Application of TM9SF1 in the preparation of reagents for monitoring the course of sepsis

Abstract

This invention relates to the field of biomedical technology and proposes the use of TM9SF1 in the preparation of a reagent for monitoring the course of sepsis. Specifically, it proposes the use of a marker in the preparation of a reagent for monitoring the course of sepsis, wherein the marker comprises the TM9SF1 gene or the mRNA corresponding to the TM9SF1 gene. In the technical solution of this invention, a nomogram model for predicting the severity of sepsis can be constructed by using the TM9SF1 gene as a marker. Receiver-operating characteristic (ROC) curve validation demonstrated an AUC of 0.883, a sensitivity of 91.5%, and a specificity of 78.4%. For predicting mortality in patients with septic shock, the nomogram model achieved a C-index of 0.931.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technology, and in particular to an application of TM9SF1 in preparing a reagent for monitoring the course of sepsis. Background Art

[0002] The incidence of sepsis is increasing year by year worldwide, and the mortality rate is high. About one-third of patients cannot survive for more than 30 days.

[0003] Significant progress has been made in the treatment of sepsis, but the efficacy of currently reported molecular markers in predicting the severity and prognosis of sepsis is still limited. There are problems such as complex detection methods, low sensitivity / specificity, and inability to effectively predict disease severity and prognosis at the same time. Summary of the Invention

[0004] The main purpose of the present invention is to propose an application of TM9SF1 in the preparation of a reagent for monitoring the course of sepsis, aiming to solve the problems of disease prediction and prognosis of sepsis.

[0005] To achieve the above objectives, the present invention proposes the use of a marker in preparing a reagent for monitoring the course of sepsis, wherein the marker includes the TM9SF1 gene.

[0006] The present invention also proposes the use of a marker in preparing a reagent for monitoring the course of sepsis, wherein the marker includes an mRNA molecule corresponding to the TM9SF1 gene.

[0007] In the technical solution of the present invention, a nomogram model for predicting sepsis severity was constructed by using the TM9SF1 gene as a marker. Receiver-operating characteristic (ROC) curve validation demonstrated an area under the curve (AUC) of 0.883, a sensitivity of 91.5%, and a specificity of 78.4%. For predicting mortality in patients with septic shock, the nomogram model achieved a C-index of 0.931. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0009] Figure 1 Statistical graph of TM9SF1 mRNA expression levels in peripheral blood mononuclear cells of different patients in Example 1 of the present invention;

[0010] Figure 2This is a graph showing the results of Spearman correlation analysis between TM9SF1 mRNA levels and cytokines in Example 2 of the present invention;

[0011] Figure 3 This is a prediction nomogram for predicting septic shock in patients in Example 5 of the present invention;

[0012] Figure 4 This is the prognostic nomogram for predicting mortality in patients with septic shock in Example 5 of the present invention;

[0013] Figure 5 This is a graph showing the mortality risk analysis results of septic shock patients at different nomogram scores in Example 5 of the present invention.

[0014] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0015] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them.

[0016] It should be noted that, in the embodiments, those without specifying specific conditions, are carried out according to conventional conditions or the conditions recommended by the manufacturer. Those for reagents or instruments used that do not specify the manufacturer are conventional products that can be purchased commercially. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes. Taking "A and / or B" as an example, it includes schemes A, B, or A and B that meet the same time. In addition, the technical solutions between the various embodiments can be combined with each other, but must be based on those of ordinary skill in the art. When the combination of the technical solutions is contradictory or cannot be realized, it should be considered that the combination of such technical solutions does not exist and is not within the scope of protection required by the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative work belong to the scope of protection of the present invention.

[0017] The incidence of sepsis is increasing year by year worldwide, and the mortality rate is high. About one-third of patients cannot survive for more than 30 days.

[0018] Significant progress has been made in the treatment of sepsis. However, the efficacy of currently reported molecular markers in predicting the severity and prognosis of sepsis is still limited. There are problems such as complex detection methods, low sensitivity / specificity, and inability to effectively predict disease severity and prognosis at the same time.

[0019] In view of this, the present invention proposes the use of a marker in preparing a reagent for monitoring the course of sepsis, wherein the marker includes the TM9SF1 gene.

