KR101759786B1 - Method for diagnosing a obesity using the concentration of serum lipid metabolites and screening of anti-obesity food or composition for treating obesity using the same - Google Patents

Abstract

The present invention relates to a method for measuring the concentration of two or more triacylglycerols (TG) in blood separated from a subject; And comparing the measured concentration of the two or more triacylglycerols (TG) and the concentration of each triacylglycerol in the blood separated from the normal group to determine whether or not the subject is obese. Information for diagnosis or treatment of obesity And to a method of providing the same. Further, by utilizing the serum lipid metabolites present in the blood separated from the subject as the marker for the diagnosis of obesity, it is possible to effectively determine whether a specific food or drug is effective for the treatment of obesity of the subject Can be used.

Description

TECHNICAL FIELD [0001] The present invention relates to a method for diagnosing obesity using serum lipid metabolite concentration, and a screening method for an anti-obesity food or a composition for treating obesity using the same. BACKGROUND ART OBESITY USING THE SAME}

The present invention relates to a method for diagnosing obesity by measuring the concentration of serum lipid metabolites in blood separated from a subject, and a method for screening an anti-obesity food or a composition for treating obesity using the method.

Recently, obesity patients are increasing as the eating habits are improved and lifestyle becomes more convenient. Most of the obesity is consumed among the energy consumed and the remaining part is converted to fat and accumulated in various parts of the body, especially in subcutaneous tissue and abdominal cavity. Obesity is a disease characterized by the accumulation of much more fat in the body than the amount of fat required for functioning of the adipose tissue, which in turn interferes with normal biochemical and physiological functions, as well as causes various diseases, especially diabetes, hypertension and coronary artery disease. Much effort must be made.

In addition, hyperlipemia refers to a state in which abnormal lipids such as cholesterol and triglyceride in blood are abnormally increased. Hyperlipidemia causes and promotes atherosclerosis, and in severe cases can cause angina, myocardial infarction, and the like. Hyperlipidemia develops into atherosclerosis, heart disease, stroke, etc., which threatens health and life.

In particular, obesity and hyperlipidemia induced by a high-fat diet (HFD) are the most important risk factors for the development of diabetes mellitus, atherosclerosis, chronic liver disease, coronary heart disease, fatty liver and hypertension, And treatment should be considered in the continuation of a healthy lifestyle.

Obesity and hyperlipidemia are both disorders of lipid metabolism characterized by abnormal lipid levels. In this study, the inventors studied biochemical abnormalities in HFD-fed obese mice using mass spectrometry (MS) -based serum lipid profiling and conventional serological chemistry analysis. MS-based lipidomics have obtained an overall profile of endogenous lipids, including lysophospholipids, phospholipids and triacylglycerols, all of which are metabolites closely related to metabolic diseases. The inventors performed multivariate statistical analysis to identify the lipid metabolites that contribute to discrimination among mice fed normal diet (ND) and high fat diet (HFD).

Korean Patent Publication No. 10-2015-0074759 Korean Patent Publication No. 10-2015-0013387

One embodiment of the present invention is to provide information for diagnosing or treating obesity by comparing the concentration of serum lipid metabolites in the blood separated from the subject to the concentration of each metabolite in the blood separated from the normal group. It is another object of the present invention to provide a screening method for an anti-obesity food or a composition for treating obesity, which uses this principle to determine whether a specific food or drug candidate group is effective for the treatment of obesity in a subject.

An aspect of the present invention provides a method for measuring the concentration of at least two triacylglycerols (TG) in blood separated from a subject; And comparing the measured concentration of the two or more triacylglycerols (TG) and the concentration of each triacylglycerol in the blood separated from the normal group to determine whether or not the subject is obese. Information for diagnosis or treatment of obesity Provide a method of providing.

As used herein, the terms "subject" and "entity" include animals such as primates, rodents, canines, felines, horses, sheep, pigs, and the like, preferably human.

