CN118311275B - Molecular marker for identifying bacterial and viral meningitis and evaluation method - Google Patents
Molecular marker for identifying bacterial and viral meningitis and evaluation method Download PDFInfo
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Abstract
The invention relates to a molecular marker for identifying bacterial and viral meningitis and an evaluation method, belonging to the technical field of molecular biology. The invention provides a molecular marker for identifying bacterial meningitis and viral meningitis, wherein the molecular marker comprises a primary marker, a secondary marker and a tertiary marker, or the molecular marker comprises a primary marker and a quaternary marker; the primary markers include cerebrospinal fluid IL-6 and/or IL-17; the secondary markers include cerebrospinal fluid IL-2, IL-8, IL-10 and/or IL-1β; the tertiary markers include cerebrospinal fluid IFN-gamma; the quaternary markers include cerebrospinal glucose, chloride, proteins, and/or leukocytes. The molecular marker is used for identifying bacterial meningitis and viral meningitis, and has the advantage of high specificity.
Description
Technical Field
The invention relates to a molecular marker for identifying bacterial and viral meningitis and an evaluation method, belonging to the technical field of molecular biology.
Background
Meningitis refers to a diffuse inflammatory change of the pia mater, caused by invasion of the pia mater and spinal cord membranes by a variety of pathogens. Bacterial meningitis (bacterial meningitis, BM) is an acute inflammatory disease of the central nervous system caused by bacterial infection, and is seen in any age group, and is most common in children under 1 year and 5-7 years, and 30% -50% of children patients can have nervous system complications such as cerebral vasospasm, thrombosis, venous obstruction, neuron necrosis and the like. Viral meningitis (VIRAL MENINGITIS, VM) is an acute inflammatory disease of the central nervous system caused by viral infection, which is common to children under 1 year and children between 5 and 7 years, and is also common to adults, wherein viral meningitis caused by respiratory syncytial virus infection alone causes about 27% of patients to produce reversible or irreversible sequelae.
Because the main clinical manifestations of bacterial meningitis and viral meningitis are fever, headache, convulsion, consciousness disturbance and the like, and the two kinds of meningitis are easily confused with upper respiratory tract infection and children febrile convulsion in early stage, the early diagnosis of the bacterial meningitis and the viral meningitis is very difficult. In addition, the main patients with bacterial meningitis and viral meningitis are children, and patients in the small age groups have unobvious symptoms and unclear expression and self-cognition due to limited physiological development, so that the clinical diagnosis of the bacterial meningitis and the viral meningitis is plagued. Bacterial meningitis and viral meningitis are distinct in clinical treatment schemes (bacterial meningitis is treated by adopting antibacterial drugs, viral meningitis is mostly a self-limiting disease and mainly adopts symptomatic treatment, and antiviral drugs can be used as part of the self-limiting disease), so that the accurate identification of bacterial meningitis and viral meningitis is critical to the establishment of treatment schemes of the bacterial meningitis and the viral meningitis.
According to records in diagnosis and treatment guidelines, at the present stage, bacterial meningitis and viral meningitis are clinically identified mainly by adopting a pathogenic microorganism culture method, a cerebrospinal fluid nucleic acid analysis method and a cerebrospinal fluid metagenome second-generation sequencing technology (mNGS). The pathogen is distinguished by culturing cerebrospinal fluid by the pathogenic microorganism culture method, but the cerebrospinal fluid culture period of the method is long (generally 48-120 hours are needed to be cultured), so that the detection efficiency is seriously affected, meanwhile, the method has the problem of low detection rate (only 60-90% of patients can have positive cerebrospinal fluid culture results), and in addition, the detection rate of the cerebrospinal fluid culture of patients which receive antibacterial drugs by self or clinical mistakes due to early symptoms can be reduced by 10-20%. The cerebrospinal fluid nucleic acid analysis method is used for determining pathogens through nucleic acid analysis, and has the advantages of high detection rate, high cost, high consumption of materials, long overall detection period (generally taking 8-10 hours), and high laboratory conditions, data analysis library capacity and personnel technical requirements. The cerebrospinal fluid metagenome second generation sequencing technology is used for detecting viral meningitis and new pathogens caused by neurotropic viruses by determining pathogens, the detection rate of the method is high, but the method is high in cost and complex in operation, and the sequencing sequence and positive quality control data in a database need to be updated regularly, otherwise, the method cannot be interpreted.
In the experimental medication, glucose (GLU), chloride ion (CL), cerebrospinal fluid total protein (CFP), cerebrospinal fluid white blood cell count (WBC) and other cerebrospinal fluid biochemical indexes are also introduced as molecular markers to assist in laboratory for bacterial meningitis and viral meningitis. Compared with a pathogenic microorganism culture method, a cerebrospinal fluid nucleic acid analysis method and a cerebrospinal fluid metagenome second generation sequencing technology, the method for identifying bacterial meningitis and viral meningitis by using the molecular markers has the advantages of short detection period (generally only takes 1-2 hours), high detection efficiency, small cerebrospinal fluid sample consumption (generally 300 mu L), low cost, less consumption, low requirements on laboratory conditions, data analysis reservoir capacity and personnel technology, simplicity in operation and the like. However, according to the WHO monitoring network 2014-2019 statistics, in the first-visit bacterial meningitis infants, the cerebrospinal fluid white blood cell count > 100/μl accounts for only 6.9% of all cases; cerebrospinal fluid proteins >100mg/dL only account for 18.3%; cerebrospinal fluid glucose <40mg/dL represents only 24.6%. Therefore, the comprehensive identification of bacterial meningitis and viral meningitis by using the cerebrospinal fluid biochemical indexes as molecular markers has the problem of low specificity, and the preparation of a treatment scheme cannot be effectively guided. Therefore, it is highly desirable to find a cerebrospinal fluid molecular marker with high specificity, which can more accurately and directly reflect the intracranial conditions, so as to realize the precise identification of bacterial and viral meningitis.
