Biomarker for prognostic prediction for sepsis and use thereof

Abstract

The present invention relates to a biomarker for prognostic prediction for sepsis, and use thereof. By evaluating the proteomic profile of sepsis patients by using SWATH-MS-based proteomics, PF4, CXCL7, ACTB, FINC, and TIMP1 were respectively identified as novel biomarkers for distinguishing the severity of sepsis and predicting outcomes of sepsis patients in the ICU, and, due to having excellent prognostic predictive performance for sepsis, are expected to be useful for prognostic predictive use and diagnostic use for sepsis, and the like.

Description

Biomarkers for Predicting Sepsis Prognosis and Their Uses

[0001] The present invention relates to a biomarker for predicting the prognosis of sepsis and its use.

[0002] The present invention claims priority based on Korean Patent Application No. 10-2025-0007521 filed on January 17, 2025, and all contents disclosed in the specification and drawings of said applications are incorporated by reference into the present application.

[0003] Sepsis is defined as life-threatening organ dysfunction caused by an uncontrolled host response to infection. Approximately one-third of critically ill patients admitted to the Intensive Care Unit (ICU) are diagnosed with sepsis. Although mortality rates have decreased due to improvements in critical care management, many patients with severe sepsis still have poor clinical outcomes in the ICU.

[0004] Early prediction of mortality risk in sepsis patients is crucial for optimizing patient management and improving outcomes. Several clinical scoring systems, such as the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Assessment (APACHE), and Simplified Acute Physiology Score (SAPS), have been developed to assess patient severity and predict ICU mortality. For example, the SOFA score during the first few days of ICU admission, calculated based on the severity of organ dysfunction, is a powerful indicator of prognosis.

[0005] However, the complexity of these scoring systems, which rely on numerous clinical and laboratory variables, limits real-time application and can lead to variability due to subjective components. On the other hand, since biomarkers are objective and measurable indicators, many studies have investigated potential biomarkers for sepsis patients. Nevertheless, biomarkers for predicting outcomes in sepsis patients remain limited.

[0006] Proteomics is a useful tool for identifying changes in protein expression and disease states, providing insights into potential biomarkers that can be used to diagnose and evaluate patients with sepsis. Sepsis is a complex and heterogeneous disease characterized by varying degrees of hyperinflammation and immunosuppression. Proteomics can provide insights into this pathophysiological heterogeneity of sepsis and enable personalized or precision medicine for individual patients. Sequential Window Mass Spectrum Acquisition (SWATH-MS) is a promising mass spectrometry technique for biomarker discovery and is highly effective for the analysis of proteins in human body fluids.

[0007] The object of the present invention is to provide a method for providing information for predicting the prognosis of sepsis, comprising the following steps:

[0008] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject; and

[0009] A step of predicting that the prognosis for sepsis of the subject will be poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group.

[0010] Another object of the present invention is to provide a method for providing information for diagnosing sepsis, comprising the following steps:

[0011] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject; and

[0012] A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group.

[0013] Another object of the present invention is to provide a method for screening a substance for the prevention or treatment of sepsis, comprising the following steps:

[0014] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a sepsis model administered a candidate substance; and

[0015] A step of selecting the candidate substance as a substance for preventing or treating sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins decreases compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 increases compared to the control group.

[0016] Another object of the present invention is to provide a composition for predicting the prognosis of sepsis, comprising as an active ingredient a preparation for measuring protein levels selected from the group consisting of the following:

[0017] Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7).

[0018] Another objective of the present invention is to provide a kit for predicting the prognosis of sepsis, comprising the above composition and instructions.

[0019]

[0020] However, the technical problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by those skilled in the art to which the present invention belongs from the description below.

[0021] The present invention provides a method for providing information for predicting the prognosis of sepsis, comprising the following steps:

[0022] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject; and

[0023] A step of predicting that the prognosis for sepsis of the subject will be poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group.

[0024] In one embodiment of the present invention, the information providing method is,

[0025] A step of additionally measuring the level of one or more proteins selected from the group consisting of TIMP1 (Metallopeptidase Inhibitor 1) and FINC (Fibronectin) in a biological sample isolated from a subject; and

[0026] A step in which the prognosis of the subject for sepsis is predicted to be poor if the protein level of TIMP1 among the above proteins is increased compared to the control group, or the protein level of FINC is decreased compared to the control group.

[0027] It may include more, but is not limited to.

[0028] In one embodiment of the present invention, the prognosis prediction may predict one or more selected from the group consisting of early death, late death, in-hospital death, and recovery, but is not limited thereto.

[0029] In one embodiment of the present invention, the information providing method is,

[0030] A step of measuring protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample separated from the subject; and

[0031] A step in which the prognosis of the subject for sepsis is predicted to be poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, and the protein levels of FINC and CXCL7 are decreased compared to the control group.

[0032] It may include more, but is not limited to.

[0033] In one embodiment of the present invention, the information providing method is,

[0034] Protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), PF4 (Platelet factor 4), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from the subject; and a step of measuring the SOFA score (Sequential [Sepsis-Related] Organ Failure Assessment Score) of the subject; and

[0035] The method may additionally include, but is not limited to, a step of predicting that the prognosis of the subject for sepsis is poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, the protein levels of FINC, PF4, and CXCL7 are decreased compared to the control group, and the SOFA score is increased compared to the control group.

[0036] In one embodiment of the present invention, the poor prognosis for sepsis may be in-hospital death, but is not limited thereto.

[0037] The present invention provides a method for providing information for diagnosing sepsis, comprising the following steps:

[0038] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject; and

[0039] A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group.

[0040] In one embodiment of the present invention, the biological sample may be any one selected from the group consisting of blood, serum, whole blood, plasma, urine, saliva, tissue, cell, organ, bone marrow, fine needle aspiration specimen, core needle biopsy specimen, and vacuum aspiration biopsy specimen, but is not limited thereto.

[0041] The present invention provides a method for screening a substance for the prevention or treatment of sepsis, comprising the following steps:

[0042] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a sepsis model administered a candidate substance; and

[0043] A step of selecting the candidate substance as a substance for preventing or treating sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins decreases compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 increases compared to the control group.

[0044] The present invention provides a composition for predicting the prognosis of sepsis, comprising as an active ingredient a preparation for measuring protein levels selected from the group consisting of the following:

[0045] Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7).

[0046] In one embodiment of the present invention, the protein may additionally include one or more selected from the group consisting of FINC (Fibronectin) and TIMP1 (Metallopeptidase Inhibitor 1), but is not limited thereto.

[0047] The present invention provides a kit for predicting the prognosis of sepsis, comprising the above composition and instructions.

[0048] In one embodiment of the present invention, the description may provide a method for providing information for predicting the prognosis, but is not limited thereto.

[0049] The present invention provides a kit for diagnosing sepsis, comprising the above composition and instructions.

[0050] In one embodiment of the present invention, the description may provide a method for providing information for diagnosing sepsis, but is not limited thereto.