As used herein, the term "triacylglycerol (TG)" refers to an ester bond of three fatty acid molecules to three hydroxyl groups contained in glycerol, and is a generic term for fats and oils. They preferably include saturated, unbranched and unsubstituted fatty acid radicals, and the number of carbon atoms contained in the fatty acid is not limited. They may also be mixed esters, i. E., Tri-esters of glycerol with different fatty acids.

As used herein, the term "normal group" means an individual having a standard body weight among individuals of the same species, same sex, and similar age as the subject. Specifically, when applied to humans, it means an individual having a body weight (kg) of {(elongation (cm) -100) X 0.9} 10%.

In the present invention, the concentration of the metabolite, such as triacylglycerol, in the blood can be measured by a method known in the art, for example, a colorimetric assay, an enzymatic method, a chemiluminescence immunoassay, or a direct measurement method using a blood chemistry analyzer.

According to one embodiment of the present invention, there is provided a method for measuring the concentration of triacylglycerol, comprising: measuring the concentration of at least one triacylglycerol having more than 50 carbon atoms and at least one triacylglycerol having less than 50 carbon atoms in the blood separated from the subject; And comparing the measured value with the concentration of each triacylglycerol in the blood separated from the normal group to determine whether or not obesity is present.

According to an embodiment of the present invention, the triacylglycerol having a carbon number of more than 50, the concentration of which is measured in blood separated from the subject, is preferably TG 50: 2, TG 50: 3, TG 50: 4, TG 52: 2, TG 52: 3, TG 52: 4, TG 52: 5, TG 54: 3, TG 54: 4, TG 54: 5, TG 54: 6, TG 54: 7, TG 56: 6, TG 56: 7, TG 56: 8 and TG 56: 9, and more preferably TG 52: 3, TG 52: 4 and TG 54: TG 46: 3, TG 47: 0, TG 47: 1, TG 48: 6, and TG 49: 3 are preferably used as the at least one triacylglycerol having a carbon number of less than 50 measured in blood separated from the subject. 2, and more preferably TG 47: 0.

The numbers listed with the metabolite names used in this specification indicate the number of carbons and the number of multiple bonds in the metabolite. For example, "TG 50: 2" refers to triacylglycerol having 50 carbons and two multiple bonds. The same applies to other metabolites in the specification unless otherwise specified below.

One embodiment of the present invention is directed to a method for the preparation of a cholesteryl ester (CE), a cholesteryl ester (CE), a cholesteryl ester (CE), a triacylglycerol and a triacylglycerol in combination with one or more triacylglycerols having more than 50 carbon atoms and one or more triacylglycerols having less than 50 carbons, Measuring the concentration of one or more lysophosphatidylcholine (LPC) or one or more phosphatidylcholine (PC); And comparing the measured value with the concentration of each substance in the blood separated from the normal group to determine whether or not obesity is present.

As used herein, the term "cholesteryl ester (CE)" refers to a molecule in which the fatty acid is esterified to the hydroxyl group of the cholesterol 3-position. About two-thirds of the serum cholesterol is ester-type and contains a lot of linoleic acid. Since it is less hydrophilic than the free form, it exists in the central part in the lipoprotein. It is produced by the action of LCAT in the serum, and when the cholesterol is deposited in the tissue, the ester form increases.

As used herein, the term " lysophosphatidylcholine (LPC) "is a type of lysophospholipid, which refers to one molecule of fatty acid bound to the 1-position or 2-position of glycerol of phosphatidylcholine (lecithin). There are two types of 1-acylisophosphatidylcholine and 2-acyllisphosphatidylcholine, but the acyl group of 2-acylisophosphatidylcholine is unstable because it is prone to dislocation, and thus generally indicates 1-acylisophosphatidylcholine. Typical inverted-cone molecules (hydrophilic in the hydrophilic group are more amphoteric than hydrophobic in the hydrophobic group) and form spherical micelles instead of bimolecular structures in aqueous solution.

