Biomarkers for metabolic syndrome

Abstract

The present disclosure relates to biomarkers of metabolic syndrome. In particular, the present disclosure relates to the field of assessing the risk of metabolic syndrome and its complications. It introduces new biomarkers that can be used to predict metabolic syndrome and complications thereof.

Description

Technical Field

[0001] The present disclosure relates to the field of prognostic biomarkers for metabolic syndrome. The present disclosure provides novel biomarkers, biomarker combinations, and novel uses and methods of the biomarkers of the present invention. Specifically, the present disclosure provides novel uses and methods for evaluating whether a subject is at risk of developing metabolic syndrome or its complications. Methods and uses for detecting the biomarkers and biomarker combinations of the present invention and compositions and kits for implementing the methods and uses described herein are provided. In addition, the present disclosure provides novel devices, device systems, and uses thereof for accurately detecting biomolecules. Background Art

[0002] Metabolic syndrome is a growing global health problem, with approximately 21% of the adult population in China and more than 35% in the United States suffering from the syndrome.

[0003] Metabolic syndrome is a group of interrelated conditions that occur together. These conditions include abdominal obesity, elevated blood pressure, elevated blood sugar levels, elevated triglyceride levels, and low high-density lipoprotein (HDL) cholesterol levels. The presence of at least three of these five conditions constitutes the diagnosis of metabolic syndrome. Metabolic syndrome increases the risk of cardiovascular disease, stroke, and type 2 diabetes. Other serious complications of the syndrome include kidney disease and non-alcoholic fatty liver disease. Patients with metabolic syndrome have twice the risk of developing cardiovascular disease in the next 5 to 10 years as individuals without the syndrome. In addition, metabolic syndrome leads to a 5-fold increased risk of developing type 2 diabetes.

[0004] The criteria for clinical diagnosis of metabolic syndrome include the following thresholds: if consistently measured as 130 / 85 mmHg or more, blood pressure is considered high. An elevated fasting blood glucose level of 100 mg / dL (5.6 mmol / L) or more indicates a high blood glucose level. A triglyceride level of 150 mg / dL (1.7 mmol / L) or more is considered a high level. Low HDL cholesterol levels are defined as less than 40 mg / dL (1.0 mmol / L) in men and less than 50 mg / dL (1.3 mmol / L) in women. Abdominal obesity is measured as an increase in waist circumference and because the threshold depends on race and gender, it is complicated to define a single threshold for it. Therefore, different populations and country-specific thresholds are used for waist circumference. For example, in China and Japan, the recommended threshold for men is 85 cm or more and the threshold for women is 80 cm and 90 cm or more, respectively. The recommended waist circumference thresholds for Europe and North America are 102 cm or more for men and 88 cm or more for women.

[0005] Most people with metabolic syndrome are asymptomatic and therefore undiagnosed. Since metabolic syndrome can lead to serious complications, including cardiovascular disease, stroke, type 2 diabetes, nephropathy and non-alcoholic fatty liver disease, it is crucial to identify patients with the syndrome. Lifestyle interventions that affect diet, weight management and physical activity can significantly reduce the risk of metabolic syndrome and its complications. Therefore, identifying those subjects who are at the greatest risk of metabolic syndrome, its development and occurrence of serious complications, and promoting lifestyle changes in these individuals can help prevent metabolic syndrome and its complications. Early detection of the risk of metabolic syndrome and its complications enables high-risk individuals to have a longer and healthier life.

[0006] The above five clinical conditions are commonly used to diagnose metabolic syndrome. However, for detecting individuals at high risk of developing metabolic syndrome and its complications, more accurate risk assessment and reliable prognostic markers that can be conveniently used in clinical practice are needed.

[0007] Previous attempts to discover easy and reliable biomarkers for metabolic syndrome have not shown markers that correlate with complications of metabolic syndrome and clinical parameters commonly used in diagnosing the syndrome. The present disclosure provides new biomarkers that provide significant improvements in risk assessment for metabolic syndrome by having strong correlations with clinical parameters that make up the diagnosis of metabolic syndrome in addition to complications of metabolic syndrome. Summary of the invention

[0008] The present invention discloses new biomarkers and biomarker combinations for predicting metabolic syndrome and its complications by quantitative lipid molecule concentrations. The inventors have found that each biomarker and biomarker combination show characteristic increases or decreases as described herein in samples obtained from subjects at risk of metabolic syndrome and its complications, and are therefore useful for methods and uses according to the present invention. The biomarkers and biomarker combinations for metabolic syndrome of the present invention are sensitive and specific, and they can be used for diagnosis and prognosis determination in clinical practice.

[0009] Risk determination based on the new biomarkers disclosed herein enables better evaluation of the future onset of metabolic syndrome and its complications. Individuals at risk of developing metabolic syndrome and its complications are identified, even though they have no symptoms and current tests cannot detect elevated risk. This enables early intervention and prevention or delay of the onset of metabolic syndrome and / or its serious complications. Therefore, the present invention discloses a clear advantage and improvement over prior methods currently used to evaluate the risk of metabolic syndrome and its complications.

[0010] Biomarkers disclosed in the present invention and biomarker combinations show strong correlation with the complications of metabolic syndrome and clinical parameters commonly used for diagnosing metabolic syndrome. Compared with the commonly used detection of syndrome using multiple parameters, the present invention provides excellent biomarkers for early detection of metabolic syndrome and enables easy, reliable and early prediction of metabolic syndrome and / or its complications. This will enable earlier intervention, occurrence and suffering from less symptoms and reduce the incidence of disease.

[0011] According to a first aspect of the present disclosure, there is provided a metabolic syndrome marker for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the metabolic marker comprises stearoylsphingosine.

[0012] According to another aspect of the present disclosure, there is provided a use of a reagent for determining the concentration of a metabolic syndrome marker in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0013] (a) assaying a sample from a subject to determine the concentration of a metabolic syndrome marker; and

[0014] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an elevated concentration of a metabolic syndrome marker when compared to the control, wherein the metabolic syndrome marker comprises stearoylsphingosine.

[0015] According to one aspect of the present disclosure, there is provided a combination of metabolic syndrome markers for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine.

[0016] According to one aspect of the present disclosure, there is provided a use of a reagent for determining the concentration of a combination of metabolic syndrome markers in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessment comprises:

[0017] (a) measuring a sample from a subject to determine the concentration of stearoyl sphingosine;

[0018] (b) assaying a sample from the subject to determine the concentration of palmitoylsphingosine; and

[0019] (c) if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine when compared to the control, then determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof.

[0020] According to one aspect of the present disclosure, there is provided a use of one or more reagents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0021] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0022] (b) if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, then determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0023] According to one aspect of the present disclosure, there is provided a use of one or more reagents in preparing a kit, a composition or a preparation for detecting the concentration of stearoylsphingosine, a metabolic syndrome marker, in a sample obtained from a subject, wherein the detection comprises assaying the sample from the subject to determine the concentration of stearoylsphingosine.

[0024] In certain embodiments, the use of one or more agents further comprises comparing the concentration of metabolic syndrome marker sphingosine to a control.

[0025] In certain embodiments, the reagent comprises one or more of any (one or more) standard, control, substance, compound, solution, solvent, medicament, composition, preparation or any combination thereof for the methods and uses disclosed herein. In certain embodiments, the reagent is a combination or mixture of one or more of any standard, control, substance, compound, solution, solvent, medicament, composition and preparation used in the methods and uses disclosed herein.

[0026] In some embodiments, one or more of any components of the reagents are isotopically labeled. In some embodiments, the isotope of the isotopically labeled component is deuterium, 13 C or 15 N. In some embodiments, the agent comprises at least one isotope-labeled marker of metabolic syndrome and / or one or more complications thereof. In some embodiments, the agent comprises at least one deuterium-labeled marker of metabolic syndrome and / or one or more complications thereof. In one embodiment, the agent comprises deuterium-labeled sphingosine. In one embodiment, the agent comprises sphingosine-d7.

[0027] According to one aspect of the present disclosure, there is provided a use of exogenous stearoyl sphingosine in the preparation of a detection reagent, a kit or a device for evaluating the risk of metabolic syndrome and / or one or more complications thereof, wherein the evaluation comprises:

[0028] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0029] (b) if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, then determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0030] According to one aspect of the present disclosure, there is provided a use of exogenous stearoyl sphingosine in preparing a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of stearoyl sphingosine.

[0031] In certain embodiments, the use of exogenous sphingosine further comprises comparing the concentration of sphingosine, a marker of metabolic syndrome, to a control.

[0032] According to one aspect of the present disclosure, an isotope-labeled sphingosine standard for detecting metabolic syndrome markers is provided, wherein the detection comprises measuring a sample from a subject to determine the concentration of sphingosine.

[0033] According to one aspect of the present disclosure, there is provided a use of an isotope-labeled stearoylsphingosine standard in preparing a standard solution, a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of stearoylsphingosine.

[0034] According to one aspect of the present disclosure, there is provided a reagent for quantifying stearoyl sphingosine from a sample obtained from a subject suspected of being at risk for metabolic syndrome and / or one or more complications thereof by liquid chromatography-mass spectrometry (LC-MS), wherein the quantification comprises assaying the sample from the subject to determine the concentration of stearoyl sphingosine.

[0035] According to one aspect of the present disclosure, there is provided a metabolic syndrome marker for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the metabolic marker comprises palmitoylsphingosine.

[0036] According to one aspect of the present disclosure, there is provided a use of a reagent for determining the concentration of a metabolic syndrome marker in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0037] (a) assaying a sample from a subject to determine the concentration of a metabolic syndrome marker; and

[0038] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a decreased concentration of a metabolic syndrome marker when compared to the control, wherein the metabolic syndrome marker comprises palmitoylsphingosine.

[0039] According to one aspect of the present disclosure, there is provided a use of one or more reagents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0040] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0041] (b) if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control, then the subject is determined to have an increased risk of metabolic syndrome and / or one or more complications thereof.

[0042] According to one aspect of the present disclosure, there is provided a use of one or more reagents in preparing a kit, a composition or a preparation for detecting the concentration of palmitoylsphingosine, a metabolic syndrome marker, in a sample obtained from a subject, wherein the detection comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

[0043] In certain embodiments, the use of one or more agents further comprises comparing the concentration of the metabolic syndrome marker palmitoylsphingosine to a control.

[0044] In certain embodiments, the reagent comprises one or more of any (one or more) standard, control, substance, compound, solution, solvent, medicament, composition, preparation or any combination thereof for the methods and uses disclosed in the present invention. In certain embodiments, the reagent is a combination or mixture of one or more of any (one or more) standard, control, substance, compound, solution, solvent, medicament, composition and preparation used in the methods and uses disclosed in the present invention.

[0045] In some embodiments, one or more of any components of the reagents are isotopically labeled. In some embodiments, the isotope of the isotopically labeled component is deuterium, 13 C or 15 N. In some embodiments, the agent comprises at least one isotope-labeled marker of metabolic syndrome and / or one or more complications thereof. In some embodiments, the agent comprises at least one deuterium-labeled marker of metabolic syndrome and / or one or more complications thereof. In one embodiment, the agent comprises deuterium-labeled palmitoylsphingosine. In one embodiment, the agent comprises palmitoylsphingosine-d7.

[0046] According to one aspect of the present disclosure, there is provided a use of exogenous palmitoylsphingosine in the preparation of a detection reagent, a kit or a device for evaluating the risk of metabolic syndrome and / or one or more complications thereof, wherein the evaluation comprises:

[0047] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0048] (b) if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control, then the subject is determined to have an increased risk of metabolic syndrome and / or one or more complications thereof.

[0049] According to one aspect of the present disclosure, there is provided a use of exogenous palmitoylsphingosine in preparing a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of palmitoylsphingosine.

[0050] In certain embodiments, the use of exogenous palmitoylsphingosine further comprises comparing the concentration of palmitoylsphingosine, a marker of metabolic syndrome, with a control.

[0051] According to one aspect of the present disclosure, an isotope-labeled palmitoylsphingosine standard for detecting metabolic syndrome markers is provided, wherein the detection comprises measuring a sample from a subject to determine the concentration of palmitoylsphingosine.

[0052] According to one aspect of the present disclosure, there is provided a use of an isotope-labeled palmitoylsphingosine standard in the preparation of a standard solution, a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of palmitoylsphingosine.

[0053] According to one aspect of the present disclosure, there is provided a reagent for quantifying palmitoylsphingosine from a sample obtained from a subject suspected of being at risk for metabolic syndrome and / or one or more complications thereof by liquid chromatography-mass spectrometry (LC-MS), wherein the quantification comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

[0054] In addition to the above aspects, the present invention relates to a device capable of accurately identifying different molecules with slight differences and determining the abundance of the molecules in a sample, and also provides a device system comprising the device and its use.

[0055] Naturally occurring molecules encompass a wide range of compounds with different chemical structures. Each molecular species or each single molecule can have different physical and chemical properties, requiring specific extraction, separation and detection methods for accurate analysis. The molecular structure of biomolecules differs only in the number and position of double bonds. This makes it difficult to identify a variety of different molecules.

[0056] Currently, methods for accurately determining and quantifying molecules are complex, requiring multiple complex steps, accurate controls and parameter optimization, selection of appropriate detection methods, and accurate data interpretation. In addition, they require sophisticated equipment and a high level of expertise in the people who use them.

[0057] The device of the present invention involves fewer steps and parameters that need to be optimized, thereby simplifying the device and use. The simpler operation and reduced complexity make it easy to learn and become familiar with the device. This expands the possibility of a wider range of uses for accurately detecting a variety of different molecules.

[0058] According to one aspect of the present disclosure, there is provided a device capable of identifying molecules and determining the abundance of said molecules in a sample, wherein the device comprises a detection module and a data processing module.

[0059] In some embodiments, the molecules comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 molecules.

[0060] In some embodiments, the molecule comprises a natural or synthetic molecule, a lipid molecule, a protein molecule, a monosaccharide molecule, a polysaccharide molecule, a fatty acid molecule, a sphingolipid molecule, a phospholipid molecule, a glyceride molecule, a sterol lipid molecule, or any combination thereof. In some embodiments, the molecule comprises at least one sphingolipid. In some embodiments, the molecule comprises stearoylsphingosine and / or palmitoylsphingosine.

[0061] In some embodiments, determining the abundance of a molecule comprises determining the relative or absolute abundance, amount, concentration, level, quantity, or activity of the molecule. The determination can be qualitative or quantitative.

[0062] In some embodiments, the detection module includes, but is not limited to: a biosensor, a spectrometer, an immunoassay system, an enzyme system, a colorimetric system, an electrochemical detector, a nucleic acid amplification system, a microfluidic system, an ion detector, a mass spectrometer, a nuclear magnetic resonance detector, an ultraviolet detector, an ultraviolet / visible light detector, an infrared light detector, a fluorometer, a differential refractometer, a thermal conductivity cell detector, a flame ionization detector, an electron capture detector, a vacuum ultraviolet detector, an evaporative light scattering detector, a chemiluminescent nitrogen detector, a charged aerosol detector, and / or an X-ray detector. In some embodiments, the detection module is capable of detecting one or more chemical, physical, and / or structural properties of a molecule. In some embodiments, the detection module is capable of detecting, including but not limited to: the molecular weight, mass, charge, electromagnetic signal, magnetic field, frequency, flow rate, light absorption, mass-to-charge ratio, light emission, chemiluminescence, luminescence, radiation, energy, speed, momentum, structure, conductivity, solubility, or any combination thereof of a molecule.

[0063] In some embodiments, the data processing module includes processing the data generated by the detection module. In some embodiments, the data processing includes, but is not limited to: interpreting the data generated by the detection module, such as spectral data, identifying molecules, determining or calculating the abundance of molecules and / or comparing the data or the abundance of molecules with a control or reference. In some embodiments, the data processing includes generating metabolic status data of the subject. In some embodiments, the data processing module also includes analyzing the data using a machine learning or artificial intelligence algorithm to generate a predictive model for evaluating the metabolic status data of the subject.