[0051]

[0052] In addition, a method for treating sepsis comprising the following steps is provided:

[0053] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject;

[0054] A step of predicting that the prognosis for sepsis of the subject is poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group; and

[0055] A step of administering a substance for treating poor-prognosis sepsis to a subject predicted to have a poor prognosis.

[0056] In addition, a method for treating sepsis comprising the following steps is provided:

[0057] A step of measuring protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), and TIMP1 (Metallopeptidase Inhibitor 1) in biological samples isolated from a subject;

[0058] A step of predicting that the prognosis for sepsis of the subject is poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, and the protein levels of FINC and CXCL7 are decreased compared to the control group; and

[0059] A step of administering a substance for treating poor-prognosis sepsis to a subject predicted to have a poor prognosis.

[0060] In addition, a method for treating sepsis comprising the following steps is provided:

[0061] Protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), PF4 (Platelet factor 4), and TIMP1 (Metallopeptidase Inhibitor 1) in biological samples isolated from the subject; and a step of measuring the subject's SOFA score (Sequential [Sepsis-Related] Organ Failure Assessment Score);

[0062] A step of predicting that the prognosis of the subject for sepsis is poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, the protein levels of FINC, PF4, and CXCL7 are decreased compared to the control group, and the SOFA score is increased compared to the control group; and

[0063] A step of administering a substance for treating poor-prognosis sepsis to a subject predicted to have a poor prognosis.

[0064] In addition, the present invention provides a method for treating sepsis comprising the following steps:

[0065] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject;

[0066] A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group; and

[0067] A step of administering a sepsis treatment substance to a subject determined to have sepsis.

[0068] In addition, the present invention provides a composition comprising as an active ingredient a preparation for measuring protein levels selected from the group consisting of the following, for use in predicting the prognosis of sepsis, or for screening substances for the prevention or treatment of sepsis:

[0069] Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7).

[0070] In addition, the present invention provides a use for manufacturing a preparation for predicting the prognosis of sepsis, comprising as an active ingredient a preparation for measuring protein levels selected from the group formed above, and a use for manufacturing a preparation for screening substances for the prevention or treatment of sepsis.

[0071] According to the study on sepsis prognosis prediction biomarkers and their uses, PF4, CXCL7, ACTB, FINC, and TIMP1 were identified as new biomarkers for distinguishing sepsis severity and predicting outcomes in sepsis patients in the ICU by evaluating the proteomic profiles of sepsis patients using SWATH-MS-based proteomics. These biomarkers have excellent sepsis prognosis prediction effects and are expected to be useful for sepsis prognosis prediction and diagnosis.

[0072] Figure 1 shows a patient inflow diagram.

[0073] Figures 2a to 2e show the proteomic profiles of healthy control groups and septic patients according to result-based subgroups.

[0074] Figure 2a shows the partial least squares discriminant analysis (PLS-DA) results based on the protein abundance of all samples.

[0075] Figure 2b shows the protein loading results.

[0076] Figure 2c shows the Projected Variable Importance (VIP) scores for the top 10 proteins.

[0077] Figure 2d shows a hierarchical heatmap for the top 25 discriminant proteins.

[0078] Figure 2e shows a volcanic plot of the difference in protein abundance between sepsis and a healthy control group.

[0079] Figures 3a to 3e show the proteomic profiles of sepsis patients according to result-based subgroups.

[0080] Figure 3a shows the results of partial least squares discriminant analysis (PLS-DA) based on protein abundance of sepsis patient samples.

[0081] Figure 3b shows the protein loading results.

[0082] Figure 3c shows the VIP (Variable importance in Projection) scores for the top 10 proteins.

[0083] Figure 3d shows a hierarchical heatmap for the top 25 discriminant proteins.

[0084] Figure 3e shows the results of a volcanic plot on the difference in protein abundance between sepsis patients who experienced early death and recovery.

[0085] Figures 4a to 4f show the CRP concentration and top 5 protein levels that can distinguish sepsis subgroups.

[0086] Figures 5a to 5f show the ROC curves of six proteins, CRP, ACTB, FINC, TIMP1, PF4, and CXCL7, which distinguish between 1) sepsis or a healthy control group (green), 2) early death of a sepsis patient (red), 3) recovery of a sepsis patient (blue), and 4) early death versus recovery of a sepsis patient (purple).

[0087] Figure 6 shows the ROC curve for the diagnosis of sepsis.

[0088] (* indicates a significant difference (p < 0.05) compared to the CRP ROC curve according to DeLong's test, and † indicates a significant difference (p < 0.05) compared to the procalcitonin ROC curve.)

[0089] Figure 7 shows the ROC curve for predicting hospital mortality.

[0090] (* indicates a significant difference (p < 0.05) compared to the CRP ROC curve according to DeLong's test, and † indicates a significant difference (p < 0.05) compared to the procalcitonin ROC curve.)

[0091] Figure 8 shows the ROC curve for predicting hospital mortality using five candidate markers.

[0092] Figure 9 shows the ROC curve for the optimal 6-variable model in predicting in-hospital mortality with the highest AUC value (AUC = 0.903), where the sensitivity and specificity at the best threshold in this model were 82.0% and 86.5%, respectively.

[0093] Figure 10 shows the correlation curves according to the SOFA scores of six proteins.

[0094] Figure 11 shows the correlation curves of six proteins and lactate (lactate was measured in mg / dL units).

[0095] Figure 12 shows the results of a gene ontology (GO) richness analysis comparing (A) sepsis patients and healthy control groups, and (B) early death group and recovery group among sepsis subgroups.

[0096] Figure 13 shows a Forest plot of the multivariate Cox proportional hazards analysis for in-hospital mortality.

[0097] Figure 14 shows the Gelsoline levels of the healthy control group and the sepsis subgroup, and the correlation between Gelsoline and ACTB, SOFA scores and lactic acid.

[0098] Figure 15 shows the correlation between GC globulin (vitamin D binding protein) levels, gelsoline, ACTB, SOFA scores, and lactic acid in healthy control groups and sepsis subgroups.

[0099] Figure 16 shows the proteomic profile (n=133) of the sepsis subgroup excluding chronic liver disease and hematological malignancies.

[0100] In one embodiment of the present invention, distinct proteomic profiles were identified when sepsis patients were compared to healthy control groups and within sepsis subgroups based on patient outcomes. While CRP showed high diagnostic accuracy for sepsis, its prognostic ability within sepsis subgroups was limited, whereas ACTB, FINC, TIMP1, PF4, and CXCL7 demonstrated superior efficacy in predicting sepsis outcomes. The combination of ACTB, TIMP1, PF4, and CXCL7 exhibited the highest AUC for predicting in-hospital mortality, and when SOFA scores were incorporated, a 6-variable model incorporating ACTB, FINC, TIMP1, PF4, CXCL7, and SOFA scores achieved the highest AUC of 0.903 for predicting in-hospital mortality. Even after adjusting for clinical variables, increased ACTB levels and decreased FINC levels were significantly associated with in-hospital mortality. In this invention, the importance of proteins associated with tissue damage, such as cytoskeletal actin, was emphasized, and it was found that increased blood actin levels are associated with higher inpatient mortality rates because they reflect the degree of tissue damage.