[0020] In the technical solution of the present invention, a nomogram model for predicting sepsis severity was constructed by using the TM9SF1 gene as a marker. Receiver-operating characteristic (ROC) curve validation demonstrated an area under the curve (AUC) of 0.883, a sensitivity of 91.5%, and a specificity of 78.4%. For predicting mortality in patients with septic shock, the nomogram model achieved a C-index of 0.931.

[0021] The present invention also provides a use of a marker in preparing a reagent for monitoring the course of sepsis, wherein the marker includes an mRNA molecule corresponding to the TM9SF1 gene.

[0022] TM9SF1 mRNA expression levels are significantly upregulated in patients with sepsis and are closely associated with shock and mortality. Furthermore, TM9SF1 significantly outperforms common clinical markers in predicting sepsis severity and mortality. Given the simplicity of TM9SF1 mRNA expression and its ability to simultaneously predict both sepsis severity and prognosis, TM9SF1 could effectively address the current challenges of complex testing methods and low predictive efficacy in the clinical diagnosis and treatment of sepsis.

[0023] The technical solutions of the present invention are further described in detail below in conjunction with specific embodiments. It should be understood that the following embodiments are only used to explain the present invention and are not used to limit the present invention.

[0024] Example 1 Expression Level of TM9SF1 mRNA in Sepsis Patients

[0025] Blood samples were collected from 45 patients with sepsis at admission and during follow-up. Peripheral blood mononuclear cells (PBMCs) were extracted from the blood samples and the expression level of TM9SF1 mRNA in PBMCs was detected.

[0026] The expression levels of TM9SF1 mRNA in PBMCs of different populations are as follows Figure 1 Figure 3 shows the expression levels of TM9SF1 mRNA in patients with sepsis and non-sepsis, Figure A shows the expression levels of TM9SF1 mRNA in patients with sepsis and non-sepsis, Figure B shows the expression levels of TM9SF1 mRNA in patients with sepsis and septic shock, Figure C shows the paired samples of patients with sepsis and septic shock, Figure D shows the expression levels of TM9SF1 mRNA in the survival group and the death group in patients with sepsis, and Figure E shows the expression levels of TM9SF1 mRNA in the survival group and the death group in patients with septic shock.

[0027] The results showed that the TM9SF1 mRNA level in sepsis patients was significantly higher than that in normal controls (0.25±0.02 vs. 0.10±0.02, P<0.001; Figure 1 A). The difference in TM9SF1 expression between the septic shock group and the sepsis group was also detected ( Figure 1 B) The expression of TM9SF1 mRNA level in septic shock patients was significantly higher than that in sepsis patients (0.29±0.02 vs. 0.16±0.01, P<0.001). Paired t-test was used to compare the expression of TM9SF1 in shock group and non-shock patients. Figure 1 C) As the condition of sepsis patients improved from severe to non-severe, the TM9SF1 mRNA level decreased significantly (0.25±0.04 vs. 0.13±0.02, P<0.001).

[0028] Furthermore, to evaluate the difference in TM9SF1 expression between patients who progressed and those who died, we performed an independent sample t-test ( Figure 1 D and Figure 1 E). The results showed that the TM9SF1 mRNA levels in patients with sepsis (0.30±0.03 vs. 0.19±0.02, P<0.001) and patients with septic shock (0.37±0.04 vs. 0.23±0.02, P = 0.005) were significantly higher in patients who died than in those who survived.

[0029] Example 2 Correlation between TM9SF1 expression and cytokines and clinical parameters in patients with sepsis

[0030] Excessive cytokine production is a key characteristic of sepsis and a key factor in causing related tissue damage. To investigate the correlation between TM9SF1 mRNA levels and cytokines in patients with sepsis, this example employed Spearman correlation analysis. TM9SF1 and cytokine expression levels were measured using RT-PCR. The primer sequences are shown in Table 1, with GAPDH used as an internal control.

[0031] Table 1 Primer sequences for RT-PCR experiments

[0032]

[0033] The results of Spearman correlation analysis are as follows Figure 2The results showed that in all patients with sepsis, TM9SF1 mRNA expression levels were significantly positively correlated with multiple key cytokines, including IFN-γ (r = 0.788, P < 0.001), TNF-α (r = 0.610, P < 0.001), IL-6 (r = 0.646, P < 0.001), IL-17A (r = 0.818, P < 0.001), and Forkhead Box P3 (FOXP3) (r = 0.607, P < 0.001).

