KR20120017912A - Detecting method of marker in biological sample for determination of obesity and the screening method using the same - Google Patents

Abstract

PURPOSE: A method for detecting a marker contained in a biological sample is provided to diagnose and treat obesity or obesity-associated diseases. CONSTITUTION: A method for detecting a marker contained in a biological sample for diagnosing obesity comprises a step of detecting the concentration of arginine, tyrosine, pipecolic acid, benzoic acid, pantothenic acid, uric acid, phenyl acetamide, serotonin, L-carnitine, decanoyl carnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitien, vacenyl carnitine, stearoyl carnitine, lysoPC(C14:0), lysoPC(C15:0), lysoPC(C16:0), lysoPC(C16:1), lysoPC(C17:0), lysoPC(C17:1), lysoPC(C18:0), lysoPC(C18:1), lysoPC(C18:2), lysoPC(C18:3), lysoPC(C19:0), lysoPC(C20:1), lysoPC(C20:4), lysoPC(C20:5), lysoPE(C18:2), lysoPE(C20:4) or PCs marker in blood or glucose, glycerol, tyrosine, valine, 7-ketodeoxy cholic acid, and betain, L-carnitine, plamitic acid, linoleic acid, oleic acid, stearic acid, lysoPC(C14:0), lysoPC(C16:0), lysoPC(C16:1), lysoPC(C18:0), lysoPC(C18:3), lysoPC(C20:4), lysoPC(C22:6), or PCs in liver tissue.

Description

DETECTING METHOD OF MARKER IN BIOLOGICAL SAMPLE FOR DETERMINATION OF OBESITY AND THE SCREENING METHOD USING THE SAME}

The present invention relates to a method for detecting a marker contained in a biological sample and a screening method using the same, and more particularly to measuring the concentration of a specific marker present in blood or liver extract or its change. The present invention relates to a method for detecting a marker contained in a biological sample of a subject that can be used for the purpose of diagnosing and treating obesity-related diseases, and to a screening method using the same.

Over the last few decades, obesity has increased in both developing and developed countries, both male and female, due to many factors, including genetics, the environment, physiology, and physical factors. Obesity is a major public health problem, such as smoking cessation, because of its role as the primary risk factor for many diseases such as non-insulin-dependent diabetes, heart disease, arthritis, and cancer, and in many countries it has become a major public health problem. It is the cause.

Recent studies have shown that obesity is usually associated with hypertrophy and hyperplasia of adipocytes due to long-term imbalances between energy absorption and consumption, and can be controlled by controlling adipocyte differentiation. However, despite physiological evidence based on many molecular studies, the metabolism of obesity and organic disorders associated with obesity is not clear. In order to better understand their biochemical mechanisms, convincing studies of obesity and related disorders have been conducted over the past several years using high efficiency assays such as genomics, proteomics, and metabolomixes. In particular, metabolomixes, defined by quantitative and qualitative analysis of all metabolites in cells, tissues, or biological fluids following genetic modification or physiological stimulation, are emerging fields in analytical biochemistry. Although there is no single instrumental platform for analyzing all metabolites, metabolomixes are a suitable technique for distinguishing between different phenotypes and finding powerful biomarkers associated with specific phenotypes. Recently, metabolism profiles of urine, serum, and / or liver from obese Zucker rats using NMR or LC / MS from mice inducing obesity with high fat diets were found to be associated with obesity or insulin resistance. Found as a powerful biomarker However, metablomixes of liver and blood from high-fat diet-induced obese mice using high-efficiency techniques by a combination of LC / MS and GC / MS showed that LC / MS produced the largest proportion of metabolites in tissues and biofluids. It is sufficient to detect and allows GC / MS to successfully analyze parts that cannot be detected by LC / MS, but is still suitable for analyzing dynamic changes in the metabolic processes of obesity and associated diseases. It is not being studied.

The present invention was derived to solve the problems of the prior art as described above, the object of the diagnosis and treatment of diseases associated with obesity to obesity by measuring the concentration of a specific marker present in the blood or liver extract or its change The present invention provides a method for detecting a marker contained in a biological sample of a subject and a screening method using the same.

The technical problem of the present invention as described above is achieved by the following means.