[0101] The present invention provides a method for providing information for predicting the prognosis of sepsis, comprising the following steps:

[0102] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject; and

[0103] A step of predicting that the prognosis for sepsis of the subject will be poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group.

[0104] In one embodiment of the present invention, the information providing method is,

[0105] A step of additionally measuring the level of one or more proteins selected from the group consisting of TIMP1 (Metallopeptidase Inhibitor 1) and FINC (Fibronectin) in a biological sample isolated from a subject; and

[0106] A step in which the prognosis of the subject for sepsis is predicted to be poor if the protein level of TIMP1 among the above proteins is increased compared to the control group, or the protein level of FINC is decreased compared to the control group.

[0107] It may include more, but is not limited to.

[0108] In all claims below, “ACTB (beta-actin)” refers to cytoplasmic actin expressed in mammalian cells, which may exist in monomeric (G-actin) or filamentary (F-actin) forms, and whose dynamics are regulated by various actin-binding proteins. Actin is essential for various cellular functions, including maintaining cell shape, motility, and contractility, and mediating cell signaling pathways. It also plays a critical role in tissue regeneration and repair following injury and is known as a damage-associated molecular pattern protein that triggers inflammatory cascades.

[0109] As disclosed herein, including all claims below, the extracellular actin clearance system (EASS) is known to play an important role in mitigating these toxic effects. Gelsoline and Gc globulin (vitamin D-binding protein), two plasma proteins known as actin-binding proteins, are key components of the EASS and possess homeostatic mechanisms.

[0110] Including the full claims below, it was confirmed that actin levels were higher in septic patients compared to healthy control groups, and that levels increased further with the severity of sepsis, particularly in patients who died early. Furthermore, it was shown that the SOFA score, which reflects the degree of organ dysfunction, and lactate, which is used as a proxy indicator for the severity of tissue hypoxia and shock and is produced by anaerobic cell metabolism, were both significantly correlated with actin levels. These findings suggest that the degree of cell and tissue damage is correlated with the severity of sepsis-related organ dysfunction, such as the SOFA score, and that higher plasma actin levels may be associated with a higher risk of death.

[0111] In all claims below, “FINC” refers to fibronectin, and soluble plasma fibronectin plays an important role in wound healing, immunological clearance of damaged tissues, removal of antibody-coated microorganisms, and phagocytosis. In the present invention, actin and fibronectin were shown to have excellent diagnostic accuracy in distinguishing septic patients from healthy controls and septic patients who died early due to recovery. Furthermore, they exhibited a significantly higher AUC in predicting in-hospital mortality than CRP and serum procalcitonin, and increased plasma actin and decreased fibronectin levels were found to be significantly associated with increased in-hospital mortality in multivariate Cox proportional hazards analysis. These results suggested that actin and fibronectin levels can serve as valuable diagnostic and prognostic markers in sepsis.

[0112] Protein levels of “TIMP1,” “PF4,” and “CXCL7” in this specification, including the full claims below, were found to differ among sepsis subgroups according to PLS-DA analysis. Substrate metalloproteinases (MMPs) are involved in the degradation and remodeling of the extracellular matrix, and since inhibitors such as TIMP1 regulate MMP activity, the balance between MMPs and TIMP1 is important for tissue integrity. MMPs are upregulated upon exposure to bacterial lipopolysaccharides or inflammatory cytokines and regulate immune responses through leukocyte efflux and recruitment to the site of infection. In this invention, it was confirmed that TIMP1 levels were significantly higher in the early death group, suggesting a correlation with a worse prognosis. However, no MMP was found to significantly differentiate the sepsis subgroups based on the results.

[0113] In all claims below, as described herein, both PF4 and CXCL7 levels decreased as the prognosis of sepsis worsened. PF4, also known as chemokine ligand 4 (CXCL4), is essential for neutrophil adhesion and degranulation, monocyte activation, and the differentiation of monocytes into macrophages and foam cells. CXCL7, which is degraded into four different chemokines by proteolysis, is particularly known as NAP-2, an active form that facilitates neutrophil chemotaxis and adhesion to endothelial cells. In the present invention, PF4 levels were found to be lowest in septic patients who died early, and PF4 levels were reduced in all septic subgroups compared to a healthy cohort, which exhibited a more severe condition with 77% experiencing septic shock and an average SOFA score of 13.4. In addition, the average platelet count of the subjects of the present invention was 97.2 K / uL, which suggests that DIC with thrombocytopenia may contribute to the decrease in PF4 levels in sepsis patients of this cohort. Meanwhile, the present invention showed that CXCL7 levels were highest in healthy controls and decreased as the sepsis outcome worsened. Although CXCL7 and PF4 initially increase in response to bacterial invasion, their levels decrease significantly as DIC and sepsis-related thrombocytopenia progress, which may exacerbate immune and coagulation dysfunction, but is not limited thereto.

[0114] Including the full claims below, it was found that the protein expression levels of ACTB and TIMP1 in the blood of septic subjects, particularly in the early death group, were significantly increased, and the protein expression levels of PF4, CXCL7, or FINC were significantly decreased.

[0115] Including all claims below, the prediction of the prognosis may be one or more selected from the group consisting of early death, late death, in-hospital death, and recovery, but is not limited thereto.

[0116] Including all claims below, the early death is a diagnosis of sepsis and death within 3 days of admission to the intensive care unit, and

[0117] The aforementioned late death is death within 3 to 60 days after diagnosis of sepsis and admission to the intensive care unit, and

[0118] The above in-hospital death is defined in the experimental method of the present invention [early death group and late death group defined in the study design and patients], and may include both early death and late death, and may mean death within 60 days of diagnosis of sepsis and admission to the intensive care unit.

[0119] Including all claims below, the present specification may mean recovery from sepsis and survival, but is not limited thereto.

[0120] In the present invention, it was confirmed that a combination of ACTB, FINC, CXCL7, and TIMP1 exhibits an excellent AUC for predicting the prognosis of sepsis. Accordingly, in this specification, including the entire claims below, the information providing method comprises:

[0121] A step of measuring protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample separated from the subject; and

[0122] The step of predicting that the prognosis of the subject for sepsis is poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group and the protein levels of FINC and CXCL7 are decreased compared to the control group may be further included, but is not limited thereto.

[0123] In addition, as per the entire claim below, it was confirmed that when using a 6-variable model combining protein levels of ACTB, FINC, CXCL7, PF4, and TIMP1; and SOFA scores, it exhibits an excellent AUC for predicting the prognosis of sepsis. At this time, it was confirmed that the prognosis of sepsis is worse as the protein levels of ACTB and TIMP1 increase, as the protein levels of FINC, PF4, and CXCL7 decrease, and as the SOFA score increases. Therefore, as per the entire claim below, the information providing method comprises

[0124] Protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), PF4 (Platelet factor 4), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from the subject; and a step of measuring the SOFA score (Sequential [Sepsis-Related] Organ Failure Assessment Score) of the subject; and

[0125] The method may additionally include, but is not limited to, a step of predicting that the prognosis of the subject for sepsis is poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, the protein levels of FINC, PF4, and CXCL7 are decreased compared to the control group, and the SOFA score is increased compared to the control group.

