WO2021123249A1 - Procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux - Google Patents

Procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux Download PDF

Info

Publication number
WO2021123249A1
WO2021123249A1 PCT/EP2020/087145 EP2020087145W WO2021123249A1 WO 2021123249 A1 WO2021123249 A1 WO 2021123249A1 EP 2020087145 W EP2020087145 W EP 2020087145W WO 2021123249 A1 WO2021123249 A1 WO 2021123249A1
Authority
WO
WIPO (PCT)
Prior art keywords
septic shock
expression
patient
level
patients
Prior art date
Application number
PCT/EP2020/087145
Other languages
English (en)
Inventor
Eduardo TAMAYO GÓMEZ
Emilio GARCÍA MORÁN
María HEREDIA RODRÍGUEZ
Esther GÓMEZ SÁNCHEZ
Pedro José MARTÍNEZ DE PAZ
Original Assignee
Gerencia Regional de Salud de Castilla y León
Universidad De Valladolid
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Gerencia Regional de Salud de Castilla y León, Universidad De Valladolid filed Critical Gerencia Regional de Salud de Castilla y León
Priority to ES202290051A priority Critical patent/ES2921224R1/es
Publication of WO2021123249A1 publication Critical patent/WO2021123249A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6854—Immunoglobulins
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6844—Nucleic acid amplification reactions
    • C12Q1/686—Polymerase chain reaction [PCR]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/26—Infectious diseases, e.g. generalised sepsis

