WO2024037387A1

WO2024037387A1 - Blood biomarkers and methods for diagnosis of acute kawasaki disease

Info

Publication number: WO2024037387A1
Application number: PCT/CN2023/111855
Authority: WO
Inventors: Limin Chen
Original assignee: Tianjin Yunjian Medical Technology Co., Ltd.; Tianjin Yunjian Medical Device Co., Ltd.
Priority date: 2022-08-19
Filing date: 2023-08-09
Publication date: 2024-02-22
Also published as: CN116773825A; CN116773825B

Abstract

Blood biomarkers combination and characterization methods can be used to diagnose Kawasaki disease (KD) in clinical setting. In particular, the combination of biomarkers and their body fluid concentration can be used to derive a KD score for aiding diagnosis, risk evaluation, and the treatment/monitoring of KD. More specifically, these biomarkers characterizing reagents will be packaged in a kit in conjunction with a testing system e.g. Luminex xMAP that measures biomarker concentrations to generate KD scores that can be used to distinguish KD from other febrile pediatric indications.

Description

Blood biomarkers and methods for diagnosis of acute Kawasaki disease

Technical Field

The present invention pertains to biomarkers combination and characterization methods for the diagnosis of Kawasaki disease (KD) in a clinical setting. In particular, the invention claims the use of the combination of biomarkers and their concentration to derive a KD score for aiding diagnosis, risk evaluation, and the treatment/monitoring of KD. More specifically, these biomarkers characterizing reagents will be packaged in a kit in conjunction with a testing system e.g. Luminex xMAP that measures biomarker concentrations to generate KD scores that can be used to distinguish KD from other febrile pediatric indications.

Background Art

Kawasaki Disease (KD) is a rare childhood acute inflammatory disorder associated with vasculitis and persistent fever. KD is the leading cause of acquired heart disease in children in the United States and increasing significantly in developing countries.(1,2) If not treated early, serious complications can occur, with approximately 25% of children suffering coronary artery damage.(3,4) Death is rare; however, stenotic lesions can develop later due to vascular remodeling of the damaged artery. Long-term outcome studies have shown that 50% of children who suffered initial coronary artery aneurysms due to KD required revascularization surgery or were at high risk of myocardial infarction.(5-8)

The etiology of KD is currently unknown. However, it is widely believed to be an abnormal and sustained immune response to infectious agents in specific genetically predisposed individuals.(9) Unfortunately, no consistent infectious agent has been identified to date, further increasing diagnostic difficulties. In addition, different ethnic distributions of KD are also observed. KD has the highest incident rate in east Asia, affecting 1 in 150 children in Japan,(10) and it is responsible for approximately 1-2% of pediatric hospitalization in South Korea.(11) KD is significantly lower in the Caucasian population with an incident rate of 9-17/100,000,(12,13) versus the Japanese incident rate of 265/100,000 for children < 5 years of age.(14) The average incident rate in other Asian countries is 51-194/100,000.(11,15,16)

Currently, the diagnosis of KD is primarily by clinical symptoms,(3) with no objective molecular test available aiding the process today. Clinical diagnosis is difficult because KD shares many symptoms and features of common self-resolving febrile illnesses of childhood, such as fever, rash, mucocutaneous manifestations, lymphadenopathy, and inflammation.(17) Approximately 15 to 36.2% of KD cases are considered incomplete KD and do not display complete clinical features, greater than four KD clinical signs, according to American Heart Association, significantly contributing to delayed diagnosis.(18-21) Delayed diagnosis of KD increases the risk of permanent cardiac damage and coronary artery aneurysms.(22) Time to diagnosis is crucial for patients who exhibit "incomplete" KD and do not meet the full clinical criteria. Early diagnosis and treatment with intravenous immunoglobulin (IVIG) are highly effective at reducing incidents of coronary artery disease within ten days of fever onset.(23)

Timely recognition, diagnosis, and treatment are often challenging for many clinicians. Following the published guidelines to diagnose KD based on persistent fever and clinical criteria by physicians unfamiliar or confused by the complex clinical algorithms, KD clinical diagnoses are often delayed.(20,22) In addition, there is currently no clinically helpful and easily accessible objective molecular biomarker test to assist physicians in diagnosing KD. Thus, an objective blood biomarker-based test is urgently needed to aid the physician in identifying KD patients who do not meet all clinical criteria but require treatment to prevent cardiovascular damage.

We investigated seventeen biomarkers involving myocardial dysfunction or stress (NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1), cardiac ischemia and plaque instability/rupture (FABP3 and LIGHT (TNFSF14)), inflammation (CXCL6, CXCL16, ST2 (IL1RL1), FABP4, and Oncostatin M), cellular growth and migration (MMP-8, and MMP-9, HGF, and VEGFA), which have been associated with development and diagnosis of KD (Figure 1). Using the multiplex immune assay platform by Luminex, we determined the concentration of these analytes in plasma samples. A KD diagnostic model was then developed based on the serological concentrations of key biomarkers capable of discriminating KD from other febrile patients.

SUMMARY OF THE INVENTION

This invention discloses the use of blood/plasma/serum protein biomarkers for the diagnosis, risk evaluation, and treatment monitoring of KD. In particular, the inventors have discovered and enabled using a panel of protein biomarkers blood concentration to calculate a KD risk score that can be used for the diagnosis, risk assessment, and monitoring treatment of KD and to distinguish KD from other febrile diseases. The biomarkers can be determined using a kit with the appropriate assay system, such as the Luminex platform system, to determine biomarker concentrations to derive a KD score that can be used alone or combined with additional KD clinical criteria to rule in and confirm KD diagnosis.

Protein biomarkers concentration such as but not limited to NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1, FABP3, LIGHT (TNFSF14), CXCL6, CXCL16, ST2 (IL1RL1), FABP4, and Oncostatin M, VEGFA, HGF, MMP-8, and MMP-9, which have been associated with development and diagnosis of KD in combination presented in the blood/plasma/serum were discovered to be able to separate KD patients from other febrile patients utilizing multiplex immune-based assay system (e.g. Luminex) to accurately measure blood biomarker concentrations to dervie a KD score. The biomarker analytes include but are not limited NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1, FABP3, LIGHT (TNFSF14), CXCL6, CXCL16, ST2 (IL1RL1), FABP4, and Oncostatin M, VEGFA, HGF, MMP-8, and MMP-9 which have been associated with development and diagnosis of KD (Figure 1).

The present invention discloses a method using biomarkers that can be used in the practice of the invention, including protein biomarkers in whole or peptide sequences from the biomarkers, including, but not limited to, NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT, OSM, and ST2.

In certain embodiments, a panel of these biomarker combinations is used to diagnose KD. Biomarker panels for KD diagnosis can comprise a minimum of 2 biomarkers and up to the full panel of 8 biomarkers from above. This will include any combination of the biomarkers described above comprising at least 2, 3, 4, 5, 6, 7, and 8 biomarkers. Smaller biomarker panels are sufficient to discriminate KD from other febrile diseases and are more economical. However, a larger panel will likely provide more detailed information and can be used in the practice of the invention in different regional population groups.

In a binary scoring system, a method based on calculating a KD score to distinguish patients from other febrile diseases. A low KD score indicates that a patient is unlikely to have KD. A high KD score indicates that a patient will likely have KD (rule in).

A method based on the above biomarkers and method description to calculate a KD score and determines the risk of having KD at three different ranges to determine the risk of having KD. A low KD risk below the low score cut-off indicates that a patient is at a low-risk for KD. A high KD risk above the high score cut-off indicates that a patient is at high risk for KD. A score between the low and high KD score cut-off suggests an intermediate KD risk.

In some instances, clinical parameters are used for the diagnosis of KD in combination with the biomarkers described herein. In one example, the invention includes a method for determining a KD score for a patient suspected of having KD having 5 days of continuous fever. The method comprises measuring a minimum of seven clinical parameters according to the standard of care for the patient, including duration of fever, the concentration of hemoglobin in the blood, concentration of C-reactive protein in the blood, white blood cell count, percent eosinophils in the blood, percent monocytes in the blood, and percent immature neutrophils in the blood.

The KD score can be calculated via geometric means, multivariate linear discriminant analysis (LDA) or distributed gradient-boosted decision tree (GBDT) machine learning such as XGBoost from the values of the blood biomarkers measured. In a binary model, receiver operating characteristic (ROC) curves can be derived from the blood biomarker combination. A perfect test that yields no fa The KD score can then be classified as a low-risk KD clinical score, an intermediate risk KD clinical score, or a high-risk KD clinical score by methods described herein.

In another aspect, the invention includes the method and procedures for diagnosing KD in a patient using the biomarker panels and methods to calculate KD scores described herein. The method comprises 1) obtaining a biological sample from the patient, 2) measuring the blood concentration of each biomarker in the biological sample, and 3) comparing the levels of each biomarker with respective reference value ranges for the biomarkers. The reference value ranges can represent the levels of the biomarkers for one or more samples from subjects without KD (i.e., normal samples), or levels of the biomarkers for one or more samples from one or more subjects with KD. Differential levels of the blood biomarkers of the biomarker panel in the biological sample compared to reference values of the biomarkers for a control subject indicates that the patient has KD. In one embodiment, the method further comprises the way to calculate KD scores to distinguish a diagnosis of KD from febrile illness in the patient.

Blood biomarkers can be measured using specific antibodies and reporting system to determine the concentration of biomarkers from described above. For example, but not limited to, perform an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (IFA), immunohistochemistry (IHC), a sandwich assay, magnetic capture, microsphere capture, a Western Blot, Surface-enhanced Raman spectroscopy (SERS), flow cytometry, or mass spectrometry to determine the blood concentration of these biomarkers. In certain embodiments, the amount of a biomarker is measured from the binding of a specific antibody with the biomarker, wherein the antibody specifically binds to the entire biomarker, or a fragment, an antigenic determinant, of the biomarker. Antibodies that can be used in the practice of the invention include, but are not limited to, monoclonal antibodies, polyclonal antibodies, chimeric antibodies, recombinant fragments of antibodies, Fab fragments, Fab' fragments, F(ab')2 fragments, Ffragments, or scF fragments.

The invention also includes a method for evaluating the efficacy of an intervention agent for treating KD in a patient. The method comprises: analyzing the concentrations of each blood biomarker of the panel in samples derived from the patient before and after the patient is treated using a biomarker panel described herein. The effectiveness of the treatment can be determined in conjunction with respective reference value ranges of biomarkers and calculated KD scores.

