​group was mainly triggered by infection and rheumatism, while the HLH group was mainly triggered by infection and malignant tumors; (B) Under different triggering factors, the C3 of the HLH group was significantly lower than that of the pre-HLH ​​group; (C) Compared with the pre-HLH ​​group, the C3 of the HLH group was significantly decreased; (D) Forest plot of univariate logistic regression analysis; (E) Among the different triggering factors of HLH, the RH-HLH subgroup had the lowest C3 level, followed by the EBV-HLH and HM-HLH subgroups. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001.

[0041] Figure 3 :The significance of C3 in the prognosis and survival of HLH patients. (A) ROC curve of C3 was used to distinguish partial HLH from HLH; (B) Survival analysis showed that the low C3 group had a higher risk of death; (C) Mortality and overall mortality at 8 weeks and 1 year in the low C3 group and the high C3 group; (D) Forest plot of univariate Cox regression analysis; (E) Dynamic changes of C3 values ​​before and after HLH treatment. *P<0.05, **P<0.01, ***P<0.001. DETAILED DESCRIPTION

[0042] The present invention will be further described below in conjunction with specific research projects.

[0043] 1. Materials and Methods

[0044] A retrospective analysis was performed on patient data collected at Wuhan Union Hospital, China, from December 1, 2012, to November 9, 2023. The inclusion criteria for patients were as follows: (1) aged ≥18 years; (2) diagnosed or suspected of having HLH; (3) patients who met at least five of the HLH-2004 diagnostic criteria were classified into the HLH group, while patients who met fewer than five criteria were assigned to the partial HLH group; and (4) with traceable clinical records. The diagnostic criteria for HLH-2004 are as follows: (a) fever; (b) splenomegaly; (c) cytopenias of ≥2 lineages in peripheral blood: hemoglobin <90 g / L, platelets <100 × 10^9 / L, and neutrophils <1.0 × 10^9 / L; (d) hypertriglyceridemia and / or hypofibrinogenemia: fasting triglycerides ≥3.0 mmol / L, fibrinogen ≤1.5 g / L; (e) hyperplasia of phagocytes in the bone marrow, spleen, or lymph nodes; (f) low or absent NK cell activity (according to local laboratory reference values); (g) serum ferritin ≥500 mg / L; and (h) sCD25 (ie, soluble IL-2 receptor) ≥2,400 U / mL or ≥6,400 pg / mL. Exclusion criteria included patients under 18 years of age and patients with refractory or relapsed HLH. Telephone follow-up was performed based on hospitalization information. The follow-up period ends on December 10, 2023, or on the date of death or loss of follow-up.

[0045] Patient information was collected retrospectively from the hospital's electronic medical record system. The following variables were collected: age, sex, underlying diseases (such as infection, malignancy, rheumatological and immune diseases, and other causes), and laboratory test results at diagnosis. The laboratory parameters measured included: C3, C4, white blood cells (WBC), hemoglobin (Hb), absolute neutrophil count (ANC), platelets (PLT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbil), albumin (Alb), creatinine (Cr), amino acid nitrogen (BUN), triglycerides (TG), lactate dehydrogenase (LDH), C-reactive protein (CRP), procalcitonin (PCT), fibrinogen (FIB), activated partial thromboplastin time (APTT), prothrombin time (PT), D-dimer, carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), neuron-specific enolase (NSE), and EBV-DNA copies in plasma and peripheral blood mononuclear cells (PBMCs). Peripheral blood lymphocyte percentage changes, including total T cells, CD4+ T cells, CD8+ T cells, B cells, and NK cells, as well as cytokine levels (such as interleukin (IL)-2, IL-4, IL-6, IL-10, interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α)), and diagnostic variables were collected. In addition, the dynamic changes of C3 values ​​before, during, and after HLH treatment were also collected.

[0046] Normally distributed continuous variables were expressed as mean and standard deviation (SD), while non-normally distributed ones were described as median (M) and interquartile range (IQR). Categorical variables were reported as counts (n) and percentages (%). When comparing two independent groups of samples, the independent sample t-test was used to analyze normally distributed continuous variables, and the Mann-Whitney U test was used to analyze non-normally distributed continuous variables. For categorical variables, the chi-square test was used. In order to evaluate the diagnostic value of serum C3, the receiver operating characteristic (ROC) curve was constructed, and the area under the ROC curve (AUC) was calculated. The optimal cutoff point of C3 was determined by the Youden index (=sensitivity + specificity-1). In the univariate analysis, variables with a P value <0.05 were included in the logistic regression or COX regression analysis. C3 was included in the multivariate analysis regardless of significance. After excluding variables with very low correlation, only variables with clinical relevance and statistical significance were included in the multivariate regression analysis. All statistical analyses and graphs were performed using R software version 4.2.2 and GraphPad Prism version 9.0.