Definitions

  • the present invention refers to the medical field. Particularly, the present invention refers to an in vitro method for the differential diagnosis between septic shock and non-septic shock patients or for deciding or recommending a treatment to a patient suffering from septic shock. Moreover, the present invention also includes kits adapted for the differential diagnosis between septic shock and non-septic shock, or for deciding or recommending a treatment to a patient suffering from septic shock.
  • Sepsis is defined as organ dysfunction caused by a dysregulated host response to infection.
  • this condition is one of the main healthcare problems in the intensive care unit, reaching to 300-480 cases per 100.000 people of incidence and leading the cause of mortality (20-30%) in the ICU of the developed countries.
  • sepsis incidence remains higher than cerebrovascular accident (76-119 per 100.000), acute myocardial infarction (8%) and other pathologies with important social impact, such as breast cancer (25.9-94.2 per 100.000) or AIDS (24 per 100.000).
  • sepsis is the first cause of mortality in non coronary ICUs, reaching the 30-50% of mortality in severe sepsis and 50-60% in septic shock.
  • PCT procalcitonin
  • CRP C-reactive protein
  • the present invention is focused on solving the above-mentioned problems and it is herein provided an in vitro method for the differential diagnosis between septic shock and non-septic shock patients or for deciding or recommending a treatment to a patient suffering from septic shock. Departing from this invention, it could be possible to get a rapid and accurate identification of septic shock patients, and their differentiation from those patients suffering from non-septic shock. This would help the clinicians to provide specific antibiotic treatment to patients suffering from septic shock, avoiding the inappropriate use of broad-spectrum antibiotics, mainly in those patients suffering from non-septic shock. DESCRIPTION OF THE INVENTION
  • the inventors of the present invention have developed a method for differentiating patients suffering from septic shock from those patients suffering from non-septic shock (i.e. shock of non-infectious origin).
  • any of the genes IGHG1 , LTF , OLFM4 , LCN2, MMP8 or IL1R2 , or any combinations thereof, can be used for the diagnosis of septic shock or for the differential diagnosis of septic shock versus non-septic shock.
  • the level of expression of IGHG1 is lower in patients suffering from septic shock as compared with control healthy subjects. Consequently, IGHG1 can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of IGHG1 is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, IGHG1 can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • the level of expression of IL1R2 is higher in patients suffering from septic shock as compared with control healthy subjects. Consequently, IL1R2 can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of IL1R2 is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, IL1R2 can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • LCN2 The level of expression of LCN2 is higher in patients suffering from septic shock as compared with control healthy subjects. Consequently, LCN2 can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of LCN2 is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, LCN2 can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • the level of expression of LTF is higher in patients suffering from septic shock as compared with control healthy subjects. Consequently, LTF can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of LTF is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, LTF can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • MMP8 The level of expression of MMP8 is higher in patients suffering from septic shock as compared with control healthy subjects. Consequently, MMP8 can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of MMP8 is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, MMP8 can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • the level of expression of OLFM4 is higher in patients suffering from septic shock as compared with control healthy subjects. Consequently, OLFM4 can be used as a biomarker for the diagnosis of septic shock. Moreover, the level of expression of OLFM4 is higher in patients suffering from septic shock, as compared with the level measured in non-septic shock patients. Consequently, OLFM4 can be used as a biomarker for the differential diagnosis of septic shock versus non-septic shock.
  • the combined use of six specifics genes gives rise to a multivariate regression model with an AUC of 0.841, thus showing a very good accuracy in the differentiation of patients suffering from septic shock from those patients suffering from non- septic shock.
  • the above cited six genes are combined with non-genetic biomarkers (NGB) like: sex, age, emergency surgery, neutrophils and bilirubin, the AUC is even higher (0.892), thus showing an improved accuracy in the differentiation of patients suffering from septic shock from those patients suffering from non-septic shock.
  • NGB * non-genetic biomarkers: sex+age+emergency surgery+neutrophils+bilimbin.
  • the first embodiment of the present invention refers to an in vitro method for the differential diagnosis between septic shock and non-septic shock patients which comprises: a) Measuring the level of expression of at least the gene IGHG1 in a biological sample obtained from the patient, and b) wherein the identification of a deviation of the expression level, preferably the identification of an increased level of expression of at least the gene IGHG1 in the patient with respect to level of expression measured in non-septic shock control patients used a reference, is an indication that the patient is suffering from septic shock.