[0064] According to one aspect of the present disclosure, a device system including a device and a user interface is provided.

[0065] In some embodiments, the user interface communicates with the data processing module of the device. In some embodiments, the user interface analyzes and / or displays data processed by the data processing module. In some embodiments, the communication includes transmitting the data to a remote computing system for further analysis, processing and / or storage. In some embodiments, the device system also includes a database or cloud storage for storing, processing and / or analyzing the data.

[0066] In some embodiments, the user interface displays the subject's metabolic status data to the subject or a professional caregiver. In some embodiments, the user interface provides personalized advice or intervention based on the metabolic status data, including but not limited to: dietary advice, exercise plans, medication reminders, or any other guidance or advice.

[0067] In some embodiments, the device system further comprises a wearable component. In some embodiments, the detection module is integrated into the wearable component. In some embodiments, the detection module is integrated into the wearable component, thereby allowing continuous monitoring of the metabolic status data of the subject.

[0068] In some embodiments, the metabolic status data of the subject includes one or more biomarker data and / or one or more parameter data, including but not limited to: body mass index (BMI), age, gender, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, insulin, glycosylated hemoglobin A1c (HbA1c), C-reactive protein (CRP), triglycerides (TG), high-density lipoprotein (HDL), total cholesterol, low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (APOB), apolipoprotein AI (A poAI), apolipoprotein AII (ApoAII), apolipoprotein C (ApoC), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP), N-terminal B-type natriuretic peptide pro (NT-proBNP), cystatin C, creatine kinase (CK), oncogenicity suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein associated phospholipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp (a)), any other lipoprotein subfraction or particle number or any parameter related to glucose level, lipid profile, hormone level or nutritional marker or any combination thereof. In some embodiments, the metabolic status data of the subject includes one or more metabolic markers and / or one or more other biomarkers, parameters and / or health data disclosed in the present invention.

[0069] In some embodiments, the subject's metabolic profile data includes an assessment of the risk of metabolic syndrome and / or one or more complications thereof.

[0070] In some embodiments, the device system further comprises a notification system, wherein the notification system notifies the subject or a professional caregiver if the metabolic status data indicates an abnormality or potential health risk.

[0071] In some implementations, the data processing module performs advanced data analysis and generates processed data based on aggregate data from multiple users.

[0072] According to one aspect of the present disclosure, there is provided a use of a device for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

[0073] According to one aspect of the present disclosure, there is provided a use of a device system for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

[0074] In some embodiments, the one or more metabolic syndrome markers further include palmitoylsphingosine and / or one or more other biomarkers, parameters, and / or health data.

[0075] According to one aspect of the present disclosure, there is provided a use of a device for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

[0076] According to one aspect of the present disclosure, there is provided a use of a device system for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

[0077] In some embodiments, one or more metabolic syndrome markers also include one or more other biomarkers, parameters and / or health data. According to one aspect disclosed in the present invention, there is provided a use of a device for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the use includes:

[0078] (a) using a detection module to detect stearoyl sphingosine in a sample from a subject;

[0079] (b) determining the concentration of stearoyl sphingosine using a data processing module;

[0080] (c) comparing the concentration of stearoyl sphingosine with a control using a data processing module; and

[0081] (d) using a data processing module, if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0082] According to one aspect of the present disclosure, there is provided a use of a device system for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the use comprises:

[0083] (a) using a detection module to detect stearoyl sphingosine in a sample from a subject;

[0084] (b) determining the concentration of stearoyl sphingosine using a data processing module;

[0085] (c) comparing the concentration of stearoyl sphingosine with a control using a data processing module; and

[0086] (d) using a data processing module, if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0087] In some embodiments, the use of evaluating the risk further comprises:

[0088] (a) using a detection module to detect palmitoylsphingosine in a sample from a subject;

[0089] (b) determining the concentration of palmitoylsphingosine using a data processing module;

[0090] (c) comparing the concentration of palmitoylsphingosine to a control using a data processing module; and

[0091] (d) using a data processing module, if the sample comprises a reduced concentration of palmitoylsphingosine when compared to the control, determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof.

[0092] According to one aspect of the present disclosure, there is provided a use of a device for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the use comprises:

[0093] (e) detecting palmitoylsphingosine in a sample from a subject using a detection module;

[0094] (f) determining the concentration of palmitoylsphingosine using a data processing module;

[0095] (g) comparing the concentration of palmitoylsphingosine to a control using a data processing module; and

[0096] (h) using a data processing module, if the sample comprises a reduced concentration of palmitoylsphingosine when compared to the control, determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof.

[0097] According to one aspect of the present disclosure, there is provided a use of a device system for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the use comprises:

[0098] (e) detecting palmitoylsphingosine in a sample from a subject using a detection module;

[0099] (f) determining the concentration of palmitoylsphingosine using a data processing module;

[0100] (g) comparing the concentration of palmitoylsphingosine to a control using a data processing module; and

[0101] (h) using a data processing module, if the sample comprises a reduced concentration of palmitoylsphingosine when compared to the control, determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof.

[0102] According to one aspect of the present disclosure, a composition or kit for evaluating the risk of metabolic syndrome and / or one or more complications thereof, detecting metabolic syndrome markers, or implementing any of the methods or uses disclosed herein is provided, wherein the composition or kit comprises exogenous stearoyl sphingosine.

[0103] According to one aspect of the present disclosure, a composition or kit for evaluating the risk of metabolic syndrome and / or one or more complications thereof, detecting metabolic syndrome markers, or implementing any of the methods or uses disclosed herein is provided, wherein the composition or kit comprises exogenous palmitoylsphingosine.

[0104] In some embodiments, the exogenous stearoyl sphingosine and / or palmitoyl sphingosine comprises isotope-labeled stearoyl sphingosine and / or palmitoyl sphingosine. In some embodiments, the isotope of the isotope-labeled stearoyl sphingosine and / or palmitoyl sphingosine is deuterium, 13 C or 15 N. In some embodiments, the exogenous stearoyl sphingosine and / or palmitoyl sphingosine comprises deuterium-labeled stearoyl sphingosine and / or palmitoyl sphingosine. In one embodiment, the exogenous stearoyl sphingosine and / or palmitoyl sphingosine comprises stearoyl sphingosine-d7 and / or palmitoyl sphingosine-d7.

[0105] In some embodiments, the composition or kit comprises at least one isotope-labeled marker of metabolic syndrome and / or one or more complications thereof. In some embodiments, the isotope of the isotope-labeled marker is deuterium, 13 C or 15 N. In some embodiments, the composition or kit comprises at least one deuterium-labeled marker of metabolic syndrome and / or one or more complications thereof. In one embodiment, the composition or kit comprises deuterium-labeled sphingosine and / or palmitoylsphingosine. In one embodiment, the composition or kit comprises sphingosine-d7 and / or palmitoylsphingosine-d7.

[0106] The composition or kit may also include (one or more) standards, controls, reagents, solutions, solvents, containers, instructions for use, or other elements for practicing the methods or uses disclosed herein.

[0107] In some embodiments, the composition or kit is a combination of any (one or more) standards, controls, reagents, solutions, solvents, containers, instructions for use, or other elements for practicing the methods or uses disclosed herein, which are purchased from commercial manufacturers or prepared in-house in the laboratory, and are used to determine the concentration of stearoylsphingosine and / or palmitoylsphingosine.

[0108] In some embodiments, the composition or kit comprises an element for collecting a blood sample, e.g., a dried blood spot on a filter. In some embodiments, the composition or kit comprises a card for collecting a sample. In some embodiments, the composition or kit comprises a card for collecting a plasma or serum sample.

[0109] In some embodiments, the composition or kit further comprises palmitoyl sphingosine. In some embodiments, the composition or kit comprises isotope-labeled stearoyl sphingosine and / or palmitoyl sphingosine. In some embodiments, the composition or kit comprises deuterium-labeled stearoyl sphingosine and / or palmitoyl sphingosine. In one embodiment, the composition or kit comprises stearoyl sphingosine-d7 and / or palmitoyl sphingosine-d7.

[0110] In some embodiments, the composition or kit further comprises standards, controls, reagents, solutions, solvents, containers, instructions for use, or other elements for detecting other clinical parameters for the methods or uses disclosed herein, such as but not limited to: BMI, age, sex, weight, height, waist circumference, blood pressure, systolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin, and CRP.

[0111] The composition or kit can be a test kit for use in a laboratory or a home test kit. Depending on the circumstances, the composition or kit can be used in a determination implemented by a variety of chemical and high-resolution analytical techniques. Suitable analytical techniques according to the method and use of the present invention include, but are not limited to, mass spectrometry (MS) and nuclear magnetic resonance (NMR). Any high-resolution technology capable of distinguishing each biomarker can be used to collect information about the biomarker in question, such as the concentration of the biomarker spectrum from the biological sample. Typically, information is collected using a mass spectrometer. MS analysis can be coupled with another efficient separation method, such as gas chromatography (GC), two-dimensional gas chromatography (GC×GC), liquid chromatography (LC), two-dimensional liquid chromatography (LC×LC), high performance liquid chromatography (HPLC), ultra-performance liquid chromatography (UPLC) or ultra-high performance liquid chromatography (UHPLC).

[0112] According to one aspect of the present disclosure, a method for detecting stearoyl sphingosine by liquid chromatography-mass spectrometry (LC-MS) is provided, wherein the method comprises one or more of the following steps:

[0113] a. obtaining a sample from a subject,

[0114] b. extracting stearoyl sphingosine from the sample,

[0115] c. separation of stearoyl sphingosine by liquid chromatography (LC), and / or

[0116] d. Determination of sphingosine concentration by mass spectrometry (MS).

[0117] According to one aspect of the present disclosure, a method for detecting palmitoylsphingosine by liquid chromatography-mass spectrometry (LC-MS) is provided, wherein the method comprises one or more of the following steps:

[0118] a. obtaining a sample from a subject,

[0119] b. extracting palmitoylsphingosine from the sample,

[0120] c. separating palmitoylsphingosine by liquid chromatography (LC), and / or

[0121] d. Determination of palmitoylsphingosine concentration by mass spectrometry (MS).

[0122] Additional steps and details for detecting stearoylsphingosine and / or palmitoylsphingosine by LC-MS are described below in the present disclosure.

[0123] According to one aspect of the present disclosure, there is provided a method for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the method comprises:

[0124] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0125] (b) if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, then determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0126] According to one aspect of the present disclosure, there is provided a method for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the method comprises:

[0127] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0128] (b) if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control, then the subject is determined to have an increased risk of metabolic syndrome and / or one or more complications thereof.

[0129] According to one aspect of the present disclosure, there is provided a method for collecting data for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the method comprises:

[0130] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0131] (b) if the sample comprises an elevated concentration of stearoyl sphingosine when compared to the control, then determining that the subject has an elevated risk of metabolic syndrome and / or one or more complications thereof.

[0132] According to one aspect of the present disclosure, there is provided a method for collecting data for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the method comprises:

[0133] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0134] (b) if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control, then the subject is determined to have an increased risk of metabolic syndrome and / or one or more complications thereof.

[0135] In some embodiments, the subject can be treated with a therapy as described herein. For example, therapy can include any therapeutic treatment typically provided to a subject at risk of developing metabolic syndrome and / or one or more of its complications, such as, but not limited to, lifestyle interventions and / or suggestions for dietary changes, weight management and / or physical activity, control of the development of metabolic syndrome and / or one or more of its complications (e.g., by blood glucose and / or blood pressure monitoring, lipid monitoring and control), diabetes medication, cardiovascular disease medication, blood pressure and lipid regulating medication, or any combination thereof, as described in the detailed description disclosed herein.

[0136] In some embodiments, the method for evaluating whether a subject is at risk of developing metabolic syndrome and / or one or more complications thereof further includes, after the determining step, diagnosing the subject as having an increased risk of developing metabolic syndrome and / or one or more complications thereof based on the results in the determining step, and administering treatment to the subject diagnosed as having an increased risk of developing metabolic syndrome and / or one or more complications thereof.

[0137] In one aspect, the present invention discloses a method for treating or preventing metabolic syndrome and / or one or more complications thereof in a subject identified as being at risk of developing metabolic syndrome and / or one or more complications thereof, the method comprising: administering to the subject a treatment as described herein, wherein prior to administering the treatment, the subject is identified as being at risk of developing metabolic syndrome and / or one or more complications thereof by a method described herein.

[0138] The determination of the biomarkers stearoylsphingosine and / or palmitoylsphingosine of the present invention in a biological sample is an unconventional measure of the risk of metabolic syndrome and / or one or more of its complications. In addition, the biomarkers and methods of the present invention generally allow for a sensitive indication of the risk of developing metabolic syndrome and / or one or more of its complications, such as, but not limited to: cardiovascular disease, stroke, and type 2 diabetes. Therefore, the methods of the present invention ensure that, in contrast to the large number of individuals who are at risk of developing such syndromes, but remain unidentified and untreated, subjects at risk of metabolic syndrome and / or one or more of its complications can be correctly identified and treated, and thus they do not have to undergo the possibility of severe complications and / or premature death, as is common in the art.

[0139] Metabolic syndrome can lead to serious complications, so it is beneficial to detect individuals at high risk of developing complications of metabolic syndrome and provide preventive measures and / or treatment. Major complications of metabolic syndrome include, for example, cardiovascular disease and its complications, stroke, type 2 diabetes, kidney disease, and non-alcoholic fatty liver disease.

[0140] In some embodiments, the development of metabolic syndrome and / or one or more complications thereof in a subject is monitored over time by comparing the disclosed biomarker values ​​to previously determined biomarker values ​​in a sample obtained from the same subject.

[0141] In some embodiments, the disclosed methods and uses are used as a screening test to assess a subject's risk of developing metabolic syndrome and / or one or more complications thereof.

[0142] According to one aspect of the present disclosure, there is provided a method for evaluating the effectiveness of a therapy for metabolic syndrome and / or one or more complications thereof in a subject, wherein the method comprises:

[0143] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0144] (b) If the sample comprises a reduced concentration of stearoyl sphingosine when compared to the control, then the therapy is determined to be effective.

[0145] According to one aspect of the present disclosure, there is provided a method for evaluating the effectiveness of a therapy for metabolic syndrome and / or one or more complications thereof in a subject, wherein the method comprises:

[0146] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0147] (b) If the sample comprises an elevated concentration of palmitoylsphingosine when compared to the control, then the treatment is determined to be effective.

[0148] In the method, by analyzing the metabolic syndrome biomarker values ​​as described herein, the effectiveness of therapy is monitored. Biomarker values ​​reflect the development of metabolic syndrome and / or one or more of its complications, and when the subject is to therapy, when the therapy as described herein reacts, the biomarker value is close to the control value. Therefore, therapy can be adjusted based on the subject's response, thereby only showing a positive response, for example, the biomarker concentration is close to the control concentration, and therefore it is believed that effective therapy continues, and stops showing minimal or no response and therefore thinks that invalid therapy.

[0149] In some embodiments, the subject can be treated with a therapy as described herein, and the therapy is gradually increased. For example, the gradually increased therapy may include any therapeutic treatment that is generally provided to a subject at risk of developing metabolic syndrome and / or one or more of its complications, such as but not limited to: lifestyle interventions as described in the detailed description disclosed by the present invention and / or suggestions for affecting dietary changes, weight management and / or physical activity, control of the development of metabolic syndrome and / or one or more of its complications (e.g., by blood sugar and / or blood pressure monitoring, lipid monitoring and control), diabetes medication, cardiovascular disease medication, blood pressure and lipid regulation medication, or any combination thereof.