In particular, the invention includes a method of selecting a patient suspected of having KD for the treatment with an intravenous immunoglobulin (IVIG), the process comprising: 1) diagnosing the patient according to the method described herein, and b) selecting the patient for the administration of IVIG if the patient has a positive KD diagnosis. In another embodiment, the method comprises 1) determining the KD score of the patient and b) selecting the patient for IVIG administration if the patient has a KD score in the high-risk range or the intermediate risk range and a positive KD diagnosis based on the expression profile of a biomarker panel comprising from the description above.

In another case, the invention includes a method of treating a patient suspected of having KD, the process comprising: 1) diagnosing the patient or receiving information regarding the diagnosis of the patient according to a method described herein; and 2) treating with a therapeutically effective amount of intravenous immunoglobulin (IVIG) to the patient if the patient has a positive KD diagnosis. In one aspect, the method comprises 1) determining the KD clinical score of the patient; and 2) administering a therapeutically effective amount of intravenous immune globulin (IVIG) to the subject if the subject has a high-risk KD clinical score or an intermediate risk KD clinical score and a positive KD diagnosis based on the expression profile of a biomarker panel from above paragraphs.

In another aspect, the invention includes a kit for the use in a multiplex immune-based system i.e. Luminex xMAP system for measuring biomarkers in body fluids. The kit may include a container for holding a biological sample collected and isolated from a human patient suspected of having KD. The kit contains of at least one agent for measuring a KD biomarker and printed instructions for reacting the reagent with the biological sample or a portion of the biological sample to measure at least one KD biomarker in the biological sample. The reagents may be packaged in a separate container. The kit may further comprise one or more control reference samples and reagents for performing an immunoassay for detecting biomarkers, as described herein.

In another aspect, the invention includes an assay comprising: a) measuring each biomarker concentration of a biomarker panel, described herein, in blood, plasma, or serum sample collected from a patient suspected of having KD; and b) comparing the measured value of each biomarker of the biomarker panel in the blood, plasma, or serum sample with the reference values for each biomarker for a control subject, wherein differential expression of the biomarkers in the blood, plasma, or serum sample compared to the reference values indicate that the patient has KD. In one aspect, the assay further comprises determining a KD score from these biomarker concentrations of the patient.

In certain cases, measuring at least one biomarker by an antibody targets the biomarker, wherein the antibody specifically binds to the biomarker, or a fragment of the biomarker thereof containing an antigenic determinant of the biomarker. In certain embodiments, the antibody is selected from the group consisting of a monoclonal antibody, a polyclonal antibody, a chimeric antibody, a recombinant fragment of an antibody, an Fab fragment, an Fab' fragment, an F(ab') fragment, an F fragment, and an sch, fragment. In one case, at least one antibody is selected from the group consisting of an antibody that specifically binds to NT-ProBNP, an antibody that specifically binds to FABP4, an antibody that specifically binds to MMP8, an antibody that specifically binds to CXCL16, an antibody that specifically binds to HGF, an antibody that specifically binds to LIGHT, an antibody that specifically binds to OSM, and an antibody that specifically binds to ST2.

These and other embodiments of the subject invention will readily occur to those of skill in the art in view of the disclosure herein.

Brief Description Of The Drawings

The invention is best understood from the following detailed description when read in conjunction with the accompanying tables and figures. The patent or application file contains at least one drawing. Copies of this patent or patent application publication with drawing(s) will be provided by the Office upon request and payment of the necessary fee. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures.

Table 1a. Patient demographic information. The KD patients are slight younger than the febrile controls. b. Summary of KD signs of the studied cohort.

Table 2. Seventeen biomarkers were investigated using Luminex multiplex immune assay. The biomarkers are ranked from top to bottom based on AUC under the receiver operating characteristic curve based on univariant analysis.

Figure 1. Kawasaki Disease serological biomarker discovery and validation process. Potential serological biomarkers were initially identified via GEO analysis, pathway discovery, and serum protein data bank. Major phenotypic pathways were initially identified, and analytes from associated pathways were further included in the Luminex discovery panel.

Figure 2a. The panel is constructed based on the geometric means of the top four analytes. The serological concentration of each biomarkers was measured using Luminex multiplex antigen assay. b. The model achieved AUC of 0.946 based on ROC analysis with an optimal cutoff of 3.274. c. The overall performance of the model.

Figure 3a. A two threshold and the three-risk level scoring model separate the cohort population into high-risk, intermediate, and low-risk groups. b. The classification of the cohort population is based on the risk scoring system. c. The high-risk PPV achieves 86.4% PPV at the optimal cutoff of 3.47, and the low-risk patient population below 3.17 risk score has an NPV of 94.2%.

Figure 4. Coronary Zscore is classified based on the KD risk classification. Our panel captures the majority of aneurysm cases. KD patients with normal or dilated coronary arteries were also identified by the panel.

Detailed Description

Kawasaki disease (KD) biomarkers, KD biomarker panels, and methods for obtaining a KD biomarker level representation for a sample are provided. These compositions and methods find use in a number of applications, including, for example, diagnosing KD, risk assessement for KD, monitoring treatment for a subject with KD, and determining a neccessity of therapy for KD. In addition, systems, devices, and kits thereof that find use in practicing the subject methods are provided. These and other objects, advantages, and features of the invention will become apparent to those skilled in the art upon reading the details of the compositions and methods as described below.

Before the present methods and compositions are described, it is to be understood that this invention is not limited to the particular method or composition described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.

It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and reference to "the peptide" includes reference to one or more peptides and equivalents thereof, e.g. polypeptides, known to those skilled in the art, and so forth.

As summarized above, aspects of the subject invention include methods, compositions, systems (i.e. Luminex xMAP), and kits that find use in providing a KD assessment, e.g. diagnosing, risk assessement, monitoring, and/or treatment decision of KD in a subject. By "Kawasaki disease" or "KD" it is meant a multisystem inflammation and complication of febrile sickness that may be accompanied by one or more of rash, swelling of the hands and feet (edema), irritation and redness of the whites of the eyes, swollen lymph glands in the neck, and irritation and inflammation of the mouth, lips, and throat. KD primarily occurs in children younger than 5 years of age, but older children, teenagers, and adults can still acquire KD. If unaddressed within 10 days of fever onset, KD can lead to cardiac vascular disease and aneurism. By "diagnosing" a KD or "providing a KD diagnosis," it is generally meant providing a KD determination, e.g. a determination as to whether a subject (e.g. a subject that has clinical symptoms of KD, either complete or incomplete KDs) is presently affected by KD; a classification of the subject's KD into a subtype of the disease or disorder; a determination of the severity of KD; and the like. By “risk assessemnnt” for KD, or "providing a KD risk socre as one of the clinical signs," it is generally meant providing a KD prediction as an additional clinical sign, e.g. a diagnosis of a subject's susceptibility, or risk, of having KD in the presence of other clinical symptoms; a prediction of the course of disease progression and/or disease outcome, e.g. confirm the diagnosis of the KD and incomplete KD; a prediction of a subject's responsiveness to treatment for the KD, e.g., positive response, a negative response, no response at all; and the like. By "monitoring" a KD, it generally means monitoring a subject's condition, e.g. to inform a KD diagnosis, to inform a KD prognosis/risk together with other clinical signs, to provide information as to the effect or efficacy of a KD treatment, and the like. By "treating" a KD it is meant prescribing or providing any therapy of a KD in a mammal and includes: (a) preventing the KD and related cardiac vascular events from occurring in a subject who may be predisposed to KD but has not yet been diagnosed as having it; (b) inhibiting the KD and cardiac events, i.e., arresting its symptoms and cardiac aneurysm development; or (c) relieving the KD, i.e., causing regression of the KD and lower of cardiac aneurysm risk.

In describing the subject invention, compositions useful for providing a KD assessment will be described first, followed by methods, systems, and kits for their use.

Kawasaki biomarkers and panels

In some aspects of the invention, KD biomarkers and panels of KD biomarkers are provided. By a "KD biomarker," it is meant to be a molecular entity whose representation in a sample is associated with a KD phenotype. For example, a KD biomarker may be differentially represented, i.e. represented at a different level, in a sample from an individual that will develop or has developed KD as compared to a healthy individual. In some instances, an elevated level of the biomarker such NT-proBNP is associated with the KD phenotype. For example, the concentration of biomarker in a sample may be 1.5- fold, 2-fold, 2.5-fold, 3-fold, 4-fold, 5-fold, 7.5-fold, 10-fold, or greater in a sample associated with the KD phenotype than in a sample not associated with the KD phenotype. In other instances, a reduced level of the biomarker is associated with the KD phenotype such as VEGFA. For example, the concentration of the biomarker in a sample may be 10% less, 20% less, 30% less, 40% less, 50% less, or more in a sample associated with the KD phenotype than in a sample not associated with the KD phenotype.

KD biomarkers may include proteins and peptides associated with KD and their corresponding genetic sequences, i.e. mRNA, DNA, etc. By a "gene" or "recombinant gene" it is meant a nucleic acid comprising an open reading frame that encodes for the protein.

The boundaries of a coding sequence are determined by a start codon at the 5' (amino) terminus and a translation stop codon at the 3' (carboxy) terminus. A transcription termination sequence may be located 3' to the coding sequence. In addition, a gene may optionally include its natural promoter (i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell, i.e., a naturally occurring cell), and associated regulatory sequences, and may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation signals, translational start and stop sequences, ribosome binding sites, and the like.

As demonstrated in the examples of the present disclosure, the inventors have identified a number of molecular entities that are associated with KD and that find use in combination (i.e. as a panel) in providing a KD risk assessment, e.g. diagnosing KD, risk assessemnt of having KD, monitoring a subject with KD, determining to treat for a subject affected with KD, and the like. These include but are not limited to NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).

As mentioned above, also provided herein are KD panels. By a “panel” of KD biomarkers it is meant two or more KD biomarkers, e.g. 2 or more, 3 or more, or 4 or more biomarkers, whose levels, when considered in combination, find use in providing a KD assessment, e.g. making a KD diagnosis, prognosis, monitoring, and/or treatment. Of particular interest are panels that comprise the KD biomarker NTproBNP, FABP4, MMP-8, CXCL16, HGF. For example, in some embodiments, the KD panel may comprise NTproBNP, FABP4, MMP-8, and CXCL16.