Disclosure of Invention
In order to solve the problems, the invention provides a molecular marker for identifying bacterial meningitis and viral meningitis, wherein the molecular marker comprises a primary marker, a secondary marker and a tertiary marker, or the molecular marker comprises a primary marker and a quaternary marker; the primary markers include IL-6 and/or IL-17; the secondary markers include IL-2, IL-8, IL-10 and/or IL-1β; the tertiary markers include IFN- γ; the quaternary markers include Glucose (GLU), chloride (CL), protein (CFP, total protein) and/or white blood cells (WBC, white blood cell count).
In one embodiment of the invention, the primary marker comprises the amount of IL-6 and/or IL-17 in cerebrospinal fluid; the secondary marker comprises the content of IL-2, IL-8, IL-10 and/or IL-1 beta in cerebrospinal fluid; the tertiary marker comprises IFN-gamma content in cerebrospinal fluid; the quaternary markers include concentration of glucose, concentration of chloride ions, protein content and/or number of leukocytes in cerebrospinal fluid.
In one embodiment of the invention, the molecular markers comprise at least one primary marker, at least two secondary markers, and at least one tertiary marker;
Or the molecular markers comprise at least two primary markers and at least four quaternary markers.
In one embodiment of the invention, the molecular markers consist of at least one primary marker, at least two secondary markers and at least one tertiary marker;
Or the molecular marker is composed of at least two primary markers and at least four quaternary markers.
In one embodiment of the invention, the molecular markers include IL-2, IL-6, IL-8, IL-10, IL-17 and IFN-gamma (i.e., the molecular markers include two primary markers, three secondary markers and a tertiary marker);
Or the molecular markers include IL-6, IL-1 beta, IL-2 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-17, IL-1 beta, IL-2 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
or the molecular markers include IL-6, IL-1 beta, IL-8 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
or the molecular markers include IL-17, IL-1β, IL-8, and IFN- γ (i.e., the molecular markers include one primary marker, two secondary markers, and one tertiary marker);
Or the molecular markers include IL-6, IL-1 beta, IL-10 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-17, IL-1β, IL-10, and IFN- γ (i.e., the molecular markers include one primary marker, two secondary markers, and one tertiary marker);
Or the molecular markers include IL-6, IL-2, IL-8 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-17, IL-2, IL-8 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
or the molecular markers include IL-6, IL-2, IL-10 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
or the molecular markers include IL-17, IL-2, IL-10 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-6, IL-8, IL-10 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-17, IL-8, IL-10 and IFN-gamma (i.e., the molecular markers include a primary marker, two secondary markers and a tertiary marker);
Or the molecular markers include IL-6, IL-17, glucose, chloride, protein, and white blood cells (i.e., the molecular markers include two primary markers and four quaternary markers).
In one embodiment of the invention, the molecular marker consists of IL-2, IL-6, IL-8, IL-10, IL-17 and IFN-gamma;
Or the molecular marker consists of IL-6, IL-1 beta, IL-2 and IFN-gamma;
or the molecular marker consists of IL-17, IL-1 beta, IL-2 and IFN-gamma;
Or the molecular marker consists of IL-6, IL-1 beta, IL-8 and IFN-gamma;
Or the molecular marker consists of IL-17, IL-1 beta, IL-8 and IFN-gamma;
Or the molecular marker consists of IL-6, IL-1 beta, IL-10 and IFN-gamma;
Or the molecular marker consists of IL-17, IL-1 beta, IL-10 and IFN-gamma;
or the molecular marker consists of IL-6, IL-2, IL-8 and IFN-gamma;
or the molecular marker consists of IL-17, IL-2, IL-8 and IFN-gamma;
or the molecular marker consists of IL-6, IL-2, IL-10 and IFN-gamma;
Or the molecular marker consists of IL-17, IL-2, IL-10 and IFN-gamma;
or the molecular marker consists of IL-6, IL-8, IL-10 and IFN-gamma;
or the molecular marker consists of IL-17, IL-8, IL-10 and IFN-gamma;
Or the molecular marker consists of IL-6, IL-17, glucose, chloride ion, protein and leucocyte.
In one embodiment of the invention, the molecular markers further comprise five-level markers; the five-level markers include IL-4, IL-5, IL-12P70, TNF-alpha and/or IFN-alpha.
In one embodiment of the invention, the five-level marker comprises IL-4, IL-5, IL-12P70, TNF- α and/or IFN- α content in cerebrospinal fluid.
The invention also provides application of the reagent for detecting the level of the molecular marker in the sample to be detected in preparation of a product for identifying bacterial meningitis and viral meningitis.
In one embodiment of the invention, the application comprises the steps of:
The detection step comprises: detecting the level of the molecular marker in the sample to be detected to obtain a detection result;
and a data analysis step: analyzing and calculating the detection result of the detection module to obtain a meningitis score;
An evaluation step: and identifying bacterial meningitis and viral meningitis according to the meningitis score of the data analysis module.
In one embodiment of the invention, when the molecular markers comprise at least one primary marker, at least two secondary markers and at least one tertiary marker, the detecting step comprises: detecting the content of cytokines in cerebrospinal fluid to obtain a detection result;
when the molecular markers include at least two primary markers and at least four quaternary markers, the detecting step includes: and detecting the content of cytokines, the content of Glucose (GLU), the content of chloride ions (CL), the content of proteins (CFP, total proteins) and the number of white blood cells (WBC, white blood cell count) in cerebrospinal fluid to obtain detection results.