[0126] In one embodiment of the present invention, the poor prognosis for sepsis may be in-hospital death, but is not limited thereto.

[0127]

[0128] The present invention provides a method for providing information for diagnosing sepsis, comprising the following steps:

[0129] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject; and

[0130] A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group.

[0131] Including all claims below, the biological sample may be any one selected from the group consisting of blood, serum, whole blood, plasma, urine, saliva, tissue, cell, organ, bone marrow, fine needle aspiration specimen, core needle biopsy specimen, and vacuum aspiration biopsy specimen, but is not limited thereto.

[0132] Including all claims below, the biological sample may be pretreated before use for detection or diagnosis. For example, this may include homogenization, filtration, distillation, extraction, concentration, inactivation of interfering components, addition of reagents, etc. The sample may be prepared to increase the detection sensitivity of a protein marker, for example, the sample obtained from a subject may be pretreated using methods such as anion exchange chromatography, affinity chromatography, size exclusion chromatography, liquid chromatography, sequential extraction, or gel electrophoresis.

[0133] Including all claims below, this specification has confirmed at the protein level that the protein expression of the biomarker of the present invention can be used as a marker for predicting the prognosis or diagnosing sepsis.

[0134] At this time, in all claims below, the method for measuring protein levels in this specification is not subject to any particular limitation as long as it is a protein measurement method known in the art, but can be measured by methods such as protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Assisted LaSer Desorption / Ionization Time of Flight Mass Spectrometry) analysis, SELDI-TOF (Sulface Enhanced LaSer Desorption / Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioimmunodiffusion, Ouchteroni immunodiffusion, Rocket immunoelectrophoresis, tissue immunostaining, complement fixation assay, two-dimensional electrophoresis analysis, liquid chromatography-mass spectrometry (LC-MS), LC-MS / MS (liquid chromatography-mass spectrometry / mass spectrometry), Western blotting, ELISA (enzyme linked immunosorbent assay), FACS, etc.

[0135] In the entirety of the following claims, “the level is increased” means that something that was not previously detected is detected, or that the amount detected is greater than the normal level. For example, “the level is increased” means that the level of the experimental group is at least 1%, 2%, 3%, 4%, 5%, 10% or higher, e.g., 5%, 10%, 20%, 30%, 40%, or 50%, 60%, 70%, 80%, 90% or higher, and / or 0.5 times, 1.1 times, 1.2 times, 1.4 times, 1.6 times, 1.8 times or higher. Specifically, it may mean an increase of 1 to 1.5 times, 1.5 to 2 times, 2 to 2.5 times, 2.5 to 3 times, 3 to 3.5 times, 3.5 to 4 times, 4 to 4.5 times, 4.5 to 5 times, 5 to 5.5 times, 5.5 to 6 times, 6 to 6.5 times, 6.5 to 7 times, 7 to 7.5 times, 7.5 to 8 times, 8 to 8.5 times, 8.5 to 9 times, 9 to 9.5 times, 9.5 to 10 times, or 10 times or more compared to that of the control group, but is not limited thereto. A person skilled in the art can understand the meaning of the opposite term as having the opposite meaning in accordance with the above definition.

[0136] The term “method for providing information” as used herein, including all claims below, refers to a method for providing information regarding the diagnosis or prognosis prediction of a disease, and means a method of obtaining information regarding the onset or likelihood (risk) of onset and prognosis of a disease by analyzing biological samples of an individual or by confirming the increase or decrease in the expression level of the biomarker of the present invention. For example, it may include a method for providing information regarding whether there is a possibility of the disease of the present invention developing in an individual, whether the likelihood of said disease developing is relatively high, or whether said disease has already developed, by measuring the level of the biomarker according to the present invention and comparing it with a control group. Furthermore, through a method using the biomarker of the present invention, it is possible to predict the risk of aggravation due to the onset of the disease of the present invention, that is, whether the prognosis will be poor, and this may also be used as a method for providing information regarding the prevention and treatment of the disease of the present invention.

[0137] In the entirety of the claims below, the term “biomarker” refers to a marker that can distinguish between normal and pathological states or predict a therapeutic response and is objectively measurable; and it has been confirmed that the levels of biomarkers in biological samples of individuals having the disease of the present invention differ from the respective increases and decreases in levels of normal individuals, thereby proving that the biomarkers of the present invention can be used as biomarkers for the diagnosis or prognosis prediction of the disease of the present invention.

[0138] In all claims below, the term “measurement” in this specification includes both detecting and confirming the presence (expression) of a target substance and detecting and confirming a change in the level of presence (expression level) of the target substance. The measurement may be performed without limitation, including both qualitative methods (analysis) and quantitative methods. The types of qualitative and quantitative methods for measuring the presence of a substance according to the present invention are well known in the art, and the experimental methods described in this specification are included therein.

[0139] As used herein, including in all claims below, the term “analysis” may preferably mean “measurement,” wherein the qualitative analysis may mean measuring and confirming the presence of a target substance, and the quantitative analysis may mean measuring and confirming a change in the presence level (expression level) or amount of the target substance. In the present invention, analysis or measurement may be performed without limitation by including both qualitative and quantitative methods, and preferably, quantitative measurement may be performed.

[0140] In the entirety of the following claims, the term “prognosis prediction” may mean predicting the degree of disease progression in a patient group of the disease of the present invention. It may mean predicting the probability of progression, deterioration, recurrence, maintenance, etc. of the disease of the present invention through the increase or decrease in the level of the biomarker of the present invention.

[0141]

[0142] The present invention provides a method for screening a substance for the prevention or treatment of sepsis, comprising the following steps:

[0143] A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a sepsis model administered a candidate substance; and

[0144] A step of selecting the candidate substance as a substance for preventing or treating sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins decreases compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 increases compared to the control group.

[0145] The present invention provides a composition for screening substances for the prevention or treatment of sepsis, comprising as an active ingredient a preparation for measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1).

[0146] Including the entire claims below, it has been confirmed that one or more selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) can be used for predicting the prognosis or diagnosing sepsis. Accordingly, since the prognosis of sepsis can be predicted to be poor or sepsis depending on the increase or decrease of each protein, each gene can be used as a marker to screen for substances for the prevention or treatment of sepsis when the prognosis is poor or sepsis is predicted in this manner. Therefore, in one embodiment of the present invention, the sepsis may be sepsis with a predicted poor prognosis, but is not limited thereto.

[0147] The present invention provides a screening kit for a substance for the prevention or treatment of sepsis, comprising the above composition and instructions.

[0148] Including all claims below, the description may teach the screening method, but is not limited thereto.

[0149] In this specification, including all claims below, the term “screening kit” refers to a tool capable of screening substances for the prevention or treatment of sepsis, comprising a preparation for measuring the protein expression level of a biomarker of the present invention. Any other details may be applied to the general provisions regarding the “kit” described in the present invention.