Other combinations of KD biomarkers that find use as KD panels in the subject methods may be readily identified by the ordinarily skilled artisan using any convenient statistical methodology, e.g. as known in the art or described in the working examples herein. For example, the panel of analytes may be selected by combining genetic algorithm (GA) and all paired (AP) support vector machine (SVM) methods for KD classification analysis. Predictive features are automatically determined, e.g. through iterative GA/SVM, leading to very compact sets of non-redundant KD-relevant analytes with the optimal classification performance. While different classifier sets will typically harbor only modest overlapping gene features, they will have similar levels of accuracy in providing a KD assessment to those described above and in the working examples herein.

Methods

In some aspects of the invention, methods are provided for obtaining a KD biomarker level representation for a subject. By a KD biomarker level representation, it is meant a representation of the levels of one or more of the subject KD biomarker(s), e.g. a panel of KD biomarkers, in a biological sample from a subject. The term "biological sample" encompasses a variety of sample types obtained from an organism and can be used in a diagnostic, prognostic, or monitoring assay. The term encompasses blood and other liquid samples of biological origin or cells derived therefrom and the progeny thereof. The term encompasses samples that have been manipulated in any way after their procurement, such as by treatment with reagents, solubilization, or enrichment for certain components. The term encompasses a clinical sample, and also includes cell supernatants, cell lysates, serum, plasma, biological fluids, and tissue samples. Clinical samples for use in the methods of the invention may be obtained from a variety of sources, particularly blood samples.

Sample sources of particular interest include blood samples or preparations thereof, e.g., whole blood, or serum, or plasma. In many embodiments, a suitable initial source for the human sample is a blood sample. As such, the sample employed in the subject assays is generally a blood-derived sample. The blood-derived sample may be derived from whole blood or a fraction thereof, e.g., serum, plasma, etc., where in some embodiments, the sample is derived from blood, allowed to clot, and the serum separated and collected to be used to assay.

In some embodiments, the sample is a serum or serum-derived sample. Any convenient methodology for producing a fluid serum sample may be employed. In many embodiments, the method uses drawing venous blood by skin puncture (e.g., finger stick, venipuncture) into clotting or serum separator tube, allowing the blood to clot, and centrifuging the serum away from the clotted blood. The serum is then collected and stored until assayed. Once the patient-derived sample is obtained, the sample is assayed to determine the level of KD biomarker(s).

The subject sample is typically obtained from the individual during the clinical visit when the patient has continuous and recurring fevers. KD most likely occurs in children under five, but it could happen at any age, including teenagers and adults.

Once a sample is obtained, it can be used directly, frozen, or maintained in an appropriate culture medium for short periods of time. Typically the samples will be from human patients, although animal models may find use, e.g. equine, bovine, porcine, canine, feline, rodent, e.g. mice, rats, hamster, primate, etc. Any convenient tissue sample that demonstrates the differential representation in a patient with KD of the one or more KD biomarkers disclosed herein may be evaluated in the subject methods. Typically, a suitable sample source will be derived from fluids into which the molecular entity of interest can be analyzed, i.e. the protein, the peptide, and the RNA has been released.

The subject sample may be treated in a variety of ways so as to enhance the detection of one or more KD biomarkers. For example, where the sample is blood, the red blood cells may be removed from the sample (e.g., by centrifugation) prior to assaying. Such a treatment may serve to reduce the non-specific background levels of detecting the level of a KD biomarker using an affinity reagent. Detection of a KD biomarker may also be enhanced by concentrating the sample using procedures well known in the art (e.g. acid precipitation, alcohol precipitation, salt precipitation, hydrophobic precipitation, filtration. In some embodiments, the pH of the test and control samples will be adjusted to, and maintained at, a pH that approximates neutrality. Such a pH adjustment will prevent complex formation, thereby providing a more accurate quantitation of the level of the biomarker in the sample. In embodiments where the sample is urine, the pH of the sample is adjusted, and the sample is concentrated in order to enhance the detection of the biomarker.

In practicing the subject methods, the level(s) of KD biomarker(s) in the biological sample from an individual are evaluated. The level of one or more KD biomarkers in the subject sample may be evaluated by any convenient method. For example, protein biomarkers may be detected by measuring the levels/amounts of one or more proteins/polypeptides. KD gene expression levels may be detected by measuring the levels/amounts of one or more nucleic acid transcripts, e.g. mRNAs, of one or more KD genes. The terms “evaluating”, “assaying”, “measuring”, “assessing,” and "determining" are used interchangeably to refer to any form of measurement, including determining if an element is present or not, and including both quantitative and qualitative determinations. Evaluating may be relative or absolute.

For example, the level of at least one KD biomarker may be evaluated by detecting in a sample the amount or level of one or more proteins/polypeptides or fragments thereof to arrive at a protein level representation. The terms "protein" and "polypeptide" as used in this application are interchangeable. "Polypeptide" refers to a polymer of amino acids (amino acid sequence) and does not refer to a specific length of the molecule. Thus peptides and oligopeptides are included within the definition of polypeptides. This term also refers to or includes post-translationally modified polypeptides, for example, glycosylated polypeptide, acetylated polypeptide, phosphorylated polypeptide, and the like. Included within the definition are, for example, polypeptides containing one or more analogs of amino acid, polypeptides with substituted linkages, as well as other modifications known in the art, both naturally occurring and non-naturally occurring.

When protein levels are to be detected, any convenient protocol for evaluating protein levels may be employed wherein the level of one or more proteins in the assayed sample is determined. For example, one representative and convenient type of protocol for assaying protein levels are enzyme-linked immunosorbent assay (ELISA). In ELISA and ELISA-based assays, one or more antibodies specific for the proteins of interest may be immobilized onto a selected solid surface, preferably a surface exhibiting a protein affinity, such as the wells of a polystyrene microtiter plate. After washing to remove incompletely adsorbed material, the assay plate wells are coated with a non-specific "blocking" protein that is known to be antigenically neutral with regard to the test sample, such as bovine serum albumin (BSA), casein, or solutions of powdered milk. This allows for the blocking of non-specific adsorption sites on the immobilizing surface, thereby reducing the background caused by the non-specific binding of antigen onto the surface. After washing to remove unbound blocking protein, the immobilizing surface is contacted with the sample to be tested under conditions that are conducive to immune complex (antigen/antibody) formation. Such conditions include diluting the sample with diluents such as BSA or bovine gamma globulin (BGG) in phosphate-buffered saline (PBS)/Tweenor PBSATriton-X 100, which also tend to assist in the reduction of nonspecific background and allow the sample to incubate for about 2-4 hrs at temperatures on the order of about 25°-27°C (although other temperatures may be used). Following incubation, the antisera-contacted surface is washed so as to remove non- immunocomplex material. An exemplary washing procedure includes washing with a solution such as PBS/Tween, PBS/Triton-X 100, or borate buffer. The occurrence and amount of immunocomplex formation may then be determined by subjecting the bound immunocomplexes to a second antibody having specificity for the target that differs from the first antibody and detecting the binding of the second antibody. In certain embodiments, the second antibody will have an associated enzyme, e.g. urease, peroxidase, or alkaline phosphatase, which will generate a color precipitate upon incubating with an appropriate chromogenic substrate. For example, a urease or peroxidase-conjugated anti-human IgG may be employed for a period of time and under conditions that favor the development of immunocomplex formation (e.g., incubation for 2 hrs at room temperature in a PBS-containing solution such as PBS/Tween). After such incubation with the second antibody and washing to remove unbound material, the amount of label is quantified, for example, by incubation with a chromogenic substrate such as urea and bromocresol purple in the case of a urease label or 2,2'-azino-di-(3-ethyl-benzthiazoline)-6-sulfonic acid (ABTS) and H₂O₂, in the case of a peroxidase label. Quantitation is then achieved by measuring the degree of color generation, e.g., using a visible spectrum spectrophotometer.

The preceding format may be altered by first binding the sample to the assay plate. Then, the primary antibody is incubated with the assay plate, followed by detection of the bound primary antibody using a labeled second antibody with specificity for the primary antibody.

The solid substrate upon which the antibody or antibodies are immobilized can be made of a wide variety of materials and in a wide variety of shapes, e.g., microtiter plate, microbead, dipstick, resin particle, etc. The substrate may be chosen to maximize signal-to-noise ratios, to minimize background binding, as well as for ease of separation and cost. Washes may be effected in a manner most appropriate for the substrate being used, for example, by removing a bead or dipstick from a reservoir, emptying or diluting a reservoir such as a microtiter plate well, or rinsing a bead, particle, chromatographic column or filter with a wash solution or solvent.

Alternatively, non-ELISA based-methods for measuring the levels of one or more proteins in a sample may be employed. Representative examples include but are not limited to mass spectrometry, proteomic arrays, xMAP™ microsphere technology, flow cytometry, western blotting, and immunohistochemistry.

As another example, the level of at least one KD biomarker may be evaluated by detecting in a patient sample the amount or level of one or more RNA transcripts or a fragment thereof encoded by the gene of interest to arrive at a nucleic acid biomarker representation. The level of nucleic acids in the sample may be detected using any convenient protocol. While a variety of different manners of detecting nucleic acids are known, such as those employed in the field of differential gene expression analysis, one representative and convenient type of protocol for generating biomarker representations is array-based gene expression profiling protocols. Such applications are hybridization assays in which a nucleic acid that displays "probe" nucleic acids for each of the genes to be assayed/profiled in the biomarker representation to be generated is employed. In these assays, a sample of target nucleic acids is first prepared from the initial nucleic acid sample being assayed, where preparation may include labeling of the target nucleic acids with a label, e.g., a member of the signal producing system. Following target nucleic acid sample preparation, the sample is contacted with the array under hybridization conditions, whereby complexes are formed between target nucleic acids that are complementary to probe sequences attached to the array surface. The presence of hybridized complexes is then detected, either qualitatively or quantitatively.