  • the second embodiment of the present invention refers to an in vitro method for deciding or recommending a treatment to a patient suffering from septic shock which comprises: a) measuring the level of expression of at least the gene IGHG1 in a biological sample obtained from the patient, and b) wherein the identification of a deviation of the expression level, preferably the identification of a higher level of expression of at least the gene IGHG1 in the patient with respect to level of expression measured in non-septic shock patients used as reference, is indicative that the patient is suffering from septic shock and an anti-septic treatment is recommended.
  • the third embodiment of the present invention refers to an in vitro method for selecting patients suffering from septic shock for receiving an anti-septic treatment, which comprises: a) measuring the level of expression of at least the gene IGHG1 in a biological sample obtained from the patient, and b) wherein the identification of a higher level of expression of at least the gene IGHG1 in the patient with respect to level of expression measured in non-septic shock patients, the patient is elected for receiving an anti-septic treatment.
  • the sepsis treatment is based on pathophysiological therapy and life-sustaining treatment.
  • the pathophysiological therapy seeks different strategies that can modulate the battery of activated mediators.
  • substances like endotoxin antibodies, anti-TNF alpha antibodies, soluble TNF-alpha receptor or activated protein C could be used for conferring benefits in septic patients.
  • the real effective treatment is based on the life-sustaining treatment: early diagnosis of sepsis, control of the early infection, appropriate antibiotic treatment, hemodynamic resuscitation by objectives, protective pulmonary ventilation strategies, and finally, support the patient with a suitable nutritional intake.
  • the above-cited methods method further comprises: measuring the level of expression of at least one gene selected from the group comprising: a) LTF , OLFM4 , LCN2, MMP8 or IL1R2 in a biological sample obtained from the patient, and b) wherein the identification of a deviation (preferably an increase) of the expression level of at least one gene selected from the group comprising: LTF , OLFM4 , LCN2 , MMP8 or IL1R2 in the patient with respect to the level of expression measured in non-septic shock control patients, is indicative that the patient is suffering from septic shock.
  • the above-cited method comprises: a) measuring the level of expression of at least all the following genes: IGHG1 , LTF , OLFM4 , LCN2 , MMP8 and IL1R2 in a biological sample obtained from the patient, b) processing the expression level values in order to obtain a risk score value, and c) wherein if a deviation or variation of the risk score value obtained in step b) is identified, as compared with a reference risk score value measured in non- septic shock control patients, is indicative that the patient is suffering from septic shock.
  • the biological sample is blood, plasma or serum.
  • the fourth embodiment of the present invention refers to the in vitro use of at least the gene IGHG1 for the differential diagnosis between septic shock and non-septic shock, or for deciding or recommending a treatment to a septic shock patient.
  • the present invention also refers to the use of at least one gene selected from the group comprising: LTF , OLFM4 , LCN2, MMP8 or IL1R2 , preferably the use of the six genes in combination: IGHG1, LTF , OLFM4 , LCN2 , MMP8 and IL1R2.
  • the fifth embodiment of the present invention refers to a kit adapted for the differential diagnosis between septic shock and non-septic shock, or for deciding or recommending a treatment to a patient suffering from septic shock which comprises: a. Tools or reagents for obtaining blood samples from the patient, and b. Tools or reagents for measuring the level of expression of at least the gene IGHG1.
  • the kit further comprises tools or reagents for measuring the level of expression of at least one gene selected from the group comprising: LTF , OLFM4 , LCN2, MMP8 or IL1R2.
  • the kit further comprises tools or reagents for measuring the level of expression of at least all the following genes: IGHG1, LTF , OLFM4 , LCN2 , MMP8 and IL1R2.
  • the last embodiment of the present invention refers to an anti-septic therapy for use in the treatment of patients suffering from septic shock which have been previously diagnosed according to any of the above-described methods.
  • this embodiment refers to a method for treating septic-shock patients previously diagnosed with any of the above-cited methods.
  • the sepsis treatment is based on pathophysiological therapy and life- sustaining treatment.
  • the pathophysiological therapy seeks different strategies that can modulate the battery of activated mediators.
  • no active substances such as endotoxin antibodies, anti-TNF alpha antibodies, soluble TNF-alpha receptor or activated protein C, invoke unequivocal benefits in septic patients.
  • the real effective treatment is based on the life- sustaining treatment: early diagnosis of sepsis, control of the early infection, appropriate antibiotic treatment, hemodynamic resuscitation by objectives, protective pulmonary ventilation strategies, and finally, support the patient with a suitable nutritional intake.
  • control patient or “control subject” refers to a “reference value” of the expression level of the genes. If it is identified a deviation (increase or decrease) of the expression levels of the genes, as compared the expression level in said “control patient” or “control subject” which is used as a “reference value”, this is an indication that the patient is suffering from septic-shock.