[0150] Including all claims below, the term “screening” in this specification may mean selecting a substance having a specific desired property from a candidate group of various substances by a specific operation or evaluation method.

[0151] That is, for the purposes of the present invention, the screening method of the present invention may refer to a series of processes including the step of determining the efficacy of a drug candidate substance by the said method in order to identify a therapeutic agent that produces the best therapeutic effect on a septic patient who is septic or predicted to have a poor prognosis, but is not limited thereto.

[0152] Including all claims below, the step of confirming the therapeutic response and effect may be repeated several times depending on the therapeutic candidate substance, and may additionally include steps used in the art as general screening methods, such as adding additional substances or steps to confirm the therapeutic response and effect, but is not limited thereto.

[0153] In the entire specification including the following claims, “candidate substance” means an unknown substance used in screening to measure the increase or decrease in expression of the marker of the present invention by administering it to a target disease model in the present invention, and may be one or more selected from the group consisting of nucleotides, DNA, RNA, amino acids, aptamers, proteins, stem cells, stem cell culture media, compounds, microbial culture media or extracts, natural products, and natural extracts, but is not limited thereto.

[0154] In this specification, including the entire claim below, the term "disease model" refers to any model manufactured to reflect the characteristics of the disease, and may be a disease model in a broad sense that includes both in vivo (animal models) and in vitro (cell models, organoid models).

[0155] In the entirety of the following claims, the term “treatment” refers to any act that improves or beneficially alters the target disease and the associated metabolic abnormalities, and may use methods such as chemotherapy, surgical procedures, or biological therapies.

[0156] In this case, as per the entire claim below, if the protein expression level of the substance is increased or decreased depending on the type relative to a group to be compared, for example, a normal control group, it may be determined that the disease targeted by the present invention has been treated (or improved). In this specification, "the level is increased" is as described above.

[0157] Including all claims below, the present specification may use a treatment method commonly used for treating a target disease in the present invention, administer a commonly used therapeutic drug, or administer a candidate substance disclosed in the present invention, but is not limited thereto.

[0158]

[0159] The present invention provides a composition for predicting the prognosis of sepsis, comprising as an active ingredient a preparation for measuring protein levels selected from the group consisting of the following:

[0160] Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7).

[0161] In one embodiment of the present invention, the protein may additionally include one or more selected from the group consisting of FINC (Fibronectin) and TIMP1 (Metallopeptidase Inhibitor 1), but is not limited thereto.

[0162] The present invention provides a kit for predicting the prognosis of sepsis, comprising the above composition and instructions.

[0163] Including all claims below, the description may teach the information provision method, but is not limited thereto.

[0164] In this specification, including all claims below, the term “kit” refers to a tool that additionally includes a formulation or a substance for the function, storage, etc., of which each kit claimed in the present invention can perform its intended use. In addition to the above substances, the kit of the present invention may include other components, compositions, solutions, devices, etc., which are typically required for the storage and processing methods thereof. As a specific example, each component may be applied one or more times without limitation on the number of times, there is no restriction on the order in which each substance is applied, and the application of each substance may proceed simultaneously or sequentially.

[0165] Including all claims below, the kit may include a container; instructions; etc. The container may serve to package the material and may also serve to store and secure it. The material of the container may take the form, for example, a bottle, a tub, a sachet, an envelope, a tube, an ampoule, etc., and may be formed partially or wholly from plastic, glass, paper, foil, wax, etc. The container may be equipped with a cap that is initially part of the container or can be attached to the container by mechanical, adhesive, or other means and may also be equipped with a stopper that allows access to the contents by a needle. The kit may include an outer package, and the outer package may include instructions regarding the use of the components.

[0166] Including all claims below, the preparation capable of measuring the protein level may be one or more selected from the group consisting of antibodies, peptides, aptamers, proteins, and compounds that specifically bind to the protein, but is not limited thereto.

[0167]

[0168] Furthermore, the present invention may provide a diagnostic device for predicting or diagnosing the prognosis of a disease according to the present invention. Specifically, the disease may be sepsis. The measuring unit of the diagnostic device for predicting or diagnosing the prognosis according to the present invention may measure the expression level of a protein using a preparation that measures the protein expression level of a biomarker according to the present invention with respect to a biological sample obtained from a subject. By confirming the degree of protein expression using the preparation in the measuring unit, it is possible to diagnose whether the disease is according to the present invention and whether the prognosis of the disease is poor.

[0169] Including all claims below, the diagnostic device of the present invention may further include a detection unit that predicts and outputs the prognosis or progression of the disease of the present invention of a subject from the degree of expression of the protein obtained from the measurement unit.

[0170] Including the entire claim below, the detection unit in this specification can diagnose the disease of the present invention or predict the prognosis of the disease by generating and classifying information regarding the disease of the present invention according to the category of the expression level of the protein obtained from the measurement unit.

[0171] In this case, the term “diagnosis” in the present specification, including the entire claim below, may have a broad meaning that includes determining the susceptibility of an object to a specific disease or condition, determining whether an object currently has a specific disease or condition, determining the prognosis of an object with a specific disease or condition (e.g., identification of tumor status, determination of tumor stage or determination of responsiveness of sepsis to treatment, particularly, in the present invention, prediction of prognosis for sepsis or progression), or therametrics (e.g., monitoring the condition of an object to provide information on therapeutic efficacy).

[0172] Preferred embodiments are presented below to aid in understanding the present invention. However, the following embodiments are provided merely to facilitate a better understanding of the invention, and the scope of the invention is not limited by the following embodiments.

[0173]

[0174] [Example]

[0175]

[0176] Study Design and Patients

[0177] This retrospective cohort study was conducted using data obtained from the sepsis registry at a single tertiary hospital in Korea. It included adult sepsis patients (age > 18 years) admitted to a medical intensive care unit between January 2011 and January 2020. The study protocol was reviewed and approved by the Center's Institutional Review Board (IRB No.: 2021-0308, Approval Date: 2021-02-26). Due to the retrospective nature of the experiment and the use of existing sepsis cohort samples, informed consent was waived. Patients could be included in this registry if they met the following criteria: 1) diagnosed with sepsis according to the definition of Sepsis-2 or Sepsis-3 and admitted to a medical intensive care unit, and 2) consented to register in the sepsis registry and provide blood samples. Patients who did not consent to register in this registry were excluded. In this study, only patients with confirmed bacterial infections were analyzed. The date of registration and blood sample collection was defined as time 0. As a control group, 292 healthy individuals without active disease were selected from the registry of the Health Screening Promotion Center at Asan Medical Center. The experiment in this example consisted of two separate analyses. First, the proteomic profiles of sepsis patients were compared with those of a healthy control group. Second, differences in proteomic profiles between sepsis subgroups were investigated based on clinical outcomes.

[0178] Subgroups of sepsis were predefined based on outcomes: early mortality group (patients who died within 3 days of diagnosis of sepsis and admission to the intensive care unit), late mortality group (patients who died between 3 and 60 days of diagnosis of sepsis and admission to the intensive care unit), and recovery group (surviving patients, patients who survived and were discharged).