[0034] Further subgroup analysis of patients with septic shock showed that the strong correlations were still significant in this subgroup, particularly for IFN-γ (r = 0.834, P < 0.001), IL-6 (r = 0.784, P < 0.001), and TNF-α (r = 0.709, P < 0.001). These results indicate a close correlation between TM9SF1 expression and plasma cytokine levels, suggesting that it may play a regulatory role in the harsh microenvironment of sepsis.

[0035] Example 3: Upregulation of TM9SF1 expression increases the severity of sepsis and the risk of death in patients

[0036] The correlation between TM9SF1 expression levels and sepsis severity was evaluated by univariate and multivariate logistic regression analyses (Figure 2 and Table 3).

[0037] Table 2 TM9SF1 Correlation analysis between expression level and severity of sepsis

[0038]

[0039] *** P <0.001;

[0040] a Univariate analysis;

[0041] b Adjustment variables: age, sex, smoking history, drinking history and disease history.

[0042] Table 3 Correlation analysis between TM9SF1 expression level and prognosis of patients with septic shock

[0043]

[0044] *** P <0.001;

[0045] a Univariate analysis;

[0046] b Adjustment variables: age, sex, smoking history, drinking history and disease history.

[0047] The results showed that after adjusting for age, sex, smoking status, alcohol consumption, and medical history, high TM9SF1 levels were significantly associated with increased sepsis severity (OR = 47.14, 95% CI = 8.06-275.65, P < 0.001). After patients were divided into high-risk and low-risk groups based on the median TM9SF1 level (0.14), the high-risk group was 2.94 times more likely to develop severe sepsis than the low-risk group (OR = 3.29, 95% CI = 1.88-5.78, P < 0.001).

[0048] To further explore the relationship between TM9SF1 expression and the risk of mortality, this example used Cox regression analysis and Kaplan-Meier survival curves. After adjusting for age, sex, smoking status, alcohol consumption, and medical history, the risk of mortality increased with increasing TM9SF1 levels (HR = 37.21, 95% CI = 12.80-108.21, P < 0.001). Furthermore, patients with higher TM9SF1 expression had significantly shorter survival times than those with lower expression levels (HR = 11.12, 95% CI = 4.35-28.45, P < 0.001).

[0049] Example 4 TM9SF1 has better predictive ability in sepsis severity and mortality risk than traditional clinical indicators

[0050] ROC curve analysis was used to evaluate the predictive ability of TM9SF1 and various clinical indicators for the severity of sepsis and the risk of death. The results are shown in Table 4.

[0051] Table 4 Predictive ability of each indicator for the severity of sepsis

[0052]

[0053] This example simultaneously analyzed the effectiveness of TM9SF1 in predicting sepsis severity alongside clinical indicators such as WBC, LYM%, MON%, NEU%, NLR, PLR, MLR, CRP, ESR, D-dimer, SaO2, OI, and lactate. The results showed that among all indicators, TM9SF1 had the largest area under the receiver operating characteristic (ROC) curve (AUC = 0.822, 95% CI = 0.766 - 0.878). The AUCs for predicting ESR and OI severity were 0.768 (95% CI = 0.705-0.832) and 0.615 (95% CI = 0.541-0.688), respectively. This suggests that TM9SF1 is the optimal biomarker for distinguishing patients with sepsis from those with septic shock, with a sensitivity of 89.4% and a specificity of 72.9%.

[0054] The correlation between TM9SF1 expression levels and important clinical indicators (WBC, PLT, CRP, ESR, NEU%, LYM%, MON%, NLR, MLR, PLR, D-dimer, and Lactate) in patients with sepsis was analyzed. The analysis results are shown in Table 5.

[0055] Table 5 Correlation analysis between TM9SF1 expression levels and important clinical indicators in patients with sepsis

[0056]

[0057] Time-dependent ROC analysis was used to evaluate the predictive ability of TM9SF1 on the risk of death in patients and compared with other independent variables. The results are shown in Table 6.