[0150] In some embodiments, the method for evaluating the effectiveness of a therapy for metabolic syndrome and / or one or more complications thereof in a subject further comprises determining that the therapy is ineffective in the subject based on the results of the determining step and gradually increasing the subject's therapy.

[0151] In one aspect, the present disclosure relates to a method for treating metabolic syndrome and / or one or more complications thereof in a subject identified as being refractory to treatment, the method comprising: administering to the subject an additional treatment as described herein, wherein prior to administering the treatment, the subject has been identified as being refractory to treatment for metabolic syndrome and / or one or more complications thereof by the methods described herein.

[0152] In some embodiments, therapy may include any therapeutic treatment typically provided to subjects at risk for developing metabolic syndrome and / or one or more of its complications, such as, but not limited to: lifestyle interventions and / or advice affecting diet, weight management and physical activity, control of the development of metabolic syndrome and / or one or more of its complications (e.g., blood glucose monitoring, blood pressure and lipid control), diabetes medications, cardiovascular disease medications, blood pressure and lipid regulating medications, or any combination thereof as described in the detailed description of the present disclosure.

[0153] In some embodiments of the above methods, the method of treating metabolic syndrome and / or one or more complications thereof further comprises identifying a subject in need of treatment or prevention, e.g., by requesting testing from, e.g., a commercial laboratory and receiving test results that provide assay results useful for determining biomarker values, and if the subject has an elevated concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine as compared to a control, administering treatment, e.g., a therapeutically effective dose of a drug, to the subject.

[0154] According to one aspect of the present disclosure, a method for assessing the risk of metabolic syndrome and / or one or more complications thereof is provided, wherein assessing the risk comprises using a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value or any combination thereof.

[0155] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0156] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)))+1)]*100,

[0157] Where a is a real number.

[0158] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0159] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)))+1)]*100,

[0160] Where a is a real number.

[0161] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0162] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI))+1)]*100,

[0163] where a and b are real numbers.

[0164] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0165] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c*age))+1)]*100,

[0166] where a, b, and c are real numbers.

[0167] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0168] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c*age))+1)]*100,

[0169] where a, b, and c are real numbers.

[0170] In some embodiments, for males, the intercept is a value of -15 to -9, a is a value of 3.0 to 5.0, b is a value of 0.1 to 0.3, and c is a value of 0.025 to 0.055, and for females, the intercept is a value of -15 to -6, a is a value of 3.0 to 5.0, b is a value of 0.05 to 0.25, and c is a value of 0.020 to 0.050. In some embodiments, for males, the intercept is -11.66, a is 4.30, b is 0.18 and c is 0.040, and for females, the intercept is -10.43, a is 4.01, b is 0.13 and c is 0.036.

[0171] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0172] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c*age+d*sex))+1)]*100,

[0173] where a, b, c, and d are real numbers.

[0174] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0175] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+e*glucose))+1)]*100,

[0176] where a and e are real numbers.

[0177] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0178] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+f*HbA1c))+1)]*100,

[0179] Wherein a and f are real numbers. In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0180] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+e*glucose))+1)]*100,

[0181] where a, b, and e are real numbers.

[0182] In some embodiments, for males, the intercept is a value of -25 to -10, a is a value of 2.00 to 7.00, b is a value of 0.05 to 0.30, and e is a value of 0.50 to 2.50, and for females, the intercept is a value of -25 to -10, a is a value of 1.00 to 6.00, b is a value of 0.01 to 0.15, and e is a value of 1.0 to 3.0. In some embodiments, for males, the intercept is -18.64, a is 4.55, b is 0.15, and e is 1.60, and for females, the intercept is -18.63, a is 3.35, b is 0.07, and e is 2.11.

[0183] In some embodiments of all aspects disclosed herein, assessing the risk of developing metabolic syndrome and / or one or more complications thereof comprises using the following formula:

[0184] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c*age+d*sex+e*glucose+f*HbA1c+g*LDL-cholesterol+h*HDL-cholesterol+i*triglycerides+j*systolic blood pressure+k*insulin+l*CRP))+1)]*100,

[0185] where a, b, c, d, e, f, g, h, i, j, k, and l are real numbers.

[0186] According to another aspect of the present disclosure, there is provided a use of one or more reagents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein assessing the risk comprises using the following formula:

[0187] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c*age+d*sex+e*glucose+f*HbA1c+g*LDL-cholesterol+h*HDL-cholesterol+i*triglycerides+j*systolic blood pressure+k*insulin+l*CRP))+1)]*100,

[0188] where a, b, c, d, e, f, g, h, i, j, k, and l are real numbers.

[0189] In some embodiments of all aspects of the present disclosure, the intercept can be altered based on gender.

[0190] In certain embodiments of all aspects disclosed herein, the formula comprises 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 parameters and / or 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 intercepts, and the parameters are selected from BMI, age, sex, glucose, HbA1c, LDL-cholesterol, HDL-cholesterol, triglycerides, systolic blood pressure, insulin and CRP.

[0191] In certain embodiments of all aspects disclosed herein, assessing the risk of metabolic syndrome and / or one or more complications thereof further comprises determining the concentration of the metabolic syndrome marker palmitoylsphingosine in addition to determining the concentration of the metabolic syndrome marker stearoylsphingosine.

[0192] In certain embodiments of all aspects disclosed herein, assessing the risk of metabolic syndrome and / or one or more complications thereof further comprises, in addition to determining the concentration of metabolic syndrome markers stearoylsphingosine and / or palmitoylsphingosine, detecting other clinical parameters such as, but not limited to: BMI, age, sex, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin and / or CRP. In certain embodiments, at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the following clinical parameters are detected: BMI, age, sex, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin and / or CRP.

[0193] In certain embodiments of all aspects disclosed herein, the method or use further comprises determining the level of one or more other biomarkers or parameters in a sample from a subject, the biomarkers or parameters including but not limited to: triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (ApoB), apolipoprotein AI (ApoAI), apolipoprotein AII (ApoAII), apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), cystatin C, creatine kinase (CK), glycosylated hemoglobin A1c (HbA1c), glucose, oncogenicity suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein-associated phospholipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp(a)), any other lipoprotein subfraction or particle number and / or any combination thereof.

[0194] In certain embodiments of all aspects disclosed herein, the method or use further comprises using one or more other personal information or health data, including but not limited to: gender, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid-lowering therapy or other drug therapy, ethnic background, genetic data, geographic location, history of cardiovascular disease (CVD) and / or cardiovascular (CV) events, family history of CVD and / or CV events, history of diabetes, family history of diabetes, history of other diseases, family history of other diseases, medical imaging data, for example, medical imaging data from angiography or computed tomography (CT), and / or any combination thereof.

[0195] In some embodiments of all aspects disclosed herein, marker combinations can be constructed by linear combinations, regression models, other unsupervised or supervised frequency theory or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimation, decision trees or neural networks. In some embodiments, conversion to a logistic or event time model is implemented in the methods and uses disclosed herein. In some embodiments, conversion to a logarithmic scale is implemented.

[0196] In some embodiments of all aspects disclosed by the invention, the marker combination is a continuous or discontinuous scoring system based on the metabolic syndrome biomarkers disclosed by the invention and / or one or more other biomarkers or parameters disclosed herein. For discontinuous scoring, points can be provided based on intervals, quantiles or other cutoffs with unequal probabilities of a single score component determined according to the same or other populations. In some embodiments of all aspects disclosed by the invention, the risk of metabolic syndrome and / or one or more complications thereof is determined as a percentage.

[0197] In some embodiments of all aspects disclosed herein, the risk of developing metabolic syndrome and / or one or more complications thereof in a subject over a specific time period is evaluated. In some embodiments, the risk is evaluated in the next 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 years.

[0198] In some embodiments of all aspects disclosed herein, one or more complications of metabolic syndrome include, but are not limited to, diabetes (e.g., type 2 diabetes), cardiovascular disease (CVD), cardiovascular (CV) events, such as stroke, major adverse cardiovascular events (MACE), CV death, stable angina, unstable angina, myocardial infarction (MI), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attack, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral arterial disease and different forms of arrhythmia (e.g., atrial fibrillation), nephropathy and / or fatty liver disease (e.g., non-alcoholic fatty liver disease). In some embodiments, one or more complications of metabolic syndrome include diabetes, stroke, cardiovascular disease, and / or cardiovascular events. In some embodiments, one or more complications of metabolic syndrome include diabetes.

[0199] Determination of biomarkers is usually performed using assays. Depending on the circumstances, the assay can be implemented by a variety of chemical and high-resolution analytical techniques. Suitable analytical techniques according to the methods and use of the present invention include, but are not limited to, mass spectrometry (MS) and nuclear magnetic resonance (NMR). Any high-resolution technique capable of distinguishing a single small molecule biomarker can be used to collect information related to the biomarker in question, such as the concentration of biomarkers from the biological sample, such as blood, serum, plasma, tissue, urine or saliva. In some embodiments, information is collected using mass spectrometry or tandem mass spectrometry (MS / MS). MS analysis can be coupled with another efficient separation method, such as gas chromatography (GC), two-dimensional gas chromatography (GC×GC), liquid chromatography (LC), two-dimensional liquid chromatography (LC×LC), high performance liquid chromatography (HPLC), ultra-performance liquid chromatography (UPLC), ultra-high performance liquid chromatography (UHPLC) or coupled to a direct sample injection method, such as an automatic nanoflow ion source device. In certain embodiments, the analysis is performed using LC-MS / MS, HPLC-MS / MS or UHPLC-MS / MS.

[0200] In some embodiments, biomarker concentrations are determined using mass spectrometry, nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry, immunoassays, enzymatic assays, colorimetric assays, fluorometric assays, rapid tests, and / or using binding moieties that are capable of specifically binding to the biomarker.

[0201] The sample and control sample from the subject can be a blood sample, a serum sample, a plasma sample, a blood fraction, a lipid fraction, a saliva sample, a urine sample or a tissue sample. Serum and plasma samples are commonly used. Samples can be prepared using techniques well known in the art.

[0202] In some embodiments, prior to mass spectrometry analysis, a solvent or solvent mixture is used to extract biomarkers from the sample. Suitable solvents include organic solvents, including but not limited to methanol, chloroform, isopropanol, ethyl acetate, other similar solvents, and / or combinations thereof.

[0203] In some embodiments, the biomarkers are derivatized prior to mass spectrometry analysis. In some embodiments, the derivatization comprises extraction with an organic solvent, evaporation of the solvent under reduced pressure, and derivatization.

[0204] In other embodiments, the sample is filtered by using a filter that removes cells before determining the biomarker. In some embodiments, a filter with a cutoff value of 30kDa is used to remove cells. In other embodiments, a filter that removes protein is used. In other embodiments, the sample is reconstituted after filtering. In other embodiments, the sample or the reconstituted sample is diluted before determining the biomarker. In other embodiments, the sample is diluted at least 1:2 before determining the biomarker. In other embodiments, a preservative or a quality internal standard is added to the sample.

[0205] In certain embodiments of all aspects disclosed herein, the methods and uses further comprise the step of adding at least one isotope-labeled biomarker to the sample prior to determining the concentration of the biomarker. Any isotope suitable for detecting the biomarker may be used, including but not limited to hydrogen, carbon, nitrogen and oxygen isotopes, including but not limited to: 2 H (deuterium), 13 C and 15 N. In the methods and uses for determining the concentration of biomarkers, isotope-labeled biomarkers can be used, for example, as internal standards, calibration standards, reference standards and / or in quality control samples. Isotope-labeled biomarkers can be used for both qualitative and quantitative analysis of biomarkers.

[0206] In certain embodiments, at least one deuterium-labeled biomarker of metabolic syndrome and / or one or more complications thereof is added to the sample. In one embodiment, deuterium-labeled sphingosine is added to the sample. In certain embodiments, deuterium-labeled sphingosine includes sphingosine-d7.

[0207] In some embodiments, at least one deuterium-labeled biomarker of metabolic syndrome and / or one or more of its complications is also added to the sample. In one embodiment, deuterium-labeled palmitoylsphingosine is added to the sample. In some embodiments, deuterium-labeled palmitoylsphingosine includes palmitoylsphingosine-d7.

[0208] As described elsewhere in the present disclosure, the control can be a concentration determined from a single healthy individual. The control can also be a sample representing a combination of samples from a general population of healthy individuals. Alternatively, the control can be a control value or data set previously determined, calculated or extrapolated for a biomarker in a sample, or can be yet to be determined, calculated or extrapolated, or can also be taken from the literature.

[0209] In certain embodiments of all aspects disclosed herein, detecting stearoyl sphingosine and / or palmitoyl sphingosine and determining the concentration of stearoyl sphingosine and / or palmitoyl sphingosine may further comprise one or more of the following steps:

[0210] (a) obtaining a sample from a subject,

[0211] (b) extracting lipids (including stearoyl sphingosine and / or palmitoyl sphingosine) from the sample,

[0212] (c) separating the marker stearoyl sphingosine and / or palmitoyl sphingosine by liquid chromatography (LC), and / or

[0213] (d) Determination of the concentration of marker sphingosine and / or palmitoylsphingosine by mass spectrometry (MS).

[0214] In some embodiments, the sample is a human plasma sample or a human serum sample. In some embodiments, the sample volume is 10-200 μL. In some embodiments, 20 μL, 10 μL, or 5 μL of sample is used.

[0215] In some embodiments, a 96-well extraction plate and / or automated lipid extraction is used. In some embodiments, a biomarker of a sample is extracted from a sample using a solvent or a solvent mixture. Suitable solvents include organic and inorganic solvents and solutions, including but not limited to: methanol, ethanol, butanol, chloroform, isopropanol (2-propanol), n-propanol, ethyl acetate, acetone, acetonitrile, n-hexane, isohexane, benzene, cyclohexane, dichloromethane, heptane, diethyl ether, dichloromethane, toluene, water, other polar or non-polar solvents or solutions and / or any mixture or combination thereof. In some embodiments, isopropanol:ethyl acetate is used. In some embodiments, an 8:2 (v / v) ratio of isopropanol:ethyl acetate is used. In some embodiments, one or more internal standards are added to the sample. In some embodiments, one or more internal standards are isotopically labeled. In some embodiments, the isotope of the isotopically labeled standard is deuterium. In some embodiments, the isotope of the isotopically labeled standard is 13 C or 15 N. In some embodiments, the isotope-labeled standard comprises deuterium-labeled sphingosine and / or palmitoylsphingosine. In certain embodiments, the deuterium-labeled standard comprises sphingosine-d7 and / or palmitoylsphingosine-d7.

[0216] In some embodiments, an internal standard is added to the sample along with the extraction solvent. In some embodiments, after the extraction solvent is added, the sample is mixed and centrifuged. In some embodiments, after extraction, the sample extract is placed in a 96-well MS plate.

[0217] Any type of liquid chromatography technique can be used. Suitable LC techniques include, but are not limited to, reverse phase chromatography, normal phase chromatography, ion exchange chromatography, ion chromatography, ion pair chromatography, size exclusion chromatography, and / or affinity chromatography. In some embodiments, reverse phase chromatography, normal phase chromatography, and / or ion exchange chromatography are used.

