Biomarkers for metabolic syndrome biomarkers for metabolic syndrome

Abstract

The present disclosure is related to biomarkers for metabolic syndrome. Specifically, the present disclosure is related to the field of assessing the risk of developing metabolic syndrome and its complications. It introduces novel biomarkers that can be used to predict metabolic syndrome and its complications.

Description

[0001] BIOMARKERS FOR METABOLIC SYNDROME

[0002] FIELD OF THE INVENTION

[0003] The present disclosure is related to the field of prognostic biomarkers for metabolic syndrome. The present disclosure presents novel biomarkers, biomarker combinations and also novel uses and methods of the present biomarkers. Especially, the present disclosure provides a novel use and method for assessing whether a subject is at risk to develop metabolic syndrome or its complications. Methods and uses for detecting the present biomarkers and biomarker combinations are presented as well as compositions and kits for performing the methods and uses described herein. In addition, the present disclosure presents a novel device, device system and uses thereof for accurate detection of biomolecules.

[0004] BACKGROUND

[0005] Metabolic syndrome is a growing global health problem, approximately 21 % of the adult population in China and over 35% in the USA is suffering from the syndrome.

[0006] Metabolic syndrome is a group of interrelated conditions that occur together. These conditions include abdominal obesity, raised 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 a diagnosis of metabolic syndrome. Metabolic syndrome increases the risk of cardiovascular disease, stroke and type 2 diabetes. Other serious complications of the syndrome comprise kidney disease and non-alcoholic fatty liver disease. Patients suffering metabolic syndrome are at twice the risk of developing cardiovascular disease over the next five to ten years as individuals without the syndrome. Moreover, metabolic syndrome causes a 5-fold increased risk of developing type 2 diabetes.

[0007] Criteria for clinical diagnosis of metabolic syndrome include the following thresholds: Blood pressure is considered high if it consistently measures 130 / 85 mmHg or higher. Elevated fasting blood glucose levels of 100 mg / dL (5.6 mmol / L) or higher are indicative of high blood sugar levels. Triglyceride levels of 150 mg / dL (1.7 mmol / L) or higher are considered high. Low levels of HDL cholesterol 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 elevated waist circumference and defining a single threshold for it is complicated as the threshold depends on ethnicity and sex. Hence, different population- and country-specific thresholds for waist circumference are used. For example, in China and Japan recommended threshold is 85 cm or more in men and 80 cm and 90 cm or more in women, respectively. Recommended waist circumference thresholds in Europe and North America are 102 cm or more in men and 88 cm or more in women.

[0008] Most of the people suffering from metabolic syndrome are symptomless and are, therefore, undiagnosed. As metabolic syndrome can lead to severe complications, including cardiovascular disease, stroke, type 2 diabetes, kidney disease and non-alcoholic fatty liver disease, identifying patiens suffering from the syndrome is crucial. Lifestyle interventions affecting diet, weight management and physical activity may significantly reduce the risk of developing metabolic syndrome and its complications. Therefore, identifying those subjects that are at the greatest risk for metabolic syndrome, its progression and developing severe complications, and promoting lifestyle changes in such individuals may help to prevent metabolic syndrome and its complications. Early detection of the risk of metabolic syndrome and its complications enables a longer and healthier life for the high-risk individuals.

[0009] The above-mentioned five clinical conditions are commonly used for diagnosing metabolic syndrome. However, more precise risk assessment and reliable prognostic markers which could be conveniently used in clinical practice are needed for detecting individuals at increased risk of developing metabolic syndrome and its complications.

[0010] Previous attempts to find easy and reliable biomarkers for metabolic syndrome have not revealed markers that associate with both the complications of metabolic syndrome and the clinical parameters commonly used in diagnosing the syndrome. The present disclosure presents novel biomarkers that provide a significant improvement to the risk assessment of metabolic syndrome by having a strong association with, in addition to the metabolic syndrome complications, also with the clinical parameters constituting the diagnosis of metabolic syndrome.

[0011] SUMMARY

[0012] The present disclosure describes novel biomarkers and biomarker combinations for predicting metabolic syndrome and its complications by quantifying the concentrations of the lipid molecular species. The present inventors have found that each biomarker and biomarker combination displays a characteristic increase or decrease as described herein in samples obtained from subjects being at risk of metabolic syndrome and its complications and are therefore useful for the methods and uses in accordance with the present disclosure. The present biomarkers and biomarker combinations for metabolic syndrome are sensitive and specific and they can be used in diagnostic and prognostic assays in the clinical practice.

[0013] The risk determination based on the novel biomarkers disclosed herein allow for better assessment of future onset of metabolic syndrome and its complications. Individuals at risk of developing metabolic syndrome and its complications are identifyed even though they have no symptoms and the current tests fail to detect the increased risk. This allows earlier intervention and prevention or delay of the onset of metabolic syndrome and / or its severe complications. The present disclosure therefore shows a significant advantage and improvement over the prior methods currently used to assess the risk of metabolic syndrome and its complications.

[0014] The biomarkes and biomarker combinations of the present disclosure show strong association with both the complications of metabolic syndrome and the clinical parameters commonly used to diagnose metabolic syndrome. Compared to the commonly used detection of the syndrome with multiple parameters, the present invention provides superior biomarkers for early detection of metabolic syndrome and allow for easy, reliable and early prediction of metabolic syndrome and / or its complications. This will enable earlier intervention, less symptom development and suffering and decreased morbidity.

[0015] According to a first aspect of the disclosure there is provided a metabolic syndrome marker for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises stearoylsphingosine.

[0016] According to another aspect of the disclosure there is provided a use of a reagent for determining a concentration of a metabolic syndrome marker in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessingcomprises:

[0017] (a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and

[0018] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic syndrome marker comprises stearoylsphingosine.

[0019] According to one aspect of the disclosure there is provided a combination of metabolic syndrome markers for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine.

[0020] According to one aspect of the disclosure there is provided a use of a reagent for determining a concentration of a metabolic syndrome marker combination in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessing comprises:

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

[0022] (c) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine, when compared to a control.

[0023] According to one aspect of the disclosure there is provided a use of one or more reagent in the preparation of a kit, composition or preparation for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0024] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0025] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

[0026] According to one aspect of the disclosure there is provided a use of one or more reagent in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker stearoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of stearoylsphingosine.

[0027] In certain embodiments, the use of one or more reagent further comprises comparing the concentration of the metabolic syndrome marker stearoylsphingosine to a control.

[0028] In certain embodiments, the reagent comprises one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s), preparation(s), or any combination thereof used for the methods and uses of the present disclosure. In certain embodiments, the reagent is a combination or mixture of one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s) and preparation(s) used in the methods and uses of the present disclosure.

[0029] In some embodiments, one or more of any components of a reagent is isotope-labelled. In some embodiments, the isotope of the isotope-labelled component is deuterium,13C or15N. In some embodiments, a reagent comprises at least one isotope-labelled marker of metabolic syndrome and / or one or more of its complications. In some embodiments, the reagent comprises at least one deuterium-labelled marker of metabolic syndrome and / or one or more of its complications. In one embodiment, the reagent comprises deuterium-labelled stearoylsphingosine. In one embodiment, the reagent comprises stearoylsphingosine-d7.

[0030] According to one aspect of the disclosure there is provided a use of an exogenous stearoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0031] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0032] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

[0033] According to one aspect of the disclosure there is provided a use of an exogenous stearoylsphingosine in the preparation of a detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0034] In certain embodiments, the use of an exogenous stearoylsphingosine further comprises comparing the concentration of the metabolic syndrome marker stearoylsphingosine to a control.

[0035] According to one aspect of the disclosure there is provided an isotope-labelled standard of stearoylsphingosine for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0036] According to one aspect of the disclosure there is provided a use of isotope-labelled standard of stearoylsphingosine in the preparation of a standard solution, detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0037] According to one aspect of the disclosure there is provided a reagent for quantifying stearoylsphingosine from a sample obtained from a subject suspected to be at risk of metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0038] According to one aspect of the disclosure there is provided a metabolic syndrome marker for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises palmitoylsphingosine. According to one aspect of the disclosure there is provided a use of a reagent for determining a concentration of a metabolic syndrome marker in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0039] (a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and

[0040] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic syndrome marker comprises palmitoylsphingosine.

[0041] According to one aspect of the disclosure there is provided a use of one or more reagent in the preparation of a kit, composition or preparation for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0042] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0043] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0044] According to one aspect of the disclosure there is provided a use of one or more reagent in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker palmitoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

[0045] In certain embodiments, the use of one or more reagent further comprises comparing the concentration of the metabolic syndrome marker palmitoylsphingosine to a control.

[0046] In certain embodiments, the reagent comprises one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s), preparation(s), or any combination thereof used for the methods and uses of the present disclosure. In certain embodiments, the reagent is a combination or mixture of one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s) and preparation(s) used in the methods and uses of the present disclosure.

[0047] In some embodiments, one or more of any components of a reagent is isotope-labelled. In some embodiments, the isotope of the isotope-labelled component is deuterium,13C or15N. In some embodiments, a reagent comprises at least one isotope-labelled marker of metabolic syndrome and / or one or more of its complications. In some embodiments, the reagent comprises at least one deuterium-labelled marker of metabolic syndrome and / or one or more of its complications. In one embodiment, the reagent comprises deuterium-labelled palmitoylsphingosine. In one embodiment, the reagent comprises palmitoylsphingosine-d7.

[0048] According to one aspect of the disclosure there is provided a use of an exogenous palmitoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0049] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0050] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0051] According to one aspect of the disclosure there is provided a use of an exogenous palmitoylsphingosine in the preparation of a detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0052] In certain embodiments, the use of an exogenous palmitoylsphingosine further comprises comparing the concentration of the metabolic syndrome marker palmitoylsphingosine to a control.

[0053] According to one aspect of the disclosure there is provided an isotope-labelled standard of palmitoylsphingosine for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0054] According to one aspect of the disclosure there is provided a use of isotope-labelled standard of palmitoylsphingosine in the preparation of a standard solution, detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0055] According to one aspect of the disclosure there is provided a reagent for quantifying palmitoylsphingosine from a sample obtained from a subject suspected to be at risk of metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine. In addition to the above-described aspects, the present invention relates to a device capable of accurately identifying different molecules with small differences and determining abundances of the molecules in a sample. A device system comprising the device and uses thereof are presented as well.

[0056] Naturally occurring molecules encompass a broad range of compounds with varying chemical structures. Each molecular class, or each single molecule, may have different physical and chemical properties, requiring specific extraction, separation and detection methods for accurate analysis. Molecular structure of a biomolecule may only vary in the number and positions of double bonds. This makes it challenging to identify various different molecules.

[0057] At present, methods for determining and quantifying molecules accurately are complicated requiring multiple complex steps, precise control and optimization of parameters, selection of appropriate detection modes, and accurate data interpretation. Furthermore, they require careful setup and high level of expertise from the persons using them.

[0058] The device of the present invention involves fewer steps and parameters to optimize, simplifying setup and usage. The simpler operation and reduced complexity make it easier to learn and familiarize with the device. This expands the possibilities for broader use for accurate detection of various different molecules.

[0059] According to one aspect of the disclosure there is provided a device capable of identifying a molecule and determining an abundance of the molecule in a sample, wherein the device comprises a detection module and a data processing module.

[0060] In some embodiments, the molecule comprises at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19 or 20 molecules.

[0061] 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 glycerolipid molecule, a sterol lipid molecule or any combinations thereof. In some embodiments, the molecule comprises at least one sphingolipid. In some embodiments, the molecule comprises stearoylsphingosine and / or palmitoylsphingosine.

[0062] In some embodiments, determining the abundance of the molecule comprises determining a relative or absolute abundance, amount, concentration, level, quantity, or activity of the molecule. The determining can be qualitative or quantitative.

[0063] In some embodiments, the detection module comprises, including, but not limited to, a biosensor, spectrometer, immunoassay system, enzymatic system, colorimetric system, electrochemical detector, nucleic acid amplification system, microfluidic system, ion detector, mass spectrometer, nuclear magnetic resonance detector, ultraviolet detector, ultraviolet / visible light detector, infrared light detector, fluorometer, refractive index detector, thermal conductivity 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. In some embodiments, the detection module is capable of detecting one or more chemical, physical and / or structural property of a molecule. In some embodiments, the detection module is capable of detecting, including, but not limited to, molecular weight, mass, charge, electromagnetic signal, magnetic field, frequency, flow rate, light absorption, mass-to-charge ratio, emission of light, chemoluminescence, luminescence, radiance, energy, velocity, momentum, structure, conductivity, solubility, or any combinations thereof, of a molecule.

[0064] In some embodiments, the data processing module comprises processing data generated by the detection module. In some embodiments, the data processing comprises, including, but not limited to, interpreting the data generated by the detection module, such as spectral data, identifying the molecule, determining or calculating the abundance of the molecule and / or comparing the data or abundance of the molecule to a control or reference. In some embodiments, the data processing comprises generating metabolic condition data of a subject. In some embodiments, the data processing module further comprises analyzing the data using machine learning or artificial intelligence algorithms to generate predictive models for assessing the metabolic condition data of a subject.

[0065] According to one aspect of the disclosure there is provided a device system comprising the device and a user interface.

[0066] In some embodiments, the user interface communicates with the data processing module of the device. In some embodiments, the user interface analyses and / or displays the data processed by the data processing module. In some embodiments, the communication comprises transmitting the data to a remote computing system for further analysis, processing and / or storage. In some embodiments, the device system further comprises a database or cloud storage for storing, processing and / or analysing the data.

[0067] In some embodiments, the user interface displays the metabolic condition data of a subject to the subject or a healthcare professional. In some embodiments, the user interface provides personalized recommendations or intervention based on the metabolic condition data, including, but not limited to, dietary suggestions, exercise plans, medication reminders or any other instructions or recommendations.

[0068] 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 allowing continuous monitoring of a metabolic condition data of a subject.

[0069] In some embodiments, the metabolic condition data of the subject comprises 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, glycated haemoglobin 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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), suppression of tumorigenicity 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 subgroup composition or particle number, or any parameter related to glucose levels, lipid profiles, hormone levels, or nutritional markers, or any combination thereof. In some embodiments, the metabolic condition data of the subject comprises one or more metabolic markers of the present disclosure and / or one or more other biomarkers, parameters and / or health data.

[0070] In some embodiments, the metabolic condition data of a subject comprises assessing the risk of metabolic syndrome and / or one or more of its complications.

[0071] In some embodiments, the device system further comprises a notifying system, wherein the notifying system notifies a subject or a healthcare professional if the metabolic condition data indicates an abnormality or a potential health risk.

[0072] In some embodiments, the data processing module performs advanced data analytics and generates processed data based on aggregated data from multiple users.

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

[0074] According to one aspect of the disclosure there is provided a use of the device system for detecting one or more metabolic syndrome marker, wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome marker comprises stearoylsphingosine. In some embodiments, the one or more metabolic syndrome marker further comprises palmitoylsphingosine and / or one or more of other biomarkers, parameters and / or heath data.

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

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

[0077] In some embodiments, the one or more metabolic syndrome marker further comprises one or more other biomarkers, parameters and / or heath data.According to one aspect of the disclosure there is provided a use of the device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0078] (a) detecting stearoylsphingosine in a sample of a subject using the detection module;

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

[0080] (c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and

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

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

[0083] (a) detecting stearoylsphingosine in a sample of a subject using the detection module;

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

[0085] (c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and

[0086] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control, using the data processing module. In some embodiments, the use for assessing the risk further comprises:

[0087] (a) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0088] (b) determining a concentration of palmitoylsphingosine using the data processing module;

[0089] (c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0090] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

[0091] According to one aspect of the disclosure there is provided a use of the device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0092] (e) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0093] (f) determining a concentration of palmitoylsphingosine using the data processing module;

[0094] (g) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0095] (h) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

[0096] According to one aspect of the disclosure there is provided a use of the device system for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0097] (e) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0098] (f) determining a concentration of palmitoylsphingosine using the data processing module;

[0099] (g) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0100] (h) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

[0101] According to one aspect of the disclosure there is provided a composition or kit for assessing the risk of metabolic syndrome and / or one or more of its complications, detecting the marker of metabolic syndrome or performing any one of the methods or uses disclosed herein, wherein the composition or kit comprises an exogenous stearoylsphingosine.

[0102] According to one aspect of the disclosure there is provided a composition or kit for assessing the risk of metabolic syndrome and / or one or more of its complications, detecting the marker of metabolic syndrome or performing any one of the methods or uses disclosed herein, wherein the composition or kit comprises an exogenous palmitoylsphingosine.