As used herein, the term "phosphatidylcholine (PC)" is a representative cognitive barrier, accounting for about 70% of total cognitive function in yolk sac and about 60% of total cognitive function in human serum. It has a structure in which two molecules of fatty acid, phosphoric acid and choline are bonded to glycerin. According to one embodiment of the present invention, the cholesteryl ester measured in the blood separated from the subject can be preferably CE 20: 3 or CE 20: 4. The lysophosphatidylcholine whose concentration is measured in the blood separated from the subject can be preferably LPC 18: 0, LPC 18: 1, LPC 20: 4 or LPC 22: 6, more preferably LPC 18: 0 < / RTI > The phosphatidylcholine whose concentration is measured in the blood separated from the subject can be preferably PC 34: 1, PC 36: 1, PC 36: 2 or PC 36: 3.

 In one embodiment of the present invention, the determination of the obesity is based on the concentration of blood in the blood separated from the normal group, the concentration of triacylglycerol having a carbon number of more than 50 in the blood separated from the subject is further decreased, Of the amount of triacylglycerol is increased, the subject is determined to be obese. The present invention provides a method for providing information for diagnosing or treating obesity.

According to one embodiment of the present invention, the determination of the obesity may be made by comparing the measured value of the concentration of triacylglycerol in the blood separated from the subject with the previously measured value of the concentration of the control group, By simultaneously measuring the concentration of triacylglycerol in the blood and comparing the measured values of the concentration or by comparing the concentration differences relatively.

On the other hand, the method for providing information for diagnosing or treating obesity may be one for diagnosing or treating obesity induced by high fat diet.

Another aspect of the present invention provides a method for the treatment of obesity comprising the steps of: measuring the concentration of two or more triacylglycerols (TG) in blood separated from a subject to which an anti-obesity food or a candidate compound of the composition for treating obesity has been administered; And comparing the concentrations of the two or more triacylglycerols (TG) measured and the concentration of each triacylglycerol in the blood separated from the subject before administering the subject compound to the anti-obesity food or composition for treating obesity And determining the effectiveness of the candidate group of the composition for treating obesity or an anti-obesity food. The present invention also provides a method of screening for an anti-obesity food or a composition for treating obesity.

In this method, the food or drug candidates of interest are administered to the subject, and after a predetermined time has elapsed, blood is taken from the subjects and the concentrations of the metabolites in the blood before and after the administration are compared. Whether or not it is valid and the degree of the effect can be selected.

The food or drug candidate group may be administered or carried out by a conventional method depending on the respective characteristics, but the present invention is not limited thereto. That is, the food or drug candidate group is generally administered orally, but it can be administered by parenteral administration such as injection or ointment.

The type of the specific marker for the screening method is the same as the marker used for the determination of the obesity.

Using the information providing method and screening method for diagnosing or treating obesity according to an embodiment of the present invention, serum lipid metabolites present in blood separated from a subject can be used as a marker for diagnosis of obesity, The diagnosis of the patient, the effect of the food or the drug on the anti-obesity, and the comparison before and after the treatment can be effectively judged. Especially, it is effective in diagnosis and treatment of obesity derived from acquired dietary habits, etc.