  • a “reference value” can be a threshold value or a cut-off value. Typically, a “threshold value” or “cut-off value” can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by a person of ordinary skilled in the art. The threshold value must be determined to obtain the optimal sensitivity and specificity according to the function of the test and the benefit/risk balance (clinical consequences of false positive and false negative). Preferably, the person skilled in the art may compare the biomarker levels (or scores) obtained according to the method of the invention with a defined threshold value.
  • the optimal sensitivity and specificity can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data.
  • ROC Receiver Operating Characteristic
  • the full name of ROC curve is receiver operator characteristic curve, which is also known as receiver operation characteristic curve. It is mainly used for clinical biochemical diagnostic tests.
  • ROC curve is a comprehensive indicator that reflects the continuous variables of true positive rate (sensitivity) and false positive rate (1-specificity). It reveals the relationship between sensitivity and specificity with the image composition method.
  • a series of different cut-off values are set as continuous variables to calculate a series of sensitivity and specificity values. Then sensitivity is used as the vertical coordinate and specificity is used as the horizontal coordinate to draw a curve. The higher the area under the curve (AUC), the higher the accuracy of diagnosis.
  • AUC area under the curve
  • the point closest to the far upper left of the coordinate diagram is a critical point having both high sensitivity and high specificity values.
  • the AUC value of the ROC curve is between 1.0 and 0.5. When AUC>0.5, the diagnostic result gets better and better as AUC approaches 1. When AUC is between 0.5 and 0.7, the accuracy is low. When AUC is between 0.7 and 0.9, the accuracy is good.
  • shock refers to a life-threatening condition that occurs when the body is not getting enough blood flow. Lack of blood flow means the cells and organs do not get enough oxygen and nutrients to function properly. Many organs can be damaged as a result. Shock requires immediate treatment and can get worse very rapidly.
  • the main types of shock include: Cardiogenic shock (due to heart problems), hypovolemic shock (caused by too little blood volume), anaphylactic shock (caused by allergic reaction), septic shock (due to infections) and neurogenic shock (caused by damage to the nervous system).
  • non-septic shock refers to a life-threatening condition that occurs when the body is not getting enough blood flow, but it is not caused by an infection.
  • Non-septic shock due to heart problems
  • hypovolemic shock caused by too little blood volume
  • anaphylactic shock caused by allergic reaction
  • neurogenic shock caused by damage to the nervous system
  • risk score refers to a risk value obtained after processing one or more expression levels into a single value (or risk value), which represents the probability of disease for the individual. This risk value will be compared with a reference value to evaluate if the patient might be suffering from septic shock.
  • FIG. 1 Scatterplot of the first 2 principal components (PCI and PC2) obtained from the Principal Component Analysis performed on the 335 DE transcripts. PCA plot reveal three distinct patient groups.
  • B Volcano plot.
  • C Heat map plot from genes of interest ( LCN2 , IGHG3, IGHG2 , LTF , OLFM4 , IGHA /, IGHA2, MMP8 , and IL1R2). Row represents the gene expression value and column represents the sample. The colour conventions are as follows: green represents over-expressed transcripts and red indicates under-expressed transcripts; septic shock patients are represented by light blue and non-septic shock patients are represented by dark blue.
  • D Enriched biological functions.
  • FIG. 1 Relative mRNA levels of IGHG1 (A), IL1R2 (B), LCN2 (C), LTF (D), MMP8 (E), and OLFM4 (F) in non-septic shock and septic shock patients as measured by qRT-PCR with primers and reference genes as indicated in Materials and methods.
  • the horizontal line within the box indicates the median, the boundaries of the box indicate the 25th and 75th percentiles, and the whiskers indicate the highest and lowest values.
  • Figure 3 (A) ROC AUC analysis of gene expression.
  • FIG. 1 Relative mRNA levels of IGHG1 (A), IL1R2 (B), LCN2 (C), LTF (D), MMP8 (E), and OLFM4 (F) in non-septic shock and septic shock patients as measured by qRT-PCR with primers and reference genes as indicated in Materials and methods.
  • the horizontal line within the box indicates the median, the boundaries of the box indicate the 25th and 75th percentiles, and
  • FIG. 4 (A) ROC AUC analysis of gene expression regression model including sex, age, emergency surgery, neutrophils and bilirubin as adjust variables. (B) ROC AUC analysis of multivariate regression model that includes all gene expression and sex, age, emergency surgery, neutrophils and bilirubin as adjust variables.
  • Figure 6 It shows the regression model for each gene including new adjust variables.
  • FIG. 7 Comparison between the levels of expression of the genes IGHG1 , LTF , OLFM4 , LCN2, MMP8 or IL1R2 in control healthy subjects, septic shock patients and non-septic shock patients are identified with their statistical values. * indicate the p- alue between control and non-septic shock; # indicate the p-v alue between control and septic shock. Differences between 96 h and 24 h, super indexes ap ⁇ 0.05; bp ⁇ 0.01; cp ⁇ 0.001.
  • Example 1.1 Patient selection and clinical data.