[0103] In some embodiments, the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises isotope-labelled stearoylsphingosine and / or palmitoylsphingosine. In some embodiments, the isotope of the isotope-labelled stearoylsphingosine and / or palmitoylsphingosine is deuterium,13C or15N. In some embodiments, the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine. In one embodiment, the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0104] In some embodiments, the composition or kit comprises at least one isotope-labelled marker of metabolic syndrome and / or one or more of its complications. In some embodiments, the isotope of the isotope-labelled marker is deuterium,13C or15N. In some embodiments, the composition or kit comprises at least one deuterium-labelled marker of metabolic syndrome and / or one or more of its complications. In one embodiment, the composition or kit comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine. In one embodiment, the composition or kit comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0105] The composition or kit may further comprise standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein or other element(s) for performing the methods or uses disclosed herein.

[0106] In some embodiments, the composition or kit is a combination of any standard(s), control(s), reagent(s), solution(s), solvent(s) container(s), instruction(s) to use it for the methods or uses disclosed herein or other element(s) for performing the methods or uses disclosed herein, either purchased from a commercial manufacturer or prepared in-house in a laboratory, used for assaying a concentration of stearoylsphingosine and / or palmitoylsphingosine.

[0107] In some embodiments, the composition or kit comprises element(s) for collecting a blood sample, for example, 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. In some embodiments, the composition or kit further comprises palmitoylsphingosine. In some embodiments, the composition or kit comprises isotope-labelled stearoylsphingosine and / or palmitoylsphingosine. In some embodiments, the composition or kit comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine. In one embodiment, the composition or kit comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0108] In some embodiments, the composition or kit further comprises standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein or other element(s) for detecting other clinical parameters, such as, but not limited to, BMI, age, gender, weight, height, waist circumference, blood pressure, systolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1 c, low-density lipoprotein (LDL) cholesterol, insulin and CRP.

[0109] The composition or kit may be a test kit for used in a laboratory or a home use test kit. The composition or kit may be used in assays performed with various chemical and high-resolution analytical techniques, as appropriate. Suitable analytical techniques according to the present methods and uses include, but are not limited to, mass spectrometry (MS) and nuclear magnetic resonance (NMR). Any high-resolution technique capable of resolving individual biomarkers can be used to collect the information on the biomarker in question, such as the concentration of biomarker profile from the biological sample. Typically, the information is collected using mass spectrometry. The MS analysis can be coupled to another high performance separation method, such as gas chromatography (GC), two-dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC) or ultra-high performance liquid chromatography (LIHPLC).

[0110] According to one aspect of the disclosure there is provided a method for detecting stearoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps a. Obtaining a sample from a subject, b. Extracting stearoylsphingosine from the sample, c. Separating stearoylsphingosine by liquid chromatography (LC), and / or d. Determining the concentration of stearoylsphingosine by mass spectrometry (MS).

[0111] According to one aspect of the disclosure there is provided a method for detecting palmitoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps a. Obtaining a sample from a subject, b. Extracting palmitoylsphingosine from the sample, c. Separating palmitoylsphingosine by liquid chromatography (LC), and / or d. Determining the concentration of palmitoylsphingosine by mass spectrometry (MS).

[0112] Further steps and details of detecting stearoylsphingosine and / or palmitoylsphingosine by LC-MS are descriped below in the precent disclosure.

[0113] According to one aspect of the disclosure there is provided a method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:

[0114] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0115] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

[0116] According to one aspect of the disclosure there is provided a method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:

[0117] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0118] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0119] According to one aspect of the disclosure there is provided a method of collecting data for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:

[0120] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0121] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control. According to one aspect of the disclosure there is provided a method of collecting data for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:

[0122] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0123] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0124] In some embodiments, the subject is capable of being treated with a therapy as described herein. For example, the therapy may comprise any therapeutic treatment typically given 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 counselling to effect a change in diet, weight management and / or physical activity, controlling the progression 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 modifying medications as described in the detailed description of the present disclosure, or any combination thereof.

[0125] In some embodiments, the method for assessing whether a subject is at risk to develop metabolic syndrome and / or one or more of its complications further comprises, after the determining step, diagnosing the subject as having an increased risk of developing metabolic syndrome and / or one or more of its complications from the results in the determining step and administering a treatment to the subject diagnosed as having an increased risk of developing metabolic syndrome and / or one or more of its complications.

[0126] In one aspect, the present disclosure is directed to a method of treating or preventing metabolic syndrome and / or one or more of its complications in a subject identified as being at risk to develop metabolic syndrome and / or one or more of its complications, the method comprising: administering to the subject a treatment as described herein, wherein prior to administering the treatment, the subject has been identified as being at risk to develop metabolic syndrome and / or one or more of its complications by the method described herein.

[0127] Assaying the present biomarker(s) stearoylsphingosine and / or palmitoylsphingosine in a biological sample is an unconventional measure for the risk of metabolic syndrome and / or one or more of its complications. Moreover, the present biomarkers and methods generally allow for the 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. Thus, the present methods ensure that subjects having a risk for metabolic syndrome and / or one or more of its complications can be properly identified and receive treatment as opposed to the large number of individuals who are at risk of developing this syndrome, but remain unidentified and untreated, and consequently are unnecessarily subjected to the possibility of severe complications and / or premature mortality as is commonplace in this field.

[0128] Metabolic syndrome can lead to severe complications, therefore it is beneficial to detect individuals that are at high risk of developing complications of metabolic syndrome, and provide preventive measures and / or treatment. The major complications of metabolic syndrome comprise, e.g., cardiovascular disease and its complications, stroke, type 2 diabetes, kidney disease and non-alcoholic fatty liver disease.

[0129] In some embodiments, the progression of metabolic syndrome and / or one or more of its complications over time in a subject is monitored by comparing the disclosed biomarker value to a previously determined biomarker value in a sample obtained from the same subject.

[0130] In some embodiments, the disclosed methods and uses are used as screening tests to assess the risk of a subject to develop metabolic syndrome and / or one or more of its complications.

[0131] According to one aspect of the disclosure there is provided a method of evaluating the effectiveness of a therapy of metabolic syndrome and / or one or more of its complications in a subject, wherein the method comprises:

[0132] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0133] (b) determining that the therapy is effective, if the sample comprises a decreased concentration of stearoylsphingosine, when compared to a control.

[0134] According to one aspect of the disclosure there is provided a method of evaluating the effectiveness of a therapy of metabolic syndrome and / or one or more of its complications in a subject, wherein the method comprises:

[0135] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0136] (b) determining that the therapy is effective, if the sample comprises an increased concentration of palmitoylsphingosine, when compared to a control.

[0137] In the method, the effectiveness of the therapy is monitored by analysing the metabolic syndrome biomarker value as described herein. The biomarker value reflects the progress of metabolic syndrome and / or one or more of its complications and the biomarker value approaches that of the control when the subject responds to a therapy, such as the therapies described herein. Accordingly, a therapy may be tailored based on the response of a subject such that only a therapy which shows a positive response, e.g., the biomarker concentration approaching that of a control, and is thus found effective, is continued, and a therapy which shows minimal or no response, and is thus found ineffective, is discontinued.

[0138] In some embodiments, the subject is capable of being treated with a therapy as described herein, which is escalated. For example, the therapy to be escalated may comprise any therapeutic treatment typically given 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 counselling to affect a change in diet, weight management and / or physical activity, controlling the progression 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 modifying medications as described in the detailed description of the present disclosure, or any combination thereof.

[0139] In some embodiments, the method for evaluating the effectiveness of a therapy of metabolic syndrome and / or one or more of its complications in a subject further comprises, determining that the therapy is not effective in the subject from the results in the determining step and escalating the therapy of the subject.

[0140] In one aspect, the present disclosure is directed to a method of treating metabolic syndrome and / or one or more of its complications in a subject identified as being ineffectively treated, the method comprising: administering to the subject a further treatment as described herein, wherein prior to administering the treatment, the subject has been identified as being ineffectively treated for metabolic syndrome and / or one or more of its complications by the methods described herein.

[0141] In some embodiments, the therapy may comprise any therapeutic treatment typically given 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 counselling affecting diet, weight management and physical activity, control of progression of metabolic syndrome and / or one or more of its complications (e.g. blood glucose monitoring, blood pressure and lipid control), diabetes medication, cardiovascular disease medication, blood pressure and lipid modifying medications as described in the detailed description of the present disclosure, or any combination thereof.

[0142] In some embodiments of the aforementioned methods, the method of treating metabolic syndrome and / or one or more of its complications further comprises identifying the subject as in need of the treatment or prevention, for example, by requesting a test or receiving the test results, for example, from a commercial laboratory, which provides the results of an assay useful for determining the biomarker value and administering to the subject a treatment, for example, a therapeutically effective dose of a drug, if the subject has an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine, as compared to a control.

[0143] According to one aspect of the disclosure there is provided a method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein assessing the risk comprises using a formula, score, equation, algorithm, alculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0144] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0145] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

[0146] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0147] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

[0148] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0149] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI)) +1)] * 100, wherein a and b are real numbers.

[0150] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0151] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)] * 100, wherein a, b and c are real numbers. In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0152] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)] * 100, wherein a, b and c are real numbers.

[0153] In some embodiments, for men intercept is a value from -15 to -9, a is a value from 3.0 to 5.0, b is a value from 0.1 to 0.3 and c is a value from 0.025 to 0.055, and for women intercept is a value from -15 to -6, a is a value from 3.0 to 5.0, b is a value from 0.05 to 0.25 and c is a value from 0.020 to 0.050. In some embodiments, for men intercept is -11.66, a is 4.30, b is 0.18 and c is 0.040, and for women intercept is -10.43, a is 4.01 , b is 0.13 and c is 0.036.

[0154] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0155] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender)) +1)] * 100, wherein a, b, c and d are real numbers.

[0156] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0157] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + e * glucose)) +1)] * 100, wherein a and e are real numbers.

[0158] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0159] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + f * HbA1c)) +1)] * 100, wherein a and f are real numbers. In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula: [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + e * glucose)) +1)] * 100, wherein a, b and e are real numbers.

[0160] In some embodiments, for men intercept is a value from -25 to -10, a is a value from 2.00 to 7.00, b is a value from 0.05 to 0.30 and e is a value from 0.50 to 2.50 and for women intercept is a value from -25 to -10, a is a value from 1.00 to 6.00, b is a value from 0.01 to 0.15 and e is a value from 1.0 to 3.0. In some embodiments, for men intercept is -18.64, a is 4.55, b is 0.15 and e is 1.60 and for women intercept is -18.63, a is 3.35, b is 0.07 and e is 2.11.

[0161] In some embodiments of all aspects of the present disclosure, assessing the risk to develop metabolic syndrome and / or one or more of its complications comprises using the following formula:

[0162] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender + e * glucose + f * HbA1c + g * LDL-cholesterol + h * HDL-cholesterol + i * triglycerides + j * systolic blood pressure + k * insulin + I * CRP )) +1)] * 100, wherein a, b, c, d, e, f, g, h, i, j, k and I are real numbers.

[0163] According to yet another aspect of the disclosure there is provided a use of one or more reagent in the preparation of a kit, composition or preparation for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein assessing the risk comprises using the following formula:

[0164] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender + e * glucose + f * HbA1c + g * LDL-cholesterol + h * HDL-cholesterol + i * triglycerides + j * systolic blood pressure + k * insulin + I * CRP )) +1)] * 100, wherein a, b, c, d, e, f, g, h, i, j, k and I are real numbers.

[0165] In some embodiments of all aspects of the present disclosure, the intercept may change depending on gender.

[0166] In certain embodiments of all aspects of the present disclosure, the formula comprises 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 parameter(s) selected from BMI, age, gender, glucose, HbA1 c, LDL- cholesterol, HDL-cholesterol, triglycerides, systolic blood pressure, insulin and CRP, and / or 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 intercept(s).

[0167] In certain embodiments of all aspects of the present disclosure, assessing the risk of metabolic syndrome and / or one or more of its complications further comprises, in addition to determining the concentration of the metabolic syndrome marker stearoylsphingosine, determining a concentration of metabolic syndrome marker palmitoylsphingosine.

[0168] In certain embodiments of all aspects of the present disclosure, assessing the risk of metabolic syndrome and / or one or more of its complications further comprises, in addition to determining the concentration of the metabolic syndrome markers stearoylsphingosine and / or palmitoylsphingosine, detecting other clinical parameters, such as, but not limited to, BMI, age, gender, weight, height, waist circumference, blood pressure, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, HbA1 c, low- density lipoprotein (LDL) cholesterol, insulin and / or CRP. In certain embodiment, 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, gender, 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.

[0169] In certain embodiments of all aspects of the present disclosure, the method or use further comprises determining the level of one or more of other biomarkers or parameters, including, but not limited to, triglyseride (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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, and / or any combination thereof, in a sample from the subject.

[0170] In certain embodiments of all aspects of the present disclosure, the method or use further comprises using one or more other personal information or health data, including, but not limited to, sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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, e.g. from angiography or computed tomography (CT), and / or any combination thereof. In some embodiments of all aspects of the disclosure, the marker combination may be constructed by linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimations, decision trees or, neural networks. In some embodiments, transformation to logistic or time-to-event model is performed in the methods and uses of the present disclosure. In some embodiments, transformation to logarithmic scale is performed.

[0171] In some embodiments of all aspects of the disclosure, the marker combination is a continuous or discrete scoring systems based on the metabolic syndrome biomarker(s) of the present disclosure and / or one or more of any other biomarker or parameter dislosed herein. For discrete scoring, the points may be given based on intervals with non-equal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components. In some embodiments of all aspects of the disclosure, the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

[0172] In some embodiments of all aspects of the disclosure, a risk of a subject to developing metabolic syndrome and / or one or more of its complications is assessed for a certain period of time. In some embodiments, the risk is assessed over 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, 23, 24, 25, 26, 27, 28, 29 or 30 years.

[0173] In some embodiments of all aspects of the disclosure, the one or more complications of metabolic syndrome comprise, including, but not limited to, diabetes (such as type 2 diabetes), cardiovascular disease (CVD), cardiovascular (CV) events, such as stroke, major adverce cardiovascular event (MACE), CV death, stable angina pectoris, unstable angina pectoris, myocardial infarction (Ml), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attacks, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral artery disease and different forms of arrhythmias (such as atrial fibrillation), kidney disease and / or fatty liver disease (such as non-alcoholic fatty liver disease). In some embodiments, the one or more complications of metabolic syndrome comprise diabetes, stroke, cardiovascular disease and / or cardiovascular events. In some embodiments, the one or more complications of metabolic syndrome comprise diabetes.

[0174] The determination of the biomarkers is typically performed using an assay. The assay can be performed with various chemical and high-resolution analytical techniques, as appropriate. Suitable analytical techniques according to the present methods and uses include, but are not limited to, mass spectrometry (MS) and nuclear magnetic resonance (NMR). Any high-resolution technique capable of resolving individual small molecule biomarkers can be used to collect the information on the biomarker in question, such as the concentration of biomarker from the biological sample, such as blood, blood serum, blood plasma, tissue, urine or saliva. In some embodiments, the information is collected using mass spectrometry or tandem mass spectrometry (MS / MS). The MS analysis can be coupled to another high performance separation method, such as gas chromatography (GC), two-dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC), ultra-high performance liquid chromatography (LIHPLC) or to a direct sample infusion method, such as a robotic nanoflow ion source device. In certain embodiments, the analysis is performed using LC- MS / MS, HPLC-MS / MS or UHPLC-MS / MS.

[0175] In some embodiments, the biomarker concentration is determined by using mass spectrometry, nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry, an immunoassay, enzymatic assay, colorimetric assay, fluorometric assay, a rapid test, and / or with a binding moiety capable of specifically binding the biomarker.

[0176] The sample from the subject and the control sample may be a blood sample, a blood serum sample, a blood plasma sample, a fraction of blood, a lipid fraction, a saliva sample, an urine sample or a tissue sample. Blood serum and plasma samples are typically used. The sample can be prepared with techniques well known in the art.

[0177] In some embodiments, before the mass spectrometric analysis, the biomarkers of the sample are extracted with a solvent or a solvent mixture 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.

[0178] In some embodiments, the biomarkers are derivatized before the mass spectrometric analysis. In some embodiments, the derivatization comprises extraction with an organic solvent, evaporation of the solvent under reduced pressure, and derivatization.