FIG. 1 shows the characteristics ((A) body weight, (B) liver weight, (C) subcutaneous fat mass, (D) body weight of mice fed with the general diet (ND, n = 7) and high fat diet (HFD, n = Kidney fat mass, (E) spleen fat mass, (F) triacylglycerol level, (G) cholesterol level and (H) LDL-cholesterol level.
Fig. 2 shows the tissue organization of the fatty liver part (the rod shows 30 mu m) in which the liver tissue of the general diet (ND) and high fat diet (HFD) mice was stained with oil-red O. Fig.
Figure 3 is a graph showing the changes in phospholipid and triacylglycerol (LPC: lysophosphatidylcholine, DG: diacylglycerol, CE: cholesterol) in mouse serum by direct injection into a direct injection ionization-tandem mass spectrometer (ESI-MS / MS) Tg: triacylglycerol, m / z: mass to charge ratio, NL: normalized intensity level).
Figure 4 (A) shows the principal component analysis (PCA) numerical plot (PC1 vs. PC2) (normal diet (ND, ●) based on direct injection of mouse serum samples from both groups on nanoelectronic spray- (HFD, □) and quality control (QC, ◆) samples, wherein each point in the numerical plot represents an individual sample and the center and distance differences of the ellipses represent the mean and standard deviation, respectively; (B) shows a PCA numerical plot (R ² X: 0.587; Q ² : 0.45) of serum samples obtained without abnormalities from both groups.
5 (A) shows a direct injection nanoelectronic atomic-mass spectrometry profile of serum lipids in a mouse fed with a general diet (ND, 占) and a high fat diet (HFD,?), (B) (R ² X: 0.686, Q ² : 0.799), (C) the loading plot, and (D) the permutation test. Identified metabolites are numbered on the loading plot and on the metabolite list, and the predictable vectors are shown in Tables 1 and 2.
6 (A) shows OPLS-DA numerical plots of serum lipids from mice fed with a normal diet () and a high fat diet (), and FIG. 6 (B) shows a direct injection nanoelectronic atom- Gt; OPLS-DA < / RTI > loading plot of the serum metabolite profile elicited by < RTI ID = The number of metabolites is shown in Table 2.
7 shows the quantitative multiples of the serum lipid metabolites in the high fat diet (HFD) group on the basis of the general diet (ND) group [CE (cholesteryl ester), LPC (lysophosphatidylcholine), PC (phosphatidylcholine) And TG (triacylglycerol).
Figure 8 shows a box-and-whisker plot showing compounds whose levels are significantly different between the general diet (ND) group and the high fat diet (HFD) group. The Y axis indicates the mass peak intensity. Statistical analysis of each biomarker candidate in HFD on the basis of ND was performed through analysis of variance.

Hereinafter, the present invention will be described in more detail with reference to one or more embodiments. However, these embodiments are illustrative of one or more embodiments, and the scope of the present invention is not limited to these embodiments.

1. Materials and Methods

1.1. Chemicals and Reagents

Methanol and water were purchased from Merck. (8: 0/8: 0/8: 0, 10: 0/10: 0/10: 0, and 12: 0/12) of ammonium acetate, chloroform, methyl- tert -butyl ether (MTBE) and triacylglycerol mixture standards : 0/12: 0) was purchased from Sigma-Aldrich. Phosphatidylethanolamine (PE 16: 0/18: 1), phosphatidylglycerol (PG 16: 0/18: 1), phosphatidylinositol (PC 18: 2/16: (LP 16: 0/18: 1), lysophosphatidylcholine (LPC 16: 0 and LPC 18: 0), lysophosphatidylethanolamine (LPE 16: 0), lysophosphatidylglycerol (LPG 16: 0) and lysophosphatidylinositol LPI 18: 1) was purchased from Avanti Polar Lipids.

1.2. Animal studies

5-week-old male C57BL / 6J mice purchased from Central Experimental Animal Co., Ltd. (Seoul, Korea) were inoculated in a room under constant temperature (21 ± 2.0) and relative humidity (50 ± 5%) at a cycle of 12 hours / And food were stored in a standard plastic cage that was fed free. The mice were adapted to the laboratory environment for one week and then randomly divided into two groups (8 per group): 1) the normal diet (ND) and 2) high fat diet (HFD). ND is the "2018S Teklad Global 18% Protein Rodent Diet (3.1 kcal / g; 18% of calories from fat)", HFD "TD.06414 Teklad Adjusted Calories Diet (5.1 kcal / g; %) "; Both foods were purchased from Harlan Laboratories. The mice were allowed free access to the food for a total of 16 weeks. Body weight was measured once a week.

1.3. Histological examination in liver tissue and Triacylglycerol

Slices of liver tissue were immediately frozen in OCT compound (purchased from Fisher Scientific) and oil-red O staining was performed. In the triacylglycerol assay, total lipids were extracted from liver tissue by the Folch method. Briefly, the frozen liver (50 mg) was weighed and homogenized in 1 mL of chloroform / methanol (2: 1, v / v ). The homogenate was centrifuged at 12,000 rpm to restore the lipid phase. After adding water (0.2 mL), the mixture was centrifuged at 4,000 rpm, maintaining the lower lipid-containing phase. The triacylglycerol content was measured by a colorimetric assay (using an Asian Biochemicals kit).