[0047] 2. Results and analysis

[0048] Patient Selection and Clinical Characteristics

[0049] This study recruited adult patients who were suspected or diagnosed with hemophagocytic lymphohistiocytosis (HLH) at Wuhan Union Hospital between December 1, 2012 and November 9, 2023. The patient selection flow chart is shown in Figure 1 As shown. A total of 2607 patients were initially included, of which 1065 duplicate patient records were deleted based on identity information. After screening, a total of 1265 patients met the inclusion criteria (such as age of onset, discharge diagnosis, and traceable clinical records). After reviewing the patient's admission records and past medical history, 50 patients with relapsed and refractory HLH were excluded, and the total number of patients included in this study was 1215. Subsequently, the patient's complete medical records were reviewed, and patients who met at least five of the HLH-2004 diagnostic criteria were assigned to the HLH group (n=627), while patients who met less than five criteria were assigned to the partial HLH group (n=588).

[0050] The demographic and diagnostic information of the included patients are shown in Table 1 , and other laboratory test results are shown in Table S1 . There was no significant difference in the age of onset between the HLH group and the partial HLH group ( P = 0.872 ). However, the proportion of females was higher in the partial HLH group ( P = 0.007 ). Among the secondary factors, infection was the main secondary factor in both groups, while malignant tumors were more common in the HLH group, and rheumatoid immune diseases were more common in the partial HLH group ( Table 1 ; Figure 2 In the HLH group, there were 309 females (49%), and the median age at diagnosis was 51 years (34, 63 years). Abnormal diagnostic indicators were more common in the HLH group, and the median number of HLH-2004 diagnostic criteria met was 5 (5, 6), while the median number of HLH-2004 criteria met in the partial HLH group was 3 (2, 4). In addition, the median C3 level in the HLH group was 0.63 g / L, which was significantly lower than the median C3 level in the partial HLH group (0.84 g / L) (P < 0.001) (Table 1; Figure 2(B). However, there was no significant difference in C4 level between the two groups (P = 0.582). The HLH group showed more severe cytopenia, with significantly lower levels of WBC (P < 0.001), Hb (P < 0.001), and PLT (P < 0.001) compared with the partial HLH group. Abnormal coagulation function (D-dimer: P = 0.002, PT: P < 0.001, APTT: P < 0.001) and liver function damage (Tbil: P < 0.001, ALT: P = 0.002, AST: P = 0.006, Alb: P < 0.001) were also more common in the HLH group. There was no significant difference in the inflammatory marker CRP between the two groups (P = 0.625), but PCT was significantly increased in the HLH group (P = 0.001). In addition, the tumor markers CA125 (P<0.001), CA153 (P<0.001), and NSE (P<0.001) were significantly increased in the HLH group. The proportion of total T cells in peripheral blood lymphocytes was higher in the HLH group (P=0.025). Although there was no significant difference, the percentages of B cells (P=0.1) and NK cells (P=0.105) were lower in the HLH group. The levels of IL-2 (P=0.032), IL-6 (P<0.001), IL-10 (P<0.001), and IFN-γ (P<0.001) were significantly increased in the HLH group. In addition, the EBV-DNA copies in plasma (P=0.01) and PBMC (P<0.001) in the HLH group were significantly higher than those in some HLH groups (Table 2).

[0051] Table 1. Demographic and diagnostic information of patients with HLH and selected HLH

[0052]

[0053]

[0054] a**P<0.01, ***P<0.001;

[0055] bInfection refers only to EBV infection and other infections, and elevated sCD25 means sCD25 ≥ 2400 U / mL or ≥ 6400 pg / mL;

[0056] cAbbreviations: HM, hematological malignancies; myelodysplastic syndrome; rheumatic diseases; Epstein-Barr virus; SF, serum ferritin; FIB, fibrinogen; triglycerides.

[0057] Table S1. Laboratory index characteristics of HLH and some HLH patients

[0058]

[0059]

[0060] a*P<0.05,**P<0.01,***P<0.001

[0061] bAbbreviations: white blood cell (WBC), absolute neutrophil count (ANC), hemoglobin (Hb), platelet (PLT), prothrombin time (PT), activated partial thromboplastin time (APTT), total bilirubin (Tbil), albumin (Alb), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (Cr), blood urea nitrogen (BUN), lactate dehydrogenase (LDH), C-reactive protein (CRP), procalcitonin (PCT), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), neuron-specific enolase (NSE), interleukin (IL), interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), Epstein-Barr virus (EBV), peripheral blood mononuclear cells (PBMC).