  • Diagnosis of septic shock were established according to the definition of the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3 definition) and non-septic shock diagnosis criteria was the same of septic shock without infection. All research involving human participants was approved by the Scientific Committee for Clinical Research of Hospital Clinico Universitario de Valladolid and the patient or legal representative provided informed written consent before recruitment. This study followed the code of ethics of the World Medical Association (Declaration of Helsinki).
  • Example 1.2 Microbial diagnosis.
  • samples were routinely gram stained and cultured on general purpose media (blood agar, chocolate agar, and the differential media McConkey agar and Chapman agar) in the Microbiology Service from Hospital Clinico Universitario de Valladolid (Spain).
  • general purpose media blood agar, chocolate agar, and the differential media McConkey agar and Chapman agar
  • sputum samples were grown on Sabouraud agar containing chloramphenicol. Isolation of microorganisms or clinical suspicion of infection, without administration of antibiotics, was not considered as infection.
  • Example 1.3 Sample collection and RNA extraction.
  • Example 1.4 Microarray processing and data analysis.
  • RNA 100 pg of total RNA was used to produce cyanine 3-CTP-labelled cRNA using the Quick Amp Labelling kit (Agilent, USA) according to the manufacturer’s instructions. Following the One- Colour Microarray-Based Gene Expression Analysis Protocol Version 5.7 (Agilent, USA), 3 pg of labelled cRNA was hybridized with the Whole Human Genome Oligo Microarray Kit (Agilent, USA) containing 41,000 unique human genes and transcripts.
  • Arrays were scanned in an Agilent G2565BA Microarray Scanner System (Agilent, USA) according to the manufacturer’s protocol, and data were extracted using Agilent Feature Extraction Software 9.5.3 following the Agilent protocol GEl-v5_95_Feb07 and the QC Metric Set GEl_QCMT_Jan08.
  • Raw data files were imported into R-Bioconductor programming environment using the read.maimages from limma package. Repeat probes were aggregated by their median value. Preprocessing was continued by background correction. The normexp (‘saddle’) method was used with an offset value of 50. Normalization between the arrays was performed by quantile method.
  • the expression matrix was summarized for further analysis by the selection of top decile of probes in variance. Differential expression analysis was continued using the lmFit function from limma package in order to obtain logFold changes between the SS and SNS groups. Functional enrichment of most relevant genes was performed using GO-BP ontology.
  • the microarray dataset has been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE131761.
  • Example 1.5 Quantitative real-time Polymerase Chain Reaction (qRT-PCR).
  • qRT-PCR Quantitative real-time Polymerase Chain Reaction
  • qRT-PCR was performed on a CFX96 thermocycler (Bio-Rad) using PrimeTime® Gene Expression Master Mix, and the following cycling conditions: initial denaturation at 95°C for 3 min and 45 cycles of denaturation at 95°C for 15 s; annealing and elongation at 62°C for 15 s.
  • initial denaturation at 95°C for 3 min and 45 cycles of denaturation at 95°C for 15 s annealing and elongation at 62°C for 15 s.
  • the gene expression patterns of SS patients were compared with those observed in SNS patients after normalization with the actin gene, that was employed as the reference genes. Sequence of primers for selected genes are listed in Table 3. In the case of IGHG3 , IGHG2 , IGHA1 , and IGHA2 genes, a primer pair was designed to amplify all IgG classes.
  • the PCR amplification efficiency was established using calibration curves. For each gene, a standard curve based on five dilutions from an equimolar mix of cDNA samples was produced in triplicate to verify the amplification efficiency. Each sample was run in triplicate wells.
  • the cycle threshold (Ct) values were obtained with the Bio-Rad CFX Maestro software and converted to relative gene expression levels using the 2 DDa method.
  • Example 2.1 Patient characteristics.
  • the blood was the most common site of infection (37% for discovery cohort and 41% for validation cohort), followed by the respiratory tract (32% and 33%), abdomen (25% and 33%) and urinary tract (17% and 19%).
  • the most common microorganism isolated was Gram-negative bacteria (76% and 67%) followed by Gram-positive (65% and 62%) and fungi (29% and 27%).
  • Example 2.2 Identification of biomarker genes discriminating septic shock from non-septic shock patients.
  • Example 2.3 Validation of the biomarker genes in a validation cohort.
  • Example 2.4 Validation of the biomarker genes in a validation cohort.
  • the AUC were not as good as expected in order to differentiate the two patient categories: 0.598 (0.505-0.690) for PCT, 0.692 (0.598-0.786) for RCP and 0.613 (0.519- 0.707) for neutrophils (Figure 3B).
  • the AUC were better than AUC presented previously for all the biomarkers analyzed ( Figure 4).
  • Example 2.5 Improved results based on a new regression model.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Immunology (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Urology & Nephrology (AREA)
  • Hematology (AREA)
  • General Health & Medical Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Organic Chemistry (AREA)
  • Biotechnology (AREA)
  • Microbiology (AREA)
  • Biochemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • General Physics & Mathematics (AREA)
  • Pathology (AREA)
  • Medicinal Chemistry (AREA)
  • Zoology (AREA)
  • Cell Biology (AREA)
  • Wood Science & Technology (AREA)
  • Food Science & Technology (AREA)
  • Biophysics (AREA)
  • Genetics & Genomics (AREA)
  • General Engineering & Computer Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Retarders (AREA)