In one embodiment of the invention, when the molecular markers include at least one primary marker, at least two secondary markers, and at least one tertiary marker, the data analysis step comprises:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker, thenThe value of (2) is 1, otherwise, the value is 0; The weight of the ith molecular marker in the sample to be detected is represented, when the ith molecular marker is a primary marker, The value of (2) is 3, when the ith molecular marker is a secondary marker,The value of (2) is given, when the ith molecular marker is a tertiary marker,The value of (2) is 1;
When the molecular markers include at least two primary markers and at least four quaternary markers, the data analysis step includes:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker when the ith molecular marker is the primary marker, thenIf the value of (2) is 1, otherwise, the value is 0, and if the ith molecular marker is glucose or chloride ion in the fourth-level marker, if the content of the ith molecular marker in the sample to be detected is lower than the critical value, thenIf the content of the ith molecular marker in the sample to be detected is higher than the critical value of the protein or the leucocyte in the fourth-level marker, the value of the ith molecular marker is 0And if not, the value of (2) is 1, otherwise, the value is 0.
In one embodiment of the present invention, the method for obtaining the critical value is: collecting the first-time admitted cerebrospinal fluid samples of patients with bacterial meningitis and viral meningitis, establishing a subject working characteristic curve (ROC) of each molecular marker content according to the meningitis type of the patient and the content of each molecular marker in cerebrospinal fluid of the patient, and obtaining a critical value (cut-off value +/-5% cut-off value, and P < 0.01) with identification significance of each molecular marker according to the subject working characteristic curve of each molecular marker content.
In one embodiment of the invention, the threshold value of the primary marker IL-6 is 17.75.+ -. 0.89pg/mL, the threshold value of the primary marker IL-17 is 1.52.+ -. 0.08pg/mL, the threshold value of the secondary marker IL-2 is 5.80.+ -. 0.29pg/mL, the threshold value of the secondary marker IL-8 is 188.01.+ -. 9.40pg/mL, the threshold value of the secondary marker IL-10 is 3.04.+ -. 0.15pg/mL, the critical value of the second-level marker IL-1 beta is 12.07+/-0.60 pg/mL, the critical value of the third-level marker IFN-gamma is 4.51+/-0.23 pg/mL, the critical value of the fourth-level marker glucose is 2.92+/-0.15 mmoL/L, the critical value of the fourth-level marker chloride ion is 117+/-5.85 mmoL/L, the critical value of the fourth-level marker protein is 477.8 +/-23.89 mg/L, and the critical value of the fourth-level marker leukocyte is (4+/-0.20) multiplied by 10 6/L.
In one embodiment of the invention, the threshold value of the primary marker IL-6 is 17.75pg/mL, the threshold value of the primary marker IL-17 is 1.52pg/mL, the threshold value of the secondary marker IL-2 is 5.80pg/mL, the threshold value of the secondary marker IL-8 is 188.01pg/mL, the threshold value of the secondary marker IL-10 is 3.04pg/mL, the threshold value of the secondary marker IL-1β is 12.07pg/mL, the threshold value of the tertiary marker IFN- γ is 4.51pg/mL, the threshold value of the quaternary marker glucose is 2.92mmoL/L, the threshold value of the quaternary marker chloride ion is 117mmoL/L, the threshold value of the quaternary marker protein is 477.8mg/L, and the threshold value of the quaternary marker leukocyte is 4X 10 6/L.
In one embodiment of the invention, the evaluating step includes:
When the molecular markers comprise at least one primary marker, at least two secondary markers and at least one tertiary marker, if the meningitis score is more than or equal to 8 points, outputting a judgment result as bacterial meningitis, and if the meningitis score is less than 8 points, outputting a judgment result as viral meningitis;
When the molecular markers comprise at least two primary markers and at least four quaternary markers, if the meningitis score is more than 9 points, outputting a judging result as bacterial meningitis, if the meningitis score is less than 9 points, outputting a judging result as viral meningitis, if the cerebrospinal fluid score is less than 9 points, adding a judging standard, and judging IL-6 and IL-17 If the scores are simultaneously scored, outputting a judging result to be bacterial meningitis, and if the scores are not simultaneously scored, outputting a judging result to be viral meningitis.
In one embodiment of the invention, the sample to be tested is cerebrospinal fluid.
In one embodiment of the invention, the product is a detection kit.
In one embodiment of the invention, the detection kit is a flow-through detection kit.
In one embodiment of the invention, the flow assay kit is a cytokine microsphere detection technology (CBA) based flow assay kit.
The invention also provides a detection kit for distinguishing bacterial meningitis from viral meningitis, which comprises a reagent for detecting the level of the molecular marker in a sample to be detected.
In one embodiment of the invention, the sample to be tested is cerebrospinal fluid.
In one embodiment of the invention, the detection kit is a flow-through detection kit.
In one embodiment of the invention, the flow assay kit is a cytokine microsphere detection technology (CBA) based flow assay kit.
The invention also provides an evaluation model for identifying bacterial meningitis and viral meningitis, which comprises a detection module, a data analysis module and an evaluation module;
the detection module is used for detecting the level of the molecular marker in the sample to be detected to obtain a detection result;
The data analysis module is used for analyzing and calculating the detection result of the detection module to obtain a meningitis score;
The evaluation module is used for identifying bacterial meningitis and viral meningitis according to the meningitis score of the data analysis module.
In one embodiment of the invention, when the molecular marker comprises at least one primary marker, at least two secondary markers and at least one tertiary marker, the detection module is used for detecting the content of cytokines in cerebrospinal fluid to obtain a detection result;
When the molecular markers comprise at least two primary markers and at least four secondary markers, the detection module is used for detecting the content of cytokines, the content of Glucose (GLU), the content of chloride ions (CL), the content of protein (CFP, total protein of cerebrospinal fluid) and the number of white blood cells (WBC, white blood cell count) in cerebrospinal fluid to obtain detection results.