(1) Arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetate in blood isolated from subjects to provide information necessary for the diagnosis and treatment of obesity or obesity-related diseases; Tamide, serotonin, L-carnitine, decanoylcarnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitine, basenyl carnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), lysoPE (C20: 4), and PCs Glucose, glycerol, tyrosine, valine, 7-ketodeoxycholine acid, pantothenic acid, betaine, L-carnitine, 3-methylgutarylcarnitine, palmitellidic acid, palmitic acid in at least one marker selected, or extract of liver , Linoleine , Oleic acid, stearic acid, melibio, lysoPC (C14: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4) , lysoPC (C22: 6), and a method for detecting the concentration of at least one marker selected from the group of PCs.

(2) The method according to claim 1,

Detecting from the blood a concentration of at least one marker selected from the group of lysoPC (C16: 0), lysoPC (C18: 0), lysoPC (C18: 1), and lysoPC (C18: 2).

(3) The method according to claim 1,

From liver extracts, 7-ketodeoxycholine acid, betaine, L-carnitine, lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C20: 4), and lysoPC (C22) Detecting the concentration of at least one marker selected from the group of: 6).

(4) Arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, serotonin, L-carnitine, deca in blood isolated from a subject taking a particular food or drug. Noyl carnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitine, basenyl carnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16: 0), lysoPC (C16 : 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), at least one marker selected from lysoPE (C20: 4) and PCs, or extracts of liver Glucose, Glycerol, Tyrosine, Valine, 7-Ketodeoxycholine Acid, Pantothenic Acid, Betaine, L-Carnitine, 3-Methylgutarylcarnitine, Palmitellidine Acid, Palmitic Acid, Linoleic Acid, Oleic Acid, Stearic Acid, Melli Biose, lysoPC (C1 4: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4), lysoPC (C22: 6), and PCs A method for screening a food or substance having anti-obesity activity, comprising detecting the concentration of at least one marker selected from the group.

(5) The method according to 4,

Detecting from the blood a concentration of at least one marker selected from the group of lysoPC (C16: 0), lysoPC (C18: 0), lysoPC (C18: 1), and lysoPC (C18: 2).

(6) the method according to 4,

From liver extracts, 7-ketodeoxycholine acid, betaine, L-carnitine, lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C20: 4), and lysoPC (C22) Detecting the concentration of at least one marker selected from the group of: 6).

According to the present invention, by measuring the concentration of the specific marker present in the blood or liver extract or changes thereof, the marker contained in the biological sample of the subject that can be used for the purpose of diagnosis and treatment of obesity-related diseases It provides a detection method and a screening method using the same.

1 is a diagram showing the characteristics of mice fed a normal diet and a high-fat diet, (A) histologic fat and liver slices, (B) body weight, (C) fat weight, (D) TG content, (E ) Cholesterol content, (F) blood sugar content, (G) NAD / NADH ratio.
2 is a PLS-DA score plot of metabolite profiles obtained from UPLC-Q-TOF MS data of serum (A) and liver (B) and GC / MS data of hepatic hydrophilic (C) and hydrophobic (D) extracts.
Figure 3 shows the PLS-DA loading plot and S of the metabolite profile obtained from UPLC-Q-TOF MS data of serum (A) and liver (B) and GC / MS data of hepatic hydrophilic (C) and hydrophobic (D) extracts. -Plot.

The present invention provides arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetate in blood isolated from subjects to provide information necessary for the diagnosis and treatment of obesity or obesity-related diseases. Tamide, serotonin, L-carnitine, decanoylcarnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitine, basenyl carnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), lysoPE (C20: 4), and PCs Glucose, glycerol, tyrosine, valine, 7-ketodeoxycholine acid, pantothenic acid, betaine, L-carnitine, 3-methylgutarylcarnitine, palmitellidic acid, palmitic acid in at least one marker selected, or extract of liver , Lee Reinic acid, oleic acid, stearic acid, melibioz, lysoPC (C14: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4), lysoPC (C22: 6), and a method for detecting the concentration of at least one marker selected from the group of PCs.