1.4. Serum analysis

The blood was centrifuged at 4 and 12,000 rpm for 10 minutes to collect the serum after allowing the blood of the mouse extracted through cardiac puncture to coagulate for 30 minutes at room temperature. Serum total cholesterol, LDL-cholesterol (LDL-c) and triacylglycerol (TG) were analyzed using an automatic hematology analyzer (Mindray) BS-400.

1.5. Sample preparation

Serum lipids were extracted using the modified Matyash method. Briefly, 225 μL of ice-cold methanol was added to 10 μL of serum and the mixture was vortexed for 10 seconds. Next, 750 μL of ice-cold methyl- tert -butyl ether (MTBE) was added, and 187.5 μL of distilled water was added to induce phase separation. After centrifugation (14,000 g, 4), the supernatant was collected and completely dried prior to lipid profiling. Prior to analysis, the dried samples were stored at -70.

1.6. Direct injection MS analysis

Each of the dried lipid extract of chloroform / methanol (1: 9, v / v ) is redissolved in 100μL, chloroform / methanol containing 7.5mM ammonium acetate in (1 9, v / v) was diluted 10 times. The lipid solution was injected into a Thermo LTQ XL ion trap mass spectrometer (Thermo Fisher Scientific) using a chip-based nano-electrospray injection system (TriVersa NanoMate, Advion Biosciences). The ion source was controlled with Chipsoft software (version 8.3.1, Advion Bioscience). The ionization voltage was 1.4 kV in the positive mode and the backpressure was 0.4 psi. The temperature of the ion transfer capillary was 200, and the tube voltage was 100V. In lipid profiling, 5 μL of each sample was randomly loaded onto a 96-well plate of a TriVersa Nanomate ion source to avoid analytical bias. Standard mixtures of triacylglycerol (TG), phosphatidylcholine (PC) and lysophosphatidylcholine (LPC); And quality control (QC) samples (pooled samples) were loaded at the beginning, middle, and end of each batch. Each 96-well plate was sealed with Thermowell aluminum sealing tape (Corning) and placed on a nanomate cooling plate 4 to prevent evaporation of the solvent. The mass spectrum of each sample was obtained in profile mode over 2 minutes. Data collection has the characteristics of a full scan (scan range: m / z 400 to 1,000) and a data-dependent MS / MS scan of abundant ions. To achieve a specific MS / MS fragmentation, a standard spectrum was obtained in a low resolution mode using a collision-induced dissociation (CID) voltage of 30 eV. All spectra were recorded with Thermo Xcalibur software (version 2.1, Thermo Fisher Scientific).

1.7. Data processing

The normat ion mass spectral data file (".raw" file) from the ion trap analyzer was loaded directly into the Genedata Expressionist MSX module (Genedata AG). Unless otherwise specified, basic processing parameters were applied. The spectral data was simplified by averaging between 0.5 and 1.0 minutes and subtracting background noise. As a result of subtraction, all data points below the threshold strength of '300' were zero. The spectral sets were then aligned in the m / z direction through a non-linear transformation and the original m / z data set was mapped onto a common universal data set. Next, spectral peak detection was used to define a peak on the temporal average spectrum; The following parameters were used: Smoothing window, three points; Method, curvature-based peak detection; Peak refining threshold, 5%; Consistency filter threshold, 0.8; 1. The detected peaks were then classified into isotopic clusters of individual peaks through a spectral clonal clustering operation using the following parameters: minimum charge, 1; Maximum charge, 2; Maximum missing peak, 1; A first permissible gap position, 3; Ionization, protonation; And m / z tolerance, 0.1. Data on all detected peaks including m / z and intensity values were exported to an Excel file. To normalize the spectral data, the average of the sum of the intensities of the QC samples was divided by the sum of the intensities of the respective sample spectra, and the next value (-fold) was multiplied by the peak intensity of each lipid species in the sample. The obtained Excel data was exported to SMICA P + software (version 13.0, Umetrics). Also, by comparing serum lipids with commercially available standard MS / MS fragmentation patterns, or by comparing the LIPID MAPS geolage gating gateway (http://www.lipidmaps.org), the human metabolism database (HMDB, . hmdb.com) and / or the inventors' in-house lipid library (LipidBlast).