[0062] Table 2. Relationship between C3 level and other variables

[0063]

[0064]

[0065] a*P<0.05, **P<0.01, ***P<0.001;

[0066] bAbbreviations: FIB, fibrinogen; TG, triglyceride; C4, complement component 4; WBC, white blood cell; ANC, absolute neutrophil count; PLT, platelet; PT, prothrombin time; APTT, activated partial thromboplastin time; Alb, albumin; AST, aspartate aminotransferase; CRP, C-

[0067] Reactive protein; CA153, carbohydrate antigen 153; peripheral blood mononuclear cells.

[0068] The predictive value of C3 in the progression of partial HLH to HLH

[0069] To determine the optimal cutoff point of serum C3 concentration in distinguishing HLH from partial HLH patients, ROC analysis was performed to evaluate its sensitivity and specificity. According to the curve and the highest Youden index, the cutoff point of C3 was 0.764 g / L ( Figure 2C in the middle). Values ​​below this critical point were defined as low C3, while values ​​above this critical point were defined as high C3. In order to clarify the predictive role of low C3 in the progression of partial HLH to HLH, a multivariate logistic regression analysis was performed on the index criteria of P<0.05 in the univariate analysis. The results verified that low C3 was an independent risk factor for predicting the progression of partial HLH to HLH (OR=3.94, P<0.001). Lower C3 levels were associated with a higher risk of HLH development. Malignant tumors and abnormal coagulation function (PT) were also identified as independent risk factors for predicting the progression of partial HLH to HLH, and RHD was considered a protective factor ( Figure 2 D in the middle, Table S2). Therefore, C3, malignant tumor, rheumatic immune system disease, and PT were included in the prediction model for logistic regression analysis to calculate the partial regression coefficient of each variable, and the prediction model formula for promoting the progression of patients from partial HLH to HLH was obtained: Riskscore = 1.25*C3+0.95*malignant tumor+0.17*PT-3.30; where C3 is the serum protein C3 level, low C3 means C3 < 0.764 g / L, low C3 is 1, non-low C3 (C3 ≥ 0.764 g / L) is 0, PT is prothrombin time, and malignant tumor index: 1 if the patient is ill, otherwise 0.

[0070] Table S2. Logistic regression analysis of predictive factors for the progression of partial HLH to HLH

[0071]

[0073] a*P<0.05, **P<0.01, ***P<0.001;

[0074] bAbbreviations: Complement component 3 (C3), rheumatic disease (RHD), prothrombin time (PT), aminotransferase (ALT), neuron-specific enolase

[0075] (NSE).

[0076] In the HLH group and partial HLH group, regardless of whether the secondary factor was infection, rheumatic autoimmune disease or malignant tumor, the C3 level was significantly lower ( Figure 2 In addition, among HLH patients with different underlying diseases, the RH-HLH subgroup had the lowest C3 level.

[0077] Correlation between HLH severity and C3 level

[0078] There were no significant differences in age (P=0.591) and sex (P=0.066) between the high C3 group and the low C3 group. However, there was a significant difference in mortality between the two groups, with a higher mortality in the low C3 group (P=0.009). The decreases in WBC (P=0.034), ANC (P=0.022), and PLT (P<0.001) were more significant in patients with low C3. In terms of coagulation function, the D-dimer level was significantly increased (P=0.002), PT (P<0.001) and APTT (P=0.001) were more significantly prolonged, and FIB was more significantly decreased (P<0.001) in the low C3 group. In addition, AST (P=0.029), CA153 (P=0.022), EBV-DNA copies in PBMC (P=0.019), and decreased Alb levels (P=0.013) were more common in the low C3 group (Table 2).