Abstract

La présente invention concerne un procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux. La présente invention concerne un procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux ou pour décider ou recommander un traitement à un patient souffrant de choc infectieux. De plus, la présente invention comprend également des kits conçus pour le diagnostic différentiel entre un choc infectieux et un choc non infectieux ou pour décider ou recommander un traitement à un patient souffrant de choc infectieux.
PCT/EP2020/087145 2019-12-20 2020-12-18 Procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux WO2021123249A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
ES202290051A ES2921224R1 (es) 2019-12-20 2020-12-18 Metodo in vitro para el diagnostico diferencial entre pacientes con shock septico y no septico

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP19383174.0 2019-12-20
EP19383174 2019-12-20

Publications (1)

Publication Number Publication Date
WO2021123249A1 true WO2021123249A1 (fr) 2021-06-24

Family

ID=69167586

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2020/087145 WO2021123249A1 (fr) 2019-12-20 2020-12-18 Procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux

Country Status (2)

Country Link
ES (1) ES2921224R1 (fr)
WO (1) WO2021123249A1 (fr)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090186034A1 (en) * 2006-12-19 2009-07-23 Genetech, Inc. Gene expression markers for inflammatory bowel disease
WO2013119869A1 (fr) * 2012-02-07 2013-08-15 Children's Hospital Medical Center Modèle de stratification des risques, fondé sur de multiples biomarqueurs, concernant l'issue d'un choc septique chez l'adulte
EP2796878A1 (fr) * 2008-05-23 2014-10-29 Biocartis NV Nouveaux biomarqueurs pour le diagnostic, la prédiction et/ou le pronostic d'une sepsie et ses utilisations
US20170356903A1 (en) * 2014-11-21 2017-12-14 Caris Science, Inc. Oligonucleotide probes and uses thereof
CN106093416B (zh) * 2016-05-18 2018-10-12 北京北方生物技术研究所有限公司 一种一步法检测降钙素原的试剂盒及其制备方法
WO2018220129A1 (fr) * 2017-05-31 2018-12-06 B.R.A.H.M.S Gmbh Mmp-8 en tant que marqueur pour identifier une maladie infectieuse