1.8. Statistical analysis

Featuring average centering and Pareto scaling, Principal component analysis (PCA) was performed to determine the degree of difference between the two groups (ND and HFD). The Hotelling's T2 test was used to exclude singularities from the 95% confidence interval. Partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA, using the same scaling mode as used in PCA, which provides more distinct separation than PCA by considering the characteristics of each group ) Were performed. Then, the levels of fitness and predictability were checked by determining the values of R ² Y and Q ² Y, respectively. In general, R ² Y varies between 0 and 1 (where 1 means a perfect model), while Q ² Y greater than 0.5 is considered to reflect good predictability. The reliability of the PLS-DA modeling was rigorously verified through a permutation test (n = 999). All variables in the model have a p -value (<0.05) obtained using SIMCA-P + software and Stastistica 7 (StatSoft Inc), and the value of variable importance in the projection (>&Lt; / RTI &gt; S-slots showing binding covariance p (1) and correlation p (corr) values from the OPLS-DA model were created to allow detection of the metabolites contributing to the identification. In addition, statistical comparisons of weight, liver weight, renal fat mass, spleen fat mass, subcutaneous fat mass, triglyceride level and cholesterol level were performed using Duncan's multi-range test.

2. Experimental results

2.1. Animal feature

The characteristics of a mouse fed with a general diet (ND) and a high fat diet (HFD) are shown in Fig. The body weight (47.3 ± 4.2 g), liver weight (1.84 ± 0.74 g) and subcutaneous fat (3.12 ± 0.08 g) of HFD-fed mice were significantly larger than those of ND fed mice (FIG. (E)). These results show HFD induced obesity in mice. The sterol regulatory element-1c gene (SREBP-1c) plays a major role in the regulation of cholesterol and fatty acid synthesis. As evidenced by the oil-red O staining, fatty liver was evident in mice fed a high fat diet (HFD) histologically (see FIG. 2). Consistent with these observations, the hepatic triacylglycerol contents of ND and HFD were 28.3 ± 5.0 and 75.6 ± 12.8 mg / g, respectively.

2.2. Multivariate Statistical Analysis of Serum Metabolite Levels

To demonstrate the validity of the model of the present invention, QC (quality control) samples were prepared by mixing equal volumes of serum from all samples studied. After analyzing the 8 serum sample groups, the stability of the system was assessed by analyzing fresh QC samples. Of the 250 ions detected, the number of ions with a CV value of less than 30% exceeded 95%, and these results indicate excellent stability and reproducibility of the mass spectrometry. To normalize the spectrum, the average of the sum of the QC sample intensities was divided by the sum of the sample spectral intensities, and then each value (-fold) was multiplied by the intensity of each lipid species in the sample. After normalization, an outlier was selected with the help of the T2 test of Hotelling (see Fig. 4 (A)). If the anomalies were outside of the ellipse representing the 95% confidence region of the PCA numerical plot (thus, they were strong anomalies), the analysis was repeated after eliminating these anomalies to remove elements that were not suitable for identification of metabolites (See Fig. 4 (B)). PLS-DA is a form of PLS regression that uses categorical response variables and is a powerful tool that enables prediction with minimal error probability when many variables are present. In the PLS-DA model, VIP reflects the effect of all X variables on Y, and usually, if Y is to be accounted for, a VIP cutoff value of about 0.7 to 0.8 is considered significant. To select the metabolites that play an important role in the differentiation of each group, the inventors implemented a PLS-DA model constructed using selected variables with reference to various VIP block values with the help of permutation test parameters. In the context of the various VIP cutoff values, these parameters are listed in Table 1 below. The highest R ² Y and Q ² Y values were observed when the PLS-DA model was constructed using a metabolite with a VIP greater than 0.7 (65 lipids) (see Table 1). Thus, the PLS-DA model can be optimized to allow differentiation among the two groups. Table 1 below shows the validation parameters of the Partial Least Squares Distinction Analysis (PLS-DA) model developed by the inventors, using the variable importance (VIP) block values in the projection and using 999 permutations.

