WO2014081974A1 - Biomarqueurs pour la dengue et leur utilisation - Google Patents

Biomarqueurs pour la dengue et leur utilisation Download PDF

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WO2014081974A1
WO2014081974A1 PCT/US2013/071329 US2013071329W WO2014081974A1 WO 2014081974 A1 WO2014081974 A1 WO 2014081974A1 US 2013071329 W US2013071329 W US 2013071329W WO 2014081974 A1 WO2014081974 A1 WO 2014081974A1
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ifn
infection
saa
lymph
rantes
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PCT/US2013/071329
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Eng Eong Ooi
Steven R. Tannenbaum
Yadunanda Kumar BUDIGI
Yie Hou LEE
Vijaya B. Kolachalama
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Massachusetts Institute Of Technology
National University Of Singapore
The Charles Stark Draper Laboratory, Inc.
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Publication of WO2014081974A1 publication Critical patent/WO2014081974A1/fr

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    • 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
    • C12Q1/70—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving virus or bacteriophage
    • C12Q1/701—Specific hybridization probes
    • 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
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • 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
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • Viral infections such as Dengue causes a range of clinical conditions including Dengue Fever, Dengue Hemorrhagic Fever and Dengue Shock syndrome the latter of which are associated with significant human mortality. Aspects of the invention relate to evaluating Dengue virus infection.
  • the Dengue Virus causes a collection of illnesses ranging from mild Dengue
  • DHF Dengue Hemorrhagic fever
  • DSS Dengue Shock Syndrome
  • aspects of the disclosure relate to biomarker combinations that provide high sensitivity and/or specificity for Dengue fever classification.
  • biomarkers e.g., cytokines, serum proteins, protein adducts, and clinical features
  • biomarker panels that are clinically relevant (e.g., provide high specificity and/or sensitivity) for evaluating patients with Dengue fever infection to provide early classification of patients likely to develop DHF.
  • aspects of the invention relate to methods and devices for evaluating (e.g., identifying, assisting in identifying, diagnosing, assisting in diagnosing, triaging, or assisting in triaging) Dengue Fever infection in a subject.
  • the invention provides novel biomarkers useful for evaluating subjects at risk for developing or having developed DHF.
  • the invention provides kits and devices useful for evaluating subjects at risk for or having developed DHF.
  • the invention provides biomarkers, kits, and devices for use in evaluation of drug efficacy during clinical trials of potential drugs and vaccines for Dengue Virus.
  • the invention provides biomarkers, kits, and devices for use in epidemiological surveys of disease pathology of Dengue Virus.
  • the invention relates to a method, comprising:
  • the method further comprises managing treatment of the subject based on the identification of the subject as having developed or being at risk of developing DHF.
  • the managing treatment of a subject comprises hospitalization of the subject based on the identification of the subject as having developed or being at risk of developing DHF.
  • the biological sample is a blood or serum sample. In some embodiments, the biological sample is obtained from the subject less than about 72 hours after of onset of fever.
  • the invention relates to a method, comprising:
  • the 5 biomarkers selected from Table 11 are a 5 biomarker panel selected from Table 12, Table 13, and/or Table 14. In some
  • the determining the presence or absence of a statistically significant difference comprises performing a statistical test. In some embodiments, the method further comprises managing treatment of the subject based on the statistically significant difference. In some embodiments, the managing treatment of a subject comprises hospitalization of the subject based on the presence of the statistically significant difference.
  • the control levels are derived from patients with Dengue Fever (DF) who do not develop Dengue Hemorrhagic Fever (DHF). In some embodiments, the control levels are pre-determined.
  • the biological sample is a blood or serum sample. In some embodiments, the biological sample is obtained from the subject less than about 72 hours after of onset of fever.
  • the invention relates to a method, comprising determining the presence or absence of a statistically significant difference between levels of 5 biomarkers selected from Table 11 and control levels, wherein the presence of statistically significant difference is indicative of a subject having developed or being at risk of developing Dengue hemorrhagic fever (DHF).
  • the 5 biomarkers selected from Table 11 are a 5 biomarker panel selected from Table 12, Table 13, and/or Table 14.