[0179] In other embodiments, the sample is filtered before determining the biomarkers by using a filter which removes cells. In some embodiments, a filter having a cut-off value of 30 kDa is used to remove cells. In other embodiments, a filter is used which removes proteins. In other embodiments, the sample is reconstituted after the filtering. In other embodiments, the sample or the reconstituted sample is diluted prior to determining the biomarkers. In other embodiments, the sample is diluted at least 1 :2 before determining the biomarkers. In other embodiments, a preservative or an internal mass standard is added to the sample.

[0180] In certain embodiments of all aspects of the present disclosure, the methods and uses further comprise a step of adding to the sample at least one isotope-labelled biomarker prior to determining the concentration of the biomarker. Any isotope that is suitable for detecting the biomarkers can be used, including, but not limited to, hydrogen, carbon, nitrogen and oxygen isotopes, including, but not limited to,2H (deuterium),13C and15N. In the methods and uses for determining the biomarker concentration, the isotope-labelled biomarkers can be used, e.g., as internal standards, calibration standards, reference standards and / or in quality control samples. The isotope-labelled biomarkers can be used in both qualitative and quantitative analysis of the biomarkers.

[0181] In certain embodiments, at least one deuterium-labelled biomarker of metabolic syndrome and / or one or more of its complications is added to the sample. In one embodiment, deuterium-labelled stearoylsphingosine is added to the sample. In certain embodiments, the deuterium-labelled stearoylsphingosine comprises stearoylsphingosine-d7.

[0182] In certain embodiments, at least one deuterium-labelled biomarker of metabolic syndrome and / or one or more of its complications is further added to the sample. In one embodiment, deuterium- labelled palmitoylsphingosine is added to the sample. In certain embodiments, the deuterium- labelled palmitoylsphingosine comprises palmitoylsphingosine-d7.

[0183] As described elsewhere in the present disclosure, the control may be a concentration determined from a single healthy individual. The control may also be a sample that represents a combination of samples from a generalized population of healthy individuals. Alternatively, the control may be a control value or a set of data concerning the biomarker in a sample previously determined, calculated or extrapolated, or may have yet to be determined, calculated or extrapolated, or may also be taken from the literature.

[0184] In certain embodiments of all aspects of the present disclosure, detecting stearoylsphingosine and / or palmitoylsphingosine and determining the concentration of stearoylsphingosine and / or palmitoylsphingosine may futher comprise one or more of the following steps:

[0185] (a) obtaining a sample from a subject,

[0186] (b) extracting lipids (including stearoylsphingosine and / or palmitoylsphingosine) from the sample,

[0187] (c) separating the marker stearoylsphingosine and / or palmitoylsphingosine by liquid chromatography (LC), and / or

[0188] (d) determining the concentration(s) of the marker stearoylsphingosine and / or palmitoylsphingosine by mass spectrometry (MS).

[0189] In some embodiments, the sample is a human plasma sample or a human serum sample. In some embodiments, the sample volume is 10 - 200 pl. In some embodiments, 20 pl, 10 pl or 5 pl of the sample is used. In some embodiments, a 96-well extraction plate and / or automated lipid extraction is used. In some embodiments, the biomarkers of the sample are extracted from the sample with 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, methylene chloride, toluene, water, other polar or nonpolar solvents or solutions and / or any mixtures or combinations thereof. In some embodiments, isopropanokethyl acetate is used. In some embodiments, isopropanokethyl acetate at ratio of 8:2 (v / v) is used. In some embodiments, one or more internal standard is added to the sample. In some embodiments, the one or more internal standard is isotope-labelled. In some embodiments, the isotope of the isotope-labelled standard is deuterium. In some embodiments, the isotope of the isotope-labelled standard is13C or15N. In some embodiments, the isotope-labelled standard comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine. In certain embodiments, the deuterium-labelled standards comprise stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0190] In some embodiements, the internal standards are added to the sample with the extraction solvent. In some embodiments, the sample is mixed and centrifuged after adding the extraction solvent. In some embodiments, the sample extract is placed into a 96-well MS plate after extraction.

[0191] Any types of liquid chromatography techniques can be used. Suitable LC techniques comprise, including, but not limited to, reversed phase, normal phase, ion-exchange, ion, ion pair, size exclusion and / or affinity chromatography. In some embodiments, reversed phase, normal phase and / or ion-exchange chromatography is used.

[0192] Suitable mobile phase solvents for the liquid chromatography comprise any solvents and solutions suitable for the liquid chromatography separation of the biomarkers of the present disclosure, 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 nonpolar solvent or solution and / or any mixtures or combinations thereof. In some embodiments, a gradient comprising two or more mobile phase solvents is used. In some embodiments, a gradient with solvent A comprising ammonium acetate in water with formic acid and solvent B comprising ammonium acetate in acetonitrile:isopropanol with formic acid is used. In some embodiments, a gradient with solvent A comprising 1-30 mM ammonium acetate in water with 0.02-0.30% formic acid and solvent B comprising 1-30 mM ammonium acetate in acetonitrile:isopropanol with 0.02-0.30% formic acid is used. In some embodiments, a gradient with solvent A comprising 10 mM ammonium acetate in water with 0.1% formic acid and solvent B comprising 10 mM ammonium acetate in acetonitrile:isopropanol (4:3, v / v) with 0.1 % formic acid is used. In some embodiments, the following gradient with solvent A and B is used: A 5-40% and B 60-95% from 0 to 0.2-2.0 min, B 60-100% from 0.2-2.0 to 1.0-6.0 min and A to 5-40% and B to 60-95% from 1.0-6. O to 1.5-10 min. In some embodiments, the following gradient with solvent A and B is used: A 15% and B 85% from 0 to 0.5 min, B to 100% from 0.5 to 1.5 min, B 100% from 1.5 to 4.0 min and A to 15% and B to 85 from 4.0 to 5.0 min. In some embodiments, a gradient with solvent A comprising 5 mM ammonium acetate in water with 0.1 % formic acid, and solvent B comprising 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: 0.5 min at 80% B, linear increase of B from 80% to 84% in 0.5 min, 84% to 89% B in 1.4 min, 89% to 100% in 0.1 min, 2.0 min at 100% B, 100% to 80% B in 0.1 min and 0.4 min equilibration at 80%. Suitable liquid chromatography conditions and materials comprise any conditions and materials suitable for the liquid chromatography separation of the biomarkers of the present disclosure. In some embodiments, injection volume is 1-30 pl, mobile phase flow rate is 100-2000 pl / min and / or temperature is 30-90°C. In some embodiments, injection volume is 5, 10 or 20 pl. In some embodiments, injection volume is 5 pl, flow rate is 500 pl / min and / or temperature is 60°C. Any suitable columns can be used, including, but not limited to, reversed phase, normal phase and ion-exchange columns. Any suitable sized columns can be used. In some embodiments, reversed phase column is used. In some embodiments, silica, bonded phase (e.g. C3, C4, C8 and C18) or polymer phase column is used. In some embodiments, C18 column is used. In some embodiments, C18 column at size 2.1 x 50 mm, id. 1.7 pm is used.

[0193] In some embodiments of all aspects of the precent disclosure, the mass spectrometry determining comprises one or more of the following steps:

[0194] (a) ionizing stearoylsphingosine and / or palmitoylsphingosine to generate ions of stearoylsphingosine and / or palmitoylsphingosine,

[0195] (b) detecting the ions of stearoylsphingosine and / or palmitoylsphingosine,

[0196] (c) determining the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine; and / or

[0197] (d) determining concentrations of stearoylsphingosine and / or palmitoylsphingosine in the sample based on the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine.

[0198] In some embodiments, the mass spectrometry comprises tandem mass spectrometry (MS / MS) and / or the liquid chromatography comprises high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC) or ultra-high performance liquid chromatography (LIHPLC). In some embodiments, LC-MS / MS, HPLC-MS / MS or UHPLC-MS / MS is used.

[0199] Any types of mass spectrometry instruments can be used. Suitable MS instruments comprise, including, but not limited to, quadrupole, single-quadrupole, triple-quadrupole, time-of flight, quadrupole time-of-flight, ion-trap, quadrupole ion trap, sector, magnetic sector, electrostatic sector, ion cyclotron, Fourier transform instruments, and any combination instrument thereof. Any ionization techniques can be used. Suitable ionization techniques comprise, including, but not limited to, electrospray, atmospheric pressure chemical, atmospheric pressure photo, chemical, field, electron impact., fast atom bombardment, matrix assisted laser desoption ionization, and any combination techniques thereof.

[0200] In some embodiments, the mass spectrometry determination is performed in positive and / or negative ion mode. In some embodiments, multiple reaction monitoring, multiple precursor ion scanning and / or neutral loss scanning is used. In some embodiments, select ion monitoring, total ion chromatogram scan and / or extracted ion chromatogram monitoring is used. In some embodiments, electrospray ionization in positive ion mode and multiple reaction monitoring is used.

[0201] Various exemplary embodiments, examples of which are discussed in the detailed description are listed in the following clauses:

[0202] 1. A metabolic syndrome marker, for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises stearoylsphingosine.

[0203] 2. Use of a reagent for determining a concentration of a metabolic syndrome marker in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0204] (a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and

[0205] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic marker comprises stearoylsphingosine.

[0206] 3. A combination of metabolic syndrome markers, for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine. Use of a reagent for determining a concentration of a metabolic syndrome marker combination in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessing comprises:

[0207] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine;

[0208] (b) assaying the sample from the subject to determine a concentration of palmitoylsphingosine; and

[0209] (c) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine, when compared to a control. A use of one or more reagent in the preparation of a kit, composition or preparation for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0210] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0211] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control. A use of one or more reagent in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker stearoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of stearoylsphingosine. A use of an exogenous stearoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0212] (a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and

[0213] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control. 8. A use of an exogenous stearoylsphingosine in the preparation of a detection reagent, kit or device for detecting the markers of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0214] 9. An isotope-labelled standard of stearoylsphingosine for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0215] 10. A use of isotope-labelled standard of stearoylsphingosine in the preparation of a standard solution, detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0216] 11. A reagent for quantifying stearoylsphingosine from a sample obtained from a subject suspected to be at risk of metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

[0217] 12. A metabolic syndrome marker, for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises palmitoylsphingosine.

[0218] 13. A use of a reagent for determining a concentration of a metabolic syndrome marker in preparation of an agent for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0219] (a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and

[0220] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic marker comprises palmitoylsphingosine.

[0221] 14. A use of one or more reagent in the preparation of a kit, composition or preparation for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0222] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0223] 15. A use of one or more reagent in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker palmitoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

[0224] 16. A use of an exogenous palmitoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:

[0225] (a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and

[0226] (b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

[0227] 17. A use of an exogenous palmitoylsphingosine in the preparation of a detection reagent, kit or device for detecting the markers of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0228] 18. An isotope-labelled standard of palmitoylsphingosine for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0229] 19. A use of isotope-labelled standard of palmitoylsphingosine in the preparation of a standard solution, detection reagent, kit or device for detecting the marker of metabolic syndrome, wherein the detecting comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

[0230] 20. A reagent for quantifying palmitoylsphingosine from a sample obtained from a subject suspected to be at risk of metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine. 21 . A device capable of identifying a molecule and determining an abundance of the molecule in a sample, wherein the device comprises a detection module and a data processing module.

[0231] 22. A device system, wherein the device system comprises the device of clause 21 and a user interface.

[0232] 23. A use of the device of clause 21 , for detecting one or more metabolic syndrome marker, wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome marker comprises stearoylsphingosine.

[0233] 24. A use of the device system of clause 22, for detecting one or more metabolic syndrome marker, wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome marker comprises stearoylsphingosine

[0234] 25. A use of the device of clause 21 , for detecting one or more metabolic syndrome marker, wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome marker comprises palmitoylsphingosine.

[0235] 26. A use of the device system of clause 22, for detecting one or more metabolic syndrome marker, wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome marker comprises palmitoylsphingosine.

[0236] 27. A use of the device of clause 21 , for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0237] (a) detecting stearoylsphingosine in a sample of a subject using the detection module;

[0238] (b) determining a concentration of stearoylsphingosine using the data processing module;

[0239] (c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and

[0240] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control, using the data processing module.

[0241] 28. A use of the device system of clause 22, for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises: (a) detecting stearoylsphingosine in a sample of a subject using the detection module;

[0242] (b) determining a concentration of stearoylsphingosine using the data processing module;

[0243] (c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and

[0244] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control, using the data processing module.

[0245] 29. The use of clause 28, wherein the use for assessing the risk further comprises:

[0246] (a) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0247] (b) determining a concentration of palmitoylsphingosine using the data processing module;

[0248] (c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0249] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

[0250] 30. A use of the device of clause 21 , for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0251] (a) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0252] (b) determining a concentration of palmitoylsphingosine using the data processing module;

[0253] (c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0254] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module. 31. A use of the device system of clause 22, for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the use comprises:

[0255] (a) detecting palmitoylsphingosine in a sample of a subject using the detection module;

[0256] (b) determining a concentration of palmitoylsphingosine using the data processing module;

[0257] (c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and

[0258] (d) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

[0259] 32. A composition or kit for assessing the risk of metabolic syndrome and / or one or more of its complications, for detecting the marker of metabolic syndrome or for performing any of the methods or uses disclosed in any one of the preceding clauses, wherein the composition or kit comprises an exogenous stearoylsphingosine.

[0260] 33. A composition or kit for assessing the risk of metabolic syndrome and / or one or more of its complications, for detecting the marker of metabolic syndrome or for performing any of the methods or uses disclosed in any one of the preceding clauses, wherein the composition or kit comprises an exogenous palmitoylsphingosine.

[0261] 34. The composition or kit of clause 32 or 33, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises isotope-labelled stearoylsphingosine and / or palmitoylsphingosine..

[0262] 35. The composition or kit of any one of clauses 32-34, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine.

[0263] 36. The composition or kit of any one of clauses 32-35, wherein the exogenous stearoylsphingosine and / or palmitoylsphingosine comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

[0264] 37. The composition or kit of any one of clauses 32-36, wherein the composition or kit further comprises standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein and / or other element(s) for performing the methods or uses disclosed herein. 38. The composition or kit of any one of clauses 32-37, wherein the composition or kit comprises element(s) of collecting a blood sample.

[0265] 39. The composition or kit of clause 38, wherein the blood sample is a dried blood spot on a filter or a plasma or serum sample collected on a filter or card.

[0266] 40. The composition or kit of any one of clauses 32-39, wherein the composition or kit further comprises standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein and / or other element(s) for detecting one or more clinical parameters, wherein the one or more clinical paramethers comprises BMI, age, gender, 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.

[0267] 41 . The composition or kit of any one of clauses 32-40, wherein the composition or kit is a test kit for used in a laboratory or a home use test kit.

[0268] 42. The composition or kit of any one of clauses 32-41 , wherein the composition or kit is a combination of any standard(s), control(s), reagent(s), solution(s), solvent(s) container(s), instruction(s) to use it for the methods or uses disclosed herein or other element(s) for performing the methods or uses disclosed herein, either purchased from a commercial manufacturer or prepared in-house in a laboratory, used for assaying a concentration of stearoylsphingosine and / or palmitoylsphingosine.

[0269] 43. The composition or kit of any one of clauses 32-42, wherein the composition or kit is used in mass spectrometry, nuclear magnetic resonance, gas chromatography (GC), two- dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC), ultra-high performance liquid chromatography (LIHPLC) or any combination thereof.

[0270] 44. A method for detecting stearoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps:

[0271] (a) Obtaining a sample from a subject;

[0272] (b) Extracting stearoylsphingosine from the sample;

[0273] (c) Separating stearoylsphingosine by liquid chromatography (LC); and / or

[0274] (d) Determining the concentration of stearoylsphingosine by mass spectrometry (MS). 45. A method for detecting palmitoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps:

[0275] (a) Obtaining a sample from a subject;

[0276] (b) Extracting palmitoylsphingosine from the sample;

[0277] (c) Separating palmitoylsphingosine by liquid chromatography (LC); and / or

[0278] (d) Determining the concentration of palmitoylsphingosine by mass spectrometry (MS).

[0279] 46. A method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein assessing the risk comprises using a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0280] 47. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0281] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

[0282] 48. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0283] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

[0284] 49. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0285] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI)) +1)] * 100, wherein a and b are real numbers.

[0286] 50. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0287] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)] * 100, wherein a, b and c are real numbers. 51. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0288] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)]

[0289] * 100, wherein a, b and c are real numbers.

[0290] 52. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0291] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender)) +1)] * 100, wherein a, b, c and d are real numbers.

[0292] 53. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0293] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + e * glucose)) +1)] * 100, wherein a and e are real numbers.

