CN111060640A - Method, application and device for determining blood lipid profile related to insulin resistance - Google Patents
Method, application and device for determining blood lipid profile related to insulin resistance Download PDFInfo
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- CN111060640A CN111060640A CN201911378505.0A CN201911378505A CN111060640A CN 111060640 A CN111060640 A CN 111060640A CN 201911378505 A CN201911378505 A CN 201911378505A CN 111060640 A CN111060640 A CN 111060640A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/64—Electrical detectors
- G01N30/68—Flame ionisation detectors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/72—Mass spectrometers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
- G01N2030/8809—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample
- G01N2030/8813—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample biological materials
- G01N2030/8822—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample biological materials involving blood
Abstract
The invention relates to a method for determining a blood lipid profile associated with insulin resistance, comprising the steps of: determining insulin resistance in a range of biological systems; determining one or more blood lipid profiles of a series of biological system samples; determining a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis; selecting a correlation between insulin resistance and one or more blood lipids; the invention provides a method for determining the correlation between one or more blood lipid spectrums of a biological system and the insulin resistance of the biological system by a multivariate analysis method, and the insulin resistance of the biological system can be measured according to the detection condition of blood lipid in practical application according to the correlation, so that the method is not only simple, but also low in cost.
Description
Technical Field
The invention relates to the technical field of insulin resistance detection, in particular to a method, application and device for determining a blood lipid profile related to insulin resistance.
Background
Metabolic Syndrome (MSX) is a characteristic manifestation of insulin resistance and is closely related to the body's fatty excess and sedentary lifestyle. It is closely associated with the increase in western obesity, which leads to serious health problems including severe obesity, type II diabetes, dyslipidemia, hypertension, heart disease and stroke. The disease is usually asymptomatic at first, so most people do not realize that they are suffering from the disease until they start to internally attack the host with serious consequences.
Currently, insulin resistance is commonly measured by the euglycemic clamp method, which returns glucose levels to the initial levels prior to insulin infusion by measuring the Glucose Infusion Rate (GIR) after insulin infusion, which is a measure of systemic insulin resistance.
However, this method of using the euglycemic forceps is expensive, complicated, and invasive and thus not suitable for any routine activities, and is only suitable for scientific research work, and thus there is a need for an easy, low-cost method and apparatus for determining insulin resistance.
Disclosure of Invention
The present invention is directed to a method, an application and a device for determining a blood lipid profile associated with insulin resistance, which overcome the above-mentioned drawbacks of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method of constructing a blood lipid profile associated with insulin resistance, wherein the method comprises the steps of:
the first step is as follows: determining insulin resistance in a range of biological systems;
the second step is that: determining one or more blood lipid profiles of a series of biological system samples;
the third step: determining a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis;
the fourth step: the correlation between insulin resistance and one or more blood lipids is selected.
The method for determining the blood lipid profile related to insulin resistance is provided, wherein the sample is from a mammal.
The method for determining the blood lipid profile related to insulin resistance is provided, wherein the sample comprises tissues or body fluids.
The method for determining a blood lipid profile associated with insulin resistance according to the present invention, wherein in the first step, insulin resistance is determined using the glucose clamp.
The method for determining a blood lipid profile associated with insulin resistance according to the present invention, wherein in the second step the blood lipid profile is determined using at least one spectroscopic technique, at least one electromigration-based technique or at least one chromatographic technique.
Use of a method for determining a blood lipid profile associated with insulin resistance according to the above method for determining a blood lipid profile associated with insulin resistance, characterized in that the method of use comprises the steps of:
the first step is as follows: determining one or more blood lipid profiles in a sample of the biological system;
the second step is that: determining insulin resistance of the biological system from the correlation based on the determined one or more blood lipid profiles.
The invention relates to application of a method for determining a blood lipid profile related to insulin resistance, which further comprises the following steps: adding information of biomolecules to one or more of the blood lipid profiles.
Use of a method for determining a blood lipid profile associated with insulin resistance according to the above method for determining a blood lipid profile associated with insulin resistance, wherein the use comprises: one or more characteristics of blood lipids are used to determine the level of insulin resistance in a biological system.
Use of a method for determining a blood lipid profile associated with insulin resistance according to the above method for determining a blood lipid profile associated with insulin resistance, wherein the use comprises: one or more blood lipid profiles are used to design intervention strategies in pharmaceutical, nutraceutical, functional food, herbal or nutritional applications.