  • the method further comprises identifying a subject having developed or being at risk of developing Dengue
  • determining the presence or absence of a statistically significant difference between levels of 5 biomarkers selected from Table 11 and control levels comprises measuring the levels of one or more biomarkers from a biological sample. In some embodiments, the determining the presence or absence of a statistically significant difference comprises performing a statistical test. In some embodiments, the method further comprises managing treatment of the subject based on the statistically significant difference. In some embodiments, the managing treatment of a subject comprises hospitalization of the subject based on the presence of the statistically significant difference. In some embodiments, the control levels are derived from patients with Dengue Fever (DF) who do not develop Dengue Hemorrhagic Fever (DHF). In some embodiments, the control levels are pre-determined. In some embodiments, the biological sample is a blood or serum sample. In some embodiments, the biological sample is obtained from the subject less than about 72 hours after of onset of fever.
  • DF Dengue Fever
  • DHF Dengue Hemorrhagic Fever
  • the invention relates to a method, comprising:
  • the method further comprises identifying a subject having developed or being at risk of developing Dengue hemorrhagic fever (DHF).
  • a) further comprises measuring the levels of one or more biomarkers from a biological sample.
  • the determining the presence or absence of a statistically significant difference comprises performing a statistical test. In some embodiments, the method further comprises managing treatment of the subject based on the statistically significant difference. In some embodiments, the managing treatment of a subject comprises hospitalization of the subject based on the presence of the statistically significant difference.
  • the control levels are derived from patients with Dengue Fever (DF) who do not develop Dengue Hemorrhagic Fever (DHF). In some embodiments, the control levels are pre-determined.
  • the biological sample is a blood or serum sample. In some embodiments, the biological sample is obtained from the subject less than about 72 hours after of onset of fever.
  • Some aspects of the invention relate to methods for evaluating (e.g., identifying, assisting in identifying, diagnosing, assisting in diagnosing, triaging, or assisting in triaging) a subject at risk of developing Dengue hemorrhagic fever (DHF) or having developed DHF.
  • the method comprises: a) measuring in a biological sample from a subject a level of one or more biomarkers selected from Table 1, Table 2, and/or Table 3; b) determining the presence or absence of a statistically significant difference between the level of one or more biomarkers and a control level; and c) identifying the subject as being having developed or being at risk of developing Dengue hemorrhagic fever (DHF) if the statistically significant difference is present.
  • DHF Dengue hemorrhagic fever
  • the method comprises determining whether a statistically significant difference exists between a level of one or more biomarkers selected from Table 1, Table 2, and/or Table 3 and a control level, wherein the presence of statistically significant difference is indicative of a subject having developed or being at risk of developing Dengue hemorrhagic fever (DHF).
  • the method comprises a) determining levels of one or more biomarkers selected from: Table 1, Table 2 and/or Table 3; and b) determining whether a statistically significant difference exists between the levels of one or more biomarkers and control levels, wherein the presence of statistically significant difference is indicative of a subject having developed or being at risk of developing Dengue hemorrhagic fever (DHF).
  • the one or more biomarkers further comprise white blood cell count (WBC), red blood cell count (RBC), blood hemoglobin (HGB), hematocrit (HCT), macrophage cell volume (MCV), mean corpuscular haemoglobin (MCH), Mean corpuscular hemoglobin concentration (MCHC), platelet count (PLT), lymphocyte percentage (LYMPH ), lymphocyte count (LYMPH), mixed cell distribution (MXD), neutrophil percentage (NEUT ), neutrophil count (NEUT), red blood cell distribution width-coefficient of variation (RDW-CV), and viral titers.
  • WBC white blood cell count
  • RBC red blood cell count
  • HGB blood hemoglobin
  • HCT hematocrit
  • MCV macrophage cell volume
  • MCV mean corpuscular haemoglobin
  • MHC mean corpuscular hemoglobin concentration
  • PHT lymphocyte percentage
  • LYMPH lymphocyte count
  • MXD mixed cell distribution
  • neutrophil percentage NEUT
  • NEUT neutrophil
  • control levels are derived from patients with Dengue Fever (DF) who do not develop Dengue Hemorrhagic Fever (DHF). In some embodiments, the control levels are pre-determined.