[0058] Table 6 Predictive ability of each indicator for sepsis mortality risk based on time-dependent ROC analysis

[0059]

[0060] The results in Table 6 show that TM9SF1 has high predictive accuracy, with a Harrell's C index of 0.853 (95% CI = 0.782-0.924), a sensitivity of 91.8%, and a specificity of 78.3%. In comparison, the Harrell's C index for mortality prediction for ESR was 0.680 (95% CI = 0.584-0.775), NLR was 0.668 (95% CI = 0.567-0.769), and lactate was 0.749 (95% CI = 0.654-0.874). These results suggest that TM9SF1 has a high predictive ability in assessing sepsis severity and mortality risk. Therefore, TM9SF1 may be a promising new biomarker for predicting sepsis prognosis.

[0061] Example 5 Construction of a prediction model for sepsis severity and mortality risk based on TM9SF1

[0062] To construct a prediction model for sepsis severity, this example first performed a multivariate logistic regression analysis on variables with a P < 0.05 in the univariate logistic regression analysis. After adjusting for other covariates, only variables with a P < 0.05 were included in the final model.

[0063] The results showed that TM9SF1, D-dimer, ESR, and CRP were independent risk factors for predicting the severity of sepsis, with OR values ​​of 47.81 (95% CI = 28.33-74.41, P < 0.001), 1.20 (95% CI = 1.10-1.30, P < 0.001), 1.04 (95% CI = 1.02-1.05, P < 0.001), and 1.13 (95% CI = 1.02-1.47, P = 0.040), respectively.

[0064] Multivariate Cox proportional hazards regression analysis was used to further evaluate the mortality risk in patients with sepsis. The results showed that the mortality risk in patients with septic shock was significantly associated with higher TM9SF1 levels (HR = 28.69, 95% CI = 17.19-47.48, P < 0.001), CRP (HR = 1.14, 95% CI = 1.03-3.07, P = 0.027), ESR (HR = 1.05, 95% CI = 1.01-1.37, P = 0.046), lactate (HR = 8.69, 95% CI = 5.01-11.13, P < 0.001), and oxygenation index (HR = 0.08, 95% CI = 0.04-0.26, P = 0.047).

[0065] Based on the above multivariate logistic regression analysis results, this embodiment constructs a new nomogram prediction model, such as Figure 3 As shown in Figure 2, it is used to quantitatively predict the probability of a patient developing septic shock. This nomogram model combines the levels of TM9SF1, D-dimer, ESR, and CRP, and calculates the probability of each patient developing septic shock by adding up the scores of these four variables. Similarly, based on the significant independent predictors of COX regression analysis, including TM9SF1, ESR, CRP, lactate, and OI, a prognostic nomogram for predicting mortality in patients with septic shock was constructed, as shown in Figure 2. Figure 4 By summing the predictors in the nomogram, the probability of death in patients with septic shock can be calculated.

[0066] The nomogram model for predicting sepsis severity was validated by receiver operating characteristic (ROC) curves, with an area under the curve (AUC) of 0.883 (95% CI = 0.839-0.927), a sensitivity of 91.5%, and a specificity of 78.4% (Table 4). For predicting mortality in patients with septic shock, the C-index of the nomogram model was 0.931 (95% CI = 0.884-0.978, Table 6).

[0067] In addition, this embodiment divides patients into high-risk group and low-risk group according to the total score of the nomogram prediction model. The optimal total score cutoff value for risk classification is 44.30. The Kaplan-Meier survival curve is used to analyze the mortality risk of patients with septic shock under different nomogram scores. The analysis results are as follows: Figure 5 As shown in the figure, low-risk refers to patients with septic shock whose TM9SF1 expression level is less than 0.22, while high-risk refers to patients with septic shock whose TM9SF1 expression level is not less than 0.22. The results showed that patients in the high-risk group were 8.39 times more likely to develop severe sepsis than those in the low-risk group (HR = 8.39, 95% CI = 3.74-18.80, P < 0.001).

[0068] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention specification under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. Use of a reagent for detecting the expression level of a marker in the preparation of a reagent for monitoring the course of sepsis, characterized in that: The marker is the TM9SF1 gene.

2. The use according to claim 1, characterized in that The marker is the TM9SF1 gene or the mRNA molecule corresponding to the TM9SF1 gene.

Images