In the above, lysoPC is an abbreviation of lysophosphatidylcholine, and one fatty acid is bound. For example, C14: 0 means an aliphatic hydrocarbon having 14 carbon atoms and no double bond.

lysoPE stands for lysophosphatidylethanolamine, and one fatty acid is bound. C18: 2, for example, refers to an aliphatic hydrocarbon having 18 carbon atoms and two double bonds in the chain.

PC means phosphatidylcholine, and two fatty acids form an acyl bond, and one fatty acid is separated from the PC by lysoPC.

Hereinafter, the content of the present invention will be described in detail.

Biological samples for diagnosis and treatment of obesity or obesity-related diseases according to the present invention are blood and liver extracts isolated from the subject. In this case, the subject may be a human or an animal except human.

Biological markers for the diagnosis and treatment of obesity or obesity-related diseases used in the present invention include arginine, tyrosine, pipecolic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, and phenylacetamide in the blood. , Serotonin, L-carnitine, decanoylcarnitine, myristoyl carnitine, hexadekenoylcarnitine, linoleyl carnitine, basenylcarnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC ( C16: 0), lysoPC (C16: 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18 : 3), at least selected from lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), lysoPE (C20: 4) and PCs One marker is used, and liver extracts include glucose, glycerol, tyrosine, valine, 7-ketodeoxycholine acid, pantothenic acid, betaine, L-carnitine, 3-methylgutarylcarnitine, palmitellidine acid, palmitic acid, Linole Acid, oleic acid, stearic acid, melibioz, lysoPC (C14: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4 ), lysoPC (C22: 6), and at least one marker selected from the group of PCs are used.

According to the present invention, in blood isolated from an obese subject, arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, serotonin, L-carnitine, steroylcarnitine, PCs, and lysoPCs (C17: 0, C18: 0, and C18: 3) tend to increase significantly. Whereas acylcarnitine (C14: 0, C16: 1, C18: 0, C18: 1, and C18: 2), lysoPCs (C14: 0, C15: 0, C16: 0, C16: 1, C17: 1, C18 : 1, C18: 2, C19: 0, C20: 1, and C20: 4) and lysoPEs (C18: 2, C20: 4) tend to decrease. In particular, among these, lysoPCs containing C16: 0, C18: 0, C18: 1, or C18: 2 with VIP values of 2.3 or higher function as the major serum metabolites that distinguish between obese and non-obese subjects.

In addition, according to the present invention, the concentration of 7-ketodeoxycholine acid, pantothenic acid, PCs, and lysoPCs (C20: 4, C22: 6) in the liver extract isolated from obese subjects tends to increase. Evalin, betaine, L-carnitine, 3-methylgutarylcarnitine, and lysoPCs (C14: 0, C16: 0, C16: 1, C18: 0, and C18: 3) tend to decrease. In particular, 7-ketodeoxycholine acid, betaine, L-carnitine, and lysoPCs with Cv values above 1.2 (C16: 0, C16: 1, C18: 0, C20: 4, and C22: 6) are obese Corresponds to the liver's most important metabolite, and not just obesity.

In addition, according to the present invention, seven fatty acids (palmitelliidin acid, palmitic acid, linoleic acid, oleic acid, stearic acid, and two unidentified substances) in the liver analyzed using GC / MS, five sugars (glucose, Melibiose, maltose, and two unidentified substances), glycerol, and tyrosine have been shown to have an effect on obesity, among which glucose with a VIP value of greater than 1.8, two unidentified monosaccharides, palmitellidic acid, palmitic acid , Linoleic acid and oleic acid are the major metabolites that contribute to this distinction.

Therefore, according to the present invention, the markers can be used to determine whether obesity is currently progressing or not by measuring the concentration of a substance corresponding to the marker in the blood or liver extract obtained from a subject and observing the change. Of course, it is possible to set a reference value in the blood to liver extract of these markers and exceeding this value can be useful for diagnosing whether the current obesity state or belonging to a specific disease associated with obesity.

In addition, the present invention relates to arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, serotonin, L-carnitine in blood isolated from a subject taking a particular food or drug. , Decanoyl carnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitine, basenyl carnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), lysoPC ( At least one marker selected from C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), lysoPE (C20: 4) and PCs, or liver Extracts from glucose, glycerol, tyrosine, valine, 7-ketodeoxycholine acid, pantothenic acid, betaine, L-carnitine, 3-methylgutarylcarnitine, palmitellidine acid, palmitic acid, linoleic acid, oleic acid, stearic acid , Meli Oz, lysoPC (C14: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4), lysoPC (C22: 6) And it provides a method for screening a food or substance having anti-obesity activity comprising the step of detecting the concentration of at least one marker selected from the group of PCs.