[0218] Mobile phase solvents suitable for liquid chromatography include any solvents and solutions suitable for liquid chromatography separation of biomarkers disclosed herein, including but not limited to: water, ammonium acetate, methanol, isopropanol (2-propanol), acetonitrile, formic acid, tetrahydrofuran, hexane, n-hexane, pentane, n-pentane, heptane, dichloromethane, ethanol, propanol, ethyl acetate, acetic acid, trifluoroacetic acid, cyclohexane, cyclopentane, benzene, toluene, chloroform, acetone, other organic, inorganic, polar or non-polar solvents or solutions and / or any mixture or combination thereof. In some embodiments, a gradient comprising two or more mobile phase solvents is used. In some embodiments, a gradient of solvent A comprising a solution of ammonium acetate in water with formic acid and solvent B comprising a solution of ammonium acetate in acetonitrile: isopropanol with formic acid is used. In some embodiments, a gradient with solvent A and solvent B is used, wherein solvent A comprises a solution of 1-30 mM ammonium acetate in water with 0.02-0.30% formic acid, and solvent B comprises a solution of 1-30 mM ammonium acetate in acetonitrile:isopropanol with 0.02-0.30% formic acid. In some embodiments, a gradient with solvent A and solvent B is used, wherein solvent A comprises a solution of 10 mM ammonium acetate in water with 0.1% formic acid, and solvent B comprises a solution of 10 mM ammonium acetate in acetonitrile:isopropanol (4:3, v / v) with 0.1% formic acid. In some embodiments, the following gradient with solvents A and B is used: 0 to 0.2-2.0 min, A 5-40% and B 60-95%, 0.2-2.0 to 1.0-6.0 min, B 60-100%, and 1.0-6.0 to 1.5-10 min, A to 5-40% and B to 60-95%. In some embodiments, the following gradient with solvents A and B is used: 0 to 0.5 min, A 15% and B 85%, 0.5 to 1.5 min, B to 100%, 1.5 to 4.0 min, B 100%, and 4.0 to 5.0 min, A to 15% and B to 85%. In some embodiments, there is a gradient of solvent A and solvent B, wherein solvent A comprises a solution of 5 mM ammonium acetate in water with 0.1% formic acid, and solvent B comprises a solution of 5 mM ammonium acetate in acetonitrile: 2-propanol (4:3, v / v) with 0.1% formic acid (FA). In some embodiments, the following gradient is used: hold at 80% B for 0.5 min, linear increase from 80% to 84% in 0.5 min, 84% to 89% B in 1.4 min, 89% to 100% in 0.1 min, hold at 100% B for 2.0 min, 100% to 80% B in 0.1 min, and balance at 80% for 0.4 min. Suitable liquid chromatography conditions and materials include any conditions and materials suitable for liquid chromatography separation of biomarkers disclosed herein.In some embodiments, the injection volume is 1-30 μL, the mobile phase flow rate is 100-2000 μl / min and / or the temperature is 30-90°C. In some embodiments, the injection volume is 5, 10 or 20 μL. In some embodiments, the injection volume is 5 μL, the flow rate is 500 μl / min and / or the temperature is 60°C. Any suitable column can be used, including but not limited to: a reverse phase column, a normal phase column, and an ion exchange column. Any column of suitable size can be used. In some embodiments, a reverse phase column is used. In some embodiments, a silica bonded phase (e.g., C3, C4, C8, and C18) or a polymer phase column is used. In some embodiments, a C18 column is used. In some embodiments, a C18 column of size 2.1×50 mm, id.1.7 μm is used.

[0219] In some embodiments of all aspects disclosed herein, the mass spectrometric determination comprises one or more of the following steps:

[0220] (a) ionizing stearoylsphingosine and / or palmitoylsphingosine to produce ions of stearoylsphingosine and / or palmitoylsphingosine,

[0221] (b) detecting ions of stearoylsphingosine and / or palmitoylsphingosine,

[0222] (c) determining the amount of ions of stearoylsphingosine and / or palmitoylsphingosine; and / or

[0223] (d) determining the concentration of stearoylsphingosine and / or palmitoylsphingosine in the sample based on the amount of stearoylsphingosine and / or palmitoylsphingosine ions.

[0224] In some embodiments, mass spectrometry includes tandem mass spectrometry (MS / MS) and / or liquid chromatography includes high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC) or ultra high performance liquid chromatography (UHPLC). In some embodiments, LC-MS / MS, HPLC-MS / MS or UHPLC-MS / MS are used.

[0225] Any type of mass spectrometer can be used. Suitable MS instruments include, but are not limited to, quadrupole, single quadrupole, triple quadrupole, time-of-flight, quadrupole time-of-flight, ion trap, quadrupole ion trap, sector, sector magnetic field, sector electrostatic field, ion cyclotron, Fourier transform instrument and any combination thereof. Any ionization technique can be used. Suitable ionization techniques include, but are not limited to, electrospray ionization, atmospheric pressure chemical ionization, atmospheric pressure optical ionization, chemical ionization, field ionization, electron bombardment ionization, fast atom bombardment ionization, matrix-assisted laser desorption ionization and any combination thereof.

[0226] In some embodiments, mass spectrometry is performed in positive and / or negative ion mode. In some embodiments, multiple reaction monitoring, multiple precursor ion scanning, and / or neutral loss scanning are used. In some embodiments, selected ion monitoring, total ion chromatogram scanning, and / or extracted ion chromatogram monitoring are used. In some embodiments, electrospray ionization in positive ion mode and multiple reaction monitoring are used.

[0227] Some embodiments of all aspects of the present disclosure are listed below:

[0228] 1. A metabolic syndrome marker for use in assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the metabolic marker comprises stearoyl sphingosine.

[0229] 2. Use of a reagent for determining the concentration of a metabolic syndrome marker in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0230] (a) assaying a sample from a subject to determine the concentration of said metabolic syndrome marker; and

[0231] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an elevated concentration of a metabolic syndrome marker when compared to a control, wherein the metabolic marker comprises stearoylsphingosine.

[0232] 3. A combination of metabolic syndrome markers for use in assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine.

[0233] 4. Use of an agent for determining the concentration of a combination of metabolic syndrome markers in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessment comprises:

[0234] (a) measuring a sample from a subject to determine the concentration of stearoyl sphingosine;

[0235] (b) assaying a sample from the subject to determine the concentration of palmitoylsphingosine; and

[0236] (c) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine when compared to the control.

[0237] 5. Use of one or more agents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0238] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0239] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to the control.

[0240] 6. Use of one or more reagents in the preparation of a kit, composition or preparation for detecting the concentration of stearoylsphingosine, a metabolic syndrome marker, in a sample obtained from a subject, wherein

[0241] The test involves assaying a sample from a subject to determine the concentration of stearoylsphingosine.

[0242] 7. Use of exogenous stearoyl sphingosine in the preparation of a test reagent, a kit or a device for evaluating the risk of metabolic syndrome and / or one or more complications thereof, wherein the evaluation comprises:

[0243] (a) assaying a sample from a subject to determine the concentration of stearoylsphingosine; and

[0244] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to the control.

[0245] 8. Use of exogenous stearoyl sphingosine in the preparation of a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of stearoyl sphingosine.

[0246] 9. An isotope-labeled sphingosine standard for use in detecting metabolic syndrome markers, wherein the detection comprises assaying a sample from a subject to determine the concentration of sphingosine.

[0247] 10. Use of an isotope-labeled sphingosine standard in the preparation of a standard solution, a detection reagent, a kit or a device for detecting a metabolic syndrome marker, wherein the detection comprises measuring a sample from a subject to determine the concentration of sphingosine.

[0248] 11. A reagent for quantifying stearoyl sphingosine from a sample obtained from a subject suspected of being at risk for metabolic syndrome and / or one or more complications thereof by liquid chromatography-mass spectrometry (LC-MS), wherein the quantification comprises assaying the sample from the subject to determine the concentration of stearoyl sphingosine.

[0249] 12. A metabolic syndrome marker for use in assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the metabolic marker comprises palmitoylsphingosine.

[0250] 13. Use of a reagent for determining the concentration of a metabolic syndrome marker in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0251] (a) assaying a sample from a subject to determine the concentration of said metabolic syndrome marker; and

[0252] (b) determining that the subject has elevated metabolic syndrome and / or a metabolic syndrome marker if the sample comprises a decreased concentration of the metabolic syndrome marker when compared to the control.

[0253] or more risks of complications thereof, wherein the metabolic markers include palmitoylsphingosine.

[0254] 14. Use of one or more agents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises:

[0255] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0256] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control.

[0257] 15. Use of one or more reagents in the preparation of a kit, composition or formulation for detecting the concentration of palmitoylsphingosine, a metabolic syndrome marker, in a sample obtained from a subject, wherein

[0258] The detection comprises assaying a sample from a subject to determine the concentration of palmitoylsphingosine.

[0259] 16. Use of exogenous palmitoylsphingosine in the preparation of a detection reagent, a kit or a device for evaluating the risk of metabolic syndrome and / or one or more complications thereof, wherein the evaluation

[0260] include:

[0261] (a) assaying a sample from a subject to determine the concentration of palmitoylsphingosine; and

[0262] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a decreased concentration of palmitoylsphingosine when compared to the control.

[0263] 17. Use of exogenous palmitoylsphingosine in the preparation of a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of palmitoylsphingosine.

[0264] 18. An isotope-labeled palmitoylsphingosine standard for use in detecting metabolic syndrome markers, wherein the detection comprises assaying a sample from a subject to determine the concentration of palmitoylsphingosine.

[0265] 19. Use of an isotope-labeled palmitoylsphingosine standard in the preparation of a standard solution, a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of palmitoylsphingosine.

[0266] 20. A reagent for quantifying palmitoylsphingosine from a sample obtained from a subject suspected of being at risk for metabolic syndrome and / or one or more complications thereof by liquid chromatography-mass spectrometry (LC-MS), wherein the quantification comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

[0267] 21. A device capable of identifying molecules and determining the abundance of said molecules in a sample, wherein said device comprises a detection module and a data processing module.

[0268] 22. A device system, wherein the device system comprises a device according to claim 21, and

[0269] user interface.

[0270] 23. Use of the device according to item 21 for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

[0271] 24. Use of the device system according to item 22 for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

[0272] 25. Use of the device according to item 21 for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

[0273] 26. Use of the device system according to item 22 for detecting one or more metabolic syndrome markers, wherein the use comprises using a detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

[0274] 27. Use of the device according to item 21 for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein said use comprises:

[0275] (a) using the detection module to detect stearoyl sphingosine in a sample from a subject;

[0276] (b) determining the concentration of stearoyl sphingosine using the data processing module;

[0277] (c) comparing the concentration of stearoyl sphingosine with a control using the data processing module; and

[0278] (d) determining, using the data processing module, that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to a control.

[0279] 28. Use of the device system according to item 22 for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein said use comprises:

[0280] (a) using the detection module to detect stearoyl sphingosine in a sample from a subject;

[0281] (b) determining the concentration of stearoyl sphingosine using the data processing module;

[0282] (c) comparing the concentration of stearoyl sphingosine with a control using the data processing module; and

[0283] (d) determining, using the data processing module, that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to a control.

[0284] 29. The use according to item 28, wherein the use for risk assessment further comprises:

[0285] (a) using the detection module to detect palmitoylsphingosine in a sample from a subject;

[0286] (b) determining the concentration of palmitoylsphingosine using the data processing module;

[0287] (c) comparing the concentration of palmitoylsphingosine with a control using the data processing module; and

[0288] (d) determining, using the data processing module, that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a reduced concentration of palmitoylsphingosine when compared to a control.

[0289] 30. Use of the device according to item 21 for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein said use comprises:

[0290] (a) using the detection module to detect palmitoylsphingosine in a sample from a subject;

[0291] (b) determining the concentration of palmitoylsphingosine using the data processing module;

[0292] (c) comparing the concentration of palmitoylsphingosine with a control using the data processing module; and

[0293] (d) determining, using the data processing module, that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a reduced concentration of palmitoylsphingosine when compared to a control.

[0294] 31. Use of the device system according to item 22 for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein said use comprises:

[0295] (a) using the detection module to detect palmitoylsphingosine in a sample from a subject;

[0296] (b) determining the concentration of palmitoylsphingosine using the data processing module;

[0297] (c) comparing the concentration of palmitoylsphingosine with a control using the data processing module; and

[0298] (d) determining, using the data processing module, that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises a reduced concentration of palmitoylsphingosine when compared to a control.

[0299] 32. A composition or kit for assessing the risk of metabolic syndrome and / or one or more complications thereof, for detecting said metabolic syndrome markers, or for implementing any method or use disclosed in any of the above items, wherein said composition or kit comprises exogenous stearoyl sphingosine.

[0300] 33. A composition or kit for assessing the risk of metabolic syndrome and / or one or more complications thereof, for detecting said metabolic syndrome markers, or for implementing any method or use disclosed in any of the above items, wherein said composition or kit comprises exogenous palmitoylsphingosine.

[0301] 34. The composition or kit according to item 32 or 33, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises isotopically labeled stearoylsphingosine and / or palmitoylsphingosine.

[0302] 35. The composition or kit according to any one of items 32 to 34, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises deuterium-labeled stearoylsphingosine and / or palmitoylsphingosine.

[0303] 36. The composition or kit according to any one of items 32 to 35, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0304] 37. The composition or kit according to any one of items 32 to 36, wherein the composition or kit further comprises standards, controls, reagents, solutions, solvents, containers, instructions for use, and / or other elements for carrying out the methods or uses disclosed herein.

[0305] 38. The composition or kit according to any one of items 32 to 37, wherein the composition or kit comprises an element for collecting a blood sample.

[0306] 39. The composition or kit according to item 38, wherein the blood sample is a blood spot dried on a filter or a plasma or serum sample collected on a filter or a card.

[0307] 40. The composition or kit according to any one of items 32 to 39, wherein the composition or kit further comprises standards, controls, reagents, solutions, solvents, containers, instructions for use and / or other elements for detecting one or more clinical parameters for the methods or uses disclosed herein, wherein the one or more clinical parameters comprise BMI, age, sex, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL)

[0308] Cholesterol, insulin and / or CRP.

[0309] 41. The composition or kit according to any of items 32 to 40, wherein the composition or kit is a test kit for use in a laboratory or a home test kit.

[0310] 42. The composition or kit according to any one of items 32 to 41, wherein the composition or kit is a combination of any standards, controls, reagents, solutions, solvents, containers, instructions for use or other elements for practicing the methods or uses disclosed herein, which are purchased from commercial manufacturers or prepared in-house in the laboratory, and are used to determine the concentration of stearoylsphingosine and / or palmitoylsphingosine.

[0311] 43. The composition or kit according to any one of items 32 to 42, wherein the composition or kit is used in mass spectrometry, nuclear magnetic resonance, gas chromatography (GC), two-dimensional gas chromatography (GC×GC), liquid chromatography (LC), two-dimensional liquid chromatography (LC×LC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), ultra high performance liquid chromatography (UHPLC) or any combination thereof.

[0312] 44. A method for detecting stearoyl sphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein

[0313] The method comprises one or more of the following steps:

[0314] (a) obtaining a sample from a subject;

[0315] (b) extracting stearoyl sphingosine from the sample;

[0316] (c) separating sphingosine by liquid chromatography (LC); and / or

[0317] (d) Determination of sphingosine concentration by mass spectrometry (MS).

[0318] 45. A method for detecting palmitoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein

[0319] The method comprises one or more of the following steps:

[0320] (a) obtaining a sample from a subject;

[0321] (b) extracting palmitoylsphingosine from the sample;

[0322] (c) separating palmitoylsphingosine by liquid chromatography (LC); and / or

[0323] (d) The concentration of palmitoylsphingosine was determined by mass spectrometry (MS).

[0324] 46. ​​A method for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein

[0325] Evaluating the risk includes using a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0326] 47. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0327] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)))+1)]*100, where a is a real number.

[0328] 48. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0329] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)))+1)]*100,

[0331] Where a is a real number.

[0332] 49. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0333] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI))

[0334] +1)]*100,

[0335] where a and b are real numbers.

[0336] 50. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0337] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c

[0338] *age))+1)]*100,

[0339] where a, b, and c are real numbers.

[0340] 51. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0341] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*

[0342] BMI+c*age))+1)]*100,

[0343] where a, b, and c are real numbers.