In one embodiment of the present invention, when the molecular markers include at least one primary marker, at least two secondary markers, and at least one tertiary marker, the process of analyzing and calculating the detection result of the detection module by the data analysis module includes:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker, thenThe value of (2) is 1, otherwise, the value is 0; The weight of the ith molecular marker in the sample to be detected is represented, when the ith molecular marker is a primary marker, The value of (2) is 3, when the ith molecular marker is a secondary marker,The value of (2) is given, when the ith molecular marker is a tertiary marker,The value of (2) is 1;
when the molecular markers comprise at least two primary markers and at least four quaternary markers, the process of analyzing and calculating the detection result of the detection module by the data analysis module comprises the following steps:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker when the ith molecular marker is the primary marker, thenIf the value of (2) is 1, otherwise, the value is 0, and if the ith molecular marker is glucose or chloride ion in the fourth-level marker, if the content of the ith molecular marker in the sample to be detected is lower than the critical value, thenIf the content of the ith molecular marker in the sample to be detected is higher than the critical value of the protein or the leucocyte in the fourth-level marker, the value of the ith molecular marker is 0And if not, the value of (2) is 1, otherwise, the value is 0.
In one embodiment of the present invention, the method for obtaining the critical value is: collecting the first-time admitted cerebrospinal fluid samples of patients with bacterial meningitis and viral meningitis, establishing a subject working characteristic curve (ROC) of each molecular marker content according to the meningitis type of the patient and the content of each molecular marker in cerebrospinal fluid of the patient, and obtaining a critical value (cut-off value +/-5% cut-off value, and P < 0.01) with identification significance of each molecular marker according to the subject working characteristic curve of each molecular marker content.
In one embodiment of the invention, the threshold value of the primary marker IL-6 is 17.75.+ -. 0.89pg/mL, the threshold value of the primary marker IL-17 is 1.52.+ -. 0.08pg/mL, the threshold value of the secondary marker IL-2 is 5.80.+ -. 0.29pg/mL, the threshold value of the secondary marker IL-8 is 188.01.+ -. 9.40pg/mL, the threshold value of the secondary marker IL-10 is 3.04.+ -. 0.15pg/mL, the critical value of the second-level marker IL-1 beta is 12.07+/-0.60 pg/mL, the critical value of the third-level marker IFN-gamma is 4.51+/-0.23 pg/mL, the critical value of the fourth-level marker glucose is 2.92+/-0.15 mmoL/L, the critical value of the fourth-level marker chloride ion is 117+/-5.85 mmoL/L, the critical value of the fourth-level marker protein is 477.8 +/-23.89 mg/L, and the critical value of the fourth-level marker leukocyte is (4+/-0.20) multiplied by 10 6/L.
In one embodiment of the invention, the threshold value of the primary marker IL-6 is 17.75pg/mL, the threshold value of the primary marker IL-17 is 1.52pg/mL, the threshold value of the secondary marker IL-2 is 5.80pg/mL, the threshold value of the secondary marker IL-8 is 188.01pg/mL, the threshold value of the secondary marker IL-10 is 3.04pg/mL, the threshold value of the secondary marker IL-1β is 12.07pg/mL, the threshold value of the tertiary marker IFN- γ is 4.51pg/mL, the threshold value of the quaternary marker glucose is 2.92mmoL/L, the threshold value of the quaternary marker chloride ion is 117mmoL/L, the threshold value of the quaternary marker protein is 477.8mg/L, and the threshold value of the quaternary marker leukocyte is 4X 10 6/L.
In one embodiment of the invention, the process of identifying bacterial meningitis from viral meningitis by the evaluation module according to the meningitis score of the data analysis module comprises:
When the molecular markers comprise at least one primary marker, at least two secondary markers and at least one tertiary marker, if the meningitis score is more than or equal to 8 points, outputting a judgment result as bacterial meningitis, and if the meningitis score is less than 8 points, outputting a judgment result as viral meningitis;
When the molecular markers comprise at least two primary markers and at least four quaternary markers, if the meningitis score is more than 9 points, outputting a judging result as bacterial meningitis, if the meningitis score is less than 9 points, outputting a judging result as viral meningitis, if the cerebrospinal fluid score is less than 9 points, adding a judging standard, and judging IL-6 and IL-17 If the scores are simultaneously scored, outputting a judging result to be bacterial meningitis, and if the scores are not simultaneously scored, outputting a judging result to be viral meningitis.
The invention also provides an evaluation method for identifying bacterial meningitis from viral meningitis, which is not diagnostic or therapeutic for the purpose of disease, comprising: bacterial meningitis is identified from viral meningitis using the molecular markers described above or the assessment model described above.
The technical scheme of the invention has the following advantages:
1. The invention provides a molecular marker for identifying bacterial meningitis and viral meningitis, wherein the molecular marker comprises a primary marker, a secondary marker and a tertiary marker, or the molecular marker comprises a primary marker and a quaternary marker; the primary markers include cerebrospinal fluid IL-6 and/or IL-17; the secondary markers include cerebrospinal fluid IL-2, IL-8, IL-10 and/or IL-1β; the tertiary markers include cerebrospinal fluid IFN-gamma; the quaternary markers include cerebrospinal Glucose (GLU), chloride (CL), proteins (CFP, total proteins) and/or white blood cells (WBC, white blood cell count). The molecular marker is used for identifying bacterial meningitis and viral meningitis, has the advantages of high specificity (AUC can reach 0.599-0.858, specificity can reach 75.51-97.96%, positive predictive value can reach 61.30-94.40%), and can more accurately and directly reflect intracranial conditions. In addition, bacterial meningitis and viral meningitis can be identified by using the molecular marker, the result can be directly obtained by combining flow cytometry, the method has the advantages of short detection period (generally only 4-6 hours are consumed), high detection efficiency, small cerebrospinal fluid sample consumption (generally 200 mu L), medical insurance settlement, low cost, less consumption, low requirements on laboratory conditions and personnel technology, and simplicity in operation, and has a great application prospect.