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090186034A1 (en) * 2006-12-19 2009-07-23 Genetech, Inc. Gene expression markers for inflammatory bowel disease
EP2796878A1 (fr) * 2008-05-23 2014-10-29 Biocartis NV Nouveaux biomarqueurs pour le diagnostic, la prédiction et/ou le pronostic d'une sepsie et ses utilisations
WO2013119869A1 (fr) * 2012-02-07 2013-08-15 Children's Hospital Medical Center Modèle de stratification des risques, fondé sur de multiples biomarqueurs, concernant l'issue d'un choc septique chez l'adulte
US20170356903A1 (en) * 2014-11-21 2017-12-14 Caris Science, Inc. Oligonucleotide probes and uses thereof
CN106093416B (zh) * 2016-05-18 2018-10-12 北京北方生物技术研究所有限公司 一种一步法检测降钙素原的试剂盒及其制备方法
WO2018220129A1 (fr) * 2017-05-31 2018-12-06 B.R.A.H.M.S Gmbh Mmp-8 en tant que marqueur pour identifier une maladie infectieuse

Also Published As

Publication number Publication date
ES2921224R1 (es) 2023-05-12
ES2921224A2 (es) 2022-08-22

Similar Documents

Publication Publication Date Title
US20200172978A1 (en) Apparatus, kits and methods for the prediction of onset of sepsis
AU2012261820B2 (en) Molecular diagnostic test for cancer
EP2925885A1 (fr) Essai de diagnostic moléculaire pour cancer
AU2012261820A1 (en) Molecular diagnostic test for cancer
WO2009115478A2 (fr) Procédé de détection et de différenciation in vitro d’états pathophysiologiques
Martínez-Paz et al. Distinguishing septic shock from non-septic shock in postsurgical patients using gene expression
US20190128878A1 (en) Methods for Categorizing and Treating Subjects at Risk for Pulmonary Exacerbation and Disease Progression
Almansa et al. Transcriptomic depression of immunological synapse as a signature of ventilator-associated pneumonia
WO2019175803A1 (fr) Procédé de prédiction de la progression d'une maladie de tuberculose active
CN114369656A (zh) 一种结核性脑膜炎辅助诊断分子标记物及其应用和试剂盒
WO2018146162A1 (fr) Biomarqueur moléculaire pour le pronostic de patients atteints de septicémie
WO2021073017A1 (fr) Application de la chimiokine ccl8 dans la préparation d'un réactif d'évaluation d'état et de pronostic associés à une dermatomyosite
WO2021123249A1 (fr) Procédé in vitro pour le diagnostic différentiel entre des patients souffrant de choc infectieux et des patients ne souffrant pas de choc infectieux
Xi et al. Patients with infectious diseases undergoing mechanical ventilation in the intensive care unit have better prognosis after receiving metagenomic next-generation sequencing assay
JP7392224B2 (ja) びまん性肺胞傷害型薬剤性間質性肺炎のｍｉＲＮＡ診断バイオマーカー
CN112481380B (zh) 一种评估晚期膀胱癌抗肿瘤免疫治疗反应性和预后生存的标志物及其应用
Liu et al. A multicenter study on clinical characteristics of Acinetobacter bacteremia in patients with liver cirrhosis
WO2017148951A1 (fr) Signature génétique pour le pronostic de la sécheresse oculaire
CN115605608A (zh) 帕金森氏病的检测方法
KR20200039654A (ko) 신장이식 환자의 급성거부반응 진단용 소변 전사체 및 이의 용도
CN112575078B (zh) lncRNAs作为活动性肺结核病特异性标志物的应用
Kasaras Future diagnostic of Sepsis: Biomarker miRSeps-5 manual vs robotic extraction and optimization of miRNA detection by Two-Tailed RT-qPCR technology
Wan et al. Potential clinical impact of metagenomic next-generation sequencing of plasma for cervical spine injury with sepsis in intensive care unit: a retrospective study
EP4060343A1 (fr) Procédé de diagnostic d'une infection à coronavirus
KR102561438B1 (ko) 뇌 아밀로이드 베타 축적 가능성을 예측하는 방법

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20835809

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20835809

Country of ref document: EP

Kind code of ref document: A1