Specific hybridization technology which may be practiced to generate the biomarker representations employed in the subject methods includes the technology described in U.S. Patent Nos.: 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661,028; 5,800,992; the disclosures of which are herein incorporated by reference; as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280. In these methods, an array of "probe" nucleic acids that includes a probe for each of the phenotype determinative genes whose expression is being assayed is contacted with target nucleic acids as described above. Contact is carried out under hybridization conditions, e.g., stringent hybridization conditions and unbound nucleic acid is then removed. The term "stringent assay conditions" as used herein refers to conditions that are compatible with producing binding pairs of nucleic acids, e.g., surface-bound and solution phase nucleic acids, of sufficient complementarity to provide for the desired level of specificity in the assay while being less compatible to the formation of binding pairs between binding members of insufficient complementarity to provide for the desired specificity. Stringent assay conditions are the summation or combination (totality) of both hybridization and wash conditions.

The resultant pattern of hybridized nucleic acid provides information regarding expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, typically, at what level, where the expression data, i.e., biomarker representation (e.g., in the form of a transcriptosome), may be both qualitative and quantitative.

Alternatively, non-array-based methods for quantitating the level of one or more nucleic acids in a sample may be employed, including those based on amplification protocols, e.g., Polymerase Chain Reaction (PCR)-based assays, including quantitative PCR, reverse-transcription PCR (RT-PCR), real-time PCR, and the like.

The resultant data provides information regarding levels in the sample for each of the biomarkers that have been probed, wherein the information is in terms of whether or not the biomarker is present and, typically, at what level, and wherein the data may be both qualitative and quantitative. As such, where detection is qualitative, the methods provide a reading or evaluation, e.g., assessment, of whether or not the target biomarker, e.g., nucleic acid or protein, is present in the sample being assayed. In yet other embodiments, the methods provide quantitative detection of whether the target biomarker is present in the sample being assayed, i.e., an evaluation or assessment of the actual amount or relative abundance of the target analyte, e.g., nucleic acid or protein in the sample being assayed. In such embodiments, the quantitative detection may be absolute or, if the method is a method of detecting two or more different analytes, e.g., target nucleic acids or protein, in a sample, relative. As such, the term "quantifying" when used in the context of quantifying a target analyte, e.g., nucleic acid(s) or protein(s), in a sample can refer to absolute or to relative quantification. Absolute quantification may be accomplished by the inclusion of known concentration(s) of one or more control analytes and by referencing the detected level of the target analyte with the known control analytes (e.g., through the generation of a standard curve). Alternatively, relative quantification can be accomplished by comparison of detected levels or amounts between two or more different target analytes to provide a relative quantification of each of the two or more different analytes, e.g., relative to each other.

Once the level of one or more KD biomarkers has been determined, the measurement(s) may be analyzed in several ways to obtain a KD biomarker level representation.

For example, the measurements of one or more KD biomarkers may be analyzed individually to develop a KD score. As used herein, a “KD score" is the normalized level of one or more KD biomarkers in a patient sample, for example, the normalized level of serological protein concentrations in a patient sample. A profile may be generated by any of a number of methods known in the art. For example, the level of each biomarker may be log₂ transformed and normalized relative to the expression of a selected housekeeping gene, relative to the signal across a whole panel, etc. Other methods of calculating a KD profile will be readily known to the ordinarily skilled artisan.

As another example, the measurements of a panel of KD biomarkers may be analyzed collectively to arrive at a single KD score. By a “KD score” is meant a single metric value that represents the weighted levels of each of the KD biomarkers in the KD panel. As such, in some embodiments, the subject method comprises detecting the level of biomarkers of a KD panel in the sample and calculating a KD score based on the weighted levels of the KD biomarkers. A KD score for a patient sample may be calculated by any of a number of methods and algorithms known in the art for calculating biomarker scores. For example, weighted biomarker levels, e.g. log₂ transformed and normalized biomarker levels that have been weighted by, e.g., multiplying each normalized biomarker level to a weighting factor, may be totaled and, in some cases, averaged to arrive at a single value representative of the panel of KD biomarkers analyzed.

In some instances, the weighting factor, or simply "weight" for each biomarker in a panel, may be a reflection of the change in analyte level in the sample. For example, the analyte level of each KD biomarker may be log-transformed and weighted either as 1 (for those biomarkers that are increased in level in KD) or -1 (for those biomarkers that are decreased in level in KD), and the ratio between the sum of increased biomarkers as compared to decreased biomarkers determined to arrive at a KD signature. In other instances, the weights may be reflective of the importance of each biomarker to the specificity, sensitivity and/or accuracy of the biomarker panel in the making the diagnostic, prognostic, or monitoring assessment. Such weights may be determined by any convenient statistical machine learning methodology, e.g. Principle Component Analysis (PCA), linear regression, support vector machines (SVMs), and/or random forests of the dataset from which the sample was obtained may be used. In some instances, weights for each biomarker are defined by the dataset from which the patient sample was obtained. In other instances, weights for each biomarker may be defined based on a reference dataset or "training dataset".

These methods of analysis may be readily performed by one of ordinary skill in the art by employing a computer-based system, e.g. using any hardware, software and data storage medium as is known in the art, and employing any algorithms convenient for such analysis. For example, data mining algorithms can be applied through "cloud computing", smartphone-based or client-server-based platforms, and the like.

In certain embodiments, the expression, e.g. polypeptide level, of only one biomarker is evaluated to produce a biomarker level representation. In yet other embodiments, the levels of two or more, i.e. a panel, biomarkers, is evaluated. Accordingly, in the subject methods, the expression of at least one biomarker in a sample is evaluated. In certain embodiments, the evaluation that is made may be viewed as an evaluation of the proteome, as that term is employed in the art.

In some instances, the subject methods of determining or obtaining a KD biomarker representation (e.g. KD score or KD profile) for a subject further comprise providing the KD biomarker representation as a report. Thus, in some instances, the subject methods may further include a step of generating or outputting a report providing the results of a KD biomarker evaluation in the sample, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible media). Any form of the report may be provided, e.g. as known in the art or as described in greater detail below.Input the paragraph which describes the best mode here.

Utility

KD biomarker level representations so obtained find many uses. For example, the biomarker level representation may be employed to diagnose a KD; that is, to provide a determination as to whether a subject is affected by KD, the type of KD (complete KD and incomplete KD), the severity of KD (normal heart phenotype, dilation, or aneurysm, etc. In some instances, the subject may present with clinical symptoms of KD, e.g. fever, rash, swelling of the hands and feet, irritation and redness of the whites of the eyes, swollen lymph glands in the neck, and irritation and inflammation of the mouth, lips, and throat.

As another example, the KD biomarker level representation may be employed to determine of risk of having KD when the patients have incomplete KD; that is, to provide a KD clinical sign as a prognosis. For example, the KD biomarker level representation may be used to predict a subject's diagnosis of KD by substitution as an additional clinical sign. "adding biomarker signs if the individual has KD" means determining the likelihood that an individual has KD even if less than four clinical signs are present according to the AHA guideline. The KD biomarker level representation and KD score may be used as a clinical sign the course of disease progression and/or disease outcome, e.g. expected to confirm the diagnosis of the KD, expected duration of the KD, expectations as to whether the KD will develop cardiac phenotypes, etc. The KD biomarker level representation may be used to predict a subject's responsiveness to treatment for the KD, e.g., a positive response, a negative response, or no response at all.

As another example, the KD biomarker level representation may be employed to monitor a KD. By "monitoring" a KD, it is generally meant monitoring a subject's condition, e.g. to inform a KD diagnosis, to inform a KD prognosis, to provide information as to the effect or efficacy of a KD treatment, and the like.

As another example, the KD biomarker level representation may be employed to determine a treatment necessity for a subject. The terms "treatment, treating," and the like are used herein to generally mean obtaining a desired pharmacologic and/or physiologic effect. The effect may be prophylactic in terms of completely or partially preventing a disease or symptom thereof and/or may be therapeutic in terms of a partial or complete cure for a disease and/or adverse effect attributable to the disease. "Treatment" as used herein covers any treatment of a disease in a mammal and includes: (a) preventing the disease from occurring in a subject who may be predisposed to the disease but has not yet been diagnosed as having it; (b) inhibiting the disease, i.e., arresting its development; or (c) relieving the disease, i.e., causing regression of the disease. The therapeutic agent may be administered before, during, or after the onset of disease or injury. The treatment of ongoing disease, where the treatment stabilizes or reduces the undesirable clinical symptoms of the patient, is of particular interest. The subject therapy may be administered prior to the symptomatic stage of the disease and in some cases after the symptomatic stage of the disease. The terms "individual," "subject," "host," and "patient" are used interchangeably herein and refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans. KD treatments are well known in the art and may include bed rest, drinking extra water, a low salt diet, medicine to control blood pressure, corticosteroids, inducing pregnancy, and the like.

In some embodiments, the subject methods of providing a KD assessment, e.g. diagnosing a KD, risk assessement of KD, monitoring the KD, treating the KD, and the like, may comprise comparing the obtained KD biomarker level representation to a KD phenotype determination element to identify similarities or differences with the phenotype determination element, where the similarities or differences that are identified are then employed to provide the KD assessment, e.g. diagnosis the KD, prognosis the KD, monitor the KD, determine a KD treatment, etc. By a "phenotype determination element" is meant an element, e.g., a tissue sample, a biomarker profile, a value (e.g., score), a range of values, and the like, that is representative of a phenotype (in this instance, a KD phenotype) and may be used to determine the phenotype of the subject, e.g., if the subject is healthy or is affected by KD, if the subject has an incomplete KD that is likely to progress to complete/confirm KD, if the subject has a KD that is responsive to therapy, etc.

For example, a KD phenotype determination element may be a sample from an individual that has or does not have KD, which may be used, for example, as a reference/control in the experimental determination of the biomarker level representation for a given subject. As another example, a KD phenotype determination element may be a biomarker level representation, e.g. biomarker profile or score, which is representative of a KD state and may be used as a reference/control to interpret the biomarker level representation of a given subject. The phenotype determination element may be a positive reference/control, e.g., a sample or biomarker level representation thereof from a child that has KD, or that will develop from incomplete KD to complete KD, or that has KD that is manageable by known treatments, or that has KD that has been determined to be responsive to IVIG. Alternatively, the phenotype determination element may be a negative reference/control, e.g., a sample or biomarker level representation thereof from a child that does not have KD or a child that has other febrile illness. Phenotype determination elements are preferably the same type of sample or if biomarker level representations are obtained from the same type of sample as the sample that was employed to generate the biomarker level representation for the individual being monitored. For example, if the serum of an individual is being evaluated, the phenotype determination element would preferably be plasma.