[0294] 54. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0295] [1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + f * HbA1c)) +1)] * 100, wherein a and f are real numbers.

[0296] 55. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0297] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + e * glucose)) +1)] * 100, wherein a, b and e are real numbers.

[0298] 56. The use or method of any one of the preceding clauses, wherein assessing the risk comprises using the following formula:

[0299] [1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender + e * glucose + f * HbA1c + g * LDL-cholesterol + h * HDL-cholesterol + i * triglycerides + j * systolic blood pressure + k * insulin + I * CRP)) +1)] * 100, wherein a, b, c, d, e, f, g, h, i, j, k and I are real numbers.

[0300] 57. The method or use of any one of the preceding clauses, wherein the formula comprises 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 parameter(s) selected from BMI, age, gender, glucose, HbA1 c, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, systolic blood pressure, insulin and CRP, and / or 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 intercept(s).

[0301] 58. The method or use of any one of the preceding clauses, wherein the intercept may change depending on gender.

[0302] 59. The method or use of any one of the preceding clauses, wherein the method or use further comprises palmitoylsphingosine and / or determining a concentration of palmitoylsphingosine.

[0303] 60. The method or use of any one of the preceding clauses, wherein the method or use further comprises detecting at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 clinical parameters comprising BMI, age, gender, 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.

[0304] 61 . The method or use of any one of the preceding clauses, wherein the method or use further comprises detecting one or more other biomarkers or parameters comprising triglyseride (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 particle (LDL-P), high-density lipoprotein particle (HDL- P), , Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, and / or any combination thereof, in a sample from the subject.

[0305] 62. The method or use of any one of the preceding clauses, wherein the method or use further comprises using one or more other personal information or health data comprising sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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 from angiography or computed tomography (CT), and / or any combination thereof.

[0306] 63. The method or use of any one of the preceding clauses, wherein the marker combination comprises linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimations, decision trees and / or neural networks.

[0307] 64. The method or use of any one of the preceding clauses, wherein transformation to logistic model, time-to-event model or logarithmic scale is performed.

[0308] 65. The method or use of any one of the preceding clauses, wherein the marker combination comprises a continuous or discrete scoring systems based on the metabolic syndrome biomarker(s) and / or one or more of any other biomarker or parameter.

[0309] 66. The method or use of any one of the preceding clauses, wherein the marker combination comprises discrete scoring, wherein the points are given based on intervals with nonequal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components.

[0310] 67. The method or use of any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

[0311] 68. The method or use of any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more of its complications is assessed for a certain period of time.

[0312] 69. The method or use of any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more of its complications is assessed over 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, 23, 24, 25, 26, 27, 28, 29 or 30 years.

[0313] 70. The method or use of any one of the preceding clauses, wherein the one or more complications of metabolic syndrome comprise diabetes, such as type 2 diabetes, cardiovascular disease (CVD), cardiovascular (CV) events, stroke, major adverce cardiovascular event (MACE), CV death, stable angina pectoris, unstable angina pectoris, myocardial infarction (Ml), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attacks, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral artery disease and different forms of arrhythmias, such as atrial fibrillation, kidney disease and / or fatty liver disease, such as non-alcoholic fatty liver disease.

[0314] 71. The method or use of any one of the preceding clauses, wherein the one or more complications of metabolic syndrome comprise diabetes, stroke, cardiovascular disease and / or cardiovascular events.

[0315] 72. The method or use of any one of the preceding clauses, wherein the one or more complications of metabolic syndrome comprise diabetes.

[0316] 73. The method or use of any one of the preceding clauses, wherein the method or use comprises using mass spectrometry (MS), tandem mass spectrometry (MS / MS), nuclear magnetic resonance (NMR), gas chromatography (GC), two-dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC), ultra-high performance liquid chromatography (UHPLC), LC-MS / MS, HPLC-MS / MS, UHPLC-MS / MS, resonance spectroscopy, fluorescence spectroscopy, dual polarization interferometry, an immunoassay, enzymatic assay, colorimetric assay, fluorometric assay, a rapid test, a binding moiety capable of specifically binding the biomarker and / or any combination thereof.

[0317] 74. The method or use of any one of the preceding clauses, wherein the sample from the subject and / or the control sample may be a blood sample, a blood serum sample, a blood plasma sample, a fraction of blood, a lipid fraction, a saliva sample, an urine sample and / or a tissue sample.

[0318] 75. The method or use of clause 74, wherein the blood sample comprises a dried blood spot on a filter and / or a blood plasma sample and / or a blood serum sample comprises a plasma or serum sample collected on a filter or card.

[0319] 76. The method or use of any one of the preceding clauses, wherein the biomarkers of the sample are extracted with a solvent or a solvent mixture from the sample, and wherein the solvent or solvent mixture comprises organic and / or inorganic solvents and solutions, comprising methanol, ethanol, butanol, chloroform, isopropanol (2-propanol), n-propanol, ethyl acetate, acetone, acetonitrile, n-hexane, isohexane, benzene, cyclohexane, dichloromethane, heptane, diethyl ether, methylene chloride, toluene, water, other polar or nonpolar solvents or solutions and / or any mixtures or combinations thereof. 77. The method or use of clause 76, wherein the solvent mixture comprises isopropanokethyl acetate.

[0320] 78. The method or use of clause 76 or 77, wherein the solvent mixture comprises isopropanokethyl acetate at ratio 8:2 (v / v).

[0321] 79. The method or use of any one of the preceding clauses, wherein the method or use further comprises adding to the sample at least one isotope-labelled standard prior to determining the concentration of the biomarker.

[0322] 80. The method or use of clause 79, wherein the at least one isotope-labelled standard comprises hydrogen, carbon, nitrogen and oxygen isotopes, such as,2H (deuterium),13C and15N.

[0323] 81 . The method or use of clause 79 or 80, wherein the isotope-labelled standards are used in qualitative or quantitative analysis, as internal standards, calibration standards, reference standards and / or in quality control samples

[0324] 82. The method or use of any one of clauses 79-81 , wherein at least one deuterium-labelled standard is added to the sample.

[0325] 83. The method or use of any one of clauses 79-82, wherein deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine is added to the sample.

[0326] 84. The method or use of any one of clauses 79-83, wherein the deuterium-labelled stearoylsphingosine comprises stearoylsphingosine-d7 and / or the deuterium-labelled palmitoylsphingosine comprises palmitoylsphingosine-d7.

[0327] 85. The method or use of any one of the preceding clauses, wherein the control comprises a concentration determined from a single healthy individual, a sample that represents a combination of samples from a generalized population of healthy individuals, a control value or a set of data, previously determined, calculated or extrapolated, or to be determined, calculated or extrapolated, or is taken from the literature.

[0328] 86. The method or use of any one of the preceding clauses, wherein detecting stearoylsphingosine and / or palmitoylsphingosine and / or determining the concentration of the metabolic syndrome marker stearoylsphingosine and / or palmitoylsphingosine futher comprises one or more of the following steps:

[0329] (a) obtaining a sample from a subject; (b) extracting lipids, comprising stearoylsphingosine and / or palmitoylsphingosine, from the sample;

[0330] (c) separating the marker stearoylsphingosine and / or palmitoylsphingosine by liquid chromatography (LC); and / or

[0331] (d) determining the concentration of the marker stearoylsphingosine and / or palmitoylsphingosine by mass spectrometry (MS).

[0332] 87. The method or use of any one of the preceding clauses, wherein 10-200 pl of the sample is used.

[0333] 88. The method or use of clause 87, wherein 20pl, 10pl or 5 pl of the sample is used.

[0334] 89. The method or use of any one of the preceding clauses, wherein automated lipid extraction and / or a 96-well extraction plate is used.

[0335] 90. The method or use of any one of the preceding clauses, wherein the sample is mixed and centrifuged after adding the extraction solvent.

[0336] 91. The method or use of any one of the preceding clauses, wherein the sample extract is placed into a 96-well MS plate after extraction.

[0337] 92. The method or use of any one of the preceding clauses, wherein the liquid chromatography comprises reversed phase, normal phase, ion-exchange, ion, ion pair, size exclusion and / or affinity chromatography.

[0338] 93. The method or use of any one of the preceding clauses, wherein the liquid chromatography comprises using 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 nonpolar solvent or solution and / or any mixtures or combinations thereof.

[0339] 94. The method or use of any one of the preceding clauses, wherein the liquid chromatography comprises using a gradient comprising two or more mobile phase solvents.

[0340] 95. The method or use of clause 94, wherein the gradient comprises a gradient with solvent A comprising ammonium acetate in water with formic acid and solvent B comprising ammonium acetate in acetonitrile:isopropanol with formic acid. 96. The method or use of clause 94 or 95, wherein the gradient comprises a gradient with solvent A comprising 1-30 mM ammonium acetate in water with 0.02-0.30% formic acid and solvent B comprising 1-30 mM ammonium acetate in acetonitrile:isopropanol with 0.02-0.30% formic acid.

[0341] 97. The method or use of any one of the preceding clauses, wherein the liquid chromatography comprises using injection volume of 1-30 pl, mobile phase flow rate of 100-2000 pl / min and / or temperature of 30-90°C.

[0342] 98. The method or use of any one of the preceding clauses, wherein the liquid chromatography comprises using reversed phase, normal phase and / or ion-exchange column(s).

[0343] 99. The method or use of any one of the preceding clauses, wherein the mass spectrometry comprises one or more of the following steps:

[0344] (a) ionizing stearoylsphingosine and / or palmitoylsphingosine to generate ions of stearoylsphingosine and / or palmitoylsphingosine;

[0345] (b) detecting the ions of stearoylsphingosine and / or palmitoylsphingosine;

[0346] (c) determining the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine; and / or

[0347] (d) determining concentrations of stearoylsphingosine and / or palmitoylsphingosine in the sample based on the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine.

[0348] 100. The method or use of any one of the preceding clauses, 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 (LIPLC) or ultra-high performance liquid chromatography (LIHPLC).

[0349] 101. The method or use of any one of the preceding clauses, wherein the LC-MS comprises LC-MS / MS, HPLC-MS / MS and / or UHPLC-MS / MS.

[0350] 102. The method or use of any one of the preceding clauses, wherein the mass spectrometry comprises quadrupole, single-quadrupole, triple-quadrupole, time-of flight, quadrupole time-of-flight, ion-trap, quadrupole ion trap, sector, magnetic sector, electrostatic sector, ion cyclotron, Fourier transform instruments, and / or any combination instrument thereof. 103. The method or use of any one of the preceding clauses, wherein the mass spectrometry comprises electrospray, atmospheric pressure chemical, atmospheric pressure photo, chemical, field, electron impact., fast atom bombardment, matrix assisted laser desoption ionization, and / or any combination ionization techniques thereof.

[0351] 104. The method or use of any one of the preceding clauses, wherein the mass spectrometry comprises positive and / or negative ion mode, multiple reaction monitoring, multiple precursor ion scanning, neutral loss scanning, select ion monitoring, total ion chromatogram scan and / or extracted ion chromatogram monitoring.

[0352] 105. The method or use of any one of the preceding clauses, wherein the use of one or more reagent further comprises comparing the concentration of the metabolic syndrome marker stearoylsphingosine and / or palmitoylsphingosine to a control.

[0353] 106. The method or use of any one of the preceding clauses, wherein the reagent comprises one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s), preparation(s), or any combination thereof used for the methods and uses disclosed herein.

[0354] 107. The method or use of any one of the preceding clauses, wherein the reagent comprises a combination or mixture of one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s) and preparation(s) used in the methods and uses disclosed herein.

[0355] 108. The method or use of any one of the preceding clauses, wherein the reagent comprises one or more isotope-labelled components.

[0356] 109. The method or use of clause 108, wherein the one or more isotope-labelled component comprises deuterium,13C or15N.

[0357] 110. The method or use of clause 108 or 109, wherein the reagent comprises at least one isotope-labelled marker of metabolic syndrome.

[0358] 111. The method or use of any one of clauses 108-110, wherein the reagent comprises at least one deuterium-labelled marker of metabolic syndrome.

[0359] 112. The method or use of any one of clauses 108-111 , wherein the reagent comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine.

[0360] 113. The method or use of any one of clauses 108-112, wherein the reagent comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7. 114. The method or use of any one of the preceding clauses, wherein the control comprises a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0361] 115. The method or use of any one of the preceding clauses, wherein the control comprises a value obtained from a previously taken sample from the same subject.

[0362] 116. The method or use of any one of the preceding clauses, wherein exogenous stearoylsphingosine comprises any synthetic or isolated stearoylsphingosine.

[0363] 117. The method or use of any one of the preceding clauses, wherein exogenous stearoylsphingosine comprises an isotope-labelled stearoylsphingosine.

[0364] 118. The method or use of any one of the preceding clauses, wherein the isotope of the isotope-labelled exogenous stearoylsphingosine is deuterium,13C or15N.

[0365] 119. The method or use of any one of the preceding clauses, wherein exogenous stearoylsphingosine comprises stearoylsphingosine-d7.

[0366] 120. The method or use of any one of the preceding clauses, wherein exogenous palmitoylsphingosine comprises any synthetic or isolated palmitoylsphingosine.

[0367] 121. The method or use of any one of the preceding clauses, wherein exogenous palmitoylsphingosine comprises an isotope-labelled palmitoylsphingosine.

[0368] 122. The method or use of any one of the preceding clauses, wherein the isotope of the isotope-labelled exogenous palmitoylsphingosine is deuterium,13C or15N.

[0369] 123. The method or use of any one of the preceding clauses, wherein exogenous palmitoylsphingosine comprises palmitoylsphingosine-d7.

[0370] 124. The method or use of any one of the preceding clauses, wherein the subject has previously suffered from metabolic syndrome and / or its complications, is suffering from metabolic syndrome and / or its complications, is suspected of suffering from metabolic syndrome and / or its complications or the subject is a healthy individual with no previous signs or symptoms of metabolic syndrome and / or its complications.

[0371] 125. The method or use of any one of the preceding clauses, wherein the subject is or has been under a treatment, such as, diabetes, CVD, blood pressure or lipid modifying medication, or has not had any previous treatment or medication. 126. The method or use of any one of the preceding clauses, wherein the subject has previously suffered or is suffering from cardiovascular disease and / or its complication(s) and / or has been or is undergoing statin treatment.

[0372] 127. The method or use of any one of the preceding clauses, wherein the subject has previously suffered or is suffering from type 2 diabetes and / or its complications and has been or is undergoing diabetes treatment.

[0373] 128. The method or use of any one of the preceding clauses, wherein the subject has a blood glucose and / or blood pressure levels in the normal range.

[0374] 129. The method or use of any one of the preceding clauses, wherein the subject has a blood lipid levels, such as, triglyceride, high-density lipoprotein cholesterol and / or low- density lipoprotein cholesterol, in the normal range.

[0375] 130. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more other biomarkers, parameters or health data.

[0376] 131. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises a ratio, sum, difference, product, remainder, value, score, calculation, formula, equation, algorithm, or any combination thereof.

[0377] 132. The combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the combination of metabolic syndrome markers comprises stearoylsphingosine / palmitoylsphingosine and / or palmitoylsphingosine / stearoylsphingosine.

[0378] 133. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more of 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.

[0379] 134. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more of other biomarkers or parameters, such as, triglyseride (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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C- reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, and / or any combination thereof. . The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more of other personal information or health data, such as, sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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, angiography or computed tomography (CT), and / or any combination thereof. . The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers is constructed by linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as, support vector machines, kernel estimations, decision trees, and / or neural networks. . The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises transformation to logistic or time-to-event model is performed. . The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises transformation to logarithmic scale.

[0380] 139. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises a continuous or discrete scoring systems based on the metabolic syndrome biomarker(s) and / or one or more of any other biomarker or parameter.

[0381] 140. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises giving the points for discrete scoring based on intervals with non-equal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components.

[0382] 141. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding clauses, wherein the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

[0383] 142. The device of clause 21 , wherein the molecule comprises at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19 or 20 molecules.

[0384] 143. The device of clause 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 glycerolipid molecule, a sterol lipid molecule or any combinations thereof.

[0385] 144. The device of clause 21 , wherein the molecule comprises at least one sphingolipid.

[0386] 145. The device of clause 21 , wherein the molecule comprises stearoylsphingosine and / or palmitoylsphingosine.

[0387] 146. The device of clause 21 , wherein the determining is qualitative or quantitative.

[0388] 147. The device of clause 21 , wherein the determining the abundance of the molecule comprises determining a relative or absolute abundance, amount, concentration, level, quantity, or activity of the molecule.