  • the biological sample is a blood or serum sample. In some embodiments, the levels are protein levels. In some embodiments, the protein levels are measure by an immuno-based assay.
  • the one or more biomarkers are two biomarkers. In some embodiments, the one or more biomarkers are three biomarkers. In some embodiments, the one or more biomarkers are four biomarkers.
  • the biological sample is obtained from the subject within about 72 hours of onset of fever (>38.0°C).
  • the method further comprises managing treatment of the subject based on the statistically significant difference.
  • the managing treatment of a subject comprises hospitalization of the subject based on the presence of the statistically significant difference.
  • the invention provides a kit or device for evaluating Dengue Fever infection.
  • the kit or device comprises one or more binding partners for one or more biomarkers selected from: Table 1, Table 2 and/or Table 3, wherein the one or more binding partners are attached to a surface.
  • the device generates an output that indicates that a subject has or is at risk for DHF.
  • the kit or device further comprises at least one control binding agent.
  • the surface comprises microfluidic channels.
  • the device is a dipstick.
  • the one or more binding partners are two binding partners.
  • the one or more binding partners are three binding partners.
  • the one or more binding partners are four binding partners.
  • the binding partner is an antibody.
  • Fig. 1 depicts graphs of clinical laboratory features and cytokine responses in primary dengue infections.
  • Fig. 2A and 2B shows graphs of cytokine profiles in dengue patients grouped by fever day.
  • the graphs Y-axis labels, from left to right and then top to bottom are: PDGF-BB, IL-lb, IL-5, IL-6, IL-9, IL-10, IL-17, Eoxtaxin, IFN-gamma, IP- 10, and RANTES.
  • the graphs Y-axis labels, from left to right and then top to bottom are: IL-lra, IL-4, IL-7, IL-8, IL-12, IL-13, FGF-basic, G-CSF, MCP-1, MIP-lb, and VEGF. All Y-axis values are pg/mL.
  • the bars in each graph in Figs. 2A and 2B are, from left to right: Healthy, Visit- 1, Visit-2, and Visit 3.
  • Fig. 3 depicts graphs of early cytokine responses in DF and DHF patients.
  • Fig. 4 shows a pie chart and graphs serum protein flux at different stages of dengue infections.
  • Fig. 5 depicts graphs of markers of macrophage and neutrophil activity in dengue patient sera.
  • Fig. 6 is a box diagram showing a community biomarker selection strategy for comprehensive evaluation of statistical performance of multiple algorithms.
  • Fig. 7 is a plot depicting multivariate statistics results for early classification of
  • Fig. 8 displays graphs of serum cytokine profiles on different days in dengue patients during early febrile, defervescence and convalescent stages of infection.
  • Fig. 9 is a series of graphs and a table.
  • Receiver operator characteristics (ROC) curves showing performance of Linear Discriminant Analysis (A), Ensemble Learning followed by Bootstrap Aggregation (B) and Logistic Regression (C). The performance characteristics of the ROC curves are shown as c- statistic, sensitivity and specificity of classification of DHF.
  • aspects of the invention relate to methods and devices for evaluating Dengue Virus infection and early prediction of DHF.
  • Other previous studies have attempted to develop methods for early prediction of DHF by statistical analysis of a variety of clinical laboratory indicators. For example, Potts et al reported a classification and regression tree (CART) analysis of clinical indicators from patient cohort of 1384 dengue-infected children in Thailand [45,46], while Tanner et al employed a decision tree algorithm in a 1200 patient cohort from Singapore and Vietnam [47]. Both these studies reported a subset of clinical variables that, when applied in a regression tree format, achieved high sensitivity but poor specificity.
  • CART classification and regression tree
  • cytokines such as IFN-gamma [19], IL-8[28], IL-6, TNF-a [29], MIP-lb [19], IL-10 [30], and free VEGF [23], in DHF patients compared with DF patients.
  • these studies have resulted in the widely held belief that onset of DHF is caused or accompanied by overproduction of certain cytokines with consequent pathology.