In certain embodiments, the obtained biomarker level representation is compared to a single phenotype determination element to obtain information regarding the individual being tested for KD. In other embodiments, the obtained biomarker level representation is compared to two or more phenotype determination elements. For example, the obtained biomarker level representation may be compared to a negative reference and a positive reference to obtain confirmed information regarding if the individual will develop KD. As another example, the obtained biomarker level representation may be compared to a reference that is representative of a KD that is responsive to treatment and a reference that is representative of a KD that is not responsive to treatment to obtain information as to whether or not the patient will be responsive to treatment.

The comparison of the obtained biomarker level representation to the one or more phenotype determination elements may be performed using any convenient methodology, where a variety of methodologies are known to those of skill in the art. For example, those of skill in the art of ELISAs will know that ELISA data may be compared by, e.g. normalizing to standard curves, comparing normalized values, etc. The comparison step results in information regarding how similar or dissimilar the obtained biomarker level profile is to the control/reference profile(s), which similarity/dissimilarity information is employed to, for example, predict the onset of a KD, diagnose KD, monitor a KD patient, etc. Similarly, those of skill in the art of arrays will know that array profiles may be compared by, e.g., comparing digital images of the expression profiles, by comparing databases of expression data, etc. Patents describing ways of comparing expression profiles include, but are not limited to, U.S. Patent Nos. 6,308,170 and 6,228,575, the disclosures of which are herein incorporated by reference. Methods of comparing biomarker level profiles are also described above. Similarity may be based on relative biomarker levels, absolute biomarker levels, or a combination of both. In certain embodiments, a similarity determination is made using a computer having a program stored thereon that is designed to receive input for a biomarker level representation obtained from a subject, e.g., from a user, determine similarity to one or more reference profiles or reference scores, and return a KD clinical sign diagnosis, e.g., to a user (e.g., lab technician, physician, febrile children, etc.). Further descriptions of computer-implemented aspects of the invention are described below. In certain embodiments, a similarity determination may be based on a visual comparison of the biomarker level representation, e.g., KD score, to a range of phenotype determination elements, e.g., a range of KD scores, to determine the reference KD score that is most similar to that of the subject. Depending on the type and nature of the phenotype determination element to which the obtained biomarker level profile is compared, the above comparison step yields a variety of different kinds of information regarding the cell/bodily fluid that is assayed. As such, the above comparison step can produce a positive/negative prediction of the onset of KD, a positive/negative diagnosis of KD, a characterization of a KD, information on the responsiveness of a KD to treatment, and the like.

In other embodiments, the biomarker level representation is employed directly, i.e. without comparison to a phenotype determination element, to make a KD prognosis, KD diagnosis, or monitor a KD.

The subject methods may be employed for a variety of different types of subjects. In many embodiments, the subjects are within the class mammalian, including the orders carnivore (e.g., dogs and cats), Rodentia (e.g., mice, guinea pigs, and rats), Lagomorpha (e.g. rabbits), and primates (e.g., humans, chimpanzees, and monkeys). In certain embodiments, the animals or hosts, i.e., subjects (also referred to herein as patients), are humans.

In some embodiments, the subject methods of providing a KD assessment include providing a diagnosis, prognosis, or result of the monitoring. In some embodiments, the KD assessment of the present disclosure is provided by providing, i.e. generating, a written report that includes the artisan's assessment, for example, the artisan's determination of whether the patient is currently affected by KD, of the type, stage, or severity of the subject's KD, etc. (a "KD diagnosis"); the artisan's prediction of the patient's susceptibility to developing KD, of the course of disease progression, of the patient's responsiveness to treatment, etc. (i.e., the artisan's "KD prognosis"); or the results of the artisan's monitoring of the KD. Thus, the subject methods may further include a step of generating or outputting a report providing the results of an artisan's assessment, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible media). Any form of a report may be provided, e.g. as known in the art or as described in greater detail below.

Reports

A "report," as described herein, is an electronic or tangible document which includes report elements that provide information of interest relating to the assessment of a subject and its results. In some embodiments, a subject report includes at least a KD biomarker representation, e.g. a KD profile or a KD score, as discussed in greater detail above. In some embodiments, a subject report includes at least an artisan's KD assessment, e.g. KD diagnosis, KD prognosis as a KD clinical sign, an analysis of a KD monitoring, a treatment recommendation, etc. A subject report can be completely or partially electronically generated. A subject report can further include one or more of: 1) information regarding the testing facility; 2) service provider information; 3) patient data; 4) sample data; 5) an assessment report, which can include various information including a) reference values employed, and b) test data, where test data can include, e.g., a protein level determination; 6) other features.

The report may include information about the testing facility and which information is relevant to the hospital, clinic, or laboratory in which sample gathering and/or data generation was conducted. Sample gathering can include obtaining a fluid sample, e.g. blood, saliva, urine etc.; a tissue sample, e.g. a tissue biopsy, etc., from a subject. Data generation can include measuring the biomarker concentration in KD patients versus healthy individuals, i.e. individuals that do not have and/or do not develop KD. This information can include one or more details relating to, for example, the name and location of the testing facility, the identity of the lab technician who conducted the assay and/or who entered the input data, the date and time the assay was conducted and/or analyzed, the location where the sample and/or resulting data is stored, the lot number of the reagents (e.g., kit, etc.) used in the assay, and the like. Report fields with this information can generally be populated using the information provided by the user.

The report may include information about the service provider, which may be located outside the healthcare facility at which the user is located or within the healthcare facility. Examples of such information can include the name and location of the service provider, the name of the reviewer, and, where necessary or desire, the name of the individual who conducted sample gathering and/or data generation. Report fields with this information can generally be populated using data entered by the user, which can be selected from among pre-scripted selections (e.g., using a drop-down menu). Other service provider information in the report can include contact information for technical information about the result and/or about the interpretive report.

The report may include a patient data section, including patient medical history (which can include, e.g., age, race, serotype, prior KD episodes, and any other characteristics of the patients), as well as administrative patient data such as information to identify the patient (e.g., name, patient date of birth (DOB), gender, mailing and/or residence address, a medical record number (MRN), room and/or bed number in a healthcare facility), insurance information, and the like), the name of the patient's physician or other health professionals who ordered the monitoring assessment and, if different from the ordering physician, the name of a staff physician who is responsible for the patient's care (e.g., primary care physician).

The report may include a sample data section, which may provide information about the biological sample analyzed in the monitoring assessment, such as the source of a biological sample obtained from the patient (e.g. blood, saliva, or type of tissue, etc.), how the sample was handled (e.g. storage temperature, preparatory protocols) and the date and time collected. Report fields with this information can generally be populated using data entered by the user, some of which may be provided as pre-scripted selections (e.g., using a drop-down menu). The report may include a results section.

The report may include an assessment report section, which may include information generated after processing the data as described herein. The interpretive report can include a prediction of the likelihood that the subject will develop KD. The interpretive report can include a diagnosis of KD. The interpretive report can include a characterization of KD. The assessment portion of the report can optionally also include a recommendation(s). For example, where the results indicate that KD is likely, the recommendation can include a recommendation that diet is altered, blood pressure medicines administered, etc., as recommended in the art.

It will also be readily appreciated that the reports can include additional elements or modified elements. For example, where electronic, the report can contain hyperlinks that point to internal or external databases which provide more detailed information about selected elements of the report. For example, the patient data element of the report can include a hyperlink to an electronic patient record or a site for accessing such a patient record, which patient record is maintained in a confidential database. This latter embodiment may be of interest in an in-hospital system or in-clinic setting. When in electronic format, the report is recorded on a suitable physical medium, such as a computer-readable medium, e.g., in computer memory, flash drive, CD, DVD, etc.

It will be readily appreciated that the report can include all or some of the elements above, with the proviso that the report generally includes at least the elements sufficient to provide the analysis requested by the user (e.g. a calculated KD biomarker level representation; a prediction, diagnosis or characterization of KD).

Reagents, Systems and Kits

Also provided are reagents, systems, and kits for practicing one or more of the above-described methods. The subject reagents, systems, and kits thereof may vary greatly. Reagents of interest include reagents specifically designed for use in producing the above-described biomarker level representations of KD biomarkers from a sample, for example, one or more detection elements, e.g. antibodies or peptides for the detection of protein, oligonucleotides for the detection of nucleic acids, etc. In some instances, the detection element comprises a reagent to detect the abundance of a single KD biomarker; for example, the detection element may be a dipstick, a plate, an array, or a cocktail that comprises one or more detection elements, e.g. one or more antibodies, one or more oligonucleotides, one or more sets of PCR primers, etc. which may be used to detect the abundance of one or more KD biomarker simultaneously,

One type of reagent that is specifically tailored for generating biomarker level representations, e.g. KD biomarker level representations, is a collection of antibodies that bind specifically to the protein biomarkers, e.g. in an ELISA format, in an xMAP™ microsphere format, on a proteomic array, in suspension for analysis by flow cytometry, by western blotting, by dot blotting, or by immunohistochemistry. Methods for using the same are well understood in the art. These antibodies can be provided in solution. Alternatively, they may be provided pre-bound to a solid matrix, for example, the wells of a multi-well dish or the surfaces of xMAP microspheres.

Another type of such reagent is an array of probe nucleic acids in which the genes (biomarkers) of interest are represented. A variety of different array formats are known in the art, with a wide variety of different probe structures, substrate compositions and attachment technologies (e.g., dot blot arrays, microarrays, etc.). Representative array structures of interest include those described in U.S. Patent Nos.: 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661,028; 5,800,992; the disclosures of which are herein incorporated by reference; as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280.

Another type of reagent that is specifically tailored for generating biomarker-level representations of genes, e.g. KD genes, is a collection of gene-specific primers that is designed to selectively amplify such genes (e.g., using a PCR-based technique, e.g., real-time RT-PCR). Gene-specific primers and methods for using the same are described in U.S. Patent No. 5,994,076, the disclosure of which is herein incorporated by reference.