A device for determining a blood lipid profile associated with insulin resistance, according to the method for determining a blood lipid profile associated with insulin resistance as described above, wherein the device comprises a first detection means, a second detection means and an analysis means;
the first detection mechanism is used for measuring insulin resistance of a series of biological systems;
the second detection mechanism is used for measuring one or more blood lipid spectrums of a series of biological system samples;
the analysis mechanism is configured to determine a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis.
The invention has the beneficial effects that: the invention provides a method for determining the correlation between one or more blood lipid spectrums of a biological system and the insulin resistance of the biological system by a multivariate analysis method, and the insulin resistance of the biological system can be measured according to the detection condition of blood lipid in practical application according to the correlation, so that the method is not only simple, but also low in cost.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be further described with reference to the accompanying drawings and embodiments, wherein the drawings in the following description are only part of the embodiments of the present invention, and for those skilled in the art, other drawings can be obtained without inventive efforts according to the accompanying drawings:
FIG. 1 is a flow chart of a method for determining a blood lipid profile associated with insulin resistance according to a preferred embodiment of the present invention;
FIG. 2 is a flowchart of the method of determining a blood lipid profile associated with insulin resistance according to a preferred embodiment of the present invention;
FIG. 3 is a graph showing the correlation between the measured blood lipid profile and insulin resistance and the prediction of insulin resistance from the blood lipid profile in the experiment of the present invention;
FIG. 4 is a more in-depth analysis chart of the experiment of the present invention for individual components;
FIG. 5 is a graph of the effectiveness analysis of herbal interventions for the experiments of the present invention;
FIG. 6 is a graph of the PCA analysis of the differences between the treatment control group and the treatment groups of different batches of the drug substance for the experiments of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without inventive step, are within the scope of the present invention.
The method for determining the blood lipid profile associated with insulin resistance according to the preferred embodiment of the present invention, as shown in fig. 1, comprises the following steps:
s01: determining insulin resistance in a range of biological systems;
s02: determining one or more blood lipid profiles of a series of biological system samples;
s03: determining a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis;
s04: selecting a correlation between insulin resistance and one or more blood lipids;
the invention provides a method for determining the correlation between one or more blood lipid spectrums of a biological system and the insulin resistance of the biological system by a multivariate analysis method, the insulin resistance of the biological system can be determined according to the detection condition of blood lipid in practical application according to the correlation, the determination can be carried out before the disease develops to an irreversible stage, the prevention effect is achieved, and the method is simple and low in cost
The screening method is suitable for screening general healthy people, people with one or more symptoms of metabolic syndrome, high-incidence people of metabolic syndrome or any related diseases, and particularly has remarkable effects in aspects such as impaired glucose tolerance test, fasting blood glucose level test and the like;
wherein the biological system may be a number of different biological systems or a number of different conditions of a particular biological system; the series of biological systems preferably comprises at least two biological systems or at least two different conditions of one biological system, preferably the number of biological systems is between 5 and 100.
When the blood fat spectrum is measured, the measurement can be carried out according to the gender, the age and other modes;
wherein, multivariate analysis technique is a conventional technical means in the field, and preferably, in order to extract the maximum value from the data, a multivariate analysis tool can be used together with other statistical and informatics methods;
one or more of the profiles may or may not contain a particular lipoprotein component or characteristic thereof, such as High Density Lipoprotein (HDL), Very Low Density Lipoprotein (VLDL), and Low Density Lipoprotein (LDL);
suitable blood lipids for measurement include polar and non-polar lipids such as free fatty acids, diglycerides and triglycerides, sterol sterols, mushroom sterols, β -sitosterol, cholesterol and cholesterol esters, arachidonic acid, prostaglandins, steroids, isoprenoids, hopanes, lipid peroxides, myo-mycolic acid, ether lipids, phospholipids, lysine phosphatidylcholine, sphingomyelin, phosphatidylglycerol, phosphatidylinositol and phosphatidylserine, bile acids, ceramides and glycolipids such as glycolipids and glyceroglycolipids, and the like;
preferably, one or more blood lipids are selected from the group comprising sphingomyelin.
Preferably, the sample is from a mammal, such as a human or an animal, preferably a human, for the purpose of assay and intervention, and the animal sample is more suitable for testing and designing new interventions or for studying different phenotypes or other biologically relevant parameters associated with metabolic syndrome.
Preferably, the sample comprises tissue or body fluid, preferably body fluid; suitable body samples include blood, urine, saliva or in special cases cerebrospinal fluid (CSF), etc.
Preferably, in S01, the insulin resistance is measured by the positive glucose clamp, and other known methods can be used to measure the insulin resistance of the biological system, and such equivalent alternatives are included in the scope of the present invention.