2. The invention provides an evaluation model for distinguishing bacterial meningitis from viral meningitis, which comprises a detection module, a data analysis module and an evaluation module; the detection module is used for detecting the level of the molecular marker in the sample to be detected to obtain a detection result; the data analysis module is used for analyzing and calculating the detection result of the detection module to obtain a meningitis score; the evaluation module is used for identifying bacterial meningitis and viral meningitis according to the meningitis score of the data analysis module; the molecular markers comprise a primary marker, a secondary marker and a tertiary marker, or the molecular markers comprise a primary marker and a quaternary marker; the primary markers include cerebrospinal fluid IL-6 and/or IL-17; the secondary markers include cerebrospinal fluid IL-2, IL-8, IL-10 and/or IL-1β; the tertiary markers include cerebrospinal fluid IFN-gamma; the quaternary markers include cerebrospinal Glucose (GLU), chloride (CL), proteins (CFP, total proteins) and/or white blood cells (WBC, white blood cell count). The evaluation model is used for identifying bacterial meningitis and viral meningitis, has the advantages of high specificity (AUC can reach 0.599-0.858, specificity can reach 75.51-97.96%, positive predictive value can reach 61.30-94.40%), and can more accurately and directly reflect intracranial conditions. And moreover, bacterial meningitis and viral meningitis can be identified by using the evaluation model, the result can be directly obtained by combining a flow cytometry, the method has the advantages of short detection period (generally only 4-6 hours are consumed), high detection efficiency, small cerebrospinal fluid sample consumption (generally 200 mu L), medical insurance settlement, low cost, less consumption, low requirements on laboratory conditions and personnel technology, and simplicity in operation, and has a great application prospect.
Drawings
Fig. 1: the discrimination ability of model a was evaluated.
Fig. 2: the discrimination ability of model B was evaluated (in fig. 2, a is a combination of IL-6+il-17+glu+cl+cfp+wbc, and B is a combination of glu+cl+cfp+wbc).
Fig. 3: the discrimination ability of model C was evaluated.
Fig. 4: the discrimination ability of model D was evaluated.
Fig. 5: the discrimination ability of the model E was evaluated.
Fig. 6: the discrimination ability of the model F was evaluated.
Fig. 7: the discrimination ability of the model G was evaluated.
Fig. 8: the discrimination ability of model H was evaluated.
Fig. 9: the discrimination ability of model I was evaluated.
Fig. 10: the discrimination ability of model J was evaluated.
Fig. 11: the discrimination ability of the model K was evaluated.
Fig. 12: the discrimination ability of the model L was evaluated.
Fig. 13: the discrimination ability of the model M was evaluated.
Fig. 14: the discrimination ability of model N was evaluated.
Detailed Description
The following examples are provided for a better understanding of the present invention and are not limited to the preferred embodiments described herein, but are not intended to limit the scope of the invention, any product which is the same or similar to the present invention, whether in light of the present teachings or in combination with other prior art features, falls within the scope of the present invention.
The following examples do not identify specific experimental procedures or conditions, which may be followed by procedures or conditions of conventional experimental procedures described in the literature in this field. The reagents or apparatus used were conventional reagent products commercially available without the manufacturer's knowledge.
Experimental example 1: screening of molecular markers and construction of evaluation models
1. Screening of molecular markers for the identification of bacterial and viral meningitis
The cytokine test box (China RAISECARE company) of the multiple microbead flow type immunofluorescence luminescence method is used for detecting the activity content of cytokines IL-6, IL17, IL-2, IL8, IL10, IL-1 beta, IFN-gamma, IL-4, IL-5, IL-12P70, TNF-alpha and IFN-alpha in cerebrospinal fluid samples, and counting the median and quarter level of each cytokine in bacterial meningitis and viral meningitis, and the statistical results are shown in Table 1; the results of Table 1 were subjected to rank and test Mann-Whitney analysis to obtain differences in bacterial meningitis and viral meningitis for each cytokine, and the analysis results are shown in Table 2; a subject operating characteristic curve (ROC) was established based on the results of table 1, and the threshold and discrimination ability of each cytokine were obtained based on the subject operating characteristic curve, and the analysis results are shown in table 3. Referring to table 3, a subject operating characteristic curve (ROC) was established based on cerebrospinal fluid GLU, CL, CFP and WBCs of each case of table 1, and critical values and discrimination capacities of GLU, CL, CFP and WBCs were obtained based on the subject operating characteristic curve, and the analysis results are shown in table 4.
In cerebrospinal fluid samples, 44 cases of bacterial meningitis are clinically diagnosed, 60 cases of viral meningitis are clinically diagnosed, and 104 cases are taken from first-time hospital admission cerebrospinal fluid specimens of the pediatric study of the capital of 1 st to 9 th 2021 st.
The cytokine detection process is: centrifuge 1000g of cerebrospinal fluid specimen for 10 minutes; adding 25 mu L of experiment buffer solution into 10mL of upper machine tube, adding 25 mu L of centrifuged bottom cerebrospinal fluid (taking the centrifuged bottom cerebrospinal fluid by a pipette), adding 25 mu L of capture microsphere, adding 25 mu L of detection antibody, and incubating for 2 hours at room temperature (25 ℃) under light-proof shaking (500 r.min -1) to obtain an incubation product A; adding 25 mu L of SA-PE fluorescent developer into the incubation product A, and performing light-proof shaking (500 r.min -1) at room temperature (25 ℃) for incubation for 0.5 hour to obtain an incubation product B; adding 800 mu L of 1X 9 existing washing buffer (namely 100 mu L of washing buffer mixed with 900 mu L of water for injection) into the incubation product B, swirling for 8 seconds, centrifuging 400g for 5 minutes, slowly pouring the liquid, reversely buckling to absorb water, and finally adding 300 mu L of 1X 9 existing washing buffer, swirling for 8 seconds to obtain an on-machine sample C; the sample C was taken and tested on a full-automatic flow cytometer (commercially available from BECKMAN COULTER, inc., model CYTOMICS FC, USA) to obtain the test results.