Of particular interest are arrays of probes, collections of primers, or collections of antibodies that include probes, primers, or antibodies (also called reagents) that are specific for at least 1 gene/protein/lipd selected from the group consisting of NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1, FABP3, LIGHT, CXCL6, CXCL16, FABP4, Endocan-1, and Oncostatin M, VEGFA, HGF, MMP-8, and MMP-9, or a biochemical substrate specific associated with them. The subject probe, primer, or antibody collections or reagents may include reagents that are specific only for the genes/proteins/lipids/cofactors that are listed above, or they may include reagents specific for additional genes/proteins/lipids/cofactors that are not listed above, such as probes, primers, or antibodies specific for genes/proteins/lipids/cofactors whose expression pattern are known in the art to be associated with KD, e.g. and NT-proBNP and MMP8.

In some instances, a system may be provided. As used herein, the term “system” refers to a collection of reagents, however, compiled, e.g., by purchasing the collection of reagents from the same or different sources. In some instances, a kit may be provided. As used herein, the term "kit" refers to a collection of reagents provided, e.g., sold, together. For example, the nucleic acid- or antibody-based detection of the sample nucleic acid or protein, respectively, may be coupled with an electrochemical biosensor platform that will allow multiplex determination of these biomarkers for personalized KD care.

The systems and kits of the subject invention may include the above-described arrays, gene-specific primer collections, or protein-specific antibody collections. The systems and kits may further include one or more additional reagents employed in the various methods, such as primers for generating target nucleic acids, dNTPs and/or rNTPs, which may be either premixed or separate, one or more uniquely labeled dNTPs and/or rNTPs, such as biotinylated or Cy3 or Cy5 tagged dNTPs, gold or silver particles with different scattering spectra, or other post syntheses labeling reagent, such as chemically active derivatives of fluorescent dyes, enzymes, such as reverse transcriptases, DNA polymerases, RNA polymerases, and the like, various buffer mediums, e.g. hybridization and washing buffers, prefabricated probe arrays, labeled probe purification reagents and components, like spin columns, etc., signal generation and detection reagents, e.g. labeled secondary antibodies, streptavidin-alkaline phosphatase conjugate, chemifluorescent or chemiluminescent substrate, and the like.

The subject systems and kits may also include one or more KD phenotype determination elements, which element is, in many embodiments, a reference or control sample or biomarker representation that can be employed, e.g., by a suitable experimental or computing means, to make a KD prognosis based on an "input" biomarker level profile, e.g., that has been determined with the above-described biomarker determination element. Representative KD phenotype determination elements include samples from an individual known to have or not have KD, databases of biomarker level representations, e.g., reference or control profiles or scores, and the like, as described above.

In addition to the above components, the subject kits will further include instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc. Yet another means would be a computer-readable medium, e.g., diskette, CD, etc., on which the information has been recorded. Yet another means that may be present is a website address which may be used via the internet to access the information at a removed site. Any convenient means may be present in the kits.

The following examples are offered by way of illustration and not by way of limitation.

EXAMPLES

The following examples are put forth so as to provide those of ordinary skill in the art with a description of how to make and use the present invention and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, the temperature is in degrees Centigrade, and pressure is at or near atmospheric.

Material and Methods

KD patient validation cohort, demographic information, and clinical criteria. All study protocols were approved by the Chang-Gen Memorial Hospital Institutional Review Board (IRB). Blood samples were obtained from confirmed KD, and the febrile control samples were drawn from the same cohort but later determined not to be KD. KD patients met American Heart Association for complete and incomplete KD clinical criteria and were treated with IVIG within ten days of the initial onset of fever.(3) Patient blood samples were obtained and analyzed at baseline before IVIG or medication was given. Samples for this study were drawn exclusively from Cheng-Gen Memorial Hospital, and informed consent was obtained from guardians of participating children.

Meta-analysis of Vasculitis and KD MicroarryIdentified. Differentially expressed genes (DEGs) were extracted from seven data sets from PBMC microarray experiment. The seven data sets include PBMC microarray experiments profiling primary vasculitis, including KD, subjects from the NCBI Gene Expression Omnibus (GEO) 20: 4 KD datasets, GSE15297 (KD vs. FC), GSE18606 (KD vs. normal controls), GSE9864 (KD vs. normal controls); GSE9863 (KD vs. normal controls); 3 other vasculitis datasets, GSE33910 (Takayasu's arteritis vs. normal controls), GSE17114 (Bechet's disease vs. normal controls), GSE16945 (Takayasu's arteritis vs. normal controls). After DEGs were found in each data set, Ingenuity Pathway Analysis (IPA) was performed to identify pathways associated with the DEGs in each of the seven data sets. Gene biomarkers, present in the DEG list in at least one of the data sets and involved in at least one of the commonly enriched pathways shared across seven datasets, composed the collective vasculitis meta-signature. To identify potential biomarker candidates, gene makers were further filtered with the human biofluid proteome database with known serum- and urine- detectable proteins containing data from the HUPO plasma Proteome Project,(24) a non-redundant list from the plasma Proteome Institute,(25) the MAPU Proteome database,(26) and the Urinary Exosome database.(27,28)

Biomarker Testing via multiplex immune-assay platform. The plasma from both KD and febrile control cohorts was isolated from the blood. The plasma was stored shortly after isolation at -80oC and thawed before the analysis. The assays were performed on the Luminex 200 xMap IVD platform using plasma for 17 protein targets using commercially available kits with the customized addition of several KD-associated proteins. The assay was performed according to the reagent manufacturers' recommended procedures and dilution, and each analyte's linearity, LOQ/LOD, and concentration were determined.

Statistical Analysis. The overall study population included 184 patients, with 91 confirmed KD and 93 febrile control cases. The blood concentration was measured for each analyte. Patient characteristics was tested between KD patients and febrile control using fisher's exact test for gender and rank-sum test for age. Univariate analysis was performed on individual analytes from KD patients compared to those from the febrile controls. Receiver operating characteristic (ROC) analysis was performed, and the specificity, sensitivity, positive predictive value (PPV), negative predicitive vlaue (NPV), and area under the curve (AUC) values were determined for each analyte. The Wilcoxon rank-sum test and fold change analysis was also used to compare all the KD patients' analyte concentration values with the febrile controls. The age differences of the confirmed KD diagnosis versus febrile controls were compared using a similar rank-sum test. To aid the statistical analysis, any assay values that were below the LOQ were extrapolated as half the LOQ value, and any analyte values that were above the upper limit of quantification (ULQ) were extrapolated as twice the ULQ value. This ensures more inclusive data for values either below LOQ or above ULQ. Setting the value at either LOQ and ULQ does not affect the analysis. Ten analytes were selected to pick significant differential analytes using criteria rank-sum test p-value less than 0.05, fold change greater than 1.5 or smaller than 0.67, and AUC larger than 0.6.

The analyte concentrations were analyzed via a linear significant different analyte through an iterative search of all ten analyte combinations to find maximum ROC AUC values. The geometric mean was calculated for each distinct combination of analytes, and log-transform was applied on the geometric mean and then scaled to a range of 0 and 10, and ROC analysis was performed. For the first iteration, the best analytes with the highest AUC > 0.5 are selected one at a time based on their univariate analysis. During the next iteration, each of the retaining analytes was added to the previous best AUC combination panel. If a new analyte improves the performance of the model by maximizing AUC, it is retained in the panel and vice versa. The process was repeated until a maximum AUC was achieved, and the remaining features constituted the final panel.

KD biomarker panel and diagnosis score. The model was then tested using in-sample validation to evaluate the performance with the area under the receiver operating characteristic curve. A KD score was generated using the geometric means from the final panel. With a single cutoff in a binary model, the optimal cutoff was determined using the optimal Youden's index. Other operating characteristics such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were computed based on the optimal cutoff score with 95% confidence intervals for all metrics. All statistics were performed via R software, version 4.1 (R Foundation for Statistical Computing). Two-sided p values were computed, and p <0.05 are considered significant.

Results

Patient demographics and characteristics. This study focuses on the pediatric population suffering from continuous high fever, with 91 later confirmed KD cases and 93 febrile children (Table 1a). Forty-nine patients have five clinical signs and twenty-six KD patients (28.5%) have four clinical signs, which qualified for complete KD diagnostic criteria by AHA guidelines at blood collection (Table 1b), while the remaining 16 cases were diagnosed as incomplete at the time of blood collection. The ages of the confirmed KD diagnosis (1.4 years, 0.9 – 3) are younger than the febrile control (2.8 years, 1.7 – 3.9), p < 0.001. The IRB approval limited clinical information for the control group, but none of the febrile control patients qualified for KD diagnosis.

	Case (n=91)	Control (n=93)	Test stat.	P value
Gender, N(%)			Fisher's exact test	0.378
Female	48 (52.7)	58 (62.4)
Male	42 (46.2)	33 (35.5)
Missing	1 (1.1)	2 (2.2)
Age, median(IQR)	1.4 (0.9,3)	2.8 (1.7,3.9)	Ranksum test	< 0.001

Table 1a. Patient demographic information. The KD patients are slightly younger than the febrile controls.

Column1	1	2	3	4	5
Clinical sign	KD (n=1)	KD (n=2)	KD (n=13)	KD (n=49)	KD (n=26)
Lip	0	1	9	48	26
Eye	1	1	12	47	26
Lymph	0	0	0	7	26
Edematous	0	1	10	47	26
Skin	0	1	11	46	26

Table 1b. Summary of KD signs of the studied cohort.

Meta-analysis Identified Luminex Discovery Panel of KD Biomarkers. Thirteen pathways were overlapped through the meta-analysis of the seven vasculitis and KD microarray data. A total of 82 genes were identified and filtered with a human biofluid proteome database. This led to the identification of potential 53 vasculitis-specific gene markers (meta-signature), which may be differentially expressed in the blood (Figure 1). VEGF, MMP8, and HGF, which are within our vasculitis meta-signature, were reported to be differentially expressed in serum between KD and FC (p-value < 0.0001) and between KD and normal control (p-value <0.001) subjects. This observation provides direct evidence supporting the validity of our overall biomarker discovery approach and our hypothesis that meta-analysis of vasculitis PBMC microarray data sets can lead to specific KD diagnostic biomarkers. This observation is also in line with our successful experience in the application of the same approach to identify novel preeclampsia biomarkers. To adapt the discovery into a common platform, seventeen biomarkers were identified based on cardiac stress, immune responses, and vascular growth and remodeling, including myocardial dysfunction or stress markers (NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Troponin 1), cardiac ischemia (FABP3), plaque instability/rupture (LIGHT), inflammation (CXCL6, CXCL16, FABP4, Endocan-1, and Oncostatin M), and cellular growth and migration (VEGFA, HGF, MMP-8, and MMP-9).