[0389] 148. The device of clause 21 , wherein the detection module comprises a biosensor, spectrometer, immunoassay system, enzymatic system, colorimetric system, nucleic acid amplification system, microfluidic system, ion detector, mass spectrometer, nuclear magnetic resonance detector, ultraviolet detector, ultraviolet / visible light detector, fluorometer, refractive index detector, thermal conductivity 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.

[0390] 149. The device of clause 21, wherein the detection module is capable of detecting one or more chemical, physical and / or structural property of a molecule.

[0391] 150. The device of clause 21, wherein the detection module is capable of detecting molecular weight, mass, charge, electromagnetic signal, magnetic field, frequency, flow rate, light absorption, mass-to-charge ratio, emission of light, chemoluminescence, luminescence, radiance, energy, structure, conductivity, solubility, or any combinations thereof, of a molecule.

[0392] 151. The device of clause 21, wherein the data processing module comprises processing data generated by the detection module.

[0393] 152. The device of clause 21 , wherein the data processing comprises interpreting the data generated by the detection module, such as spectral data, identifying the molecule, determining or calculating the abundance of the molecule and / or comparing the data or abundance of the molecule to a control or reference.

[0394] 153. The device of clause 21 , wherein the data processing comprises generating metabolic condition data of a subject.

[0395] 154. The device of clause 21 , wherein the data processing module further comprises analyzing the data using machine learning or artificial intelligence algorithms to generate predictive models for assessing the metabolic condition data of a subject.

[0396] 155. The device system of clause 22, wherein the user interface communicates with the data processing module of the device

[0397] 156. The device system of clause 22, wherein the user interface analyses and / or displays the data processed by the data processing module.

[0398] 157. The device system of clause 22, wherein the communication comprises transmitting the data to a remote computing system for further analysis, processing and / or storage.

[0399] 158. The device system of clause 22, wherein the device system further comprises a database or cloud storage for storing, processing and / or analysing the data. . The device system of clause 22, wherein the user interface displays the metabolic condition data of a subject to the subject or a healthcare professional. . The device system of clause 22, wherein the user interface provides personalized recommendations or intervention based on the metabolic condition data, such as, dietary suggestions, exercise plans, medication reminders and / or any other instructions or recommendations. . The device system of clause 22, wherein the device system further comprises a wearable component. . The device system of clause 22, wherein the detection module is integrated into the wearable component. . The device system of clause 22, wherein the detection module is integrated into the wearable component allowing continuous monitoring of a metabolic condition data of a subject. . The device system of clause 22, wherein the metabolic condition 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, glycated haemoglobin 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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), suppression of tumorigenicity 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 subgroup composition or particle number, or any parameter related to glucose levels, lipid profiles, hormone levels, or nutritional markers, or any combination thereof. . The device system of clause 22, wherein the metabolic condition data of the subject comprises one or more metabolic markers disclosed herein and / or one or more other biomarkers, parameters and / or health data. . The device system of clause 22, wherein the metabolic condition data of a subject comprises assessing the risk of metabolic syndrome and / or one or more of its complications. 167. The device system of clause 22, wherein the device system further comprises a notifying system, wherein the notifying system notifies a subject or a healthcare professional if the metabolic condition data indicates an abnormality or a potential health risk.

[0400] 168. The device system of clause 22, wherein the data processing module performs advanced data analytics and generates processed data based on aggregated data from multiple users.

[0401] 169. The use of clause 23 or 24, wherein the one or more metabolic syndrome marker further comprises palmitoylsphingosine and / or one or more of other biomarkers, parameters and / or heath data.

[0402] 170. The use of any one of clauses 23-26, wherein the one or more metabolic marker further comprises one or more other biomarkers, parameters and / or heath data.

[0403] DETAILED DESCRIPTION OF THE INVENTION

[0404] Reference will now be made in detail to various exemplary embodiments, examples of which are discussed in the detailed description that follows. It is to be understood that the following detailed description is provided to give the reader a fuller understanding of certain embodiments, features, and details of aspects of the invention, and should not be interpreted as limiting the scope of the invention.

[0405] Abbreviations

[0406] Unless indicated otherwise, the abbreviations used in this description have the following meanings: ACE - angiotensin-converting enzyme, ACS - acute coronary syndrome, AMI - acute myocardial infarction, ApoB - apolipoprotein B, ApoAl - apolipoprotein Al, ApoAII - apolipoprotein All, ApoC - apolipoprotein C, ARB - angiotensin II receptor blocker, AUC - area under the curve, beta - regression coefficient, BMI - body mass index, BNP - B-type natriuretic peptide, bpsys - systolic blood pressure, CAD - coronary artery disease, CETP - cholesteryl ester transfer protein, CHD - coronary heart disease, Cl - confidence interval, CK - creatine kinase, CKD - chronic kidney disease, CRP - C-reactive protein, CT - computed tomography, CV - cardiovascular, CVD - cardiovascular disease, DM2 - diabetes mellitus type 2, DPP-4 - dipeptidyl peptidase-4, El - electron ionization, FA - fatty acid, FLD - fatty liver disease, GC - gas chromatography, GCxGC - two dimensional gas chromatography, GDF15 - growth differentiation factor 15, GLP- 1 - glucagon-like peptide 1 , HbA1c - glycated haemoglobin, haemoglobin A1c, HDL - high density lipoprotein, HDL-C - high density lipoprotein cholesterol, HDL-P - high density lipoprotein particle, HMG-CoA - 3-hydroxy-3-methylglutaryl-coenzyme A, HPLC - high performance liquid chromatography, IHD - ischemic heart disease, LC - liquid chromatography, LCxLC - 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 particle, Lp(a) - lipoprotein (a), Lp-PLA2 - lipoprotein-associated phospholipase A2, MACE - major adverce cardiovascular event, Ml - myocardial infarction, MRM - multiple reaction monitoring, MS - mass spectrometry, MS / MS - tandem mass spectrometry, NAFL - nonalcoholic fatty liver, NAFLD - non-alcoholic fatty liver disease, NASH - non-alcoholic 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 - suppression of tumorigenicity 2, TC - total cholesterol, T2D - type 2 diabetes, TG - triglyceride, TMAO - trimethylamine-N-oxide, TNI or Tnl - troponin I, TNT or TnT - troponin T, LIHPLC - ultra-high performance liquid chromatography, LIPLC - ultra performance liquid chromatography, waist - waist circumference.

[0407] Definitions

[0408] In order that the present disclosure may be more readily understood, certain terms are first defined. Additional definitions are set forth throughout the present description.

[0409] As used herein, “metabolic syndrome” comprises, but is not limited to, a group of interrelated conditions that occur together, comprising abdominal obesity, raised blood pressure, elevated blood sugar levels, elevated triglyceride levels and low high-density lipoprotein cholesterol levels. The presence of at least three of these five conditions constitutes a diagnosis of metabolic syndrome. Metabolic syndrome increases the risk of cardiovascular disease, stroke and type 2 diabetes. Other serious complications of the syndrome comprise kidney disease and nonalcoholic fatty liver disease.

[0410] As used herein, “complication of metabolic syndrome” or “metabolic syndrome complication” comprises, but is not limited to, diabetes (such as type 2 diabetes), cardiovascular disease (CVD), cardiovascular (CV) events, such as stroke, major adverce cardiovascular event (MACE), CV death, stable angina pectoris, unstable angina pectoris, myocardial infarction (Ml), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attacks, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral artery disease and different forms of arrhythmias (such as atrial fibrillation), kidney disease and / or fatty liver disease (such as non-alcoholic fatty liver disease). As used herein, “abdominal obesity” refers to elevated waist circumference. The threshold for elevated waist circumference depends on ethnicity and sex and, therefore, different population- and country-specific thresholds are used. For example, in China and Japan recommended threshold is 85 cm or more in men and 80 cm and 90 cm or more in women, respectively. Recommended waist circumference thresholds in Europe and North America are 102 cm or more in men and 88 cm or more in women.

[0411] As used herein, “raised blood pressure” comprises measures 130 / 85 mmHg or higher. Different population- and country-specific thresholds may be used as well.

[0412] As used herein, “elevated blood sugar levels” comprise fasting blood glucose levels of 100 mg / dL (5.6 mmol / L) or higher. Different population- and co untry- specific thresholds may used as well.

[0413] As used herein, “elevated triglyceride (TG) levels” comprise levels of 150 mg / dL (1.7 mmol / L) or higher. Different population- and country-specific thresholds may be used as well.

[0414] As used herein, “low high-density lipoprotein (HDL) cholesterol levels” comprise 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 be used as well.

[0415] As used herein, “diabetes” or “diabetes mellitus” is a chronic condition in which the body is not able to produce enough insulin or is not able to use insulin properly. This leads to elevated blood glucose levels. There are three main types of diabetes: type 1 diabetes, type 2 diabetes and gestational diabetes. “Diabetes” and “type 2 diabetes” are used interchangeably in this disclosure.

[0416] The terms “type 2 diabetes”, “type 2 diabetes mellitus”, “diabetes mellitus type 2”, “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 capacity to produce sufficient amounts of insulin.

[0417] As used herein, “cardiovascular disease (OVD)” has its general meaning in the art and it is used to classify numerous conditions that affect the heart, heart valves, blood, and vasculature of the body, including coronary artery disease (CAD). The CVD may or may not involve atherosclerosis.

[0418] As used herein, “coronary artery disease (CAD)”, also known as “coronary heart disease (CHD)” and “ischemic heart disease (I HD)”, is characterized by atherosclerosis in the coronary arteries. Atherosclerotic plaques narrow the coronary artery lumen decreasing blood flow to the heart. When the flow of oxygen-rich blood to the heart is reduced or blocked, angina or myocardial infarction can occur. In the present disclosure, “cardiovascular (CV) event” comprises stable angina pectoris, unstable angina pectoris, myocardial infarction (Ml), acute myocardial infarction (AMI), acute coronary syndrome (ACS), stroke, transient ischemic attacks, deep vein thrombosis, heart failure, hospitalization for heart failure and cardiovascular death, peripheral artery disease (also called peripheral arterial disease) and different forms of arrhythmias, such as atrial fibrillation. Such events may involve atherosclerosis.

[0419] As used herein, “stroke” comprises a condition in which blood flow to the brain is interrupted or reduced leading to parts of the brain to stop functioning properly due to cell death. Two main types of stroke are ischemic and hemorrhagic stroke Ischemic stroke is caused by lack of blood flow to the brain and hemorrhagic stroke due to bleeding. A stroke is a medical emergency, and prompt treatment is crucial. Early action can reduce brain damage and other complications.

[0420] As used herein, “kidney disease” comprises both acute and chronic kidney conditions and diseases. Chronic kidney disease, also known as chronic renal disease or CKD, is a condition characterized by a gradual loss of kidney function over time. Chronic kidney disease includes conditions that damage the kidneys and decrease their ability to filter wastes from the blood. If kidney disease worsens, wastes can build to high levels in the blood and lead to serious conditions. Complications, such as cardiovascular disease, high blood pressure, anemia, weak bones, poor nutritional health and nerve damage can occur due to prolonged kidney disease. These problems may happen slowly over a long time. Early detection and treatment can often keep chronic kidney disease from getting worse. When kidney disease progresses, it may eventually lead to kidney failure, which requires dialysis or a kidney transplant to maintain life.

[0421] As used herein, “fatty liver disease” or “FLD” comprises a condition in which excess fat builds up in the liver. The two main types of fatty liver disease are alcoholic fatty liver disease and nonalcoholic fatty liver disease (NAFLD). As used herein, “alcoholic fatty liver disease” is a fatty liver disease related to heavy alcohol use. As used herein, “non-alcoholic fatty liver disease” or “NAFLD” is a range of fatty liver conditions which are not related to heavy alcohol use. Early stages of NAFLD can be symptomless but if not detected and managed, NAFLD can progress to serious liver damage. NAFLD can progress from a harmless fatty liver stage (steatosis) to nonalcoholic steatohepatitis (NASH), a more serious form of NAFLD, and eventually to fibrosis, cirrhosis, liver failure and liver cancer. As used herein, “non-alcoholic steatohepatitis” or “NASH” is a severe fatty liver condition, in which the liver is often inflamed.

[0422] The terms “subject,” “host,” “patient,” and “individual” are used interchangeably herein to refer to any mammalian subject for whom prognosis, diagnosis or therapy is desired, particularly humans. The subject may have previously suffered 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 with no previous signs or symptoms of metabolic syndrome and / or its complications.

[0423] The subject may be or may have been under a treatment, such as, but not limited to, diabetes, CVD, blood pressure or lipid modifying medication, or may not have had any previous treatment or medication.

[0424] The subject may have previously suffered or is suffering from cardiovascular disease and / or its complication(s) and may have been or may be undergoing statin treatment. The subject may have previously suffered or is suffering from type 2 diabetes and / or its complications and may have been or may be undergoing diabetes treatment.

[0425] In some embodiments of the aforementioned methods and uses of the present disclosure, 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 haemoglobin 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 sugar on awakening of about 100 mg / dL or less. In some embodiments, the subject has a before-meal glucose level of about 70 mg / dL to about about 99 mg / dL. In some embodiments, the subject has a glucose level of about 140 mg / dL or less about two hours after a meal. Typically, the subject has a fasting venous plasma glucose concentration of less than 6.1 mmol / L (110 mg / dL).

[0426] In some embodiments of the aforementioned methods and uses of the present disclosure, the subject has a blood pressure level in the normal range.

[0427] In some embodiments of the aforementioned methods and uses of the present disclosure, the subject has a blood lipid levels, such as, but not limited to, triglyceride levels, high-density lipoprotein cholesterol levels and / or low-density lipoprotein cholesterol levels, in the normal range.

[0428] As used herein, “statins” is a class of lipid-lowering medications (HMG-CoA reductase inhibitors). Statin is selected from the group consisting of atorvastatin, cerivastatin, fluvastatin, fluvastatin XL, lovastatin, pitavastatin, pravastatin, rosuvastatin and simvastatin or a combination thereof.

[0429] As used herein, a “sample” is a biological sample obtained from a subject or a group or population of subjects. The sample may be a blood sample, a serum sample, a plasma sample, a saliva sample, a tissue sample, an urine sample or a fraction thereof. Blood serum and plasma samples are typical. The sample can be prepared with techniques well known in the art. In certain embodiments, the blood sample is a blood spot dried on a filter, card or other medium. In certain embodiments, a plasma or serum sample is collected on a filter, card or other medium. As used herein, a “control” may be a control sample. A control may also be a concentration determined from a sample from a single healthy individual. The control may also be a sample that represents a combination of samples from a generalized population of healthy individuals. Alternatively, the control may be a control value or a set of data concerning the biomarker in a sample previously determined, calculated or extrapolated, or may have yet to be determined, calculated or extrapolated, or may also be taken from the literature. The control may also be a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

[0430] A control as used herein, i.e. , a control value or a control sample, is typically representative of a group of subjects or a population of subjects. In this context, “representative” means that the biomarker concentration (s) reflected by said control value to which a comparison is made in the context of the present disclosure correspond(s) to the average concentration value(s) of said biomarker concentration(s) in corresponding individual samples from the subjects of said group or population. Likewise, in the case of a control sample “representative” means that the biomarker concentration(s) in said control sample to which a comparison is made in the context of the present disclosure correspond(s) to the average concentration(s) of said biomarker concentration(s) in corresponding individual samples from the subjects of said group or population. Typically, the concentrations of all biomarker concentrations in said control sample correspond to the average concentrations of said biomarker concentrations in corresponding individual samples from the subjects of said group or population. An individual with such values can be considered a “healthy individual” for the purposes of the present disclosure.

[0431] A control sample can be particularly suitably compared to the subject’s sample if it has been obtained from the same type of biological tissue or source in the same, or essentially the same, manner. For example, if the subject’s sample is a serum sample or a plasma sample, a corresponding control sample will likewise be a serum sample or a plasma sample, respectively.

[0432] In some embodiments of the methods and uses described herein, a control may be a control value. The control value may be obtained from a previously taken sample from the same subject.

[0433] It will be appreciated that a useful control value for the purposes of the present disclosure is typically one that has been, or is, obtained using any one of the suitable control samples described herein.

[0434] As used herein, “metabolic syndrome marker”, “marker of metabolic syndrome”, “metabolic syndrome biomarker”, “biomarker of metabolic syndrome”, “metabolic marker”, “marker of the present disclosure”, “biomarker of the present disclosure”, or the similar, comprises at least one biomarker for metabolic syndrome and / or one or more of its complications comprising stearoylsphingosine and / or palmitoylsphingosine as disclosed on the present disclosure. “Metabolic syndrome marker”, “marker of metabolic syndrome”, “metabolic syndrome biomarker”, “biomarker of metabolic syndrome”, “metabolic marker”, “marker of the present disclosure”, “biomarker of the present disclosure”, or the similar, may be used interchangeably in the present disclosure.