[0179]

[0180] This definition applies the definition of resistant organ failure, primarily associated with primary infection, to early death occurring within the first three days of admission to the Intensive Care Unit (ICU). Patients discharged to hospice were recorded as having died on the day of discharge.

[0181]

[0182] Data Collection

[0183] Patient data collected from electronic medical records are as follows: age, sex, height, weight, body mass index (BMI), underlying complications, hospital and ICU admission and discharge dates, date of death, type of pathogen, site of infection, the highest Sequential Organ Failure Assessment (SOFA) score (hereinafter referred to as SOFA score) and lactate levels at the date of study enrollment, and whether mechanical ventilation, renal replacement therapy, extracorporeal membrane oxygenation, or adjuvant steroids were used during ICU admission.

[0184]

[0185] Proteomic Data Processing and Statistical Analysis

[0186] Samples from septic patients and healthy controls were analyzed using SWATH-MS. The proteomic dataset was log2 transformed, normalized, and filtered to ensure that valid values ​​were included in at least 70% of each group. Missing values ​​were filled with random numbers drawn from a normal distribution with a width of 0.3 and a downward shift of 1.8. Proteins differentially expressed between groups were analyzed using Partial Least Squares Discriminant Analysis (PLS-DA) and Variable Importance Projection (VIP) scores to measure variable importance in the PLS-DA model. Hierarchical clustering heatmaps were generated based on the Euclidean distance measure and Ward's method. Fold change thresholds of 2.0 and 0.5 and a False Discovery Rate (FDR) of 0.05 were used to generate volcano plots. Proteins exceeding these thresholds were further analyzed to interpret biological processes.

[0187] Clinical variables were expressed as means with standard deviations or medians with interquartile ranges (IQRs) according to their distribution. Reference patient characteristics and ICU treatment were compared among three sepsis subgroups. One-way analysis of variance (ANOVA) or the Kruskal-Wallis test was used for continuous variables, while the chi-square test or Fisher's exact test was used for categorical variables. For proteins with significantly different log2 abundances in the ANOVA test, Tukey's post-hoc analysis for honestly significant differences was performed. Receiver Operational Characteristics (ROC) curve analysis was conducted to evaluate the discriminative ability of the proteins. Pearson correlation analysis was used to compare the log2 abundance of proteins with SOFA scores, and the correlation coefficient (R) was calculated accordingly.

[0188] Risk factors for in-hospital mortality were analyzed using Cox proportional hazards analysis. Variables with a p-value <0.1 in the univariate analysis were included in the multivariate analysis through reverse elimination. All p-values ​​were two-sided, and the critical value for statistical significance was set at a p-value <0.05.

[0189] After a significant association was confirmed between actin levels and the prognosis of sepsis, actin-binding proteins, including gelsoline and Gc globulin, were investigated through a post-hoc analysis. In addition, sensitivity analysis was performed by excluding patients with the most common underlying conditions, chronic liver disease and hematological malignancies, to further validate the study results and evaluate the robustness of the findings by excluding patients who could affect the proteomic profile.

[0190] Perseus software v2.1.2.0 (https: / maxquant.net / perseus) was used for proteomic data processing, and MetaboAnalyst 6.0 (https: / www.metaboanalyst.ca) and R 4.2.1 (R Core Team, Vienna, Austria) were used for the analysis of proteomic and clinical variables. Metascape (https: / metascape.org) was used for enrichment analysis to help identify important biological pathways and gene functions.

[0191]

[0192] Example 1. Reference characteristics of sepsis patients and ICU treatment

[0193] In this study, 217 patients diagnosed with bacterial sepsis were included (Fig. 1). The median age of the patients was 64.0 years (IQR, 54-72), and 70% were male (Table 1). The most common site of infection was the lungs (53.5%), and the average SOFA score and lactate levels were 13.4±4.7 and 4.7±4.4, respectively. The rate of septic shock was 77.0%, and bacteremia was present in 60.4% of the patients. Of the 217 sepsis patients, 17.5% (38 patients) were in the early death group, 54.4% (118 patients) were in the late death group, and 28.1% (61 patients) were in the recovery group. The median age of the early death group was 55 years (IQR, 44–70), and the highest SOFA scores (17.0±3.7) and lactate levels (8.4±4.6 mmol / L) were recorded on the day of enrollment (p < 0.001 in both cases). In this group, chronic liver disease (39.5%, p = 0.003) and hematological malignancies (26.3%, p = 0.004) were the most common. Furthermore, mechanical ventilation (42.6%), renal replacement therapy (18.0%), and the use of adjuvant steroids (29.5%) were less frequent in the recovery group compared to other groups (p < 0.001 for each intervention). Serum procalcitonin levels did not differ significantly within the subgroups (p = 0.384). Among the 292 healthy controls, the median age was 50.5 years (IQR, 31–61), and 69.1% were male.

[0194]

[0195]

[0196]

[0197] Example 2. Proteomic profile analysis comparing a sepsis patient group and a healthy control group

[0198] Of the 509 samples from sepsis patients and healthy controls, 189 proteins were included in the dataset after data processing.

[0199]

[0200] When comparing the sepsis group and the healthy control group, a slope along Component 1 was observed from the healthy control group to the sepsis group, and the sepsis subgroup was distinguished along Component 2 as shown in PLS-DA (Fig. 2a).

[0201] Acute phase proteins such as CRP (C-reactive protein), SAA1 (serum amyloid A1), and SAA2 (serum amyloid A2) showed high positive loadings for both Component 1 and Component 2 (Fig. 2b). Analysis of VIP scores revealed that SAA1, CRP, and SAA2 exhibited the highest VIP scores (Fig. 2c). However, when heatmaps were derived for the mean protein abundance of the sepsis group and healthy controls, CRP, SAA1, and SAA2 did not show significant differences between the sepsis subgroups, and their mean values ​​were not correlated with sepsis outcomes (Fig. 2d). A volcano plot showed that CRP, SAA1, and SAA2 were expressed more highly in sepsis patients than in healthy controls (Fig. 2e).

[0202]

[0203] Example 3. Analysis of proteomic profiles within the sepsis subgroup

[0204] When comparing the sepsis subgroups according to the results, a slope was observed from the early death group to the late death group, and finally to the recovery group along components 1 and 2 (Fig. 3a). Although a clearer distinction was found between the early death group and the recovery group, the late death group exhibited characteristics that were a mixture of the early death and recovery groups.

[0205]

[0206] In the loading plot, ACTB showed negative loading for both components, whereas FINC (fibronectin), CXCL7 (CXC motif chemokine 7), and PF4 (platelet factor 4) showed high positive loading for both components (Fig. 3b).

[0207] The top five proteins with the highest VIP scores explaining the differences in sepsis groups were identified as ACTB, CXCL7, PF4, FINC, and TIMP1 (Metalloproteinase Inhibitor 1) (Fig. 3c). The heatmaps among sepsis subgroups showed that the five proteins (ACTB, CXCL7, PF4, FINC, TIMP1) exhibited distinct values ​​across the sepsis subgroups, and their mean values ​​were correlated with sepsis outcomes (Fig. 3d).