Metabolite profiles of sera from ND and HFD fed mice were statistically evaluated using PLS-DA, as specified via direct injection nanoelectrospray-ion trap mass spectrometry. Figure 5 (A) shows a typical direct-injection mass spectrum of serum from ND and HFD groups. The HFD-fed group can be clearly distinguished from the ND group on the first two-component PLS-DA numerical plot generated using Pareto scaling (see FIG. 5 (B)). Significant differences ( p <0.001) between the two groups indicate that the metabolic pattern is distinct. The inventors used the PLS-DA model to obtain good quality parameters, including 7-fold cross-validation (p <0.001) [fitness (R ² X) = 0.686 and R ² Y = 0.869]; Predictability (Q ² = 0.799); And permutation values (R ² intercepts = 0.338 and Q ² intercepts = -0.348, respectively), indicating that the PLS-DA model is not over-fit and can be considered a predictable model (FIG. 5B) And (D)). The PLS-DA loading plot for all groups was generated using Pareto scaling and the metabolites contributing to the observed identification were identified (see FIG. 5 (C)). Metabolites of positive w * c [1] were increased in mice on HFD, whereas negative in w * c [1]. The major metabolites were detected based on p-values and VIP values (see Table 2), and the numbers were displayed on the loading plot (see FIG. 5 (C)).

To explore the differences between pairs of treatment groups, the identification provided by the model between the ND and HFD groups was visualized on an OPLS-DA numerical plot (see FIG. 6 (A)). Samples from all groups were significantly separated from each other. To identify the metabolites contributing to each identification, S-plots of all models were generated using Pareto scaling (see FIG. 6 (B)). This revealed metabolites responsible for the separation between groups. The numbered metabolites in the plots were identified (see Table 2). The greater the distance of metabolism from the origin, the greater its potential as a biomarker candidate; These metabolites were responsible for the differences observed in ND versus HFD.

2.3. From the mouse Highland  effect

Of the 250 metabolites detected by direct injection-mass spectrometry, 65 species exhibited a VIP value of greater than 0.7, which was highly correlated with the difference between the two groups, indicating that the nonparametric t- Statistical analysis using the test. Of the 65 different metabolites, 33 (all lysophosphatidylcholine (LPC), cholesteryl ester (CE), phosphatidylcholine (PC) and triacylglycerol (TG)) showed statistically significant differences between the ND and HFD groups p < 0.05). PC 36: 2, PC 36: 3, TG 47: 0, TG 52: 3, TG 52: 3, CE 20: 4, 4 and TG 54: 5 had VIP values of greater than 2.0, which were the major metabolites contributing to the discrimination between the two groups (see Table 2). The level of high carbon (> 50) TG was significantly reduced in the HFD group, while the low carbon (<50) TG and CE (CE 20: 3 and CE 20: 4) ) Reference). The high carbon number TG and large double bond content (TG 56: 9, TG 58:10 and TG 60:12) of the present invention were associated with a reduced risk of disease. Table 2 shows the identification of mouse serum metabolites analyzed by direct injection nanoelectrospray mass spectrometry.

In a recent study by the present inventors, the VIP value increased to 2.726 for TG 47: 0 whereas the VIP value for TG 52: 3, 52: 4, 52: 5, 54: 4, 54: 5 and 54: To 2.712, 2.736, 1.489, 1.792, 2.002 and 1.726, respectively (see Table 2). It has been reported that diabetic- and obesity-induced changes in liver lipid compositions are correlated with changes in the levels of fatty acid elongase and desaturase. For example, insulin is known to increase the level of expression of various fatty acid unsaturation enzymes in animals. In addition, HFD significantly inhibited the expression of fatty acid elongase-5 (Elovl-5) (a key enzyme in the synthesis of polyunsaturated fatty acids) by inhibiting the expression of nuclear sterol-regulatory element binding protein-1 (SREBP-1). In addition, deletion of Elovl-5 induced fatty liver development in mice by activating SREBP-1c. Based on these findings, the inventors propose that the carbon number and double bond value of TG can be provided as highly useful markers of metabolic diseases including obesity and diabetes.