Preferably, in S02, the blood lipid profile is determined using at least one spectroscopic technique, at least one electromigration-based technique or at least one chromatographic technique; preferably, a liquid chromatography-mass spectrometry or gas chromatography-mass spectrometry or flame ionization detection or liquid chromatography-mass spectrometry technique (LCMS) is used.
An application of the method for determining the blood lipid profile associated with insulin resistance, as shown in fig. 2, comprises the following steps:
s11: determining one or more blood lipid profiles in a sample of the biological system;
s12: based on the determined one or more blood lipid profiles, insulin resistance of the biological system is determined from the correlation.
Preferably, step S11 is repeated at a plurality of time points;
preferably, the method further comprises the following steps: the addition of information on biomolecules, such as genes, transcripts, proteins, metabolites and (trace) elements, etc., to one or more of the blood lipid profiles.
Use of a method for determining a blood lipid profile associated with insulin resistance, according to which method the use comprises: using one or more characteristics of blood lipids to determine a level of insulin resistance in a biological system; preferably, the sample being assayed comprises a body fluid or tissue.
Use of a method for determining a blood lipid profile associated with insulin resistance, according to which method the use comprises: one or more blood lipid profiles are used to design intervention strategies in pharmaceutical, nutraceutical, functional food, herbal or nutritional applications.
A device for determining a blood lipid profile associated with insulin resistance, according to the method for determining a blood lipid profile associated with insulin resistance as described above, the device comprising a first detection means, a second detection means and an analysis means;
a first detection mechanism for determining insulin resistance of a range of biological systems;
a second detection mechanism for determining one or more blood lipid profiles of a series of biological system samples;
an analysis mechanism for determining a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis.
Experimental data:
the feasibility of using blood lipids to measure insulin resistance was demonstrated by steps S01-S03 in experiments using APOE 3Leiden transgenic mouse model, which has been used to induce insulin resistance using a special diet regime.
APOE 3Leiden (E3L) transgenic mice have elevated plasma cholesterol and triglyceride levels, mainly in the VLDL/LDL lipoprotein fraction. Numerous studies have shown that E3L mice respond more strongly to sucrose, fat and cholesterol feeding and have a more pronounced effect on plasma VLDL and chylomicron levels than wild type mice. In addition, E3L mice were also sensitive to high lipid-induced insulin resistance. Male mice are used as a model of early-onset type II diabetes based on insulin resistance. Male heterozygote E3L mice were from SPF breeders and were housed in a clean, conventional animal room (relative humidity 50-60%, temperature 21 ℃, photoperiod 6 am to 6 pm) during the experiment. Mice were randomly fed food and acidified tap water and analyzed by positive clamp technique for the effect of a high fat, high calorie diet on insulin sensitivity in APOE x 3Leiden mice.
After inducing insulin resistance using a High Fat High Calorie (HFHC) diet, plasma was collected from APOE x 3Leiden mice and insulin resistance was determined by blood glucose clamp analysis of each mouse in step S01.
In step S02, the blood lipids are analyzed in the broadest manner by a blood lipid analysis method, which can be variously combined with gas chromatography analysis techniques, but preferably, the blood lipids can be analyzed and quantified using mass spectrometry or flame ionization detection or the mentioned methods in combination with mass spectrometry (LC/MS) or any other method. In this example, the LC/MS configuration is selected.
In step S03, a multiple regression method is selected, and after Orthogonal Signal Correction (OSC), Partial Least Squares (PLS) are used to determine which components are most suitable for predicting insulin resistance.
The results are shown in fig. 3, which shows the correlation between the insulin resistance values predicted by the lipid method and the observed insulin resistance measured by the analysis of the positive glycocalyx technique, wherein the X-axis is the correlation between the measured blood lipid profile and insulin resistance, and the numbers are statistically determined relative amounts, and the Y-axis is the prediction of insulin resistance from the blood lipid profile, and the numbers are statistically determined relative amounts. The correlation is very high, indicating that the lipid molecules have a high information content in insulin resistance. A more in-depth analysis chart of individual components can be obtained by examining the component with the highest weight factor in partial least squares regression (PLS), see fig. 4, in which the X-axis is the ranking of the molecular weights of the blood lipids determined by liquid chromatography mass spectrometry in units of molecular weights, and the Y-axis is the weight factor for determining the effectiveness of the blood lipid component by partial least squares regression, where 0 is invalid, greater than 0 indicates that the blood lipid component is directly proportional to insulin sensitivity, and less than 0 indicates that the blood lipid component is inversely proportional to insulin sensitivity;
another example of the invention measures insulin resistance by using longitudinal and multilevel information based on blood lipids or on blood lipids in combination with other biochemical components:
blood glucose levels were measured 5 times within 3 hours after the high-sugar beverage was taken, and the body's ability to properly handle excess sugar after the high-sugar beverage was taken was measured.