[0079] Prognostic and survival significance of C3 in patients with HLH

[0080] Survival analysis was performed to evaluate the survival significance of C3 in HLH patients. Among the total patients, 57 patients (14.96%) were lost to follow-up. The overall median follow-up time was 46 days, the median follow-up time in the high C3 group was 97 days, and the median follow-up time in the low C3 group was 41 days. There was no significant difference in follow-up time between the two groups (P=0.245) (Table 2). The median survival time was not reached in the high C3 group, while the median survival time in the low C3 group was 63 days. There was a significant difference in the overall mortality rate between the high C3 group and the low C3 group (35% vs 57%, P<0.001) (Table 2). Survival analysis showed that malignancy-related HLH had the highest risk of death, rheumatic disease-related HLH had the lowest risk of death, and HLH caused by other related triggering factors had a death risk between the two (P=0.00067) ( Figure 3 Survival analysis showed that the low C3 group had a higher risk of death in overall survival (OS) (P = 0.00099) ( Figure 3 (B). Considering that most HLH patients died during the induction period, the survival rates at 4 weeks, 8 weeks, 1 year, 2 years, and 3 years were analyzed. The results showed that most patients in the low C3 group died within 1 year, and most deaths occurred within 8 weeks. Similarly, for the high C3 group, most deaths also occurred within 8 weeks, and there were no additional deaths after 1 year ( Figure 3 C, Table S3).

[0081] Table S3. Incidence of death events at different time points

[0082]

[0083] Multivariate Cox regression analysis included variables with P < 0.05 as well as C3. Since most patients died within 8 weeks and long-term mortality in HLH was mainly related to secondary factors, the risk factors for early death within 8 weeks in HLH patients were analyzed. The results showed that low C3 was an independent risk factor for early death in HLH patients within 8 weeks (HR = 1.64, P = 0.019). Lower C3 values ​​were associated with an increased risk of death. According to the results, in addition to C3, PCT was identified as a risk factor associated with an increased risk of death, and rheumatic immune disease was considered a protective factor ( Figure 3 D in the middle, Table S4). Therefore, low C3 and PCT were included in the prediction model for regression analysis to calculate the partial regression coefficient of each variable, and the prediction model formula for predicting early death of patients was obtained: Riskscore = 0.53*C3 + 0.44*PCT; where C3 is the serum protein C3 level, low C3 represents C3 < 0.764 g / L, low C3 is 1, and non-low C3 is 0; PCT represents the procalcitonin level, high PCT represents PCT > 2 ug / L, high PCT is 1, and non-high PCT (PCT ≤ 2 ug / L) is 0.

[0084] Table S4. COX regression analysis of risk factors affecting death within 8 weeks

[0085]

[0086] Dynamic changes of C3 in HLH patients

[0087] In order to further verify the above results, the dynamic changes of C3 in HLH patients were collected. A total of 66 patients had their C3 values ​​tested before and during the onset of HLH. The median time of C3 detection before HLH was 69.5 days before diagnosis, and the median time of C3 detection in the active state of HLH was 6.7 days after diagnosis. The median C3 level of these patients before the onset of HLH was 0.87g / L, and the median C3 level dropped to 0.62g / L in the onset of HLH. The results showed that most patients had normal C3 values ​​before the onset of HLH, and the C3 values ​​decreased after the onset of HLH (P<0.0001).

[0088] In addition, 47 HLH patients had C3 levels measured both at the onset of HLH and after treatment. Among these patients, 11 patients died within 8 weeks, and 36 patients survived within 8 weeks. For patients who survived within 8 weeks, the median time of C3 detection at the onset of HLH was 2 days after diagnosis, and the median time of C3 detection after HLH treatment was 26.3 days after diagnosis. After HLH treatment, the median C3 level increased from 0.56 g / L at the onset of HLH to 0.77 g / L after treatment (P=0.0003). For patients who died within 8 weeks, the median time of C3 detection at the onset of HLH was also 2 days after diagnosis, and the median time of C3 detection after HLH treatment was 17 days after diagnosis. The median C3 level at the onset was 0.62 g / L, and it decreased to 0.58 g / L after treatment, but there was no statistical significance (P=0.90). These results suggest that C3 decreases when HLH occurs, and changes in C3 values ​​can reflect the progression and prognosis of the disease ( Figure 3 Middle E).

[0089] 3. Research Conclusion

[0090] In this study, clinical data of adult HLH and partial HLH patients in the target population over an 11-year period were reviewed. The purpose was to identify clinical characteristics of adult HLH patients and biomarkers that promote the progression of partial HLH patients to HLH. It is worth noting that complement C3, as a key component of the complement system, was found to be an important biomarker for distinguishing HLH from partial HLH. In addition, C3 levels (serum protein levels) were found to be associated with disease severity and early death in adult HLH patients. Therefore, it is believed that these data can provide clinicians with a better basis for disease prediction and efficacy evaluation. In summary, the study identified C3 as a valuable predictive and prognostic biomarker in adult HLH for the first time, and clarified that low C3 levels were associated with increased disease severity and poor prognosis, indicating that monitoring the dynamic changes of C3 may help clinicians better understand disease progression and prognosis.