[0344] 52. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0345] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*BMI+c

[0346] *age+d*sex))+1)]*100,

[0347] where a, b, c, and d are real numbers.

[0348] 53. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0349] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+e*glucose))

[0350] +1)]*100,

[0351] where a and e are real numbers.

[0352] 54. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0353] [1 / (exp(-(a*stearoylsphingosine*palmitoylsphingosine^(-1)+f*HbA1c))

[0354] +1)]*100,

[0355] where a and f are real numbers.

[0356] 55. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0357] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*

[0358] BMI+e*glucose))+1)]*100,

[0359] where a, b, and e are real numbers.

[0360] 56. The use or method according to any one of the preceding clauses, wherein evaluating the risk comprises using the following formula:

[0361] [1 / (exp(-(intercept+a*stearoylsphingosine*palmitoylsphingosine^(-1)+b*

[0362] BMI+c*age+d*sex+e*glucose+f*HbA1c+g*LDL-cholesterol+h*HDL-cholesterol+i*triglycerides+j*systolic blood pressure+k*insulin

[0363] +l*CRP))+1)]*100,

[0364] where a, b, c, d, e, f, g, h, i, j, k, and l are real numbers.

[0365] 57. The method or use according to any one of the above clauses, wherein the formula comprises 0, 1,

[0366] 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 parameters and / or 0, 1, 2, 3, 4, 5,

[0367] 6, 7, 8, 9, 10 or 11 intercepts, the parameter being selected from BMI, age, sex, glucose, HbA1c, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-

[0368] - Cholesterol, triglycerides, systolic blood pressure, insulin, and CRP.

[0369] 58. The method or use according to any one of the above clauses, wherein the intercept can be varied based on gender.

[0370] 59. The method or use according to any one of the above clauses, wherein the method or use further comprises palmitoylsphingosine and / or determines the concentration of palmitoylsphingosine.

[0371] 60. The method or use according to any one of the above items, wherein the method or use further comprises detecting at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,

[0372] 15 or 16 clinical parameters, including BMI, age, sex, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin and / or CRP.

[0373] 61. The method or use according to any one of the above items, wherein the method or use further comprises detecting one or more other biomarkers or parameters in a sample from the subject, including triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (ApoB), apolipoprotein AI (ApoAI), apolipoprotein AII (ApoAII), apolipoprotein C (Apo oC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), cystatin C, creatine kinase (CK), glycosylated hemoglobin A1c (HbA1c), glucose, oncogenicity suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein-associated phospholipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp(a)), any other lipoprotein subfraction or particle number, and / or any combination thereof.

[0374] 62. A method or use according to any of the above items, wherein the method or use also includes the use of one or more other personal information or health data, including gender, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid-lowering therapy or other drug therapy, ethnic background, genetic data, geographic location, history of CVD and / or CV events, family history of CVD and / or CV events, history of diabetes, family history of diabetes, history of other diseases, family history of other diseases, medical imaging data, such as medical imaging data from angiography or computed tomography (CT) and / or any combination thereof.

[0375] 63. A method or use according to any one of the above items, wherein the marker combination comprises a linear combination, a regression model, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimation, decision trees and / or neural networks.

[0376] 64. A method or use according to any one of the preceding clauses, wherein a transformation to a logistic model, a time-to-event model or a logarithmic scale is implemented.

[0377] 65. The method or use according to any one of the above clauses, wherein the marker combination comprises a continuous or discontinuous scoring system based on the metabolic syndrome biomarker and / or one or more other biomarkers or parameters.

[0378] 66. A method or use according to any one of the above clauses, wherein the marker combination comprises discontinuous scoring, wherein scores are provided based on intervals, quantiles or other cutoff values ​​with unequal probabilities for individual score components determined according to the same or other populations.

[0379] 67. The method or use according to any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more complications thereof is determined as a percentage.

[0380] 68. The method or use according to any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more complications thereof within a specific time period is assessed.

[0381] 69. A method or use according to any one of the above clauses, wherein the future 1, 2,

[0382] risk of developing metabolic syndrome and / or one or more of its complications within 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 years.

[0383] 70. The method or use according to any one of the above items, wherein the one or more complications of metabolic syndrome include diabetes, such as type 2 diabetes, cardiovascular disease (CVD), cardiovascular (CV) events, stroke, major adverse cardiovascular events (MACE), CV death, stable angina, unstable angina, myocardial infarction (MI), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attack, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral arterial disease and different forms of arrhythmia, such as atrial fibrillation, kidney disease and / or fatty liver disease, such as non-alcoholic fatty liver disease.

[0384] 71. The method or use according to any one of the above clauses, wherein the one or more complications of metabolic syndrome include diabetes, stroke, cardiovascular disease and / or cardiovascular events.

[0385] 72. The method or use according to any one of the above clauses, wherein the one or more complications of metabolic syndrome include diabetes.

[0386] 73. A method or use according to any one of the above items, wherein the method or use comprises the use of mass spectrometry (MS), tandem mass spectrometry (MS / MS), nuclear magnetic resonance (NMR), gas chromatography (GC), two-dimensional gas chromatography (GC×GC), liquid chromatography (LC), two-dimensional liquid chromatography (LC×LC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), ultra high performance liquid chromatography (UHPLC), LC-MS / MS, HPLC-MS / MS, UHPLC-MS / MS, resonance spectroscopy, fluorescence spectroscopy, dual polarization interferometry, immunoassay, enzymatic assay, colorimetric assay, fluorescence assay, rapid test, binding portion capable of specifically binding to the biomarker and / or any combination thereof.

[0387] 74. The method or use according to any one of the above clauses, wherein the sample from the subject and / or the control sample can be a blood sample, a serum sample, a plasma sample, a blood fraction, a lipid fraction, a saliva sample, a urine sample and / or a tissue sample.

[0388] 75. The method or use according to item 74, wherein the blood sample comprises a dried blood spot on a filter and / or the plasma sample and / or the serum sample comprises a plasma or serum sample collected on a filter or a card.

[0389] 76. A method or use according to any one of the above items, wherein the biomarkers of the sample are extracted from the sample using a solvent or a solvent mixture, and wherein the solvent or solvent mixture comprises organic and / or inorganic solvents and solutions, including methanol, ethanol, butanol, chloroform, isopropanol (2-propanol), n-propanol, ethyl acetate, acetone, acetonitrile, n-hexane, isohexane, benzene, cyclohexane, dichloromethane, heptane, diethyl ether, dichloromethane, toluene, water, other polar or non-polar solvents or solutions and / or any mixture or combination thereof.

[0390] 77. The method or use according to item 76, wherein the solvent mixture comprises isopropanol:

[0391] Ethyl acetate.

[0392] 78. The method or use according to item 76 or 77, wherein the solvent mixture comprises isopropanol:ethyl acetate in a ratio of 8:2 (v / v).

[0393] 79. The method or use according to any one of the above clauses, wherein the method or use further comprises adding at least one isotope-labeled standard to the sample before determining the concentration of the biomarker.

[0394] 80. The method or use according to item 79, wherein the at least one isotopically labeled standard comprises hydrogen, carbon, nitrogen and oxygen isotopes such as 2 H (deuterium), 13 C and 15 N.

[0395] 81. The method or use according to item 79 or 80, wherein the isotopically labeled standard is used as an internal standard, a calibration standard, a reference standard and / or in a quality control sample in a qualitative or quantitative analysis.

[0396] 82. The method or use according to any one of items 79-81, wherein at least one deuterium-labelled standard is added to the sample.

[0397] 83. The method or use according to any one of items 79 to 82, wherein deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine is added to the sample.

[0398] 84. The method or use according to any one of items 79 to 83, wherein the deuterium-labeled stearoylsphingosine comprises stearoylsphingosine-d7 and / or the deuterium-labeled palmitoylsphingosine comprises palmitoylsphingosine-d7.

[0399] 85. The method or use of any one of the above clauses, wherein the control comprises a concentration determined from a single healthy individual, a combination of samples representing a general population of healthy individuals, previously determined, calculated or extrapolated, or to be determined, calculated or extrapolated, or a control value or data set obtained from the literature.

[0400] 86. The method or use according to any one of the above clauses, wherein detecting stearoylsphingosine and / or palmitoylsphingosine and / or determining the concentration of the metabolic syndrome marker stearoylsphingosine and / or palmitoylsphingosine further comprises one or more of the following steps:

[0401] (a) obtaining a sample from a subject;

[0402] (b) extracting lipids, including stearoyl sphingosine and / or palmitoyl sphingosine, from the sample;

[0403] (c) separating the marker sphingosine and / or sphingosine by liquid chromatography (LC)

[0404] or palmitoylsphingosine; and / or

[0405] (d) determining the concentration of the marker stearoylsphingosine and / or palmitoylsphingosine by mass spectrometry (MS).

[0406] 87. The method or use according to any one of the preceding clauses, wherein 10-200 μL of the sample is used.

[0407] 88. The method or use according to item 87, wherein 20 μl, 10 μl or 5 μl of the sample is used.

[0408] 89. The method or use according to any one of the above clauses, wherein automated lipid extraction and / or 96-well extraction plates are used.

[0409] 90. The method or use according to any one of the preceding clauses, wherein after adding the extraction solvent, the sample is mixed and centrifuged.

[0410] 91. The method or use according to any one of the above clauses, wherein after extraction, the sample extract is placed in a 96-well MS plate.

[0411] 92. The method or use according to any one of the above clauses, wherein the liquid chromatography comprises reverse phase chromatography, normal phase chromatography, ion exchange chromatography, ion chromatography, ion pair chromatography, size exclusion chromatography and / or affinity chromatography.

[0412] 93. A method or use according to any one of the above items, wherein the liquid chromatography comprises the use of a mobile phase solvent or solution comprising water, ammonium acetate, methanol, isopropanol (2-propanol), acetonitrile, formic acid, tetrahydrofuran, hexane, n-hexane, pentane, n-pentane, heptane, dichloromethane, ethanol, propanol, ethyl acetate, acetic acid, trifluoroacetic acid, cyclohexane, cyclopentane, benzene, toluene, chloroform, acetone, other organic, inorganic, polar or non-polar solvents or solutions and / or any mixture or combination thereof.

[0413] 94. The method or use according to any one of the preceding clauses, wherein the liquid chromatography comprises the use of a gradient comprising two or more mobile phase solvents.

[0414] 95. The method or use according to item 94, wherein the gradient comprises a gradient having solvent A comprising a solution of ammonium acetate in water with formic acid and solvent B comprising a solution of ammonium acetate in acetonitrile:isopropanol with formic acid.

[0415] 96. The method or use according to item 94 or 95, wherein the gradient comprises a gradient having solvent A and solvent B, wherein solvent A comprises a solution of 1-30 mM ammonium acetate in water with 0.02-0.30% formic acid, and solvent B comprises a solution of 1-30 mM ammonium acetate in acetonitrile:isopropanol with 0.02-0.30% formic acid.

[0416] 97. The method or use according to any one of the preceding clauses, wherein the liquid chromatography comprises using an injection volume of 1-30 μL, a mobile phase flow rate of 100-2000 μl / min and / or a temperature of 30-90°C.

[0417] 98. The method or use according to any one of the preceding clauses, wherein the liquid chromatography comprises the use of reverse phase, normal phase and / or ion exchange columns.

[0418] 99. The method or use according to any one of the above clauses, wherein the mass spectrometry comprises one or more of the following steps:

[0419] (a) ionizing stearoylsphingosine and / or palmitoylsphingosine to generate ions of stearoylsphingosine and / or palmitoylsphingosine;

[0420] (b) detecting ions of stearoylsphingosine and / or palmitoylsphingosine;

[0421] (c) determining the amount of ions of stearoylsphingosine and / or palmitoylsphingosine; and / or

[0422] or

[0423] (d) determining the concentration of stearoylsphingosine and / or palmitoylsphingosine in the sample based on the amount of stearoylsphingosine and / or palmitoylsphingosine ions.

[0424] 100. The method or use according to any one of the above items, wherein the mass spectrometry comprises tandem mass spectrometry (MS / MS) and / or the liquid chromatography comprises high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC) or ultra high performance liquid chromatography (UHPLC).

[0425] 101. The method or use according to any one of the above clauses, wherein the LC-MS comprises LC-MS / MS, HPLC-MS / MS and / or UHPLC-MS / MS.

[0426] 102. A method or use according to any one of the above items, wherein the mass spectrometer comprises a quadrupole, a single quadrupole, a triple quadrupole, a time-of-flight, a quadrupole time-of-flight, an ion trap, a quadrupole ion trap, a sector, a sector magnetic field, a sector electrostatic field, an ion cyclotron, a Fourier transformer and / or any combination thereof.

[0427] 103. A method or use according to any one of the above items, wherein the mass spectrometry comprises electrospray ionization, atmospheric pressure chemical ionization, atmospheric pressure optical ionization, chemical ionization, field ionization, electron impact ionization, fast atom bombardment ionization, matrix-assisted laser desorption ionization and / or any combination of their ionization techniques.

[0428] 104. A method or use according to any one of the above items, wherein the mass spectrometry comprises positive and / or negative ion modes, multiple reaction monitoring, multiple precursor ion scanning, neutral loss scanning, selected ion monitoring, total ion chromatogram scanning and / or extracted ion chromatogram monitoring.

[0429] 105. The method or use according to any one of the above clauses, wherein the use of the one or more agents further comprises comparing the concentration of metabolic syndrome markers stearoylsphingosine and / or palmitoylsphingosine with a control.

[0430] 106. The method or use according to any one of the above clauses, wherein the reagent comprises one or more of any standards, controls, substances, compounds, solutions, solvents, agents, ingredients, preparations or any combination thereof used in the methods and uses disclosed herein.

[0431] 107. A method or use according to any one of the above clauses, wherein the reagent comprises a combination or mixture of one or more of any standards, controls, substances, compounds, solutions, solvents, agents, ingredients and preparations used in the methods and uses disclosed herein.

[0432] 108. The method or use according to any one of the preceding clauses, wherein the reagent comprises one or more isotopically labeled components.

[0433] 109. The method or use according to item 108, wherein the one or more isotopically labeled components include deuterium, 13 C or 15 N.

[0434] 110. The method or use according to item 108 or 109, wherein the reagent comprises at least one isotope-labeled metabolic syndrome marker.

[0435] 111. The method or use according to any one of items 108 to 110, wherein the agent comprises at least one deuterium-labeled metabolic syndrome marker.

[0436] 112. The method or use according to any one of items 108 to 111, wherein the agent comprises deuterium-labeled stearoylsphingosine and / or palmitoylsphingosine.

[0437] 113. The method or use according to any one of items 108 to 112, wherein the agent comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0438] 114. A method or use according to any one of the above clauses, wherein the control comprises a formula, a score, an equation, an algorithm, a calculation, a ratio, a sum, a difference, a product, a remainder, a value or any combination thereof.

[0439] 115. The method or use according to any one of the above clauses, wherein the control comprises a value obtained from a sample previously collected from the same subject.

[0440] 116. The method or use according to any one of the preceding clauses, wherein the exogenous stearoyl sphingosine comprises any synthetic or isolated stearoyl sphingosine.

[0441] 117. The method or use according to any one of the preceding clauses, wherein the exogenous stearoyl sphingosine comprises isotopically labeled stearoyl sphingosine.

[0442] 118. The method or use according to any one of the above clauses, wherein the isotope of the isotope-labeled exogenous stearoyl sphingosine is deuterium, 13 C or 15 N.

[0443] 119. The method or use according to any one of the preceding clauses, wherein the exogenous stearoylceramide comprises stearoylceramide-d7.

[0444] 120. The method or use according to any one of the above clauses, wherein the exogenous palmitoylsphingosine comprises any synthetic or isolated palmitoylsphingosine.