[0208]

[0209] The volcanic plot showed that ACTB and TIMP1 were expressed more highly in the early death group, while PF4, CXCL7, and FINC were expressed more highly in the recovery group (Fig. 3e).

[0210]

[0211] All ANOVA significant proteins and post-hoc analysis among sepsis subgroups are shown in Table 2. CRP was not a significantly different protein among sepsis subgroups, but five proteins (ACTB, CXCL7, PF4, FINC, TIMP1) were found to be different among sepsis subgroups.

[0212]

[0213]

[0214]

[0215] Meanwhile, Figures 4a to 4f show the protein abundance of CRP and five proteins in the healthy control group, early death, late death, and recovery groups. It was confirmed that while CRP was low in the control group, there was no significant difference between the early death, late death, and recovery groups.

[0216]

[0217] Example 4. ROC curve analysis of CRP and 5 types of proteins

[0218] The AUC (area under the curve) values ​​of each protein were analyzed to distinguish between healthy controls, sepsis patients, and sepsis subgroups (early death, late death, recovery).

[0219]

[0220] As a result, CRP showed excellent ability to distinguish between septic patients and healthy controls with an AUC of 0.987 (95% CI: 0.979-0.996, p < 0.001) (Fig. 5a). However, its performance in distinguishing between early death and recovery subgroups was very poor, with an AUC of 0.517–0.535.

[0221]

[0222] ACTB demonstrated excellent ability to distinguish between septic patients and healthy controls with an AUC of 0.831 (95% CI: 0.793-0.869, p < 0.001) (Fig. 5b). It also showed a good AUC value of 0.833 (95% CI: 0.742-0.925, p < 0.001) in distinguishing between the early death group and the recovery group.

[0223] FINC demonstrated excellent diagnostic performance between septic patients and healthy controls with an AUC of 0.957 (95% CI: 0.939-0.975, p < 0.001) (Fig. 5c). It also showed moderate ability to distinguish between early death and recovery with an AUC of 0.786 (95% CI: 0.685-0.886, p < 0.001).

[0224] TIMP1 showed moderate diagnostic ability with an AUC of 0.744 (95% CI: 0.701-0.787, p < 0.001) between septic patients and healthy controls (Fig. 5d).

[0225] PF4 and CXCL7 demonstrated excellent diagnostic ability between sepsis patients and healthy controls with AUCs of 0.867 (95% CI: 0.834-0.901, p < 0.001) and 0.889 (95% CI: 0.858-0.921, p < 0.001) (Figs. 5e and 5f). They also demonstrated excellent ability to distinguish between early death and recovery with AUCs of 0.819 (95% CI: 0.727-0.911, p < 0.001) and 0.808 (95% CI: 0.713-0.902, p < 0.001).

[0226]

[0227] Meanwhile, Figure 6 shows the results of verifying the block value for sepsis diagnosis and the diagnostic accuracy of CRP and five types of proteins.

[0228] As a result, sensitivity and specificity were highest for CRP, followed by FINC, which had high values ​​with a sensitivity of 91.2% and a specificity of 91.1%.

[0229]

[0230] In addition, in Figure 7, the AUC curve and cutoff value for predicting in-hospital mortality, as well as the predicted values ​​of CRP, five types of proteins, and serum procalcitonin, were confirmed.

[0231] As a result, FINC and ACTB had higher predicted values ​​than serum procalcitonin and CRP, with AUROCs of 0.790 and 0.743 (both, p-value < 0.05). Sensitivity and specificity were 91.8%, 60.9%, 90.2%, and 48.1%, respectively.

[0232]

[0233] Example 5. Development of a Combined Model for Predicting In-Hospital Mortality

[0234] A model for predicting in-hospital death was developed by combining five types of proteins, and the model with the highest AUC value was identified. In-hospital death includes early and late death and is defined as death within 60 days of being admitted to the intensive care unit following a diagnosis of sepsis.

[0235]

[0236] As a result, four protein models including ACTB, FINC, CXCL7, and TIMP1 were identified, achieving an AUC value of 0.868 (Fig. 8). The sensitivity and specificity at the best threshold were 83.6% and 77.6%, respectively.

[0237] Subsequently, a six-variable model including SOFA scores and five proteins—ACTB, FINC, CXCL7, TIMP1, and PF4—was evaluated for predicting in-hospital mortality. The six-variable model showed the highest AUC value of 0.903 (Fig. 9). The sensitivity and specificity at the best threshold were 82.0% and 86.5%, respectively.

[0238]

[0239] Example 6. Analysis of correlation curves between CRP, SOFA scores, and lactate levels of five proteins

[0240] When comparing the concentrations of CRP and the top 5 proteins with SOFA scores and lactate levels, significant correlations were found between SOFA and lactate levels for all 5 proteins except CRP (all p < 0.001) (Figs. 10 and 11).

[0241] CXCL7 and PF4 showed a moderate to strong negative correlation with SOFA scores, with R values ​​of -0.6 and -0.57, respectively. Similarly, TIMP1 and ACTB showed a moderate to strong positive correlation with lactic acid, with R values ​​of 0.61 and 0.55, respectively.

[0242]

[0243] Example 7. Gene Ontology (GO) Concentration Analysis

[0244] A list of high-expression proteins with a fold change > 2.0 in sepsis patients compared to healthy controls and in sepsis patients who died early compared to the recovery group was used for GO enrichment analysis (Fig. 2e).

[0245]

[0246] As a result, the most highly expressed pathways in the sepsis group compared to healthy controls were the acute phase response, the wound response, and the bacterial response (Fig. 12a). Among the sepsis subgroup, patients who died early showed higher expression of pathways related to the wound response, platelet aggregation, and cell-matrix adhesion compared to the recovery group (Fig. 12b).

[0247]

[0248] Example 8. Confirmation of Clinical Significance of Proteins in Sepsis Patients

[0249] According to the univariate Cox proportional hazards analysis, 15 variables with p < 0.1 were identified (Table 3). In the multivariate Cox proportional hazards analysis, higher SOFA scores, increased ACTB levels, and Gram-negative sepsis were associated with an increased risk of in-hospital death, with hazard ratios of 1.08 (p = 0.002), 1.21 (p = 0.002), and 1.42 (p = 0.038), respectively (Fig. 13). Additionally, higher FINC levels were associated with a reduced risk of in-hospital death (hazard ratio [HR] 0.88, p = 0.024).

[0250]

[0251]

[0252]

[0253] Example 9. Analysis of the correlation between Gelsoline and Gc Globulin (Vitamin D-binding Protein) levels and ACTB, SOFA scores, and lactic acid

[0254] Plasma proteins gelsoline and Gc globulin (vitamin D-binding protein) are known as actin-binding proteins, and these two proteins regulate the levels of actin in the plasma. Therefore, in the present invention, various analyses related to ACTB were performed according to the levels of gelsoline and Gc globulin.