The longitudinal, time-resolved or time data reflecting the imbalance or change of the dynamic balance of the system can be obtained by measuring the blood lipid spectrum of different time points to judge whether the system is interfered.
The frequency of sampling may range from a few seconds to a few minutes depending on the actual interfering factor used, e.g. with or without chemicals, nutrients or special variants thereof, herbs, drugs etc. interfering with the system.
An example of herbal intervention is given in fig. 5, using the ApoE 3Leiden transgenic mouse model described above, using herbal intervention to reveal dose-response profiles based on blood lipid profiles indicative of insulin resistance, the time effect of batch intervention using Partial Least Squares (PLS); in the figure, the X-axis represents the intervention time of the drug crystals on the animal in weeks; the Y axis represents the scores of effectiveness of different production drug batches by adopting a partial least squares regression method, 0 represents invalidity, greater than 0 represents that the drug batches are in direct proportion to the effectiveness, and less than 0 represents that the drug batches are in inverse proportion to the effectiveness;
performing principal component analysis on partial least squares, wherein the therapeutic effect on blood lipid spectrum is shown in FIG. 6, which is an analysis method for analyzing and processing the difference between the control group and the medicinal material treatment groups of different batches by using a PCA method, and PC1(X axis) and PC2(Y axis) are respectively the analysis in two maximum variable directions, and the unit is;
note: PCA: principal Component Analysis (PCA) is a statistical process that uses orthogonal transformations to convert observed values of a set of possible correlated variables (each entity having a different value) into a set of linearly uncorrelated variables called principal components. This transformation is defined in such a way that the first principal component has the largest possible variance (i.e., accounts for as much of the variability in the data as possible), and each subsequent component in turn has the largest possible variance under its constraint of being orthogonal to the preceding component. The resulting vectors (each vector is a linear combination of variables, containing n observations) are an uncorrelated set of orthogonal bases. Principal component analysis is sensitive to relative scale changes of the original variables.
It should be noted that, in order to ensure the rigor and authenticity of the scientific research, fig. 3 to fig. 6 are experimental data directly obtained from the actual experiment, and are charts directly generated by the analysis software.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (10)
1. A method of determining a blood lipid profile associated with insulin resistance, the method comprising the steps of:
the first step is as follows: determining insulin resistance in a range of biological systems;
the second step is that: determining one or more blood lipid profiles of a series of biological system samples;
the third step: determining a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis;
the fourth step: the correlation between insulin resistance and one or more blood lipids is selected.
2. The method of determining a blood lipid profile associated with insulin resistance according to claim 1, wherein the sample is from a mammal.
3. The method of determining a blood lipid profile associated with insulin resistance according to claim 1, wherein the sample comprises a tissue or a body fluid.
4. The method for determining a blood lipid profile associated with insulin resistance according to any one of claims 1 to 3, wherein in the first step, insulin resistance is determined using the positive glucose clamp.
5. The method according to any one of claims 1 to 3, wherein in the second step, the lipid profile is determined using at least one spectroscopic technique, at least one electromigration-based technique or at least one chromatographic technique.
6. Use of a method for determining a blood lipid profile associated with insulin resistance according to any one of claims 1 to 5, comprising the steps of:
the first step is as follows: determining one or more blood lipid profiles in a sample of the biological system;
the second step is that: determining insulin resistance of the biological system from the correlation based on the determined one or more blood lipid profiles.
7. Use of a method of determining a blood lipid profile associated with insulin resistance according to claim 6, further comprising the method of: adding information of biomolecules to one or more of the blood lipid profiles.
8. Use of a method for determining a blood lipid profile associated with insulin resistance according to any one of claims 1 to 5, comprising: one or more characteristics of blood lipids are used to determine the level of insulin resistance in a biological system.
9. Use of a method for determining a blood lipid profile associated with insulin resistance according to any one of claims 1 to 5, comprising: one or more blood lipid profiles are used to design intervention strategies in pharmaceutical, nutraceutical, functional food, herbal or nutritional applications.
10. A device for determining a blood lipid profile associated with insulin resistance according to the method for determining a blood lipid profile associated with insulin resistance of any one of claims 1 to 5, wherein the device comprises a first detection means, a second detection means and an analysis means;
the first detection mechanism is used for measuring insulin resistance of a series of biological systems;
the second detection mechanism is used for measuring one or more blood lipid spectrums of a series of biological system samples;
the analysis mechanism is configured to determine a correlation of insulin resistance to one or more blood lipid profiles using multivariate analysis.
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