[0445] 121. The method or use according to any one of the above clauses, wherein exogenous palmitoylsphingosine

[0446] Includes isotope-labeled palmitoylsphingosine.

[0447] 122. The method or use according to any one of the above clauses, wherein the isotope-labeled

[0448] The isotopes of exogenous palmitoylsphingosine are deuterium, 13 C or 15 N.

[0449] 123. The method or use according to any one of the above clauses, wherein exogenous palmitoylsphingosine

[0450] Includes palmitoylsphingosine-d7.

[0451] 124. The method or use according to any one of the above clauses, wherein the subject previously suffered from

[0452] The subject has metabolic syndrome and / or its complications, is suffering from metabolic syndrome and / or its complications, is suspected of having metabolic syndrome and / or its complications, or is a healthy individual without the above-mentioned signs or symptoms of metabolic syndrome and / or its complications.

[0453] 125. The method or use according to any one of the above items, wherein the subject is or has

[0454] Undergoing treatment, such as diabetes, CVD, blood pressure or lipid-modulating medications, or without any prior treatment or medications.

[0455] 126. A method or use according to any one of the above items, wherein the subject has previously

[0456] Patients with or currently suffering from cardiovascular disease and / or its complications and / or who have been or are currently taking statin therapy.

[0457] 127. The method or use according to any one of the above clauses, wherein the subject previously suffered from

[0458] Have or are currently suffering from type 2 diabetes and / or its complications and have been or are currently undergoing treatment for diabetes.

[0459] 128. The method or use according to any one of the above items, wherein the subject has

[0460] Blood sugar and / or blood pressure levels within the normal range.

[0461] 129. The method or use according to any one of the above clauses, wherein the subject has blood lipid levels, such as triglycerides, high-density lipoprotein cholesterol and / or low-density lipoprotein cholesterol, in the normal range.

[0462] 130. A metabolic syndrome marker, a combination of metabolic syndrome markers, a method or a use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers further comprises one or more other biomarkers, parameters or health data. 131. A metabolic syndrome marker, a combination of metabolic syndrome markers, a method or a use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers comprises a ratio, a sum, a difference, a product, a remainder, a value, a score, a calculation, a formula, an equation, an algorithm or any combination thereof.

[0463] 132. The combination, method or use of metabolic syndrome markers according to any one of the above items, wherein the combination of metabolic syndrome markers comprises stearoylsphingosine / palmitoylsphingosine and / or palmitoylsphingosine / stearoylsphingosine.

[0464] 133. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers also includes one or more other clinical parameters, such as body mass index (BMI), weight, height, age, gender, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin, CRP and / or any combination thereof.

[0465] 134. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers also includes one or more other biomarkers or parameters, such as triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (ApoB), apolipoprotein AI (ApoAI), apolipoprotein AII (ApoAII), apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP),

[0466] N-terminal pro-B-type natriuretic peptide (NT-proBNP), cystatin C, creatine kinase (CK), glycosylated hemoglobin A1c (HbA1c), glucose, oncogenic suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein-associated phospholipase A2

[0467] (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp (a)), any other lipoprotein subfraction or particle number and / or any combination thereof.

[0468] 135. A metabolic syndrome marker, a combination of metabolic syndrome markers, a method or a use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers also includes one or more other personal information or health data, such as gender, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid-lowering therapy or other drug therapy, ethnic background, genetic data, geographic location, history of CVD and / or CV events, family history of CVD and / or CV events, history of diabetes, family history of diabetes, history of other diseases, family history of other diseases, medical imaging data, such as medical imaging data of angiography or computed tomography (CT) and / or any combination thereof.

[0469] 136. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above clauses, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers is constructed by linear combination, regression model, other unsupervised or supervised frequency theory or Bayesian statistical classification or machine learning methods, such as support vector machine, kernel estimation, decision tree and / or neural network.

[0470] 137. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises implementing a conversion to a logistic model or a time-to-event model.

[0471] 138. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises a conversion to a logarithmic scale.

[0472] 139. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers comprises a continuous or discontinuous scoring system based on the metabolic syndrome biomarker and / or one or more any other biomarkers or parameters.

[0473] 140. A metabolic syndrome marker, a combination of metabolic syndrome markers, a method or a use according to any one of the above items, wherein the metabolic syndrome marker or the combination of metabolic syndrome markers comprises providing scores for discontinuous scoring based on intervals, quantiles or other cutoff values ​​with unequal probabilities for each score component determined according to the same or other populations.

[0474] 141. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use according to any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more complications thereof is determined as a percentage.

[0475] 142. The device according to item 21, wherein the molecule comprises at least 1, 2, 3, 4, 5,

[0476] 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 molecules.

[0477] 143. The device according to item 21, wherein the molecule comprises a natural or synthetic molecule, a lipid molecule, a protein molecule, a monosaccharide molecule, a polysaccharide molecule, a fatty acid molecule, a sphingolipid molecule, a phospholipid molecule, a glyceride molecule, a sterol lipid molecule or any combination thereof.

[0478] 144. The device according to item 21, wherein said molecules comprise at least one sphingolipid.

[0479] 145. The device according to item 21, wherein the molecule comprises stearoylsphingosine and / or palmitoylsphingosine.

[0480] 146. An apparatus according to item 21, wherein the determination is qualitative or quantitative.

[0481] 147. An apparatus according to item 21, wherein determining the abundance of the molecule comprises determining the relative or absolute abundance, amount, concentration, level, quantity or activity of the molecule.

[0482] 148. The device according to item 21, wherein the detection module comprises a biosensor, a spectrometer, an immunoassay system, an enzyme system, a colorimetric system, a nucleic acid amplification system, a microfluidic system, an ion detector, a mass spectrometer, a nuclear magnetic resonance detector, an ultraviolet detector, an ultraviolet /

[0483] Visible light detector, fluorometer, differential refractometer, thermal conductivity cell detector, flame ionization detector, electron capture detector, vacuum ultraviolet detector, evaporative light scattering detector, chemiluminescent nitrogen detector, charged aerosol detector and / or X-ray detector.

[0484] 149. An apparatus according to item 21, wherein the detection module is capable of detecting one or more chemical, physical and / or structural properties of a molecule.

[0485] 150. The device according to item 21, wherein the detection module is capable of detecting the molecular weight, mass, charge, electromagnetic signal, magnetic field, frequency, flow rate, light absorption, mass-to-charge ratio, light emission, chemiluminescence, luminescence, radiation, energy, structure, conductivity, solubility or any combination thereof of a molecule.

[0486] 151. An apparatus according to item 21, wherein the data processing module includes processing data generated by the detection module.

[0487] 152. An apparatus according to item 21, wherein the data processing includes interpreting data generated by the detection module, such as spectral data, identifying molecules, determining or calculating the abundance of the molecules and / or comparing the data or the abundance of the molecules with a control or reference.

[0488] 153. The apparatus according to item 21, wherein the data processing comprises generating a metabolic profile of the subject.

[0489] Status data.

[0490] 154. The apparatus according to item 21, wherein the data processing module further comprises analyzing the data using a machine learning or artificial intelligence algorithm to generate a predictive model for evaluating the subject's metabolic status data.

[0491] 155. The device system according to item 22, wherein the user interface is connected to the data processing of the device

[0492] Module communication.

[0493] 156. The device system according to item 22, wherein the user interface analyzes and / or displays the

[0494] The data processed by the data processing module.

[0495] 157. The device system according to item 22, wherein the communication comprises transmitting data to a remote

[0496] The computing system is used for further analysis, processing and / or storage.

[0497] 158. The device system according to item 22, wherein the device system further comprises a database or cloud

[0498] Storage is used to store, process and / or analyze the data.

[0499] 159. The device system according to item 22, wherein the user interface provides a user interface to the subject or a professional caregiver.

[0500] The metabolic status data of the subjects are displayed to the personnel.

[0501] 160. The device system according to item 22, wherein the user interface is based on the metabolic status data

[0502] Provide personalized advice or interventions, such as dietary recommendations, exercise plans, medication reminders, and / or any other guidance or advice.

[0503] 161. The device system of item 22, wherein the device system further comprises a wearable component.

[0505] 162. An apparatus system according to item 22, wherein the detection module is integrated into the wearable component.

[0506] 163. The device system according to item 22, wherein the detection module is integrated into the wearable component, thereby allowing continuous monitoring of the subject's metabolic status data.

[0507] 164. The device system according to item 22, wherein the metabolic status data of the subject comprises one or more biomarker data and / or one or more parameter data, such as body mass index (BMI), age, gender, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, insulin, glycosylated hemoglobin A1c (HbA1c), C-reactive protein (CRP), triglycerides (TG), high-density lipoprotein (HDL), total cholesterol, low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (APOB), apolipoprotein A I (ApoAI), apolipoprotein AII (ApoAII), apolipoprotein C (ApoC), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), cystatin C, creatine kinase (CK), oncogenicity suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein-associated phospholipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp(a)), any other lipoprotein subfraction or particle number or any parameter related to glucose level, lipid profile, hormone level or nutritional marker or any combination thereof.

[0508] 165. The device system according to item 22, wherein the metabolic status data of the subject comprises one or more metabolic markers and / or one or more other biomarkers, parameters and / or health data disclosed herein.

[0509] 166. The device system according to item 22, wherein the metabolic status data of the subject comprises an assessment of the risk of metabolic syndrome and / or one or more complications thereof.

[0510] 167. The device system according to item 22, wherein the device system further comprises a notification system, wherein if the metabolic status data indicates an abnormality or potential health risk, the notification system notifies the subject or a professional caregiver.

[0511] 168. An apparatus system according to item 22, wherein the data processing module performs advanced data analysis and generates processed data based on aggregate data from multiple users.

[0512] 169. The use according to item 23 or 24, wherein the one or more metabolic syndrome markers further comprise palmitoylsphingosine and / or one or more other biomarkers, parameters and / or health data.

[0513] 170. The use according to any one of items 23 to 26, wherein said one or more metabolic markers further comprises one or more other biomarkers, parameters and / or health data. DETAILED DESCRIPTION

[0514] Reference will now be made in detail to various exemplary embodiments, examples of which are discussed in the detailed description that follows. It should be understood that the following detailed description is provided to provide the reader with a more comprehensive understanding of certain embodiments, features and details of aspects of the invention, and should not be construed as limiting the scope of the invention.

[0515] abbreviation

[0516] Unless otherwise indicated, the abbreviations used in the description of the present invention have the following meanings: ACE-angiotensin converting enzyme, ACS-acute coronary syndrome, AMI-acute myocardial infarction, ApoB-apolipoprotein B, ApoAI-apolipoprotein AI, ApoAII-apolipoprotein AII, ApoC-apolipoprotein C, ARB-angiotensin II receptor blocker, AUC-area under the curve, β-regression coefficient, BMI-body mass index, BNP-B-type natriuretic peptide, bpsys-systolic blood pressure, CAD-coronary artery disease, CETP-cholesterol ester transfer protein, CHD-coronary heart disease, CI-confidence interval, CK - Creatine kinase, CKD - ​​chronic kidney disease, CRP - C-reactive protein, CT - computed tomography, CV - cardiovascular, CVD - cardiovascular disease, DM2 - type 2 diabetes mellitus, DPP-4 - dipeptidyl peptidase-4, EI - electron ionization, FA - fatty acid, FLD - fatty liver disease, GC - gas chromatography, GC×GC - two-dimensional gas chromatography, GDF15 - growth differentiation factor 15, GLP-1 - glucagon-like peptide 1, HbA1c - glycosylated hemoglobin, hemoglobin A1c, HDL - high-density lipoprotein, HDL-C - high-density lipoprotein cholesterol, HDL-P - high-density lipoprotein particles, HMG-CoA -3-hydroxy-3-methylglutaryl-CoA, HPLC-high performance liquid chromatography, IHD-ischemic heart disease, LC-liquid chromatography, LC×LC-two-dimensional liquid chromatography, LC-MS-liquid chromatography-mass spectrometry, LDL-low-density lipoprotein, LDL-C-low-density lipoprotein cholesterol, LDL-P-low-density lipoprotein particles, Lp(a)-lipoprotein(a), Lp-PLA2-lipoprotein-associated phospholipase A2, MACE-major adverse cardiovascular event, MI-myocardial infarction, MRM-multiple reaction monitoring, MS-mass spectrometry, MS / MS-tandem mass spectrometry, NAFL-nonalcoholic fatty liver disease, NAFLD-nonalcoholic Fatty liver disease, NASH-nonalcoholic steatohepatitis, NMR-nuclear magnetic resonance, NT-proBNP-N-terminal pro-B-type natriuretic peptide, OR-odds ratio, PCSK9-proprotein convertase subtilisin / kexin type 9, SGLT2-sodium-glucose transporter, St2-suppressor of carcinogenesis 2, TC-total cholesterol, T2D-type 2 diabetes, TG-triglycerides, TMAO-trimethylamine-N-oxide, TNI or TnI-troponin I, TNT or TnT-troponin T, UHPLC-ultra-high performance liquid chromatography, UPLC-ultra-high performance liquid chromatography, waist-waist circumference.

[0517] definition

[0518] In order to make the present disclosure more easily understood, certain terms are first defined. Other definitions are set forth throughout the present description.

[0519] As used herein, "metabolic syndrome" includes, but is not limited to, a group of interrelated, co-occurring conditions including abdominal obesity, elevated blood pressure, elevated blood sugar levels, elevated triglyceride levels, and low HDL cholesterol levels. The presence of at least three of these five conditions constitutes the diagnosis of metabolic syndrome. Metabolic syndrome increases the risk of cardiovascular disease, stroke, and type 2 diabetes. Other serious complications of the syndrome include nephropathy and nonalcoholic fatty liver disease.

[0520] As used herein, "complications of metabolic syndrome" or "metabolic syndrome complications" include, but are not limited to, diabetes (such as type 2 diabetes), cardiovascular disease (CVD), cardiovascular (CV) events, such as stroke, major adverse cardiovascular events (MACE), CV death, stable angina, unstable angina, myocardial infarction (MI), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attack, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral arterial disease and different forms of arrhythmia (such as atrial fibrillation), kidney disease and / or fatty liver disease (such as non-alcoholic fatty liver disease).

[0521] As used herein, "abdominal obesity" refers to an increase in waist circumference. The threshold value for waist circumference increase depends on race and gender, and therefore uses different populations and country-specific threshold values. For example, in China and Japan, the threshold value for male recommendations is 85 cm or more and the threshold value for females is 80 cm and 90 cm or more, respectively. The threshold value for waist circumference recommended in Europe and North America is 102 cm or more for males and 88 cm or more for females.

[0522] As used herein, "elevated blood pressure" includes measurements of 130 / 85 mmHg or above. Different population and country specific thresholds may also be used.

[0523] As used herein, "elevated blood glucose levels" include fasting blood glucose levels of 100 mg / dL (5.6 mmol / L) or higher. Different population and country specific thresholds may also be used.

[0524] As used herein, "elevated triglyceride (TG) levels" include levels of 150 mg / dL (1.7 mmol / L) or higher. Different population and country specific thresholds may also be used.

[0525] As used herein, "low high-density lipoprotein (HDL) cholesterol levels" include levels less than 40 mg / dL (1.0 mmol / L) in men and less than 50 mg / dL (1.3 mmol / L) in women. Different population and country-specific thresholds may also be used.

[0526] As used herein, "diabetes" (diabetes or diabetes mellitus) is a chronic condition in which the body does not produce enough insulin or does not use insulin properly. This results in elevated blood sugar levels. There are three main types of diabetes: type 1 diabetes, type 2 diabetes, and gestational diabetes. In the present disclosure, "diabetes" and "type 2 diabetes" are used interchangeably.