As can be seen from Table 1, the bacterial meningitis cytokines, except IL-4, IFN- α, have higher median levels than viral meningitis activity, with significant increases in IL-1β, IL-6, IL-8 and INF- γ. The results in Table 1 suggest that the cytokine activity of cerebrospinal fluid in bacterial meningitis is higher, and that the conditions of the intracranial environmental disorder, which are guided by molecular markers, are more complex and more likely to cause nervous system complications.
As can be seen from Table 2, IL-1. Beta., IL-2, IL-6, IL-8, IL-10, IL-17 and INF-gamma were significantly different in bacterial and viral meningitis. The results in Table 2 suggest that IL-1β, IL-2, IL-6, IL-8, IL-10, IL-17 and INF- γ can be used as molecular markers to identify bacterial and viral meningitis.
As can be seen from Table 3, when each cytokine was used as a single molecular marker to identify bacterial and viral meningitis, the area under the curve of IL-6 and IL-17 was larger, the sensitivity of IL-8 and IL-17 was higher, and the specificity of IL-1β and IFN- γ was higher. The results in table 3 suggest that a single molecular marker cannot simultaneously achieve both extremely high sensitivity and specificity, i.e., cannot effectively identify bacterial and viral meningitis, and requires a combination evaluation. However, the molecular markers are evaluated for differences in intensity.
As can be seen from table 4, when the biochemical index of cerebrospinal fluid used for laboratory assistance was used as a single molecular marker to identify bacterial and viral meningitis, the area under the curve of GLU and CFP was larger, the sensitivity of WBC was highest, and the specificity of GLU and CL was higher. The results in table 4 suggest that a single existing cerebrospinal fluid biochemical index cannot simultaneously achieve both extremely high sensitivity and specificity, i.e. cannot effectively identify bacterial and viral meningitis, and needs to be combined and supplemented with other molecular marker evaluations.
2. Combination of molecular markers for identifying bacterial meningitis and viral meningitis
According to the results of tables 1-4, molecular marker combinations capable of being used for identifying bacterial meningitis and viral meningitis were obtained, and by taking the cerebrospinal fluid biochemical index combination glu+cl+cfp+wbc in the empirical medication as a control, and taking the cerebrospinal fluid of 44 clinically confirmed cases of children with bacterial meningitis and the cerebrospinal fluid of 60 clinically confirmed cases of children with viral meningitis as samples, two Logistic regression fits were first used to reconstruct the subject working characteristic curve (ROC) to verify the effectiveness of these molecular marker combinations, and the molecular marker combinations and effectiveness verification results were as follows:
IL-2+IL-6+IL-8+IL-10+IL-17+IFN-gamma, effectiveness: AUC (area under ROC curve of discrimination efficacy) =0.728, sensitivity=53.13%, specificity=97.96%, positive predictive value= 94.40% (see fig. 1 for details);
IL-6+il-17+glu+cl+cfp+wbc, effectiveness: auc=0.858, sensitivity=75.00%, specificity= 83.67%, positive predictive value=75.00% (see fig. 2 for details);
IL-6+IL-1β+IL-2+IFN- γ, effectiveness: auc=0.664, sensitivity= 46.90%, specificity=87.80%, positive predictive value= 71.40% (see fig. 3 for details);
IL-17+IL-1β+IL-2+IFN- γ, effectiveness: auc=0.717, sensitivity=59.38%, specificity=81.63%, positive predictive value=67.90% (see fig. 4 for details);
IL-6+IL-1β+IL-8+IFN- γ, effectiveness: auc=0.599, sensitivity=37.50%, specificity=91.84%, positive predictive value=75.00% (see fig. 5 for details);
IL-17+IL-1β+IL-8+IFN- γ, effectiveness: auc=0.691, sensitivity=59.38%, specificity= 79.59%, positive predictive value=65.5% (see fig. 6 for details);
IL-6+IL-1β+IL-10+IFN- γ, effectiveness: auc=0.720, sensitivity=62.50%, specificity=81.63%, positive predictive value=69.00% (see fig. 7 for details);
IL-17+IL-1β+IL-10+IFN- γ, effectiveness: auc=0.677, sensitivity=50.00%, specificity=87.76%, positive predictive value= 72.70% (see fig. 8 for details);
IL-6+IL-2+IL-8+IFN-y, effectiveness: auc=0.689, sensitivity=56.25%, specificity=77.55%, positive predictive value=62.10% (see fig. 9 for details);
IL-17+IL-2+IL-8+IFN-y, effectiveness: auc=0.719, sensitivity= 46.88%, specificity=93.88%, positive predictive value= 83.30% (see fig. 10 for details);
IL-6+IL-2+IL-10+IFN-y, effectiveness: auc=0.678, sensitivity=50.00%, specificity= 89.88%, positive predictive value=76.20% (see fig. 11 for details);
IL-17+IL-2+IL-10+IFN-y, effectiveness: auc=0.716, sensitivity=50.00%, specificity=97.96%, positive predictive value= 94.10% (see fig. 12 for details);
IL-6+IL-8+IL-10+IFN-y, effectiveness: auc=0.701, sensitivity=56.25%, specificity=85.71%, positive predictive value=72.00% (see fig. 13 for details);
IL-17+IL-8+IL-10+IFN-y, effectiveness: auc=0.709, sensitivity=59.38%, specificity= 75.51%, positive predictive value=61.30% (see fig. 14 for details);
Control: GLU + CL + CFP + WBC, effectiveness is as follows: auc=0.839, sensitivity=78.12%, specificity=77.55%, positive predictive value=69.40% (see fig. 2 for details);
From the results of FIGS. 1-14, it can be seen that IL-2+IL-6+IL-8+IL-10+IL-17+IFN-gamma is the molecular marker combination with the best effect of identifying bacterial and viral meningitis, IL-6+IL-17+GLU+CL+CFP+WBC times, and the remaining molecular marker combinations can meet the minimum evaluation requirements for identifying bacterial and viral meningitis.