[0435] As used herein, a “combination of metabolic syndrome markers”, a ’’metabolic syndrome marker combination”, a “marker combination”, a “metabolic marker combination”, a “biomarker combination”or the similar, comprises a combination of at least one biomarker for 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 may be e.g. a ratio, sum, difference, product, remainder, value, score, calculation, formula, equation, algorithm, or any combination thereof. In one embodiment, the combination comprises stearoylsphingosine and / or palmitoylsphingosine. In one embodiment, the combination comprises stearoylsphingosine / palmitoylsphingosine or palmitoylsphingosine / stearoylsphingosine. A “combination of metabolic syndrome markers”, a ’’metabolic syndrome marker combination”, a “marker combination”, a “metabolic marker combination”, a “biomarker combination”or the similar, may be used interchangeably in the present disclosure.

[0436] In certain embodiments, a metabolic syndrome marker and / or metabolic syndrome marker combination comprises, in addition to stearoylsphingosine and / or palmitoylsphingosine, one or more of other clinical parameters, such as, but not limited to, 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.

[0437] In certain embodiments, a metabolic syndrome marker and / or metabolic syndrome marker combination further comprises one or more of other biomarkers or parameters, including, but not limited to, triglyseride (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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, and / or any combination thereof. In certain embodiments, a metabolic syndrome marker and / or metabolic syndrome marker combination further comprises one or more of other personal information or health data, including, but not limited to, sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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, e.g. from angiography or computed tomography (CT), and / or any combination thereof.

[0438] In some embodiments of all aspects of the disclosure, the metabolic syndrome marker and / or marker combination may be constructed by linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimations, decision trees or, neural networks. In some embodiments, transformation to logistic (risk = (exp(r) / 1+exp(r))*100) or time- to-event model is performed. In some embodiments, transformation to logarithmic scale is performed.

[0439] In some embodiments of all aspects of the disclosure, the metabolic syndrome marker and / or marker combination is a continuous or discrete scoring systems based on the metabolic syndrome biomarker(s) of the present disclosure and / or one or more of any other biomarker or parameter dislosed herein. For discrete scoring, the points may be given based on intervals with non-equal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components. In some embodiments of all aspects of the disclosure, the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

[0440] The term “biomarker value” or “marker value” as used herein refers to a value determined by quantifying the amount of, abundance of, level of, concentration of, quantity of, or activity of, a biomarker within a sample as defined herein.

[0441] As used herein, “stearoylsphingosine” comprises N-stearoyl-D-sphingosine.

[0442] As used herein “palmitoylsphingosine” comprises N-palmitoyl-D-sphingosine.

[0443] As used herein “exogenous stearoylsphingosine” comprises any synthetic or isolated stearoylsphingosine used in the methods and uses of the present disclosure and not originating from a sample from a subject. In some embodiments, the exogenous stearoylsphingosine is isotope-labelled. In some embodiments, the isotope of the isotope-labelled exogenous stearoylsphingosine is deuterium,13C or15N. In some embodiments, the exogenous stearoylsphingosine is stearoylsphingosine-d7. As used herein “exogenous palmitoylsphingosine” comprises any synthetic or isolated palmitoylsphingosine used in the methods and uses of the present disclosure and not originating from a sample from a subject. In some embodiments, the exogenous palmitoylsphingosine is isotope-labelled. In some embodiments, the isotope of the isotope-labelled exogenous palmitoylsphingosine is deuterium,13C or15N. In some embodiments, the exogenous palmitoylsphingosine is palmitoylsphingosine-d7.

[0444] As used herein, “stearoylsphingosine-d7” comprises N-stearoyl-D-sphingosine-d7 .

[0445] As used herein, “palmitoylsphingosine-d7” comprises N-palmitoyl-D-sphingosine-d7 .

[0446] A “treatment” and “therapy” are used interchangeably in the present disclosure and may comprise any therapeutic treatment typically given to a subject at risk of developing metabolic syndrome and / or one or more of its complications or a subject having metabolic syndrome and / or one or more of its complications, such as, but not limited to, lifestyle interventions and / or counselling affecting diet, weight management and physical activity, control of progression of metabolic syndrome and / or one or more of its complications (e.g. blood glucose monitoring, blood pressure and lipid control), diabetes medication (e.g. insulin, metformin, GLP-1 analogues, DPP-4 inhibitors, SGLT2 inhibitors, sulfonylureas, meglitinides, thiazolidinediones and alphaglucosidase inhibitors), blood pressure medication (e.g. diuretics, beta-blockers, angiotensinconverting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), calcium channel blockers, alpha-blockers, alpha-beta-blockers, central agonists, alpha-2 receptor agonists, peripheral adrenergic inhibitors, vasodilators, aldosterone receptor antagonists and direct renin inhibitors), lipid modifying medications (e.g. statins, other HMG-CoA reductase inhibitors, niacin (nicotinic acid), cholesterol absorption inhibitors, cholesteryl ester transfer protein (CETP) inhibitors, bile acid sequestrants, fibrates, phytosterols and PCSK9 inhibitors), or any combination thereof.

[0447] The term “effectiveness of a treatment” and “effectiveness of a therapy” are taken to mean the ability of a treatment and therapy to achieve the therapeutic purpose for which it is administered.

[0448] A “pharmaceutical”, “drug”, “medicament”, “medicine” and “medication” are used interchangeably in the present disclosure and may comprise any pharmaceutical typically given to a subject having metabolic syndrome and / or one or more of its complications, such as, but not limited to, insulin, metformin, GLP-1 analogues, 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 (ARBs), calcium channel blockers, alpha-blockers, alpha-beta-blockers, central agonists, alpha-2 receptor agonists, peripheral adrenergic inhibitors, vasodilators, aldosterone receptor antagonists and direct renin inhibitors and lipid modifying medications, 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, phytosterols and PCSK9 inhibitors, or any combination thereof.

[0449] As used herein, a “composition” and “kit” are used for predicting, diagnosing and detecting metabolic syndrome and / or one or more of its complications and comprise means and elements for assaying the metabolic syndrome biomarkers described in the present disclosure.

[0450] As used herein, a “preparation” is used in the assays determining the biomarkers described in the present disclosure for predicting, diagnosing and detecting metabolic syndrome and / or one or more of its complications.

[0451] For the purposes of the present disclosure, the terms “obtaining data”, “collecting data”, “obtaining information” and “collecting information” may be used interchangeably.

[0452] The terms “the disclosure, description or invention”, “in accordance with the disclosure, description or invention”, “according to the disclosure, description or invention”, “the present disclosure, description or invention” as used herein, are intended to refer to all aspects and embodiments of the disclosure described and / or claimed herein.

[0453] As used herein, the term “comprising” is to be construed as encompassing both “including” and “consisting of”.

[0454] As used herein, “determining”, “assaying” or “detecting” in reference to a biomarker as disclosed herein refers to quantitatively or relatively determining an amount of a biomarker in a sample. For quantitative determination, either the absolute or precise amount of the biomarker in a sample is determined. The relative amount or level of a biomarker in a sample, may alternatively be determined, e.g., the biomarker amount in the sample is determined to be enlarged or diminished with respect to a control as described herein.

[0455] As used herein, a “reagent” or “agent” may be one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s), preparation(s), or any combination thereof used for the methods and uses of the present disclosure. A reagent or agent may also be a combination or mixture of one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s) and preparation(s) used in the methods and uses of the present disclosure.

[0456] In some embodiments, one or more of any components of a reagent is isotope-labelled. In some embodiments, the isotope of the isotope-labelled component is deuterium. In some embodiments, the isotope of the isotope-labelled component is13C or15N. In some embodiments, a reagent is used for assaying in a sample a concentration of at least one biomarker of metabolic syndrome and / or one or more of its complications of the present disclosure. In some embodiments, a reagent is used in a preparation of a reagent, kit or composition for performing the methods and uses of the present disclosure.

[0457] EXAMPLES

[0458] The following examples are provided to illustrate various aspects of the present disclosure. They are not intended to limit the disclosure, which is defined by the accompanying claims.

[0459] Example 1. Materials and Methods

[0460] Description of study cohorts and samples

[0461] Studyl is a Northern European population study. In the current study, serum samples from 7722 participants were analysed. The participants were followed 10 years and during the follow-up time 438 subjects developed diabetes, 181 subjects suffered from stroke, 579 suffered from major adverse cardiovascular event and 34 died due to cardiovascular reasons. Subjects without the outcome in question during the follow-up were used as controls.

[0462] Study2 is a population-based Northern European cohort study. Serum samples from 1260 participants were analysedin the current study. 78 subjects developed diabetes during the followup time of 15 years. Subjects who did not develop diabetes during the follow-up were used as controls.

[0463] Study3 is a prospective observational cohort study from Central Europe. In the current study, serum samples from 4286 participants were analysed. The participants were followed 10 years and 406 subjects developed diabetes and 170 died due to cardiovascular reasons during the follow-up time. Subjects without the outcome in question during the follow-up were used as controls.

[0464] Analytical Methods

[0465] Liquid chromatography mass spectrometry

[0466] Quantification of stearoylsphingosine and palmitoylsphingosine from serum samples was performed using a validated high-throughput mass spectrometry approach. 20 pL of serum or plasma was spiked with deuterated internal standards, D7-stearoylsphingosine and D7- palmitoylsphingosine, and extracted in isopropanokethyl acetate (8:2, v / v) using a Hamilton

[0467] MICROLAB® STAR robot. The levels of stearoylsphingosine and palmitoylsphingosine were quantified on a TripleMS 6500 (SCIEX, Concord, Canada) mass spectrometer equipped with an Sciex MPX LIHPLC system.

[0468] Chromatographic separation was performed on Acquity BEH C18, 2.1 * 75 mm id. 1.7 pm column (Waters, Massachusetts, USA). Mobile phases consisted of (A) 5 mM ammonium acetate in LC- MS grade water with 0.1 % formic acid, and (B) 5 mM ammonium acetate in acetonitrile: 2- propanol (4:3, V / ) with 0.1 % formic acid (FA). The following LC gradient was used: 0.5 min at 80% B, linear increase of B from 80% to 84% in 0.5 min, 84% to 89% B in 1.4 min, 89% to 100% in 0.1 min, 2.0 min at 100% B, 100% to 80% B in 0.1 min and 0.4 min equilibration at 80% prior to the next injection. Flow rate was 500 pl / min and column temperature 60°C.

[0469] Stearoylsphingosine and palmitoylsphingosine were quantified using multible reaction monitoring (MRM) in positive ion mode. Quantification was assessed through calibration line samples comprising of known amounts of synthetic stearoylsphingosine and palmitoylsphingosine and corresponding deuterated standards. The peak area ratios of each analyte to its corresponding deuterated form were calculated and plotted against the added standard concentration and fitted by linear regression analysis. Final concentrations were presented in pM.

[0470] Statistical analyses

[0471] Incidence of metabolic syndrome complications (diabetes and cardiovascular (CV) events stroke, major adverse cardiovascular event and CV death) were investigated by fitting logistic regression models for each of the outcome to obtain Odds Ratios (OR) of the metabolic syndrome markers. The area under the receiver operating characteristic curve (AUC) was also calculated to show how well the model discriminated the patients with the outcome from the patients without the outcome. In addition, associations between the metabolic syndrome markers and the clinical variables were investigated by fitting linear regression models with the metabolic syndrome markers as the response variables and clinical variables as the explanatory variables. All analyses were done using R4.3.0.

[0472] Example 2. Results

[0473] The following tables show the predicting power of the metabolic syndrome markers and marker combinations of the present disclosure. Tables 1 , 3, 5, 7, 9, 11 and 13 disclose the area under the receiver operating characteristic curve (AUC) values for subjects who developed an incidence complication of metabolic syndrome, diabetes and cardiovascular events stroke, major adverce cardiovascular event and CV death, during the follow-up as compared to the control group in Studyl , Study2 and Study3. Superior AUC values for the combinations of the metabolic markers and clinical parameters compared to the AUC values of the clinical parameters in question alone are presented in the tables. 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 marker combinations with clinical parameters of the present disclosure for subjects who developed an incidence complication of metabolic syndrome (diabetes and cardiovascular events stroke, major adverce cardiovascular event and CV death) during the follow-up as compared to the control group in Studyl , Study2 and Study3. As can be seen in the tables, Odds Ratios (OR) based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure provide strong association with incident complications of metabolic syndrome.

[0474] Tables 15, 16 and 17 disclose strong association of the metabolic syndrome markers and marker combinations of the present disclosure with the clinical parameters commonly used in diagnosing metabolic syndrome in Studyl , Study2 and Study3.

[0475] As the markes and marker combinations of the present disclosure provide significant association with both the complications of metabolic syndrome and the clinical parameters commonly used to diagnose metabolic syndrome, the present markers offer an improved method for detecting metabolic syndrome. Compared to the commonly used detection of the syndrome with multiple parameters, the present invention provides an easy, convenient and reliable detection of metabolic syndrome. Early detection of metabolic syndrome with the present biomarkers enable prevention of syndrome progression and occurence of severe complications.

[0476] Table 1 . The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who developed major adverse cardiovascular event (MACE) during the follow-up as compared to the control group in Study! Abbreviations are described in the detailed description of the present disclosure.

[0477] Table 2. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who developed major adverse cardiovascular event (MACE) during the follow-up as compared to the control group in Study"! . Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0478] Table 3. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study"! . Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0479] Table 4. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study! Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0480] Table 5. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models for subjects who developed stroke during the follow-up as compared to the control group in Studyl . Abbreviations are described in the detailed description of the present disclosure.

[0481] Table 6. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who developed stroke during the follow-up as compared to the control group in Study! Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0482] Table 7. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who died due to cardiovascular reasons during the follow-up as compared to the control group in Studyl Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI.

[0483] Other abbreviations are described in the detailed description of the present disclosure.

[0484] Table 8. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who died due to cardiovascular reasons during the follow-up as compared to the control group in Study! Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0485] Table 9. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study2. Abbreviations are described in the detailed description of the present disclosure.

[0486] Table 10. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study2. Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0487] Table 11. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study3. Abbreviations are described in the detailed description of the present disclosure.

[0488] Table 12. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who developed diabetes during the follow-up as compared to the control group in Study3. Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0489] Table 13. The area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (Cl) values of logistic regression models are shown for subjects who died due to cardiovascular reasons during the follow-up as compared to the control group in Study3. Abbreviations are described in the detailed description of the present disclosure.

[0490] Table 14. Statistically significant Odds Ratios (OR) and p-values based on the metabolic syndrome markers, marker combinations and marker combinations with clinical parameters of the present disclosure are shown for subjects who died due to cardiovascular reasons during the follow-up as compared to the control group in Study3. Score refers to a score comprising stearoylsphingosine, palmitoylsphingosine, age, gender and BMI. Other abbreviations are described in the detailed description of the present disclosure.

[0491] Table 15. Association of the metabolic markers and metabolic marker combinations with clinical parameters in Studyl Regression coefficients (beta) and p-values are shown. Abbreviations are described in the detailed description of the present disclosure.

[0492] Table 16. Association of the metabolic markers and metabolic marker combinations with clinical parameters in Study2. Regression coefficients (beta) and p-values are shown. Abbreviations are described in the detailed description of the present disclosure.

[0493] Table 17. Association of the metabolic markers and metabolic marker combinations with clinical parameters in Study3. Regression coefficients (beta) and p-values are shown. Abbreviations are described in the detailed description of the present disclosure.

[0494] Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, numerous equivalents to the specific embodiments described herein both in the Examples and in the body of the entire description. Such equivalents are considered to be within the scope of the present disclosure and are intented to be encompassed by the following claims or the items listed above.

Claims

CLAIMS1. A method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:(a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and(b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

2. A method for assessing the risk of metabolic syndrome and / or one or more of its complications, wherein the method comprises:(a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and(b) determining that the subject has an increased risk of metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

3. A method of monitoring the progression of metabolic syndrome and / or one or more of its complications over time in a subject, wherein the method comprises:(a) assaying a sample from a subject to determine a concentration of a metabolic syndrome marker; and(b) comparing the concentration of (a) to a previously determined concentration of the same metabolic syndrome marker in a sample obtained from the same subject.

4. The method of claim 3, wherein the metabolic syndrome marker comprises stearoylsphingosine.

5. The method of claim 3, wherein the metabolic syndrome marker comprises palmitoylsphingosine.

6. A method of evaluating the effectiveness of a treatment of metabolic syndrome and / or one or more of its complications in a subject, wherein the method comprises:(a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and(b) determining that the treatment is effective, if the sample comprises a decreased concentration of stearoylsphingosine, when compared to a control.