Binary and risk classification model performance. The Luminex analytes results of KD and febrile control cohorts for each protein biomarker in the exploratory discovery panel were analyzed individually via univariant analysis (Table 2). Subsequently, a linear method was used to construct the best panel with maximum AUC. The top four analytes, NTproBNP, CXCL16, FABP4, and MMP-8, resulted in a panel with the highest AUC of 0.946 via geometric means (Figures 2a and 2b).

	fold	threshold	specificity	sensitivity	ppv	npv	auc	nar
NTproBNP	8.192	32.562	0.871	0.831	0.86	0.844	0.877	0.011
FABP4	4.079	3,996.67	0.868	0.659	0.829	0.725	0.834	0.027
MMP-8	3.558	10,550.65	0.753	0.791	0.758	0.787	0.826	0
CXCL16	1.73	801.655	0.667	0.856	0.713	0.827	0.813	0.005
HGF	2.963	137.895	0.731	0.813	0.747	0.8	0.802	0
LIGHT	4.466	37.871	0.849	0.636	0.8	0.712	0.727	0.016
OSM	2.176	34.284	0.86	0.494	0.772	0.64	0.718	0.011
BNP	1.791	125.602	0.774	0.697	0.747	0.727	0.708	0.011
ST2	2.688	19,697.00	0.699	0.67	0.685	0.684	0.704	0
CK-MB	1.477	1,898.13	0.677	0.685	0.67	0.692	0.698	0.011
PlGF	1.826	3.004	0.71	0.6	0.667	0.647	0.674	0.005
CXCL6	1.46	185.775	0.495	0.795	0.598	0.719	0.67	0.016
MMP-9	1.187	50,467.00	0.774	0.648	0.738	0.692	0.657	0
FABP3	1.414	842.238	0.57	0.697	0.608	0.663	0.633	0.011
Troponin I	1.227	337.565	0.461	0.75	0.568	0.661	0.582	0.06
VEGF-A	0.643	3,737.95	0.43	0.791	0.576	0.678	0.568	0
Endocan-1	0.998	789.401	0.871	0.258	0.657	0.551	0.521	0.011

The diagnosis model has a robust AUC of 0.945 for diagnosing KD (Figure 2a). The AUC (area under a ROC curve) quantifies the ability of a diagnostic test to discriminate between individuals with and without a disease. A perfect test that yields no false positives or negatives has an AUC of 1.00; a test no better at identifying true positives than random chance has an AUC of 0.5. Based on the optimal cutoff of the Kawasaki score (KD score) at 6.64 determined using Youden's index, A diagnostic cutoff was determined to optimize sensitivity and specificity for effective KD diagnosis. The overall binary classification model performance for the total population has a sensitivity of 93.2% (87.5 – 97.7%), a specificity of 81.3% (72.5% – 89%), a positive predictive value (PPV) of 82.8%, and a negative predictive value (NPV) of 92.5% (Figure 2c).

In addition, a two-threshold-based scale was also created to classify patients into a three-level risk score system for effective KD risk stratification to aid the clinical diagnosis of KD: low-risk (KD score < 6.590), intermediate-risk (6.590 – 6.710), and high-risk (KD score > 6.710) in Figure 3a. For the high-risk KD group, the PPV is 86.4% and low-risk KD (febrile illness) group has an NPV of 93.2% (Figure 3b). This result indicates that greater than 8 out of 10 patients in the high-risk group and less the 1 out of 10 in the low-risk group are positives for KD (Figure 3c). The KD score from the diagnostic test is intended as an in vitro diagnostic test to aid physicians' decisions, especially for incomplete KD.

We also examine the correlation of coronary artery abnormalities with our KD scoring system in the studied cohort diagnosed with KD. Z-score was calculated for individual KD patients and classified into three categories: No coronary involvement (z-score <2), dilation only (z-score 2 to <2.5), and aneurysm (z-score > 2.5). Our test captured the majority of KD patients with an aneurysm in the high-risk group, 18 out of 24 (75%), and could identify KD patients with normal coronary arteries (Figure 4). The data also suggest that our panel does not require obvious cardiac stress signal or phenotype to be postively identified as KD.

We have developed a diagnostic panel to assist with the diagnosis of Kawasaki Disease with a ROC AUC of 0.946. The serological test accurately identifies KD patients and separates them from other febrile cases. The four analytes model was constructed using a linear geometric mean-based statistical model with AUC of 0.946. A simple model based on linear geometric means of the combined biomarkers avoids training bias resulting in overfitting and poor predictive outcomes in the validation set. The model is also more likely to transfer different patient population cohorts from other regions.

Our panel comprises four serological biomarkers associated with heart health, inflammation, and cellular growth and remodeling, Ntpro-BNP, CXCL16, FABP4, and MMP-8. BNP and Ntpro-BNP are natriuretic peptides synthesized by the heart.(24) NT-proBNP is the cleavage product of BNP and like BNP, is usually found at very low level in the bloodstream. When the heart is under stress, the level of NTproBNP will increase in blood, and the increased level is associated with heart failure.(25,26) However, it is known that not all KD patients will suffer cardiac stress or injury. Thus, an increase in NTproBNP does not necessarily serve as a diagnostic marker alone for KD. FABP4 expression is linked to the development of coronary atherosclerosis. It is also linked to inflammation associated with the cardiovascular system. Inhibiting FABP4 expression reduces cardiac inflammatory responses via the arachidonic acid-cyclooxygenase 2 pathway. Recently, increasing FABP4 levels in the blood has also been linked as a potential biomarker of heart failure.(27) FABP4 is mainly secreted by macrophages contributing to the development of atherosclerosis and cardiovascular disease. It is linked to CXCL16, which controls macrophage movement and localization via its chemotaxis property.(28)

The panel also potentially involves the dysregulation of the immune system. CXC chemokine family has previously been reported to be upregulated in KD.(29,30) CXCL16 is a small cytokine and control subset of T cells and natural killer T (NKT) cells migration and localization.(31,32) The upregulation of CXCL16 in the KD patient plasma suggests aberrant activation of T and NKT cells, which play a crucial role in autoimmunity. CXCL16 also controls macrophages and neutrophils localization and accumulation. Down-regulation of CXCL16 also attenuates cardiac ischemia-reperfusion injury following an ischemic event (33) which indicates a role in arterial damage observed in Kawasaki disease.

Matrix metalloproteases (MMPs) regulate the remodeling and degradation of cellular matrix. Previous studies suggested that specific MMPs such as MMP2, MMP3, and MMP9 are associated with the susceptibility, severity, and progression of coronary artery lesions and aneurysms.(34,35) However, studies have shown that MMP9 is only significantly upregulated in KD patients suffering cardiac stress but is a poor biomarker for distinguishing KD patients from other febrile diseases.(36) Surprisingly, MMP8 displayed a significant difference between KD and other febrile patients. MMP8 is known to play a key role in LPS-stimulated neutrophil chemokinesis and interleukin processing associated with innate immunity. MMP8 also plays a role in orchestrating inflammatory events, including its resolution.(37) In MMP-8 null mice, persistent inflammation was observed and non-resolving, leading to a delay in skin wound healing.(38) The expression of MMP8 has recently been observed among IVIG-resistant KD patients, and the serum levels of MMP8 have also been reported to be significantly higher in the acute phase of KD, consistent with our panel observation.(39,40)

Our biomarker panel suggests that KD is a complex disease that affects multiple biological pathways and organ systems, such as dysregulation of auto/innate immunities, continuous inflammatory responses, and abnormal vascular remodeling resulting from these dysfunctioned signaling events. With the combination of these analytes, the most severe KD cases with coronary artery aneurysms, 18 out of 23, were identified in the KD high-risk group (Figure 3). However, most KD patients without or with only mild coronary dilation were also accurately identified when the patients had high KD risk scores.

Previously, several studies aimed to discover either a specific biomarker or a multiple biomarker panel containing serological protein analyte, cytokines, or gene expression profiles via either LC mass-spectrometry-based techniques or gene microarray approaches to identify potential KD biomarkers. Recent studies targeting three serological biomarkers, myeloid-related protein 8/14 (MRP8/14), human neutrophil elastase (HNE), and C-reactive protein as a prospective biomarker panel, achieved ROC AUC values as high as 0.82, but with relatively poor negative predictive value. Another study composed 16 clinically available proteins using Random Forest models to achieve similar AUC values to our simple four analyte panel using geometric means of analytes concentration and the optimal Youden's index to determine the cutoff value. Complicated statistical models such as Random Forest are more challenging to interpret and implement than a simple equal-weight linear model. The Random Forest model is also harder to transfer the model from the original cohort to another cohort from a different region, which can limit its practicality as a practical clinical assay.

Wright et al. using microarray data also developed a 13-transcript blood gene expression signature panel capable of distinguishing KD cases from febrile patients. The study used a parallel regularized regression model search to discriminate KD cases. The panel achieved AUC of 0.946 in the final validating set. However, both training and validation cohorts only used microarray data generated by the studies with further validation of the gene expression data with a more quantitative assay such as qPCR of the 13 genes. The panel needs to be re-examined and validated using a quantitative qPCR assay of the focused gene panel in a separate cohort. Interestingly, the gene expression signature analysis has recently shown that KD shares a similar host immune response in multisystem inflammatory syndrome in children due to COVID-19 infection without the commonly associated cardiac phenotypes.(41) This suggests gene signature mainly captures the host immune response to KD but not the cardiac events. It will be interesting to see if the gene expression of our serum biomarkers is also upregulated from the whole blood gene expression analysis via quantitative PCR analysis.

In this study, we used US FDA-cleared Luminex instrument assay in combination with available clinical assays for rapid adaptation into the clinic for KD diagnosis. The panel model is also based on geometric means of the biomarkers, which outperform commonly used machine learning algorithms, which significantly improves the transferability of the model from cohort to cohort without the potential for overfitting the data, which commonly occurs if the data are processed via complicated statistical model or AI machine learning algorithm. The limitation of this study is without an additional validation cohort to determine if the panel could be easily transferred to a different patient population. KD is a rare and orphan disease considered by the US Food and Drug Administration. Thus, enrollment within a timely matter could be difficult. The most significant medical need for KD will be patients who suffer incomplete KD and are often misdiagnosed with other febrile diseases. Without IVIG treatment within ten days following the onset of fever, the likelihood of suffering cardiac events is significantly higher later in life. A KD diagnosis test panel that can be deployed with currently available clinical tests and standard statistical algorithms could substantially improve KD diagnosis speed and accuracy.