  • the study presented herein demonstrates that in some embodiments DHF is represented by a lack of or limitation in specific cytokine response pathways. Methods that rely on molecular measurements are likely to have a significant impact on diagnostic capabilities, via greater sensitivity and the possibility of
  • Dengue Virus causes a collection of human illnesses ranging from mild Dengue Fever (DF) to potentially lethal Dengue Hemorrhagic Fever (DHF) and Dengue Shock Syndrome (DSS). Viral transmission to humans occurs via the mosquito species of Aedes aegypti and Aedes albopictus. Dengue is endemic to tropical and sub-tropical regions of the world and with over 50-100 million annual cases of dengue infection. Dengue virus occurs in four distinct serotypes (DENV1-4) all of which can cause severe illnesses. A patient presenting symptoms such as fever, headache, muscle and joint pain, nausea and rashes may be exhibiting signs of DF.
  • thrombocytopenia ⁇ 100,000/dl
  • bleeding and plasma leakage are generally classified as DHF (1).
  • DHF thrombocytopenia
  • methods described herein are useful to determine whether a subject having symptoms of a Dengue virus infection is likely to develop severe DHF as opposed to having a self-limiting disease. In some embodiments, if the level of one or more markers described herein is indicative that a subject is more likely than not to develop severe DHF, then the subject is subsequently or immediately hospitalized. In some embodiments, if the level of one or more markers described herein is indicative that a subject is more likely than not to have a self-limiting form of Dengue, then the subject is not subsequently or immediately hospitalized.
  • a subject that is not hospitalized is monitored regularly (e.g., weekly, every 2-3 days, daily, more than once a day) to determine whether there are any indication that the infection is changing to a severe DHF.
  • the level of one or more markers described herein may be evaluated several times (e.g., weekly, every 2-3 days, daily, more than once a day) while a patient has other symptoms (e.g., a fever) associated with a Dengue virus infection.
  • one or more biomarkers described herein can be used to classify DHF and DF in subjects within about 72 hours of fever onset. This classification can be used to triage patients, e.g., by sending subjects suspected of having DHF to the hospital.
  • the Early Dengue (EDEN) initiative is a clinical cohort consisting of a prospective follow-up of confirmed Dengue infected individuals in Singapore, through early febrile, defervescence as well as convalescence stages [7].
  • the EDEN study combines the convenience of asynchronous patient recruitment during the early febrile phase, with individual patient follow-up, and was designed to specifically model adult dengue infections in Singapore [7].
  • a novel strategy for biomarker discovery have been developed using a robust clinical design by including patient serum samples from the EDEN study combined with the multidimensional analytical approach described herein.
  • a novel set of biomarkers has been identified and is described herein that can be used to classify DF and DHF patients with a sensitivity and specificity of >75 . Because this classification can be obtained from blood measurements within the first 72 hours of onset of febrile symptoms, they are likely to be clinically useful as 'predictors' .
  • the ability to classify patients as having DF or DHF can be used to identify subjects in need of further need of treatment, e.g., hospitalization.
  • biomarkers Additional analyses of this database of biomarkers, and including an additional biomarker "INFECTION", was performed by using statistical testing based on a test decision for the null hypothesis to reduce the large database to a shortlist of biomarkers that, in some embodiments, may form the foundation for biomarker panels that can be translated to clinical use.
  • the shortlist of 11 biomarkers is provided below in Table 11. It is to be understood that biomarkers other than the 11 provided below (e.g., other biomarkers provided in Tables 1-3) are also contemplated for use herein. In some embodiments, one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) biomarkers provided in Table 11 are contemplated for use herein.
  • biomarkers were analyzed using binary classification methods such as Logistic Regression, Linear Discriminant Analysis and Ensemble Learning, and it was determined that this shortlisted set of 11 biomarkers had a sensitivity of greater than 90% while maintaining specificity of greater than 70%.
  • a biomarker ranking approach was used to identify smaller panels of combinations of 5 biomarkers taken from the 11 biomarker shortlist. These smaller panels of 5 biomarkers, which are provided in Tables 12 to 14 are also contemplated for use herein.
  • the invention provides novel biomarkers useful for evaluating (e.g., identifying, assisting in identifying, diagnosing, assisting in diagnosing, triaging, or assisting in triaging) a subject with a disease caused by Dengue Virus, e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • the invention provides kits and devices useful for evaluating (e.g., identifying, assisting in identifying, diagnosing, assisting in diagnosing, triaging, or assisting in triaging) a subject with a disease caused by Dengue Virus, e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • the invention provides biomarkers, kits, and devices for use in evaluation of drug efficacy during clinical trials of potential drugs and vaccines for Dengue Virus. In yet another aspect, the invention provides biomarkers, kits, and devices for use in epidemiological surveys of disease pathology of Dengue Virus.