[0527] The terms "type 2 diabetes" (T2D or DM2) are used interchangeably herein to refer to the most common type of diabetes. Type 2 diabetes is a condition in which the body becomes resistant to insulin and gradually loses the ability to produce adequate amounts of insulin.

[0528] As used herein, "cardiovascular disease (CVD)" has its ordinary meaning in the art, and it is used to classify a variety of conditions that affect the heart, heart valves, blood, and vasculature of the body, including coronary artery disease (CAD). CVD may or may not include atherosclerosis.

[0529] As used herein, "coronary artery disease (CAD)", also known as "coronary heart disease (CHD)" and "ischemic heart disease (IHD)" is characterized by atherosclerosis in the coronary arteries. Atherosclerotic plaques narrow the lumen of the coronary arteries, thereby reducing blood flow to the heart. When oxygen-rich blood flow to the heart is reduced or blocked, angina or myocardial infarction can occur.

[0530] In the present disclosure, "cardiovascular (CV) events" include stable angina, unstable angina, myocardial infarction (MI), acute myocardial infarction (AMI), acute coronary syndrome (ACS), stroke, transient ischemic attack, deep vein thrombosis, heart failure, hospitalization for heart failure and cardiovascular death, peripheral arterial disease (also known as peripheral arterial disease) and different forms of arrhythmia, such as atrial fibrillation. These events can include atherosclerosis.

[0531] As used herein, "stroke" includes a condition in which blood flow to the brain is interrupted or reduced, causing parts of the brain to stop functioning properly due to cell death. The 2 main types of stroke are ischemic stroke and hemorrhagic stroke. Ischemic stroke is caused by a lack of blood flow to the brain, while hemorrhagic stroke is caused by bleeding. A stroke is a medical emergency, and rapid treatment is essential. Early action can reduce brain damage and other complications.

[0532] As used herein, "nephropathy" includes both acute and chronic kidney conditions and diseases. Chronic kidney disease, also referred to as chronic kidney disease or CKD, is a condition characterized by the gradual loss of renal function over time. Chronic kidney disease includes conditions that damage the kidneys and reduce their ability to filter waste from the blood. If nephropathy worsens, waste can accumulate to high levels in the blood and cause serious conditions. Complications such as cardiovascular disease, hypertension, anemia, bone fragility, poor nutritional health and nerve damage can occur due to prolonged nephropathy. These problems can occur slowly over a long period of time. Early detection and treatment can usually prevent chronic kidney disease from worsening. When nephropathy develops, it can eventually lead to renal failure, which requires dialysis or kidney transplantation to maintain life.

[0533] As used herein, "fatty liver disease" or "FLD" includes a condition in which excess fat accumulates in the liver. The 2 main types of fatty liver disease are alcoholic fatty liver disease and non-alcoholic fatty liver disease (NAFLD). As used herein, "alcoholic fatty liver disease" is a fatty liver disease related to severe alcohol use. As used herein, "non-alcoholic fatty liver disease" or "NAFLD" is a series of fatty liver conditions not related to severe alcohol use. The early stages of NAFLD can be asymptomatic, but if not detected and controlled, NAFLD can develop into severe liver damage. NAFLD can develop from a harmless fatty liver stage (fatty degeneration) to non-alcoholic steatohepatitis (NASH, a more severe form of NAFLD), and eventually develop into fibrosis, cirrhosis, liver failure and liver cancer. As used herein, "non-alcoholic steatohepatitis" or "NASH" is a serious fatty liver condition in which the liver is usually inflamed.

[0534] The terms "subject", "host", "patient" and "individual" are used interchangeably herein to refer to any mammalian subject, particularly a human, for whom prognosis, diagnosis or therapy is desired. The subject may have previously suffered from or is suffering from metabolic syndrome and / or its complications, may be suspected of suffering from metabolic syndrome and / or its complications, or the subject may be a healthy individual without the above-mentioned signs or symptoms of metabolic syndrome and / or its complications.

[0535] The subject may be or may have been undergoing treatment, such as but not limited to: diabetes, CVD, blood pressure or lipid regulating medication, or may not have had any prior treatment or medication.

[0536] The subject may have previously suffered from or is suffering from cardiovascular disease and / or its complications and may be undergoing or is currently taking statin therapy. The subject may have previously suffered from or is suffering from type 2 diabetes and / or its complications and may be undergoing or is currently taking diabetes treatment.

[0537] In some embodiments of the above methods and uses disclosed in the present invention, the subject has a blood glucose level in the normal range. For example, in some embodiments, the blood glucose level of the subject includes a hemoglobin A1c level of about 5.7% or less, such as about 5.5% or less, such as about 5.0% or less. In some embodiments, the subject has a fasting blood glucose of about 100 mg / dL or less when waking up. In some embodiments, the subject has a pre-meal glucose level of about 70 mg / dL to about 99 mg / dL. In some embodiments, the subject has a glucose level of about 140 mg / dL or less about 2 hours after a meal. Typically, the subject has a fasting venous plasma glucose concentration of less than 6.1 mmol / L (110 mg / dL).

[0538] In some embodiments of the above methods and uses disclosed in the present invention, the subject has a blood pressure level within the normal range.

[0539] In some embodiments of the above methods and uses disclosed in the present invention, the subject has blood lipid levels within a normal range, such as but not limited to: triglyceride levels, high-density lipoprotein cholesterol content and / or low-density lipoprotein cholesterol content.

[0540] As used herein, "statin" is a class of lipid-lowering drug therapy (HMG-CoA reductase inhibitors). The statin is selected from atorvastatin, cerivastatin, fluvastatin, fluvastatin XL, lovastatin, pitavastatin, pravastatin, rosuvastatin and simvastatin or a combination thereof.

[0541] As used herein, a "sample" is a biological sample obtained from a subject or a group or colony of subjects. The sample can be a blood sample, a serum sample, a plasma sample, a saliva sample, a tissue sample, a urine sample, or a portion thereof. Serum and plasma samples are typical. Samples can be prepared using techniques well known in the art. In some embodiments, a blood sample is a blood spot dried on a filter, a card, or other medium. In some embodiments, a plasma or serum sample is collected on a filter, a card, or other medium.

[0542] As used herein, "control" can be a control sample. A control can also be a concentration determined according to a sample from a single healthy individual. A control can also be a sample representing a combination of samples from a general population of healthy individuals. Alternatively, a control can be a control value or data set previously determined, calculated or extrapolated for a biomarker in a sample, or can be yet to be determined, calculated or extrapolated, or can also be taken from a document. A control can also be a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0543] As used herein, control, i.e., control value or control sample, generally represents a subject group or subject population. In this context, "representative" means the biomarker concentration reflected by the control value, and the comparison with the control value in the context disclosed by the present invention corresponds to the average concentration value of the biomarker concentration in the corresponding single sample of the subject from the group or group. Similarly, for control samples, "representative" means the biomarker concentration in the control sample, and the comparison with the control sample in the context disclosed by the present invention corresponds to the average concentration of the biomarker concentration in the corresponding single sample of the subject from the group or group. Typically, the concentration of all biomarker concentrations in the control sample corresponds to the average concentration of the biomarker concentration in the corresponding single sample of the subject from the group or group. For the purposes disclosed by the present invention, it can be considered that the individual with these values ​​is a "healthy individual".

[0544] If the control sample is obtained from the same type of biological tissue or source in the same or substantially the same manner, the control sample can be particularly suitably compared to the subject sample. For example, if the subject sample is a serum sample or a plasma sample, the corresponding control sample will also be a serum sample or a plasma sample, respectively.

[0545] In some embodiments of the methods and uses described herein, the control may be a control value. The control value may be obtained from a sample previously collected from the same subject.

[0546] It will be understood that for the purposes of the present disclosure, useful control values ​​are generally values ​​that have been or were obtained using any of the suitable control samples described herein.

[0547] As used herein, "metabolic syndrome marker", "marker of metabolic syndrome", "metabolic syndrome biomarker", "biomarker of metabolic syndrome", "metabolic marker", "marker disclosed in the present invention", "biomarker disclosed in the present invention" or similar terms include at least one biomarker of metabolic syndrome and / or one or more complications thereof, which includes stearoylsphingosine and / or palmitoylsphingosine as disclosed in the present disclosure. "Metabolic syndrome marker", "marker of metabolic syndrome", "metabolic syndrome biomarker", "biomarker of metabolic syndrome", "metabolic marker", "marker disclosed in the present invention", "biomarker disclosed in the present invention" or similar terms can be used interchangeably in the present disclosure.

[0548] As used herein, "a combination of metabolic syndrome markers", "a combination of metabolic syndrome markers", "a combination of markers", "a combination of metabolites", "a combination of biomarkers", "a combination of biomarkers" or similar terms include a combination of at least one metabolic syndrome and / or one or more of its complications and / or one or more other biomarkers, parameters or health data. As used herein, the combination can be, for example, a ratio, a sum, a difference, a product, a remainder, a value, a score, a calculation, a formula, an equation, an algorithm or any combination thereof. In one embodiment, the combination includes stearoylsphingosine and / or palmitoylsphingosine. In one embodiment, the combination includes stearoylsphingosine / palmitoylsphingosine or palmitoylsphingosine / stearoylsphingosine. "A combination of metabolic syndrome markers", "a combination of metabolic syndrome markers", "a combination of markers", "a combination of metabolites", "a combination of biomarkers" or similar terms may be used interchangeably in the present disclosure.

[0549] In certain embodiments, metabolic syndrome markers and / or metabolic syndrome marker combinations include one or more other clinical parameters in addition to stearoylsphingosine and / or palmitoylsphingosine, such as but not limited to: BMI, weight, height, age, sex, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1c, low-density lipoprotein (LDL) cholesterol, insulin, CRP and / or any combination thereof.

[0550] In certain embodiments, the metabolic syndrome marker and / or metabolic syndrome marker combination further comprises one or more other biomarkers or parameters, including but not limited to triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein particles (LDL-P), high-density lipoprotein particles (HDL-P), apolipoprotein B (ApoB), apolipoprotein AI (ApoAI), apolipoprotein AII (ApoAII), apolipoprotein C (ApoC), C -reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or TnI), B-type natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), cystatin C, creatine kinase (CK), glycosylated hemoglobin A1c (HbA1c), glucose, oncogenicity suppressor gene 2 (St2), galectin, trimethylamine-N-oxide (TMAO), lipoprotein-associated phospholipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF15), lipoprotein (a) (Lp(a)), any other lipoprotein subfraction or particle number, and / or any combination thereof.

[0551] In certain embodiments, the metabolic syndrome marker and / or metabolic syndrome marker combination also includes one or more other personal information or health data, including but not limited to: gender, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid-lowering therapy or other drug therapy, ethnic background, genetic data, geographic location, history of CVD and / or CV events, family history of CVD and / or CV events, history of diabetes, family history of diabetes, history of other diseases, family history of other diseases, medical imaging data, for example, medical imaging data from angiography or computed tomography (CT), and / or any combination thereof.

[0552] In some embodiments of all aspects disclosed by the present invention, metabolic syndrome markers and / or marker combinations can be constructed by linear combination, regression model, other unsupervised or supervised frequency theory or Bayesian statistical classification or machine learning methods, such as support vector machine, kernel estimation, decision tree or neural network. In some embodiments, a conversion to logic (risk=(exp(r) / 1+exp(r))*100) or event time model (time-to-event model) is implemented. In some embodiments, a conversion to logarithmic scale is implemented.

[0553] In some embodiments of all aspects disclosed by the invention, metabolic syndrome markers and / or marker combinations are continuous or discontinuous scoring systems based on metabolic syndrome biomarkers disclosed by the invention and / or one or more other biomarkers or parameters disclosed herein. For discontinuous scoring, points can be provided based on intervals, quantiles or other cutoffs with unequal probabilities of a single score component determined according to the same or other populations. In some embodiments of all aspects disclosed by the invention, the risk of metabolic syndrome and / or one or more complications thereof is determined as a percentage.

[0554] The term "biomarker value" or "marker value" as used herein refers to a value determined by quantifying the amount, abundance, level, concentration, quantity or activity of a biomarker within a sample as defined herein.

[0555] As used herein, "stearoyl sphingosine" includes N-stearoyl-D-sphingosine.

[0556] As used herein, "palmitoylsphingosine" includes N-palmitoyl-D-sphingosine.

[0557] As used herein, "exogenous stearoyl sphingosine" includes any synthetic or isolated stearoyl sphingosine used in the methods and uses disclosed herein and not derived from a sample from a subject. In some embodiments, the exogenous stearoyl sphingosine is isotopically labeled. In some embodiments, the isotope of the isotopically labeled exogenous stearoyl sphingosine is deuterium, 13 C or 15 N. In some embodiments, the exogenous sphingosine is sphingosine-d7.

[0558] As used herein, "exogenous palmitoylsphingosine" includes any synthetic or isolated palmitoylsphingosine used in the methods and uses disclosed herein and not derived from a sample from a subject. In some embodiments, the exogenous palmitoylsphingosine is isotopically labeled. In some embodiments, the isotope of the isotopically labeled exogenous palmitoylsphingosine is deuterium, 13 C or 15 N. In some embodiments, the exogenous palmitoylsphingosine is palmitoylsphingosine-d7.

[0559] As used herein, "stearoyl sphingosine-d7" includes N-stearoyl-D-sphingosine-d7.

[0560] As used herein, "palmitoylsphingosine-d7" includes N-palmitoyl-D-sphingosine-d7.

[0561] In the present disclosure, "treatment" and "therapy" are used interchangeably and may include any therapeutic treatment typically provided to a subject at risk of developing metabolic syndrome and / or one or more of its complications, or a subject with metabolic syndrome and / or one or more of its complications, such as, but not limited to: lifestyle intervention and / or advice affecting diet, weight management and / or physical activity, control of the development of metabolic syndrome and / or one or more of its complications (e.g., blood glucose monitoring, blood pressure and lipid control), diabetes medications (e.g., insulin, metformin, GLP-1 analogs, DPP-4 inhibitors, SGLT2 inhibitors, sulfonylureas, meglitinides, thiazolidinediones and alpha-glucosidase inhibitors), blood pressure medications (e.g., diuretics, beta-blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), calcium channel blockers, alpha-blockers, alpha-beta-blockers, central nervous system agonists (CNS), sedatives, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids, steroids agonists), alpha-2 receptor agonists, peripheral adrenergic inhibitors, vasodilators, aldosterone receptor antagonists and direct renin inhibitors), lipid-modulating drug therapy (e.g., statins, other HMG-CoA reductase inhibitors, niacin (nicotinic acid), cholesterol absorption inhibitors, cholesteryl ester transfer protein (CETP) inhibitors, bile acid sequestrants, fibrates, plant sterols and PCSK9 inhibitors), or any combination thereof.

[0562] The terms "therapeutic effectiveness" and "effectiveness of therapy" are used to refer to the ability of a treatment or therapy to achieve the therapeutic purpose for which it is administered.

[0563] "Pharmacological," "drug," "medication," "drug," and "drug therapy" are used interchangeably in the present disclosure and may include any drug commonly provided to subjects with metabolic syndrome and / or one or more complications thereof, such as, but not limited to, insulin, metformin, GLP-1 analogs, DPP-4 inhibitors, SGLT2 inhibitors, sulfonylureas, meglitinides, thiazolidinediones, alpha-glucosidase inhibitors, blood pressure medications, such as, but not limited to, diuretics, beta-blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin II receptor blockers, The invention relates to the treatment of patients with type 2 diabetes with ARBs, calcium channel blockers, alpha-blockers, alpha-beta-blockers, central blocking agents, alpha-2 receptor agonists, peripheral adrenergic inhibitors, vasodilators, aldosterone receptor antagonists and direct renin inhibitors and lipid-modulating drug treatments such as, but not limited to, statins, other HMG-CoA reductase inhibitors, niacin (nicotinic acid), cholesterol absorption inhibitors, cholesteryl ester transfer protein (CETP) inhibitors, bile acid sequestrants, fibrates, plant sterols and PCSK9 inhibitors or any combination thereof.