As can be seen from FIG. 2, when identifying bacterial and viral meningitis, the combination of the cerebrospinal fluid biochemical indicators GLU+CL+CFP+WBC in the empirical medicament has high sensitivity, but the specificity is far lower than that of IL-6+IL-17+GLU+CL+CFP+WBC and IL-2+IL-6+IL-8+IL-10+IL-17+IFN-gamma, which brings about a "high false positive rate", that is, the GLU+CL+CFP+WBC has strong prediction discrimination ability, but the rejection ability is far weaker than that of IL-6+IL-17+GLU+CL+CFP+WBC and IL-2+IL-6+IL-17+IFN-gamma, the IL-6+IL-17+GLU+CL+CFP+WBC and IL-2+IL-6+IL-8+IL-10+IL-17+IFN-gamma, which can assist in the rejection of excessively high "false positive rate", and the combination of the anti-bacterial and viral meningitis in the experimental medicament has better prediction ability than that of the combination of the IL-6+IL+17+GLU+WBC and the anti-2+GLU+WBC has better prediction ability.
TABLE 1 median and quartile levels of cytokines in bacterial and viral meningitis
TABLE 2 differentiation of cytokines in bacterial meningitis and viral meningitis
TABLE 3 diagnostic threshold and discrimination capability of individual cytokines
TABLE 4 diagnostic threshold and discrimination capability of biochemical indicators of cerebrospinal fluid
3. Construction of an evaluation model for the identification of bacterial meningitis and viral meningitis
IL-6, IL17, IL-2, IL8, IL10, IL-1 beta, IFN-gamma, IL-4, IL-5, IL-12P70, TNF-alpha and IFN-alpha 12 cytokines, GLU, CL, CFP and WBC 4 cerebrospinal fluid biochemical indexes are calculated according to the formula(In the formula, i is a natural number, the minimum value of i is 1, and the maximum value of i is the total number of molecular markers) to obtain a meningitis score;
Wherein, The content of the ith cytokine in the cerebrospinal fluid sample of meningitis cases was according to Mann-Whitney test, P <0.01, andDetermining that the level of each cytokine in bacterial meningitis is higher than that of viral meningitis; meanwhile, judging whether the content of each cytokine in a cerebrospinal fluid sample of a meningitis case is higher than 2 times of the critical value of each cytokine according to the critical value of each cytokine in a ROC curve of bacterial meningitis and more viral meningitis, wherein the score is higher than 1, and otherwise the score is 0;
Or alternatively Judging whether the content of the cerebrospinal fluid biochemical index in the cerebrospinal fluid sample of the meningitis case is lower than the critical value of the cerebrospinal fluid biochemical index in the meningitis case or not according to the critical value of each cerebrospinal fluid biochemical index in the ROC curve of the bacterial meningitis and the viral meningitis, if the content of the cerebrospinal fluid biochemical index in the cerebrospinal fluid sample of the meningitis case is GLU or CL, if so, the content of the cerebrospinal fluid biochemical index is lower than the critical value, if so, the score is 1, otherwise, the score is 0, and if the content of the cerebrospinal fluid biochemical index in the cerebrospinal fluid sample of the meningitis case is higher than the critical value, if so, the score is 1, otherwise, the score is 0;
The weight of the ith cytokine or cerebrospinal fluid biochemical index in the cerebrospinal fluid sample of the meningitis case is graded according to the size of the area AUC under the ROC curve of each cytokine or cerebrospinal fluid biochemical index of the bacterial meningitis and the viral meningitis, and the grading gradient is as follows:
IL-6, IL17, GLU, CL, CFP, WBC with AUC >0.7, weight assigned a score of 3;
IL-1 beta, IL-2, IL8, IL10 with AUC of 0.6< 0.7, weight divided into 2;
IFN-gamma of 0.5< AUC <0.6, weight assigned a score of 1;
IL-4, IL-5, IL-12P70, TNF- α, IFN- α with AUC <0.5, weights assigned to 0 points (see Table 5 for details);
When the molecular markers are both cytokines, the bacterial meningitis and viral meningitis are judged by =at least 1 cytokine of 3 minutes+at least 2 cytokine of 2 minutes+at least 1 cytokine of 1 minute+at least 0 cytokine of 0 minute; therefore, the output judgment result is bacterial meningitis which is more than or equal to 8, and the output judgment result is viral meningitis which is less than 8;
When the molecular marker is a combination of cytokines and cerebrospinal fluid biochemical indexes, the judgment mode of bacterial meningitis and viral meningitis=2 cytokines of 3 minutes+4 cerebrospinal fluid biochemical indexes of 3 minutes; therefore >9 score output of the evaluation result is bacterial meningitis, and <9 score output of the evaluation result is viral meningitis, if cerebrospinal fluid score=9 score, the judgment standard is increased, and IL-6 and IL-17 are judged If the scores are simultaneously scored, outputting a judging result to be bacterial meningitis, and if the scores are not simultaneously scored, outputting a judging result to be viral meningitis.
TABLE 5 weighting gradient of Biochemical indicators of cytokines and cerebrospinal fluid
4. Verification of an evaluation model for the identification of bacterial meningitis and viral meningitis
And respectively selecting the IL-2+IL-6+IL-8+IL-10+IL-17+IFN-gamma molecular marker combinations and the IL-6+IL-17+GLU+CL+CFP+WBC molecular marker combinations, and identifying cerebrospinal fluid samples by using the constructed evaluation model, wherein the identification results are shown in tables 6-7.
In the cerebrospinal fluid sample, 15 cases of bacterial meningitis are clinically diagnosed, 15 cases of viral meningitis are clinically diagnosed, and 30 cases are taken from a first hospital admission cerebrospinal fluid specimen of a pediatric study of the capital of 10 months 2023 to 3 months 2024.