7. A method of evaluating the effectiveness of a treatment of metabolic syndrome and / or one or more of its complications in a subject, wherein the method comprises:(a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and(b) determining that the treatment is effective, if the sample comprises an increased concentration of palmitoylsphingosine, when compared to a control.

8. Use of a metabolic syndrome marker for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises stearoylsphingosine.

9. Use of a reagent for determining a concentration of a metabolic syndrome marker for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic marker comprises stearoylsphingosine.

10. Use of a combination of metabolic syndrome markers for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine.

11. Use of a reagent for determining a concentration of a metabolic syndrome marker combination for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the combination comprises stearoylsphingosine and palmitoylsphingosine, and wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of stearoylsphingosine;(b) assaying the sample from the subject to determine a concentration of palmitoylsphingosine; and(c) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine, when compared to a control.

12. A use of one or more reagents in the preparation of a kit, composition or preparation for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

13. A use of one or more reagents in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker stearoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of stearoylsphingosine.

14. A use of an stearoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of stearoylsphingosine; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control.

15. A reagent for quantifying stearoylsphingosine from a sample obtained from a subject suspected to be at risk of developing metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of stearoylsphingosine.

16. Use of a metabolic syndrome marker for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the metabolic marker comprises palmitoylsphingosine.

17. A use of a reagent for determining a concentration of a metabolic syndrome marker for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of the metabolic syndrome marker; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of the metabolic syndrome marker, when compared to a control, wherein the metabolic marker comprises palmitoylsphingosine.

18. A use of one or more reagents in the preparation of a kit, composition or preparation for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

19. A use of one or more reagents in the preparation of a kit, composition or preparation for detecting in a sample obtained from a subject the concentration of the metabolic syndrome marker palmitoylsphingosine, wherein the detecting comprises assaying the sample from the subject to determine the concentration of palmitoylsphingosine.

20. A use of an palmitoylsphingosine in the preparation of a detection reagent, kit or device for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the assessing comprises:(a) assaying a sample from a subject to determine a concentration of palmitoylsphingosine; and(b) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control.

21. A reagent for quantifying palmitoylsphingosine from a sample obtained from a subject suspected to be at risk of developing metabolic syndrome and / or one or more of its complications by liquid chromatography-mass spectrometry (LC-MS), wherein the quantifying comprises assaying a sample from a subject to determine a concentration of palmitoylsphingosine.

22. A use of a device for detecting one or more metabolic syndrome markers, wherein the device (a) is capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

23. A use of a device system for detecting one or more metabolic syndrome markers, wherein the device system comprises(i) a device (a) capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and(ii) a user interface; and wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome markers comprise stearoylsphingosine.

24. A use of a device for detecting one or more metabolic syndrome markers, wherein the device (a) is capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

25. A use of a device system for detecting one or more metabolic syndrome markers, wherein the device system comprises(i) a device (a) capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and(ii) a user interface; and wherein the use comprises using the detection module, and wherein the one or more metabolic syndrome markers comprise palmitoylsphingosine.

26. A use of a device for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the device (a) is capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and wherein the use comprises:(a) detecting stearoylsphingosine in a sample of a subject using the detection module;(b) determining a concentration of stearoylsphingosine using the data processing module;(c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and(d) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control, using the data processing module.

27. A use of a device system for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the device system comprises(i) a device (a) capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and(ii) a user interface; and wherein the use comprises:(a) detecting stearoylsphingosine in a sample of a subject using the detection module;(b) determining a concentration of stearoylsphingosine using the data processing module;(c) comparing the concentration of stearoylsphingosine to a control using the data processing module; and(d) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises an increased concentration of stearoylsphingosine, when compared to a control, using the data processing module.

28. The use of claim 27, wherein the use for assessing the risk further comprises:(a) detecting palmitoylsphingosine in a sample of a subject using the detection module;(b) determining a concentration of palmitoylsphingosine using the data processing module;(c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and(d) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

29. A use of a device for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the device (a) is capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and wherein the use comprises:(a) detecting palmitoylsphingosine in a sample of a subject using the detection module;(b) determining a concentration of palmitoylsphingosine using the data processing module;(c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and(d) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

30. A use of a device system for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein the device system comprises(i) a device (a) capable of identifying a molecule and determining an abundance of the molecule in a sample, and (b) comprises a detection module and a data processing module; and(ii) a user interface; and wherein the use comprises:(a) detecting palmitoylsphingosine in a sample of a subject using the detection module;(b) determining a concentration of palmitoylsphingosine using the data processing module;(c) comparing the concentration of palmitoylsphingosine to a control using the data processing module; and(d) determining that the subject has an increased risk of developing metabolic syndrome and / or one or more of its complications, if the sample comprises a decreased concentration of palmitoylsphingosine, when compared to a control, using the data processing module.

31. A composition or kit for assessing the risk of developing metabolic syndrome and / or one or more of its complications, for detecting the marker of metabolic syndrome or for performing any of the methods or uses disclosed in any one of the preceding claims, wherein the composition or kit comprises an stearoylsphingosine.

32. A composition or kit for assessing the risk of developing metabolic syndrome and / or one or more of its complications, for detecting the marker of metabolic syndrome or for performing any of the methods or uses disclosed in any one of the preceding claims, wherein the composition or kit comprises an palmitoylsphingosine.

33. The composition or kit of claim 31 or 32, wherein the stearoylsphingosine and / or palmitoylsphingosine comprises isotope-labelled stearoylsphingosine and / or palmitoylsphingosine..

34. The composition or kit of any one of claims 31-33, wherein the stearoylsphingosine and / or palmitoylsphingosine comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine.

35. The composition or kit of any one of claims 31-34, wherein the stearoylsphingosine and / or palmitoylsphingosine comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

36. The composition or kit of any one of claims 31-35, wherein the composition or kit further comprises standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein and / or other element(s) for performing the methods or uses disclosed herein.

37. The composition or kit of any one of claims 31-36, wherein the composition or kit comprises element(s) to permit the collecting of a blood sample.

38. The composition or kit of claim 37, wherein the blood sample is a dried blood spot on a filter or a plasma or serum sample collected on a filter or card.

39. The composition or kit of any one of claims 31-38, wherein the composition or kit further comprises standard(s), control(s), reagent(s), solution(s), solvent(s), container(s), instruction(s) to use it for the methods or uses disclosed herein and / or other element(s) for detecting one or more clinical parameters, wherein the one or more clinical paramethers comprises BMI, age, gender, 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 C-reactive protein (CRP).

40. The composition or kit of any one of claims 31-39, wherein the composition or kit is a test kit for used in a laboratory or a home use test kit.

41. The composition or kit of any one of claims 31-40, wherein the composition or kit is a combination of any standard(s), control(s), reagent(s), solution(s), solvent(s) container(s), instruction(s) to use it for the methods or uses disclosed herein or other element(s) for performing the methods or uses disclosed herein, either purchased from a commercial manufacturer or prepared in-house in a laboratory, used for assaying a concentration of stearoylsphingosine and / or palmitoylsphingosine.

42. The composition or kit of any one of claims 31-41 , wherein the composition or kit is used in mass spectrometry, nuclear magnetic resonance, gas chromatography (GC), two- dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC), ultra-high performance liquid chromatography (LIHPLC) or any combination thereof.

43. A method for detecting stearoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps:(a) Extracting stearoylsphingosine from a sample derived from a subject;(b) Separating stearoylsphingosine by liquid chromatography (LC); and / or(c) Determining the concentration of stearoylsphingosine by mass spectrometry (MS).

44. A method for detecting palmitoylsphingosine by liquid chromatography-mass spectrometry (LC-MS), wherein the method comprises one or more of the following steps:(a) Extracting palmitoylsphingosine from a sample derived from a subject;(b) Separating palmitoylsphingosine by liquid chromatography (LC); and / or(c) Determining the concentration of palmitoylsphingosine by mass spectrometry (MS).

45. A method for assessing the risk of developing metabolic syndrome and / or one or more of its complications, wherein assessing the risk comprises using a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

46. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, or 26-30, wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

47. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46, wherein assessing the risk comprises using the following formula:[1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1))) +1)] * 100, wherein a is a real number.

48. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-47, wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI)) +1)] * 100, wherein a and b are real numbers.

49. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-48, wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)] * 100, wherein a, b and c are real numbers.

50. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-49, wherein assessing the risk comprises using the following formula:[1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age)) +1)] * 100, wherein a, b and c are real numbers.51 . The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-50, wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender)) +1)] * 100, wherein a, b, c and d are real numbers.

52. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-51 , wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + e * glucose)) +1)] * 100, wherein a and e are real numbers.

53. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-52, wherein assessing the risk comprises using the following formula:[1 / (exp(-(a * stearoylsphingosine * palmitoylsphingosineA(-1) + f * HbA1c)) +1)] * 100, wherein a and f are real numbers.

54. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-53, wherein assessing the risk comprises using the following formula:[1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + e * glucose)) +1)] * 100, wherein a, b and e are real numbers.

55. The use or method of any one of claims 1-2, 8-12, 14, 16-18, 20, 26-30 or 46-54, wherein assessing the risk comprises using the following formula:[1 / (exp(-(intercept + a * stearoylsphingosine * palmitoylsphingosineA(-1) + b * BMI + c * age + d * gender + e * glucose + f * HbA1c + g * LDL-cholesterol + h * HDL-cholesterol + i * triglycerides + j * systolic blood pressure + k * insulin + I * CRP)) +1)] * 100, wherein a, b, c, d, e, f, g, h, i, j, k and I are real numbers.

56. The method or use of any one of claims 45-55, wherein the formula comprises 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 parameter(s) selected from BMI, age, gender, glucose, HbA1c, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, systolic blood pressure, insulin and C-reactive protein (CRP), and / or 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 intercept(s).

57. The method or use of any one of claims 47-56, wherein the intercept may change depending on gender.

58. The method or use of any one of the preceding claims, wherein the method or use further comprises palmitoylsphingosine and / or determining a concentration of palmitoylsphingosine.

59. The method or use of any one of the preceding claims, wherein the method or use further comprises detecting at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15 or 16 clinical parameters comprising BMI, age, gender, 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 C-reactive protein (CRP).

60. The method or use of any one of the preceding claims, wherein the method or use further comprises detecting one or more other biomarkers or parameters comprising triglyseride (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 particle (LDL-P), high-density lipoprotein particle (HDL- P), , Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, or any combination thereof, in a sample from the subject.61 . The method or use of any one of the preceding claims, wherein the method or use further comprises using one or more other personal information or health data comprising sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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 otherdiseases, family history of other diseases, medical imaging data, such as from angiography or computed tomography (CT), or any combination thereof.

62. The method or use of any one of the preceding claims, wherein the marker combination comprises linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as support vector machines, kernel estimations, decision trees and / or neural networks.

63. The method or use of any one of the preceding claims, wherein transformation to logistic model, time-to-event model or logarithmic scale is performed.

64. The method or use of any one of the preceding claims, wherein the marker combination comprises a continuous or discrete scoring system based on the metabolic syndrome marker(s) and / or one or more of any other biomarker or parameter.

65. The method or use of any one of the preceding claims, wherein the marker combination comprises discrete scoring, wherein the points are given based on intervals with nonequal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components.

66. The method or use of any one of the preceding claims, wherein the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

67. The method or use of any one of the preceding claims, wherein the risk of developing metabolic syndrome and / or one or more of its complications is assessed for a certain period of time.

68. The method or use of any one of the preceding claims, wherein the risk of developing metabolic syndrome and / or one or more of its complications is assessed over 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, 23, 24, 25, 26, 27, 28, 29 or 30 years.

69. The method or use of any one of the preceding claims, wherein the one or more complications of metabolic syndrome comprise diabetes, such as type 2 diabetes, cardiovascular disease (CVD), cardiovascular (CV) events, stroke, major adverce cardiovascular event (MACE), CV death, stable angina pectoris, unstable angina pectoris, myocardial infarction (Ml), acute myocardial infarction (AMI), acute coronary syndrome (ACS), transient ischemic attacks, deep vein thrombosis, heart failure, hospitalization for heart failure, peripheral artery disease and different forms of arrhythmias, such as atrialfibrillation, kidney disease and / or fatty liver disease, such as non-alcoholic fatty liver disease.

70. The method or use of any one of the preceding claims, wherein the one or more complications of metabolic syndrome comprise diabetes, stroke, cardiovascular disease and / or cardiovascular events.

71. The method or use of any one of the preceding claims, wherein the one or more complications of metabolic syndrome comprise diabetes.

72. The method or use of any one of the preceding claims, wherein the method or use comprises using mass spectrometry (MS), tandem mass spectrometry (MS / MS), nuclear magnetic resonance (NMR), gas chromatography (GC), two-dimensional gas chromatography (GCxGC), liquid chromatography (LC), two-dimensional liquid chromatography (LCxLC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (LIPLC), ultra-high performance liquid chromatography (UHPLC), LC-MS / MS, HPLC-MS / MS, UHPLC-MS / MS, resonance spectroscopy, fluorescence spectroscopy, dual polarization interferometry, an immunoassay, enzymatic assay, colorimetric assay, fluorometric assay, a rapid test, a binding moiety capable of specifically binding the biomarker or any combination thereof.

73. The method or use of any one of the preceding claims, wherein the sample from the subject and / or the control sample may be a blood sample, a blood serum sample, a blood plasma sample, a fraction of blood, a lipid fraction, a saliva sample, an urine sample and / or a tissue sample.

74. The method or use of claim 73, wherein the blood sample comprises a dried blood spot on a filter and / or a blood plasma sample and / or a blood serum sample comprises a plasma or serum sample collected on a filter or card.

75. The method or use of any one of the preceding claims, wherein the biomarkers of the sample are extracted with a solvent or a solvent mixture from the sample, and wherein the solvent or solvent mixture comprises organic and / or inorganic solvents and solutions, comprising methanol, ethanol, butanol, chloroform, isopropanol (2-propanol), n-propanol, ethyl acetate, acetone, acetonitrile, n-hexane, isohexane, benzene, cyclohexane, dichloromethane, heptane, diethyl ether, methylene chloride, toluene, water, other polar or nonpolar solvents or solutions and / or any mixtures or combinations thereof.

76. The method or use of claim 75, wherein the solvent mixture comprises isopropanokethyl acetate.

77. The method or use of claims 75 or 76, wherein the solvent mixture comprises isopropanokethyl acetate at ratio 8:2 (v / v).

78. The method or use of any one of the preceding claims, wherein the method or use further comprises adding to the sample at least one isotope-labelled standard prior to determining the concentration of the biomarker.

79. The method or use of claim 78, wherein the at least one isotope-labelled standard comprises hydrogen, carbon, nitrogen and oxygen isotopes, such as,2H (deuterium),13C and15N.

80. The method or use of claims 78 or 79, wherein the isotope-labelled standards are used in qualitative or quantitative analysis, as internal standards, calibration standards, reference standards and / or in quality control samples81. The method or use of any one of claims 78-80, wherein at least one deuterium-labelled standard is added to the sample.

82. The method or use of any one of claims 78-81 , wherein deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine is added to the sample.

83. The method or use of any one of claims 78-82, wherein the deuterium-labelled stearoylsphingosine comprises stearoylsphingosine-d7 and / or the deuterium-labelled palmitoylsphingosine comprises palmitoylsphingosine-d7.

84. The method or use of any one of the preceding claims, wherein the control comprises a concentration determined from a single healthy individual, a sample that represents a combination of samples from a generalized population of healthy individuals, a control value or a set of data, previously determined, calculated or extrapolated, or to be determined, calculated or extrapolated, or is taken from the literature.

85. The method or use of any one of the preceding claims, wherein detecting stearoylsphingosine and / or palmitoylsphingosine and / or determining the concentration of the metabolic syndrome marker stearoylsphingosine and / or palmitoylsphingosine futher comprises one or more of the following steps:(a) extracting lipids, comprising stearoylsphingosine and / or palmitoylsphingosine, from a sample obtained from a subject;(b) separating the marker stearoylsphingosine and / or palmitoylsphingosine by liquid chromatography (LC); and / or(c) determining the concentration of the marker stearoylsphingosine and / or palmitoylsphingosine by mass spectrometry (MS).

86. The method or use of any one of the preceding claims, wherein 10-200 pl of the sample is used.

87. The method or use of claim 86, wherein 20pl, 10pl or 5 pl of the sample is used.

88. The method or use of any one of the preceding claims, wherein automated lipid extraction and / or a 96-well extraction plate is used.