Four PCs (PC 34: 1, PC 36: 1, PC 36: 2 and PC 36: 3) and four LPCs (LPC 18: 0, LPC 18: 1, LPC 20: 4 and LPC 22: 6) significantly increased levels in the HFD group (see FIG. 7 (B)). Changes at the LPC level induced by HFD have been reported. For example, levels of LPC 18: 0, 20: 4 and 22: 6 in serum and levels of LPC 20: 4 in liver were significantly higher in HFD fed mice, similar to the present invention. In addition, overweight / obese males had high levels of LPC 14: 0 and LPC 18: 0 compared to dry individuals. Obesity co-twins have higher concentrations of LPC 18: 0, 18: 1 and 20: 4 than non-obese co-twins.

The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than the foregoing description, and all changes or modifications derived from the meaning and scope of the claims and equivalents thereof are included in the scope of the present invention. .

Claims (8)

Measuring the concentration of two or more triacylglycerols (TG) in the blood separated from the subject; And
Comparing the measured concentration of two or more triacylglycerols (TG) and the concentration of each triacylglycerol in the blood separated from the normal group to determine whether or not it is obese
A method for providing information for diagnosis or treatment of obesity,
TG 52: 3, TG 52: 4, TG 52: 4, TG 52: 2, TG 52: 3, TG 52: 4 and TG 52: 5, TG 54: 3, TG 54: 4, TG 54: 5, TG 54: 6, TG 54: 7, TG 56: 5, TG 56: 6, TG 56: 7, TG 56: At least one triacylglycerol having more than 50 carbon atoms selected from the group consisting of TG 46: 3, TG 47: 0, TG 47: 1, TG 48: 6 and TG 49: Lt; RTI ID = 0.0 &gt; 50 &lt; / RTI &gt; of triacylglycerol. delete The method according to claim 1,
The determination of the obesity is based on the concentration in the blood separated from the normal group, the concentration of triacylglycerol having a carbon number of more than 50 and the concentration of triacylglycerol having less than 50 carbon atoms And if it is increased, determines that the subject is obese. The method according to claim 1 or 3,
Wherein said obesity is obesity induced by high fat diet. Measuring the concentration of two or more triacylglycerols (TG) in blood separated from a subject who has taken or treated a particular food or drug; And
The concentration of the two or more triacylglycerols (TG) measured and the concentration of each triacylglycerol in the blood separated from the subject before the subject receives the food or drug or treats the subject, Determining the validity of the treatment
A method for screening an anti-obesity food or drug or an obesity treatment method,
TG 52: 3, TG 52: 4, TG 52: 4, TG 52: 2, TG 52: 3, TG 52: 4 and TG 52: 5, TG 54: 3, TG 54: 4, TG 54: 5, TG 54: 6, TG 54: 7, TG 56: 5, TG 56: 6, TG 56: 7, TG 56: At least one triacylglycerol having more than 50 carbon atoms selected from the group consisting of TG 46: 3, TG 47: 0, TG 47: 1, TG 48: 6 and TG 49: Lt; RTI ID = 0.0 &gt; 50 &lt; / RTI &gt; of triacylglycerol. delete 6. The method of claim 5,
The determination of the effectiveness of the food, drug, or treatment is based on the concentration of blood in the blood separated from the subject before the subject takes a specific food or drug or receives treatment, Wherein the concentration of the triacylglycerol having a carbon number of more than 50 in the separated blood is further decreased and the concentration of the triacylglycerol having a carbon number less than 50 is further increased, the food, drug or treatment is determined to be effective for the treatment of obesity. The method according to claim 5 or 7,
Wherein said obesity is obesity induced by high fat diet.

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