As can be seen from the results in Table 6, when the combination of molecular markers IL-2+IL-6+IL-8+IL-10+IL-17+IFN-. Gamma.was selected to identify bacterial and viral meningitis, the results obtained in 30 cases according to the evaluation model were all clinically relevant.
As can be seen from the results in Table 7, when the molecular marker combinations of IL-6+IL-17+GLU+CL+CFP+WBC were selected to identify bacterial and viral meningitis, a critical interpretation score of 9 points resulted in a false positive rate of 23%, so that if the cerebrospinal fluid score=9 points, the criteria were increased and IL-6 and IL-17 were interpreted againIf the scores are simultaneously scored, outputting a judging result to be bacterial meningitis, and if the scores are not simultaneously scored, outputting a judging result to be viral meningitis. After the judgment standard is added, the misjudgment rate of the results obtained by 30 cases according to the evaluation model is reduced to 3.33%, and the misjudgment rate is within an acceptable range.
The results of tables 6-7 are combined to show that the effectiveness of the molecular markers and the evaluation models for identifying bacterial and viral meningitis is re-verified, and the clinical rapid establishment of a treatment scheme can be effectively guided.
TABLE 6 summary of the assignment of the formulas for cytokine entry
TABLE 7 summary of assignment of Biochemical index entry formulas for each cytokine and cerebrospinal fluid
Note that: in tables 6 to 7, the score with "/" is obtained by the difference between the two evaluation limits of "2× (critical value-5% critical value)" and "2× (critical value+5% critical value)".
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (6)
1. A molecular marker for identifying bacterial meningitis from viral meningitis, wherein the molecular marker consists of IL-2, IL-6, IL-8, IL-10, IL-17 and IFN- γ; or the molecular marker consists of IL-6, IL-17, glucose, chloride ions, cerebrospinal fluid total protein and cerebrospinal fluid leucocytes.
2. Use of a reagent for detecting the level of a molecular marker according to claim 1 in a sample to be tested for the preparation of a product for the identification of bacterial meningitis from viral meningitis.
3. A test kit for the identification of bacterial meningitis from viral meningitis, comprising reagents for detecting the level of the molecular marker according to claim 1 in a sample to be tested.
4. An evaluation model for distinguishing bacterial meningitis from viral meningitis, wherein the evaluation model comprises a detection module, a data analysis module and an evaluation module;
The detection module is used for detecting the level of the molecular marker in the sample to be detected according to the claim 1, and obtaining a detection result;
The data analysis module is used for analyzing and calculating the detection result of the detection module to obtain a meningitis score;
The evaluation module is used for identifying bacterial meningitis and viral meningitis according to the meningitis score of the data analysis module.
5. The assessment model according to claim 4, wherein when the molecular markers consist of IL-2, IL-6, IL-8, IL-10, IL-17 and IFN- γ, the process of analyzing and calculating the detection results of the detection module by the data analysis module comprises:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker, thenThe value of (2) is 1, otherwise, the value is 0; Characterizing the weight of the ith molecular marker in the sample to be tested, when the ith molecular marker is IL-6 or IL-17, When the ith molecular marker is IL-2, IL-8 or IL-10,The value of (2) is given, when the ith molecular marker is IFN-gamma,The value of (2) is 1;
When the molecular marker is composed of IL-6, IL-17, glucose, chloride ions, cerebrospinal fluid total protein and cerebrospinal fluid leucocytes, the process of analyzing and calculating the detection result of the detection module by the data analysis module comprises the following steps:
According to the formula Calculating a meningitis score; wherein,Characterizing the content of the ith molecular marker in the sample to be tested, and when the ith molecular marker is IL-6 or IL-17, if the content of the ith molecular marker in the sample to be tested is higher than 2 times of the critical value of the ith molecular marker, thenIf the content of the ith molecular marker in the sample to be detected is lower than the critical value of the ith molecular marker when the ith molecular marker is glucose or chloride ion, the value is 0If the content of the ith molecular marker in the sample to be detected is higher than the critical value of the total cerebrospinal fluid protein or cerebrospinal fluid leucocyte, the value of the ith molecular marker is 0And if not, the value of (2) is 1, otherwise, the value is 0.
6. The assessment model of claim 5, wherein the process of the assessment module for identifying bacterial meningitis from viral meningitis according to the meningitis score of the data analysis module comprises:
When the molecular marker consists of IL-2, IL-6, IL-8, IL-10, IL-17 and IFN-gamma, if the meningitis score is more than or equal to 8 points, outputting a judgment result as bacterial meningitis, and if the meningitis score is less than 8 points, outputting a judgment result as viral meningitis;
When the molecular marker consists of IL-6, IL-17, glucose, chloride ions, total cerebrospinal fluid protein and cerebrospinal fluid leucocytes, if the meningitis score is >9 points, outputting a judging result as bacterial meningitis, if the meningitis score is <9 points, outputting a judging result as viral meningitis, if the cerebrospinal fluid score is=9 points, adding a judging standard, judging IL-6 and IL-17 If the scores are simultaneously scored, outputting a judging result to be bacterial meningitis, and if the scores are not simultaneously scored, outputting a judging result to be viral meningitis.
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| BR102014004679B1 (en) * | 2014-02-27 | 2021-04-20 | Fundação Oswaldo Cruz | predictive method for differential diagnosis of meningitis in vitro, use of biomarker proteins, and, kit for differential diagnosis of meningitis to determine whether an individual has bacterial meningitis or viral meningitis |
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| CN105943048A (en) * | 2016-06-27 | 2016-09-21 | 首都医科大学附属北京胸科医院 | Method for distinguishing tubercular meningitis and virus meningitis based on nuclear magnetic resonance technology and application thereof |
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