  • the invention provides methods for early identification or determination of subjects at risk for developing or having developed DHF.
  • early identification occurs at the early febrile phase (e.g., less than about 72 hours after onset of fever (>38.0°C)).
  • Biomarkers in some aspects, provides biomarkers for use in methods of evaluating (e.g., identifying, assisting in identifying, diagnosing, assisting in diagnosing, triaging, or assisting in triaging) a subject with a disease caused by Dengue Virus, e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • a disease caused by Dengue Virus e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • the methods described herein can be used alone or in combination with other risk factors in evaluating a subject.
  • a biomarker is any organic molecule, e.g., protein, DNA, RNA, adducts or any derivative thereof, or a biological entity, e.g., a cell or a virus, that can be used as an indicator of a disease state , e.g., Dengue Fever, Dengue Hemorrhagic Fever, or Dengue Shock Syndrome.
  • a disease state e.g., Dengue Fever, Dengue Hemorrhagic Fever, or Dengue Shock Syndrome.
  • examples of biomarkers include, but are not limited to, cytokines, serum proteins, protein adducts, and clinical features.
  • At least one biomarker is used for evaluating a disease in a subject caused by Dengue Virus, e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • Dengue Virus e.g., Dengue Fever, Dengue Hemorrhagic Fever, and Dengue Shock Syndrome.
  • more than one biomarker is used, e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 40, 50 or more biomarkers are used.
  • one type of biomarker is used, e.g., cytokines.
  • more than one type of biomarker is used. In other words combinations of different types of biomarkers are used.
  • Non-limiting examples of combinations of different types of biomarkers include: 1) Cytokines and serum proteins, 2) Cytokines and protein adducts, 3) Cytokines and clinical features, 4) Serum proteins and protein adducts, 5) Serum proteins and clinical features, 6) Protein adducts and clinical features, 7) Cytokines, serum proteins, and protein adducts, 8) Cytokines, serum proteins, and clinical features, 9) Cytokines, protein adducts, and clinical features, 10) Serum proteins, protein adducts, and clinical features, or 11) Cytokines, serum proteins, protein adducts, and clinical features. It is to be appreciated that for any of the combinations described above, one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10, or more) biomarkers for each type of biomarker can be used.
  • the biomarkers include at least one of (a-d): (a) IFN-gamma and/or ILlb, (b) SAA, (c) CT, and (d) LYMPH and/or VIREMIA. In some embodiments, the biomarkers include at least two of (a-d): (a) IFN-gamma and/or ILlb, (b) SAA, (c) CT, and (d) LYMPH and/or VIREMIA.
  • the biomarkers include at least three of (a-d): (a) IFN-gamma and/or ILlb, (b) SAA, (c) CT, and (d) LYMPH and/or VIREMIA.
  • the biomarkers include:(a) IFN-gamma and/or ILlb, (b) SAA, (c) CT, and (d) LYMPH and/or VIRAL TITERS.
  • the at least one biomarker is at least one cytokine selected from IFN-gamma and ILlb.
  • the at least one biomarker includes IFN-gamma and/or ILlb.
  • the at least one biomarker is SAA.
  • the at least one biomarker includes SAA.
  • the at least one biomarker includes IFN-gamma, ILlb and SAA.
  • the at least one biomarker includes IFN-gamma and SAA. In some embodiments, the at least one biomarker includes ILlb and SAA. In some embodiments, the at least one biomarker is IFN-gamma and SAA. In some embodiments, the at least one biomarker is ILlb and SAA. In some
  • the at least one biomarker is IFN-gamma, ILlb and SAA. In some embodiments, the at least one biomarker includes IFN-gamma, CT and SAA. In some embodiments, the at least one biomarker includes IL-lb, CT and SAA. In some embodiments, the at least one biomarker includes CT and SAA. In some embodiments, the at least one biomarker includes CT. In some embodiments, the at least one biomarker is CT. In some embodiments, the at least one biomarker is at least one clinical feature selected from LYMPH and VIREMIA. In some embodiments, the at least one biomarker includes LYMPH and/or VIREMIA.