[0255]

[0256] As a result, first, among actin-binding proteins, gelsoline (GELS) levels were found to be significantly lower in sepsis patients compared to healthy controls, but there was no significant difference among sepsis subgroups (Fig. 14). In addition, gelsoline levels showed a significant but weak correlation with ACTB levels (R = 0.14), SOFA scores (R = 0.19), and lactate levels (R = 0.32). Gc globulin (VTDB) levels were found to be significantly different between the healthy cohort and the sepsis subgroup (Fig. 15).

[0257]

[0258] In addition, ANOVA tests confirmed significantly different results among sepsis subgroups (Table 2). VTDB levels were significantly correlated with ACTB levels (R = -0.25), SOFA scores (R = -0.41), and lactate levels (R = -0.37).

[0259]

[0260] Meanwhile, both gelsoline and Gc globulin levels were associated with in-hospital mortality in univariate Cox proportional hazards analysis (Table 3). However, after adjusting for other variables, neither gelsoline nor Gc globulin was found to be an independent factor associated with in-hospital mortality (Fig. 13).

[0261]

[0262] Example 10. Sensitivity analysis based on multiple linear regression analysis for exclusion of underlying diseases

[0263] Multiple linear regression analysis was performed for sensitivity analysis to exclude the influence of underlying diseases on proteomic expression patterns.

[0264]

[0265] As a result, as shown in Table 4, FINC, PF4, and CXCL7 levels were decreased in hematological malignancies, whereas TIMP1 levels were increased, which was associated with chronic liver disease. A sensitivity analysis was performed on 133 patients after excluding those with chronic liver disease (n=59) and hematological malignancies (n=33) (Fig. 16). The results showed that ACTB and FINC remained the most important proteins, each exhibiting a VIP score of approximately 3.5.

[0266]

[0267]

[0268]

[0269] The description of the present invention is for illustrative purposes only, and those skilled in the art will understand that other specific forms can be easily modified without altering the technical spirit or essential features of the invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive.

[0270] According to the biomarkers for predicting sepsis prognosis and their uses, PF4, CXCL7, ACTB, FINC, and TIMP1 were identified as new biomarkers for distinguishing sepsis severity and predicting outcomes in sepsis patients in the ICU by evaluating the proteomic profiles of sepsis patients using SWATH-MS-based proteomics. Since these biomarkers have excellent sepsis prognosis prediction effects and are expected to be useful for sepsis prognosis prediction and diagnosis, they have industrial applicability.

Claims

A method for providing information for predicting the prognosis of sepsis, comprising the following steps: A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject; and A step of predicting that the prognosis for sepsis of the subject will be poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group. In paragraph 1, the above information provision method is, A step of additionally measuring the level of one or more proteins selected from the group consisting of TIMP1 (Metallopeptidase Inhibitor 1) and FINC (Fibronectin) in a biological sample isolated from a subject; and A step in which the prognosis of the subject for sepsis is predicted to be poor if the protein level of TIMP1 among the above proteins is increased compared to the control group, or the protein level of FINC is decreased compared to the control group. A method of providing information that further includes In paragraph 1, A method of providing information, wherein predicting the above prognosis involves predicting one or more selected from a group consisting of early death, late death, in-hospital death, and recovery. In paragraph 1, the above information provision method is, A step of measuring protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample separated from the subject; and A step in which the prognosis of the subject for sepsis is predicted to be poor when the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, and the protein levels of FINC and CXCL7 are decreased compared to the control group. A method of providing information that further includes In paragraph 1, the above information provision method is, Protein levels of ACTB (Actin beta), FINC (Fibronectin), CXCL7 (Chemokine (CXC motif) ligand 7), PF4 (Platelet factor 4), and TIMP1 (Metallopeptidase Inhibitor 1) in biological samples isolated from the subject; and a step of measuring the SOFA score (Sequential [Sepsis-Related] Organ Failure Assessment Score) of the subject; and A method for providing information, further comprising the step of predicting that the prognosis of the subject for sepsis is poor if the protein levels of ACTB and TIMP1 among the above proteins are increased compared to the control group, the protein levels of FINC, PF4, and CXCL7 are decreased compared to the control group, and the SOFA score is high compared to the control group. In either paragraph 4 or 5, A method of providing information that the poor prognosis for the above sepsis is in-hospital death. A method for providing information for the diagnosis of sepsis, comprising the following steps: A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject; and A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group. In either Article 1 or Article 7, A method of providing information in which the biological sample is any one selected from the group consisting of blood, serum, whole blood, plasma, urine, saliva, tissue, cell, organ, bone marrow, fine needle aspiration specimen, core needle biopsy specimen, and vacuum aspiration biopsy specimen. A screening method for substances for the prevention or treatment of sepsis comprising the following steps: A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a sepsis model administered a candidate substance; and A step of selecting the candidate substance as a substance for preventing or treating sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins decreases compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 increases compared to the control group. A composition for predicting the prognosis of sepsis comprising, as an active ingredient, a preparation for measuring protein levels selected from the group consisting of the following: Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7). In Paragraph 10, A composition comprising one or more proteins additionally selected from the group consisting of FINC (Fibronectin) and TIMP1 (Metallopeptidase Inhibitor 1). A kit for predicting the prognosis of sepsis, comprising the composition of claim 10 and instructions. In Paragraph 12, The above instruction manual is a kit that teaches the method of providing information of paragraph 1. A sepsis treatment method including the following steps: A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), and CXCL7 (Chemokine (CXC motif) ligand 7) in a biological sample isolated from a subject; A step of predicting that the prognosis for sepsis of the subject is poor if the protein level of ACTB among the above proteins is increased compared to the control group, or the protein level of PF4 or CXCL7 is decreased compared to the control group; and A step of administering a therapeutic substance for poor-prognosis sepsis to a subject predicted to have a poor prognosis. A sepsis treatment method including the following steps: A step of measuring the level of one or more proteins selected from the group consisting of ACTB (Actin beta), PF4 (Platelet factor 4), CXCL7 (Chemokine (CXC motif) ligand 7), FINC (Fibronectin), and TIMP1 (Metallopeptidase Inhibitor 1) in a biological sample isolated from a subject; A step of determining that the subject has sepsis if the level of one or more proteins selected from the group consisting of ACTB and TIMP1 among the above proteins is increased compared to the control group, or if the level of one or more proteins selected from the group consisting of FINC, PF4, and CXCL7 is decreased compared to the control group; and A step of administering a sepsis treatment substance to a subject determined to have sepsis. Use of a composition comprising, as an active ingredient, a preparation for measuring protein levels selected from the group consisting of the following for predicting the prognosis of sepsis: Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7). Use of a composition comprising, as an active ingredient, a preparation for measuring protein levels selected from the group consisting of the following for substance screening for the prevention or treatment of sepsis: Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7). Use for manufacturing a preparation for predicting the prognosis of sepsis comprising, as an active ingredient, a preparation for measuring protein levels selected from the group consisting of the following: Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7). Use for manufacturing a screening agent for substances for the prevention or treatment of sepsis, comprising as an active ingredient a composition comprising one or more agents for measuring protein levels selected from the group consisting of the following: Actin beta (ACTB), Platelet factor 4 (PF4), and Chemokine (CXC motif) ligand 7 (CXCL7).

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