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Claims

A method of determining Kawasaki disease biomarker levels presentation for a subject, the method comprising:

a. assessing a panel of KD biomarkers concentration in a sample such as blood, serum, or plasma from a subject to determine the level of each KD biomarker in the sample;

b. obtaining the KD biomarker level representation based on the level of each KD biomarker in the panel;

c. where the panel of KD biomarkers comprises one or more biomarkers selected from the group consisting of NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1, FABP3, LIGHT (TNFSF14), CXCL6, CXCL16, ST2 (IL1RL1), FABP4, and Oncostatin M, VEGFA, HGF, MMP-8, and MMP-9.
The method according to claim 1, where the protein, in whole or their peptide sequences, DNA, RNA level of each KD biomarker is measured.
The method according to claim 1, wherein the panel comprises NTproBNP and FABP4.
The method according to claim 1, wherein the panel comprises NTproBNP, FABP4, and MMP-8.
The method according to claim 1, wherein the panel comprises NTproBNP, FABP4, MMP-8, and CXCL16.
The method according to claim 1, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, and HGF.
The method according to claim 1, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, and LIGHT (TNFSF14).
The method according to claim 1, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), and OSM.
The method according to claim 1, wherein the panel of KD biomarkers comprises wherein the biomarkers comprise NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).
The method according to claim 1, further comprising providing a report of the KD biomarker level representation such as absolute concentration or multiple of medium (MoM).
The method according to claim 1, wherein the KD biomarker presentation derives a KD score, wherein the KD score::

a. can be derived via geometric means, multivariate linear discriminant analysis (LDA), or distributed gradient-boosted decision tree (GBDT) machine learning such as XGBoost from the values of the blood biomarkers measured; or

b. can be the multiple of each biomarker's level, such as concentrations or MoM, normalized to fit a scale of 0-10 e.g. can be derived via the formula below: [Biomarker1]X[Biomarker2]X[Biomarker3]/(normalizing factor) X 10 = KD score.
A method for providing a KD diagnosis for a subject, the method comprising KD biomarker level representation for a sample from a subject.
The method according to claim 12, where the protein, in whole or their peptide sequences, DNA, RNA level of each KD biomarker is measured.
The method according to claim 12, wherein the panel comprises NTproBNP and FABP4.
The method according to claim 12, wherein the panel comprises NTproBNP, FABP4, and MMP-8.
The method according to claim 12, wherein the panel comprises NTproBNP, FABP4, MMP-8, and CXCL16.
The method according to claim 12, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, and HGF.
The method according to claim 12, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, and LIGHT (TNFSF14).
The method according to claim 12, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), .and OSM.
The method according to claim 12, wherein the panel of KD biomarkers comprises wherein the biomarkers comprise NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).
The method according to claim 12, further comprising, provides a report of the KD biomarker level representation such as absolute concentration or multiple of medium (MoM).
The method according to claim 12, wherein the KD biomarker presentation derives a KD score, wherein the KD score:

a. can be derived via geometric means, multivariate linear discriminant analysis (LDA), or distributed gradient-boosted decision tree (GBDT) machine learning such as XGBoost from the values of the blood biomarkers measured; or

b. can be the multiple of each biomarker's level, such as concentrations or MoM, normalized to fit a scale of 0-10 e.g. can be derived via the formula below: [Biomarker1]X[Biomarker2]X[Biomarker3]/(normalizing factor) X 10 = KD score;

For diagnosis, A KD score greater than 3.274 is an example but is subject to population adjustment for confirming KD when there are no sufficient clinical symptoms to confirm KD diagnosis.
A method for providing a KD risk assessment for a subject, the method comprising KD biomarker level representation for a sample from a subject.
The method according to claim 23, where the protein, in whole or their peptide sequences, DNA, RNA level of each KD biomarker is measured.
The method according to claim 23, wherein the panel comprises NTproBNP and FABP4.
The method according to claim 23, wherein the panel comprises NTproBNP, FABP4, and MMP-8.
The method according to claim 23, wherein the panel comprises NTproBNP, FABP4, MMP-8, and CXCL16.
The method according to claim 23, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, and HGF.
The method according to claim 23, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, and LIGHT (TNFSF14).
The method according to claim 23, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), .and OSM.
The method according to claim 25, wherein the panel of KD biomarkers comprises wherein the biomarkers comprise NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).
The method according to claim 25, further comprising, provides a report of the KD biomarker level representation such as absolute concentration or multiple of medium (MoM).
The method according to claim 25, wherein the KD biomarker presentation derives a KD score in two ways and cutoff values for diagnosis:

a. a geometric means, multivariate linear discriminant analysis (LDA), or distributed gradient-boosted decision tree (GBDT) machine learning such as XGBoost from the values of the blood biomarkers measured;

b. or a combination of multiple of each biomarker's level, such as concentrations or MoM, normalized to fit a scale of 0-10 e.g. can be derived via the formula below [Biomarker1]X[Biomarker2]X[Biomarker3]/(normalizing factor) X 10 = KD score;

For KD risk assessment, a KD score determines the risk of having KD at three different ranges to determine the risk of having KD. A low KD risk below the low score cutoff (3.17 as an example but subject to population adjustment) indicates that a patient is at a low-risk for KD. A high KD risk above the high score cutoff (3.47 as an example but subject to population adjustment) indicates that a patient is at high risk for KD. A score between the low and high KD score cutoff suggests an intermediate KD risk.
A method for providing a KD treatment monitoring for a subject, the method comprising KD biomarker level representation for a sample from a subject.
The method according to claim 34, where the protein, in whole or their peptide sequences, DNA, RNA level of each KD biomarker is measured.
The method according to claim 34, wherein the panel comprises NTproBNP and FABP4.
The method according to claim 34, wherein the panel comprises NTproBNP, FABP4, and MMP-8.
The method according to claim 34, wherein the panel comprises NTproBNP, FABP4, MMP-8, and CXCL16.
The method according to claim 34, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, and HGF.
The method according to claim 34, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, and LIGHT (TNFSF14).
The method according to claim 34, wherein the panel comprises NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).
The method according to claim 34, wherein the panel of KD biomarkers comprises wherein the biomarkers comprise NTproBNP, FABP4, MMP-8, CXCL16, HGF, LIGHT (TNFSF14), OSM, and ST2 (IL1RL1).
The method according to claim 34, further comprising, provides a report of the KD biomarker level representation such as absolute concentration or multiple of medium (MoM).
The method according to claim 34, wherein the KD biomarker presentation derives a KD score in two ways and cutoff values for diagnosis:

a. can be derived via geometric means, multivariate linear discriminant analysis (LDA), or distributed gradient-boosted decision tree (GBDT) machine learning such as XGBoost from the values of the blood biomarkers measured; or

b. can be the multiple of each biomarker's level, such as concentrations or MoM, normalized to fit a scale of 0-10 e.g. can be derived via the formula below: [Biomarker1]X[Biomarker2]X[Biomarker3]/(normalizing factor) X 10 = KD score;

For KD treatment monitoring, a KD score should be greater than 3.274 initially as an example but is subject to population adjustment for KD before treatment. The KD score should decrease significantly after treatment below KD score of 3.274.
A kit to generate a KD score from a sample such as blood, serum, or plasma comprising:

a. one or more detection reagents for measuring the amount of KD biomarkers in a panel comprising one or more biomarkers selected from the group consisting of NT-proBNP, BNP, CK-MB, Endocan-1, PlGF, Cardiac Troponin 1, FABP3, LIGHT, CXCL6, CXCL16, FABP4, Endocan-1, Oncostatin M, VEGFA, HGF, MMP-8, and MMP-9.
The kit of claim 45 further comprising:

a. a platform system to measure the KD biomarker such as Luminex xMAP system,

b. a calculation sheet to calculate KD score, and

c.an instruction to determine if the patient has KD.
A method according to any one of claims 12, 23, or 34, further comprising of selecting a patient suspected of having KD for the treatment with intravenous immunoglobulin (IVIG) injection, the process comprising:

a. determining the KD score of the patient,

b. diagnosing the patient according to the method described herein, and selecting the patient for the administration of IVIG if the patient has a positive KD diagnosis,

c. and selecting the patient for IVIG administration if the patient has a KD score in the high-risk range and the intermediate risk range.
A method according to any one of claims 12, 23, or 34, further comprising monitoring the KD treatment efficacy for patients having KD, the preocess comprising:

a. determining the KD score of the patient,

b. diagnosing the patient according to the method described herein, and selecting the patient for the administration of IVIG if the patient has a positive KD diagnosis,

c. selecting the patient for IVIG administration if the patient has a KD score in the high-risk range and the intermediate risk range, and

d. the effective treatment will result in a decrease in KD score.
A method includes an assay for KD sample process procedure to retain data necessary comprising:

a. measuring each biomarker concentration of a biomarker panel, described herein,

b. in blood, plasma, or serum sample collected from a patient suspected of having KD, and

c. comparing the measured value of each biomarker with the reference values for each biomarker for a control subject, wherein differential expression indicates that the patient has KD. The assay further comprises determining a KD score from these biomarker concentrations of the patient.
A method measuring at least one KD biomarker for calculating KD score by an antibody targets the biomarker, wherein the antibody specifically binds to the biomarker or a fragment of the biomarker containing an antigenic determinant of the biomarker,

a. the antibody is selected from the group consisting of a monoclonal antibody, a polyclonal antibody, a chimeric antibody, a recombinant fragment of an antibody, an Fab fragment, an Fab' fragment, an F(ab') fragment, an F fragment, and an sch, fragment;

b. at least one antibody is selected from the group consisting of an antibody that specifically binds to NT-ProBNP, an antibody that specifically binds to FABP4, an antibody that specifically binds to MMP8, an antibody that specifically binds to CXCL16, an antibody that specifically binds to HGF, an antibody that specifically binds to LIGHT, an antibody that specifically binds to OSM, and an antibody that specifically binds to ST2.