  • the at least one biomarker includes or consists of any one combination or more than one combination of biomarkers disclosed in Table 9 or 10.
  • the levels of one or more biomarkers are measured from a biological sample collected at one time point.
  • the time point is less than about 72 hours after onset of a fever in the subject (>38.0°C).
  • the expression levels of one or more cytokines are measured from a biological sample collected at more than one time points (e.g., at less than about 72 hours after fever onset, at about 4-7 days after fever onset, and at about 3-4 weeks after fever onset).
  • the at least one biomarker includes one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) biomarkers provided in Table 11.
  • the at least one biomarker includes at least one biomarker from each class of biomarkers provided in Table 11 (e.g., at least one clinical feature, at least one cytokine, at least one serum protein, and at least one protein adduct).
  • the at least one biomarker comprises a 5 biomarker panel described in Tables 12, 13 and/or 14.
  • the at least one biomarker comprises a subset of (e.g., 2, 3, or 4) biomarkers from a 5 biomarker panel described in Tables 12, 13 and/or 14.
  • the at least one biomarker consists of a 5 biomarker panel described in Tables 12, 13 and/or 14.
  • the 5 biomarker panel is a 5 biomarker panel having a sensitivity of greater than 0.7 or greater than 0.8 as provided in Tables 12, 13 and/or 14, In some embodiments, the 5 biomarker panel is a 5 biomarker panel having a specificity of greater than 0.7 or greater than 0.8 as provided in Tables 12, 13 and/or 14. In some embodiments, the 5 biomarker panel is a 5 biomarker panel having a sensitivity and specificity of greater than 0.7 or greater than 0.8 as provided in Tables 12, 13 and/or 14.
  • the 5 biomarker panel is a 5 biomarker panel having a sensitivity of greater than 0.9 or greater than 0.95 as provided in Tables 12, 13 and/or 14. In some embodiments, the 5 biomarker panel is a 5 biomarker panel provided in Tables 12, 13 and/or 14 that does not include INFECTION.

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Abstract

L'invention concerne en partie des procédés d'évaluation de la dengue et de la dengue hémorragique. L'invention concerne également en partie des coffrets et des dispositifs pour ladite évaluation.
PCT/US2013/071329 2012-11-21 2013-11-21 Biomarqueurs pour la dengue et leur utilisation WO2014081974A1 (fr)

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WO2017066538A1 (fr) * 2015-10-14 2017-04-20 Massachusetts Institute Of Technology Combinaison de sérotonine et d'une cytokine comme prédicteur pronostique précoce de la dengue grave

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US20090325167A1 (en) * 2003-09-15 2009-12-31 Board Of Regents Of The University Of Oklahoma Method of using cytokine assay to diagnose, treat, and evaluate inflammatory and autoimmune diseases
WO2010043973A2 (fr) * 2008-10-14 2010-04-22 The Royal Institution For The Advancement Of Learning/Mcgill University Biomarqueurs de la dengue biomarkers for dengue
US20130004473A1 (en) * 2011-06-06 2013-01-03 The Board Of Regents Of The University Of Texas System Methods and Biomarkers for the Detection of Dengue Hemorrhagic Fever

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Publication number Priority date Publication date Assignee Title
US20090325167A1 (en) * 2003-09-15 2009-12-31 Board Of Regents Of The University Of Oklahoma Method of using cytokine assay to diagnose, treat, and evaluate inflammatory and autoimmune diseases
WO2010043973A2 (fr) * 2008-10-14 2010-04-22 The Royal Institution For The Advancement Of Learning/Mcgill University Biomarqueurs de la dengue biomarkers for dengue
US20130004473A1 (en) * 2011-06-06 2013-01-03 The Board Of Regents Of The University Of Texas System Methods and Biomarkers for the Detection of Dengue Hemorrhagic Fever

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017066538A1 (fr) * 2015-10-14 2017-04-20 Massachusetts Institute Of Technology Combinaison de sérotonine et d'une cytokine comme prédicteur pronostique précoce de la dengue grave

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