89. The method or use of any one of the preceding claims, wherein the sample is mixed and centrifuged after adding the extraction solvent.

90. The method or use of any one of the preceding claims, wherein the sample extract is placed into a 96-well MS plate after extraction.91 . The method or use of any one of the preceding claims, wherein the liquid chromatography comprises reversed phase, normal phase, ion-exchange, ion, ion pair, size exclusion and / or affinity chromatography.

92. The method or use of any one of the preceding claims, wherein the liquid chromatography comprises using 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 nonpolar solvent or solution and / or any mixtures or combinations thereof.

93. The method or use of any one of the preceding claims, wherein the liquid chromatography comprises using a gradient comprising two or more mobile phase solvents.

94. The method or use of claim 93, wherein the gradient comprises a gradient with solvent A comprising ammonium acetate in water with formic acid and solvent B comprising ammonium acetate in acetonitrile:isopropanol with formic acid.

95. The method or use of claim 93 or 94, wherein the gradient comprises a gradient with solvent A comprising 1-30 mM ammonium acetate in water with 0.02-0.30% formic acid and solvent B comprising 1-30 mM ammonium acetate in acetonitrile:isopropanol with 0.02-0.30% formic acid.

96. The method or use of any one of the preceding claims, wherein the liquid chromatography comprises using injection volume of 1-30 pl, mobile phase flow rate of 100-2000 pl / min and / or temperature of 30-90°C.

97. The method or use of any one of the preceding claims, wherein the liquid chromatography comprises using reversed phase, normal phase and / or ion-exchange column(s).

98. The method or use of any one of the preceding claims, wherein the mass spectrometry comprises one or more of the following steps:(a) ionizing stearoylsphingosine and / or palmitoylsphingosine to generate ions of stearoylsphingosine and / or palmitoylsphingosine;(b) detecting the ions of stearoylsphingosine and / or palmitoylsphingosine;(c) determining the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine; and / or(d) determining concentrations of stearoylsphingosine and / or palmitoylsphingosine in the sample based on the amount of the ions of stearoylsphingosine and / or palmitoylsphingosine.

99. The method or use of any one of the preceding claims, 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 (LIPLC) or ultra-high performance liquid chromatography (LIHPLC).

100. The method or use of any one of the preceding claims, wherein the LC-MS comprises LC- MS / MS, HPLC-MS / MS and / or UHPLC-MS / MS.

101. The method or use of any one of the preceding claims, wherein the mass spectrometry comprises quadrupole, single-quadrupole, triple-quadrupole, time-of flight, quadrupole time-of-flight, ion-trap, quadrupole ion trap, sector, magnetic sector, electrostatic sector, ion cyclotron, Fourier transform instruments, and / or any combination instrument thereof.

102. The method or use of any one of the preceding claims, wherein the mass spectrometry comprises electrospray, atmospheric pressure chemical, atmospheric pressure photo, chemical, field, electron impact., fast atom bombardment, matrix assisted laser desoption ionization, and / or any combination ionization techniques thereof.

103. The method or use of any one of the preceding claims, wherein the mass spectrometry comprises positive and / or negative ion mode, multiple reaction monitoring,multiple precursor ion scanning, neutral loss scanning, select ion monitoring, total ion chromatogram scan and / or extracted ion chromatogram monitoring.

104. The method or use of any one of the preceding claims, wherein the use of one or more reagents further comprises comparing the concentration of the metabolic syndrome marker stearoylsphingosine and / or palmitoylsphingosine to a control.

105. The method or use of any one of the preceding claims, wherein the reagent comprises one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s), preparation(s), or any combination thereof.

106. The method or use of any one of the preceding claims, wherein the reagent comprises a combination or mixture of one or more of any standard(s), control(s), substance(s), compound(s), solution(s), solvent(s), agent(s), ingredient(s) and preparation(s).

107. The method or use of any one of the preceding claims, wherein the reagent comprises one or more isotope-labelled components.

108. The method or use of claim 107, wherein the one or more isotope-labelled components comprise deuterium,13C or15N.

109. The method or use of claim 107 or 108, wherein the reagent comprises at least one isotope-labelled marker of metabolic syndrome.

110. The method or use of any one of claims 107-109, wherein the reagent comprises at least one deuterium-labelled marker of metabolic syndrome.

111. The method or use of any one of claims 107-110, wherein the reagent comprises deuterium-labelled stearoylsphingosine and / or palmitoylsphingosine.

112. The method or use of any one of claims 107-111, wherein the reagent comprises stearoylsphingosine-d7 and / or palmitoylsphingosine-d7.

113. The method or use of any one of the preceding claims, wherein the control comprises a formula, score, equation, algorithm, calculation, ratio, sum, difference, product, remainder, value, or any combination thereof.

114. The method or use of any one of the preceding claims, wherein the control comprises a value obtained from a previously taken sample from the same subject.

115. The method or use of any one of the preceding claims, wherein stearoylsphingosine comprises synthetic or isolated stearoylsphingosine.

116. The method or use of any one of the preceding claims, wherein stearoylsphingosine comprises an isotope-labelled stearoylsphingosine.

117. The method or use of any one of the preceding claims, wherein the isotope of the isotope-labelled stearoylsphingosine is deuterium,13C or15N.

118. The method or use of any one of the preceding claims, wherein stearoylsphingosine comprises stearoylsphingosine-d7.

119. The method or use of any one of the preceding claims, wherein palmitoylsphingosine comprises synthetic or isolated palmitoylsphingosine.

120. The method or use of any one of the preceding claims, wherein palmitoylsphingosine comprises an isotope-labelled palmitoylsphingosine.

121. The method or use of any one of the preceding claims, wherein the isotope of the isotope-labelled palmitoylsphingosine is deuterium,13C or15N.

122. The method or use of any one of the preceding claims, wherein palmitoylsphingosine comprises palmitoylsphingosine-d7.

123. The method or use of any one of the preceding claims, wherein the subject has previously suffered from metabolic syndrome and / or its complications, is suffering from metabolic syndrome and / or its complications, is suspected of suffering from metabolic syndrome and / or its complications or the subject is a healthy individual with no previous signs or symptoms of metabolic syndrome and / or its complications.

124. The method or use of any one of the preceding claims, wherein the subject is or has been under a treatment, such as, diabetes, CVD, blood pressure or lipid modifying medication, or has not had any previous treatment or medication.

125. The method or use of any one of the preceding claims, wherein the subject has previously suffered or is suffering from CVD and / or its complication(s) and / or has been or is undergoing statin treatment.

126. The method or use of any one of the preceding claims, wherein the subject has previously suffered or is suffering from type 2 diabetes and / or its complications and has been or is undergoing diabetes treatment.

127. The method or use of any one of the preceding claims, wherein the subject has a blood glucose and / or blood pressure level in the normal range.

128. The method or use of any one of the preceding claims, wherein the subject has a blood lipid level, such as, triglyceride, high-density lipoprotein cholesterol and / or low- density lipoprotein cholesterol, in the normal range.

129. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more other biomarkers, parameters or health data.

130. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises a ratio, sum, difference, product, remainder, value, score, calculation, formula, equation, algorithm, or any combination thereof.

131. The combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the combination of metabolic syndrome markers comprises stearoylsphingosine / palmitoylsphingosine and / or palmitoylsphingosine / stearoylsphingosine.

132. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises 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, C-reactive protein (CRP) or any combination thereof.

133. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more other biomarkers or parameters, such as, triglyseride (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 particle (LDL- P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), C-reactive protein (CRP), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), glycated haemoglobin A1c (HbA1c), glucose, suppression of tumorigenicity 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 subgroup composition or particle number, or any combination thereof.

134. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers further comprises one or more other personal information or health data, such as, sex, age, blood pressure, BMI, weight, height, smoking status, diabetes, lipid lowering treatment or other medication, ethnic background, genetic data, geographical 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, angiography or computed tomography (CT), or any combination thereof.

135. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers is constructed by linear combinations, regression models, other unsupervised or supervised frequentist or Bayesian statistical classification or machine learning methods, such as, support vector machines, kernel estimations, decision trees, and / or neural networks.

136. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises transformation to logistic or time-to-event model is performed.

137. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises transformation to logarithmic scale.

138. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises a continuous or discrete scoring system based on the metabolic syndrome marker(s) and / or one or more other biomarker or parameter.

139. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the metabolic syndrome marker or combination of metabolic syndrome markers comprises discrete scoring, wherein points are given based on intervals with non-equal probabilities, quantiles or other cut-off values, determined from the same or other populations, of the individual score components.

140. The metabolic syndrome marker, combination of metabolic syndrome markers, method or use of any one of the preceding claims, wherein the risk of developing metabolic syndrome and / or one or more of its complications is determined as a percentage.

141. The use of claim 22, wherein the molecule comprises at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19 or 20 molecules.

142. The use of claim 22, 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 glycerolipid molecule, a sterol lipid molecule or any combinations thereof.

143. The use of claim 22, wherein the molecule comprises at least one sphingolipid.

144. The use of claim 22, wherein the molecule comprises stearoylsphingosine and / or palmitoylsphingosine.

145. The use of claim 22, wherein the determining is qualitative or quantitative.

146. The use of claim 22, wherein the determining the abundance of the molecule comprises determining a relative or absolute abundance, amount, concentration, level, quantity, or activity of the molecule.

147. The use of claim 22, wherein the detection module comprises a biosensor, spectrometer, immunoassay system, enzymatic system, colorimetric system, nucleic acid amplification system, microfluidic system, ion detector, mass spectrometer, nuclear magnetic resonance detector, ultraviolet detector, ultraviolet / visible light detector, fluorometer, refractive index detector, thermal conductivity 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.

148. The use of claim 22, wherein the detection module is capable of detecting one or more chemical, physical and / or structural properties of a molecule.

149. The use of claim 22, wherein the detection module is capable of detecting molecular weight, mass, charge, electromagnetic signal, magnetic field, frequency, flow rate, light absorption, mass-to-charge ratio, emission of light, chemoluminescence, luminescence, radiance, energy, structure, conductivity, solubility, or any combinations thereof, of a molecule.

150. The use of claim 22, wherein the data processing module is capable of processing data generated by the detection module.

151. The use of claim 22, wherein the data processing comprises interpreting the data generated by the detection module, such as spectral data, identifying the molecule, determining or calculating the abundance of the molecule and / or comparing the data or abundance of the molecule to a control or reference.

152. The use of claim 22, wherein the data processing comprises generating metabolic condition data of a subject.

153. The use of claim 22, wherein the data processing module is further capable of analyzing the data using machine learning or artificial intelligence algorithms to generate predictive models for assessing the metabolic condition data of a subject.

154. The use of claim 22, wherein the user interface is capable of communicating with the data processing module of the device.

155. The use of claim 22, wherein the user interface is capable of analysing and / or displaying the data processed by the data processing module.

156. The use of claim 22, wherein the communication comprises transmitting the data to a remote computing system for further analysis, processing and / or storage.

157. The use of claim 22, wherein the device system further comprises a database or cloud storage for storing, processing and / or analysing the data.

158. The use of claim 22, wherein the user interface is capable of displaying the metabolic condition data of a subject to the subject or a healthcare professional.

159. The use of claim 22, wherein the user interface is capable of providing personalized recommendations based on the metabolic condition data, such as, dietary suggestions, exercise plans, medication reminders and / or any other instructions or recommendations.

160. The use of claim 22, wherein the device system further comprises a wearable component.

161. The use of claim 22, wherein the detection module is integrated into the wearable component.

162. The use of claim 22, wherein the detection module is integrated into the wearable component allowing continuous monitoring of a metabolic condition data of a subject.

163. The use of claim 22, wherein the metabolic condition 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, glycated haemoglobin 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 particle (LDL-P), high-density lipoprotein particle (HDL-P), Apolipoprotein B (ApoB), Apolipoprotein Al (ApoAl), Apolipoprotein All (ApoAII), Apolipoprotein C (ApoC), troponin T (TNT or TnT), troponin I (TNI or Tnl), B-type natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Cystatin C, creatine kinase (CK), suppression of tumorigenicity 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 subgroup composition or particle number, or any parameter related to glucose levels, lipid profiles, hormone levels, or nutritional markers, or any combination thereof.

164. The use of claim 22, wherein the metabolic condition data of the subject comprises one or more metabolic syndrome markers and / or one or more other biomarkers, parameters and / or health data, optionally as specified in any one of claims 132-134.

165. The use of claim 22, wherein the metabolic condition data of a subject comprises assessing the risk of developing metabolic syndrome and / or one or more of its complications.

166. The use of claim 22, wherein the device system further comprises a notifying system, wherein the notifying system is capable of notifying a subject or a healthcare professional if the metabolic condition data indicates an abnormality or a potential health risk.

167. The use of claim 22, wherein the data processing module is capable of performing advanced data analytics and generating processed data based on aggregated data from multiple users.

168. The use of claim 22 or 23, wherein the one or more metabolic syndrome markers further comprise palmitoylsphingosine and / or one or more other biomarkers, parameters and / or heath data.

169. The use of any one of claims 22-25, wherein the one or more metabolic syndrome markers further comprise one or more other biomarkers, parameters and / or heath data.

170. A method of treating or preventing metabolic syndrome and / or one or more of its complications in a subject, the method comprising: administering to the subject a treatment, wherein prior to administering the treatment, the subject has been identified as being at risk to develop metabolic syndrome and / or one or more of its complications by the method according to claim 1 or 2.

171. The method of claim 1 or 2, wherein the method further comprises after the determining step (b),(c) diagnosing the subject as having an increased risk of developing metabolic syndrome and / or one or more of its complications from the results in the determining step (b); and(d) administering a treatment to the subject diagnosed in step (c).

172. The method of any one of claims 3 to 5, wherein the method further comprises after the determining step (b), (c) administering a treatment to the subject.

173. The method of claim 6 or 7, wherein the method further comprises:(c) determining from the results in the determining step (b) that the treatment is not effective in the subject; and(d) escalating the treatment of the subject.

174. A method of treating or preventing metabolic syndrome and / or one or more of its complications in a subject, the method comprising: administering to the subject a further treatment, wherein prior to administering the treatment, the subject has been identified as being ineffectively treated for metabolic syndrome and / or one or more of its complications by the method according to claim 6 or 7.

175. The method of any one of claims 6, 7, or 170-174, wherein the treatment comprises lifestyle interventions and / or counselling to effect a change in diet, weight management, physical activity, controlling the progression of metabolic syndrome and / or one or more of its complications, medication, or any combination thereof.

176. The method of any one of claims 6, 7, or 170-175, wherein the treatment comprises administering a pharmaceutical.

177. The method of claim 176, wherein the pharmaceutical is selected from insulin, metformin, GLP-1 analogues, DPP-4 inhibitors, SGLT2 inhibitors, sulfonylureas, meglitinides, thiazolidinediones, alpha-glucosidase inhibitors, blood pressure medications, such as diuretics, beta-blockers, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), calcium channel blockers, alphablockers, alpha-beta-blockers, central agonists, alpha-2 receptor agonists, peripheral adrenergic inhibitors, vasodilators, aldosterone receptor antagonists and direct renin inhibitors and lipid modifying medications, such as statins, other HMG-CoA reductase inhibitors, niacin (nicotinic acid), cholesterol absorption inhibitors, cholesteryl ester transfer protein (CETP) inhibitors, bile acid sequestrants, fibrates, phytosterols and PCSK9 inhibitors, or any combination thereof.

178. The method of any one of claims 6, 7, or 170-177, wherein the method further comprises requesting a test from a laboratory, which provides the results of an assay useful for determining the concentration of stearoylsphingosine and / or palmitoylsphingosine, and administering to the subject a treatment, if the subject has an increased concentration of stearoylsphingosine and / or a decreased concentration of palmitoylsphingosine, as compared to the respective control.

179. A use of a pharmaceutical for the treatment of metabolic syndrome and / or one or more of its complications comprising determining the pharmaceutical to be effective in the treatment of metabolic syndrome and / or one or more of its complications according to the method of claim 6 or 7.

180. The use of claim 179, wherein the pharmaceutical is administered at a dose which causes the concentration of stearoylsphingosine and / or palmitoylsphingosine in the sample to change from the initial concentration towards the concentration in the respective control.

181. The method or use of any one of the preceding claims, wherein the subject has a normal glucose level.

182. The method or the use of claim 181 , wherein the normal glucose level comprises a fasting venous plasma glucose concentration of less than 6.1 mmol / L (110 mg / dL).

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