[0564] As used herein, "compositions" and "kits" are used for predicting, diagnosing and detecting metabolic syndrome and / or one or more complications thereof and include means and elements for determining metabolic syndrome biomarkers described in the present disclosure.

[0565] As used herein, an "agent" is used in assays to determine the biomarkers described in the present disclosure for the prediction, diagnosis and detection of metabolic syndrome and / or one or more complications thereof.

[0566] For purposes of this disclosure, the terms "obtain data," "collect data," "obtain information," and "collect information" may be used interchangeably.

[0567] As used herein, the terms "the present disclosure, specification or invention", "according to the present disclosure, specification or invention", "according to the present disclosure, specification or invention", "the present disclosure, specification or invention" are intended to refer to all aspects and embodiments of the present disclosure described and / or claimed herein.

[0568] As used herein, the term "comprising" should be taken to cover both "including" and "consisting of."

[0569] As used herein, "determining," "measuring," or "detecting" for a biomarker as disclosed herein refers to a quantitative or relative determination of the amount of a biomarker in a sample. For a quantitative determination, the absolute amount or exact amount of the biomarker in a sample is determined. Alternatively, the relative amount or level of a biomarker in a sample can be determined, e.g., the amount of a biomarker in a sample is determined as increased or decreased relative to a control as described herein.

[0570] As used herein, "reagent" or "agent" may be one or more of any (one or more) standard, control, substance, compound, solution, solvent, reagent, ingredient, preparation or any combination thereof used in the methods and uses disclosed herein. A reagent or agent may also be a combination or mixture of one or more of any (one or more) standard, control, substance, compound, solution, solvent, reagent, ingredient and preparation used in the methods and uses disclosed herein.

[0571] In some embodiments, one or more of any components of the reagents are isotopically labeled. In some embodiments, the isotope of the isotopically labeled component is deuterium. In some embodiments, the isotope of the isotopically labeled component is 13 C or 15 N.

[0572] In some embodiments, the reagent is used to determine the sample concentration of at least one biomarker of metabolic syndrome and / or one or more complications thereof disclosed herein. In some embodiments, the reagent is used in the preparation of a reagent, kit or composition for practicing the methods and uses disclosed herein.

[0573] Example

[0574] The following examples are provided to illustrate various aspects of the present disclosure. They are not intended to limit the present disclosure, which is defined by the appended clauses.

[0575] Example 1. Materials and methods

[0576] Description of study cohort and sample

[0577] Study 1 was a Nordic population study. In the current study, serum samples from 7722 participants were analyzed. The participants were followed for 10 years, and during the follow-up period, 438 subjects developed diabetes, 181 subjects suffered a stroke, 579 subjects suffered a major adverse cardiovascular event, and 34 subjects died of cardiovascular causes. Subjects with no outcome in question during the follow-up period were used as controls.

[0578] Study 2 is a population-based Nordic cohort survey. In the current study, serum samples from 1260 participants were analyzed. During the 15-year follow-up, 78 subjects developed diabetes. Subjects who did not develop diabetes during the follow-up period were used as controls.

[0579] Study 3 is a prospective observational cohort study from Central Europe. In the current study, serum samples from 4286 participants were analyzed. The participants were followed for 10 years, and during the follow-up, 406 subjects developed diabetes and 170 died of cardiovascular causes. Subjects with no outcome in question during the follow-up period were used as controls.

[0580] Analytical methods

[0581] Liquid chromatography-mass spectrometry

[0582] Quantification of stearoylsphingosine and palmitoylsphingosine from serum samples was performed using a validated high-throughput mass spectrometry method. 20 μL of serum or plasma was spiked with deuterated internal standards D7-stearoylsphingosine and D7-palmitoylsphingosine and the quantification was performed using Hamilton Extraction was performed by the STAR robot in isopropanol:ethyl acetate (8:2, v / v). Levels of stearoylsphingosine and palmitoylsphingosine were quantified on a TripleMS 6500 (SCIEX, Concord, Canada) mass spectrometer equipped with a Sciex MPX UHPLC system.

[0583] Chromatographic separation was performed on an Acquity BEH C18, 2.1×75mm id.1.7 μm column (Waters, Massachusetts, USA). The mobile phase consisted of (A) a solution of 5 mM ammonium acetate in LC-MS grade water with 0.1% formic acid, and (B) a solution of 5 mM ammonium acetate in acetonitrile:2-propanol (4:3, v / v) with 0.1% formic acid (FA). The following LC gradient was used: 80% B for 0.5 min, B increased linearly from 80% to 84% in 0.5 min, 84% to 89% B in 1.4 min, 89% to 100% in 0.1 min, 100% to 80% B for 2.0 min, 0.1 min, 100% to 80% B, and 80% equilibration for 0.4 min before the next injection. The flow rate was 500 μl / min and the column temperature was 60°C.

[0584] Multiple reaction monitoring (MRM) was used to quantify stearoyl sphingosine and palmitoyl sphingosine in positive ion mode. The calibration line sample evaluation was quantitative by comprising a known amount of synthetic stearoyl sphingosine and palmitoyl sphingosine and corresponding deuterated standard. The peak area ratio of each analyte and its corresponding deuterated form was calculated and the added standard concentration was mapped and fitted by linear regression analysis. The final concentration was represented by μM.

[0585] Statistical analysis

[0586] The incidence of metabolic syndrome complications (diabetes and cardiovascular (CV) events stroke, major adverse cardiovascular events, and CV death) was studied by fitting logistic regression models to each outcome to obtain the odds ratio (OR) of metabolic syndrome markers. The area under the receiver operating characteristic curve (AUC) was also calculated to show how well the model distinguished patients with outcomes from those without outcomes. In addition, the association between metabolic syndrome markers and clinical variables was studied by fitting linear regression models with metabolic syndrome markers as response variables and clinical variables as explanatory variables. All analyses were performed using R4.3.0.

[0587] Example 2. Results

[0588] The following table shows the predictive power of metabolic syndrome markers and marker combinations disclosed in the present invention. Tables 1, 3, 5, 7, 9, 11 and 13 disclose the area under the receiving operating characteristic curve (AUC) of subjects with morbidity complications of metabolic syndrome, diabetes and cardiovascular events stroke, major adverse cardiovascular events and CV death during follow-up in Study 1, Study 2 and Study 3 compared with the control group. The excellent AUC values ​​of the combination of metabolic markers and clinical parameters compared with the AUC values ​​of the clinical parameters discussed alone are provided in the table.

[0589] Tables 2, 4, 6, 8, 10, 12 and 14 show statistically significant odds ratios (p < 0.05) based on the metabolic syndrome markers, marker combinations and combinations of markers and clinical parameters disclosed in the present invention for subjects with morbid complications of metabolic syndrome (diabetes and cardiovascular events stroke, major adverse cardiovascular events and CV death) compared to the control group during the follow-up period in Study 1, Study 2 and Study 3. As can be seen in the table, the odds ratios (OR) based on the metabolic syndrome markers, marker combinations and combinations of markers and clinical parameters disclosed in the present invention provide a strong connection with the morbid complications of metabolic syndrome.

[0590] Tables 15, 16 and 17 disclose the strong associations between the metabolic syndrome markers and marker combinations disclosed herein and clinical parameters commonly used in diagnosing metabolic syndrome in Study 1, Study 2 and Study 3.

[0591] Because markers disclosed in the present invention and marker combinations provide significant connections with the complications of metabolic syndrome and the clinical parameters commonly used for diagnosing metabolic syndrome, markers of the present invention provide an improved method for detecting metabolic syndrome. Compared with the commonly used detection of the syndrome using multiple parameters, the present invention provides easy, convenient and reliable detection of metabolic syndrome. Early detection of metabolic syndrome using biomarkers of the present invention can prevent the development of syndrome and the generation of serious complications.

[0592] Table 1. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects experiencing major adverse cardiovascular events (MACE) during follow-up compared to the control group in Study 1. Abbreviations are described in the Detailed Description of the Invention.

[0593]

[0594]

[0595]

[0596] Table 2. Compared with the control group in research 1, for the subject who has major adverse cardiovascular events (MACE) during the follow-up period, the statistically significant odds ratio (OR) and p-value of the combination of metabolic syndrome markers, marker combinations and markers and clinical parameters disclosed in the present invention are shown. Score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex and BMI. Other abbreviations are described in the detailed description of the invention.

[0597]

[0598]

[0599]

[0600] Table 3. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who developed diabetes during the follow-up period compared to the control group in Study 1. Score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex and BMI. Other abbreviations are described in the detailed description of the invention.

[0601]

[0602]

[0603]

[0604] Table 4. Compared with the control group in Study 1, for the subjects who developed diabetes during the follow-up period, statistically significant odds ratios (OR) and p-values ​​based on the metabolic syndrome markers, marker combinations, and combinations of markers and clinical parameters disclosed in the present invention are shown. The score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0605]

[0606]

[0607]

[0608]

[0609] Table 5. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who experienced a stroke during the follow-up period compared to the control group in Study 1. Abbreviations are described in the Detailed Description of the Invention.

[0610]

[0611]

[0612]

[0613] Table 6. Compared with the control group in Study 1, for subjects who had a stroke during the follow-up period, statistically significant odds ratios (OR) and p-values ​​based on metabolic syndrome markers, marker combinations, and combinations of markers and clinical parameters disclosed in the present invention are shown. Score refers to a score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0614]

[0615]

[0616]

[0617] Table 7. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who died from cardiovascular causes during the follow-up period compared to the control group in Study 1. Score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0618]

[0619]

[0620]

[0621] Table 8. Compared with the control group in Study 1, for the subject who died due to cardiovascular causes during the follow-up period, statistically significant odds ratios (OR) and p-values ​​based on the metabolic syndrome markers, marker combinations, and combinations of markers and clinical parameters disclosed in the present invention are shown. Score refers to a score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0622]

[0623]

[0624] Table 9. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who developed diabetes during the follow-up period compared to the control group in Study 2. Abbreviations are described in the Detailed Description of the Invention.

[0625]

[0626]

[0627] Table 10. Compared with the control group in Study 2, for the subjects who developed diabetes during the follow-up period, statistically significant odds ratios (OR) and p-values ​​based on the metabolic syndrome markers, marker combinations, and combinations of markers and clinical parameters disclosed in the present invention are shown. The score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0628]

[0629]

[0630]

[0631] Table 11. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who developed diabetes during the follow-up period compared to the control group in Study 3. Abbreviations are described in the Detailed Description of the Invention.

[0632]

[0633]

[0634]

[0635] Table 12. Compared with the control group in Study 3, for the subject who developed diabetes during the follow-up period, statistically significant odds ratios (OR) and p-values ​​based on the metabolic syndrome markers, marker combinations, and combinations of markers and clinical parameters disclosed in the present invention are shown. Score refers to a score including stearoylsphingosine, palmitoylsphingosine, age, sex, and BMI. Other abbreviations are described in the detailed description of the invention.

[0636]

[0637]

[0638]

[0639] Table 13. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) values ​​for the logistic regression model are shown for subjects who died from cardiovascular causes during the follow-up period compared to the control group in Study 3. Abbreviations are described in the Detailed Description of the Invention.

[0640]

[0641]

[0642]

[0643] Table 14. Compared with the control group in Study 3, for the subject who died due to cardiovascular causes during the follow-up period, the statistically significant odds ratio (OR) and p-value based on the metabolic syndrome markers disclosed in the present invention, the marker combinations and the combination of markers and clinical parameters are shown. The score refers to the score including stearoylsphingosine, palmitoylsphingosine, age, sex and BMI. Other abbreviations are described in the detailed description of the invention.

[0644] Markers / marker combinations OR p-value Score 1.035(1.017-1.052) 5.31E-05 Palmitoylsphingosine 1.257(1.047-1.507) 1.42E-02 Stearoylsphingosine 1.250(1.067-1.467) 5.94E-03 Stearoylsphingosine adjusted by BMI 1.198(1.018-1.410) 3.02E-02 Stearoylsphingosine adjusted by bpsys 1.207(1.027-1.421) 2.34E-02 Palmitoylsphingosine adjusted by BMI 1.261(1.051-1.513) 1.29E-02 Palmitoylsphingosine regulated by bpsys 1.230(1.022-1.480) 2.85E-02 Palmitoylsphingosine adjusted by bpsys and BMI 1.240(1.030-1.491) 2.34E-02

[0645] Table 15. Association of metabolite markers and metabolite marker combinations with clinical parameters in Study 1. Regression coefficients (β) and p-values ​​are shown. Abbreviations are described in the Detailed Description of the Invention.

[0646]

[0647] Table 16. Association of metabolite markers and metabolite marker combinations with clinical parameters in Study 2. Regression coefficients (β) and p-values ​​are shown. Abbreviations are described in the Detailed Description of the Invention.

[0648]

[0649]

[0650] Table 17. Association of metabolite markers and combinations of metabolite markers with clinical parameters in Study 3. Regression coefficients (β) and p-values ​​are shown. Abbreviations are described in the Detailed Description of the Invention.

[0651]

[0652] Using no more than routine experimentation, those skilled in the art will recognize or be able to ascertain various equivalents to the specific embodiments described herein in the examples and throughout the description as a whole. These equivalents are considered to be within the scope of the present disclosure and are intended to be covered by the following items or the above listed objects.

Claims

1. A metabolic syndrome marker for use in assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the metabolic marker comprises stearoyl sphingosine.

2. Use of a reagent for determining the concentration of a metabolic syndrome marker in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises: (a) measuring a sample from a subject to determine the concentration of said metabolic syndrome marker; and (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an elevated concentration of a metabolic syndrome marker when compared to a control, wherein the metabolic marker comprises stearoylsphingosine.

3. A combination of metabolic syndrome markers for use in assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine.

4. Use of an agent for determining the concentration of a combination of metabolic syndrome markers in the preparation of a medicament for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessment comprises: (a) measuring a sample from a subject to determine the concentration of stearoyl sphingosine; (b) assaying a sample from the subject to determine the concentration of palmitoylsphingosine; and (c) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine when compared to the control.

5. Use of one or more agents in the preparation of a kit, composition or formulation for assessing the risk of metabolic syndrome and / or one or more complications thereof, wherein the assessment comprises: (a) measuring a sample from a subject to determine the concentration of stearoyl sphingosine; and (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to the control.

6. Use of one or more reagents in the preparation of a kit, composition or formulation for detecting the concentration of metabolic syndrome marker sphingosine in a sample obtained from a subject, wherein the detection comprises assaying the sample from the subject to determine the concentration of sphingosine.

7. Use of exogenous stearoyl sphingosine in the preparation of a test reagent, a kit or a device for evaluating the risk of metabolic syndrome and / or one or more complications thereof, wherein the evaluation comprises: (a) measuring a sample from a subject to determine the concentration of stearoyl sphingosine; and (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more complications thereof if the sample comprises an increased concentration of stearoyl sphingosine when compared to the control.

8. Use of exogenous stearoyl sphingosine in the preparation of a detection reagent, a kit or a device for detecting metabolic syndrome markers, wherein the detection comprises measuring a sample from a subject to determine the concentration of stearoyl sphingosine.

9. An isotope-labeled sphingosine standard for use in detecting metabolic syndrome markers, wherein the detection comprises assaying a sample from a subject to determine the concentration of sphingosine.

10. Use of an isotope-labeled sphingosine standard in the preparation of a standard solution, a detection reagent, a kit or a device for detecting a metabolic syndrome marker, wherein the detection comprises measuring a sample from a subject to determine the concentration of sphingosine.

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