[0091] It will be clear to those skilled in the art that various modifications to the above embodiments may be made without departing from the overall spirit and concept of the present invention. All of them fall within the protection scope of the present invention. The protection scheme of the present invention shall be subject to the claims attached to the present invention.

Claims

1. Use of preparations for detecting complement C3 levels in the preparation of products for analyzing the risk of HLH or analyzing the risk of some HLH progressing to HLH.

2. Use of a preparation for detecting complement C3 levels in the preparation of a product for analyzing the severity of HLH or the prognostic effect of HLH treatment; wherein: The complement C3 level is negatively correlated with the severity of HLH, and the complement C3 level is positively correlated with the prognosis of HLH treatment.

3. A prediction model for progression from partial HLH to HLH, characterized by: The formulas include: Riskscore = 1.25*C3+0.95*malignant tumor+0.17*PT-3.30; among them, C3 is the level of serum protein C3. Low C3 means C3 < 0.764 g / L. Low C3 is 1, and non-low C3 is 0. PT is prothrombin time. Malignant tumor index: 1 if the patient is ill, 0 otherwise. Riskscore is the risk score for progression from partial HLH to HLH.

4. The prediction model for progression from partial HLH to HLH according to claim 3, characterized in that: When the riskscore is compared with the threshold: Riskscore>threshold, it progresses from partial HLH to high risk HLH. Riskscore = threshold, then to be estimated, If Riskscore < threshold, the disease progresses from partial HLH to low HLH risk.

5. Use of the prediction model for progression from partial HLH to HLH according to claim 3 or 4 in the preparation of a product for analyzing the risk of progression from partial HLH to HLH.

6. A system for predicting the risk of progression from partial HLH to HLH, characterized in that: include Sample detection module: used to detect and analyze samples from the subjects to be tested, and to obtain information on whether the subjects are suffering from malignant tumors and the levels of serum protein C3 and prothrombin time of the samples; Risk assessment module: The above data are input into the prediction model formula from partial HLH to HLH and the Riskscore is calculated, Riskscore = 1.25*C3+0.95*malignant tumor+0.17*PT-3.30; where, C3 is the serum protein C3 level. Low C3 means C3 < 0.764 g / L. Low C3 is 1, and non-low C3 is 0. PT is prothrombin time. Malignant tumor index: 1 if the patient is ill, 0 otherwise. Riskscore is the risk score for HLH with bleeding; Result comparison module: compare the obtained Riskscore with the threshold to obtain the risk rating from partial HLH to HLH. Riskscore>threshold, it progresses from partial HLH to high risk HLH. Riskscore = threshold, then to be estimated, If Riskscore < threshold, the disease progresses from partial HLH to low HLH risk.

7. A prediction model for early death in HLH patients, characterized by: The formulas include: Riskscore = 0.53*C3+0.44*PCT; where C3 is the serum protein C3 level. Low C3 means C3 < 0.764 g / L. Low C3 is 1, and non-low C3 is 0. PCT represents the level of procalcitonin. High PCT means PCT>2ug / L. High PCT is 1, and non-high PCT is 0. Riskscore is the risk score for early death in HLH patients.

8. The prediction model for early death of HLH patients according to claim 7, characterized in that: When the riskscore is compared with the threshold: Riskscore>threshold, then HLH patients have a high risk of early death, Riskscore = threshold, then to be estimated, If Riskscore < threshold, HLH patients have a low risk of early death.

9. Use of the prediction model for early death of HLH patients according to claim 7 or 8 in the preparation of a product for analyzing the risk of early death of HLH patients.

10. A risk prediction system for early death in HLH patients, characterized by: include Sample detection module: used to detect and analyze samples from the subjects to be tested, and obtain the PCT level of the subjects to be tested and the serum protein C3 level of the samples; Risk assessment module: The above data are input into the risk prediction model formula for early death of HLH patients and the Riskscore is calculated, Riskscore = 0.53*C3+0.44*PCT index; where, C3 is the serum protein C3 level. Low C3 means C3 < 0.764 g / L. Low C3 is 1, and non-low C3 is 0. PCT represents the level of procalcitonin. High PCT means PCT>2ug / L. High PCT is 1, and non-high PCT is 0. Riskscore is the risk score for early death in HLH patients; Result comparison module: Compare the obtained Riskscore with the threshold to obtain the early death risk rating of HLH patients. Riskscore>threshold, then HLH patients have a high risk of early death, Riskscore = threshold, then to be estimated, If Riskscore < threshold, HLH patients have a low risk of early death.

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