That is, the markers according to the present invention may also be used for the purpose of screening foods or drugs that induce or inhibit obesity or assaying their anti-obesity effects. This method first selects and administers a food or drug of interest to a subject, separates blood or liver extracts from them after a certain period of time, and then measures the change in the concentration of the marker to a food that induces obesity. It can be screened whether it corresponds to a food or drug having an anti-obesity activity, and furthermore, it can be usefully used to determine whether the effects of these foods or drugs are large and small.

At this time, the selected food or drug may be ingested according to a conventional dietary method according to each material, and does not exclude other administration methods other than the conventional dietary method. This indicates that each food is orally administered but does not exclude parenteral administration. Thus, each of the foods may be administered orally or parenterally in the form of tablets, capsules, microcapsules, or the like as necessary. As an additive that can be mixed with tablets, capsules and the like, for example, gelatin, corn starch, tragant, binders such as gum arabic, excipients such as crystalline cellulose, swelling agents such as corn starch, gelatin, alginic acid, stearic acid Lubricants such as magnesium, sweeteners such as sucrose, lactose or saccharin, flavorants such as peppermint, akamono-oil or cherry, and the like can be used. When the dosage form is a capsule, the material of the above type may further contain a liquid carrier such as oil or fat. As the aqueous solution for injection, for example, isotonic solutions (e.g., D-sorbitol, D-mannitol, sodium chloride, etc.) containing physiological saline, glucose, and other auxiliary agents are used, and suitable dissolution aids, for example, For example, you may use together with alcohol (for example, ethanol), poly alcohol (for example, propylene glycol, polyethylene glycol), nonionic surfactant (for example, polysorbate 80 TM, HCO-50). As an oily liquid, sesame oil, soybean oil, etc. may be used, for example, and it may be used together with benzyl benzoate, benzyl alcohol, etc. which are dissolution aids.

Although the present invention will be described in more detail with reference to the following examples, it should be noted that these examples are only presented to aid the understanding of the present invention and are not intended to limit the scope of the present invention.

[Example]

[Experimental process]

Induction of Cell Culture and Adiposis

HepG2, a hepatocellular carcinoma cell, was cultured in RPMI medium containing 10% FBS and 1% antibiotic antimicrobial solution (Welgene) in a 37 ° C. CO ₂ incubator. To induce steatosis, HepG2 cells were aliquoted into 10 cm culture dishes, grown to confluence, and cultured in culture medium containing 1 mM oleic acid and 1% bovine serum albumin. After 18 hours, HepG2 cells were washed twice with PBS, frozen with liquid nitrogen and lyophilized, and cell metabolites were extracted with 20% liquid methanol.

Animals and Diet

Six-week-old male C57BL / 6 mice were grown at constant temperature 22-26 ° C. under a light / dark cycle of 12 hours per day. Mice were free to eat water and diet. Mice were fed a high fat D12492 (60% kcal, high fat) or low fat D12450B (10% kcal, low fat) diet (Research Diet, New Brunswick, NJ) for 10 weeks and weighed weekly. Serum was separated from blood collected from the eyes of mice before sacrifice and the liver and fat obtained were placed in liquid nitrogen immediately after weighing. All samples were stored at −70 ° C. until analysis.

Histological examination

Mouse fat and liver were cut into blocks and fixed with 4% paraformaldehyde. Sections were dehydrated in alcohol with graded concentrations, placed in paraffin and stained with hematoxylin-eosin.

Triglycerides, Cholesterol, and NAD / NADH Ratio Assay

Triglyceride (TG) and cholesterol content in serum and liver extracted with a 2: 1 mixture of chloroform: methanol, TG assay kit (Biovision, Mountain View, CA) and cholesterol / cholesteric easter quantitative kit (Bio Vision). Liver NAD / NADH ratios were determined using Biovision's NAD / NADH Quantification Kit.

Preparation of the sample

Lyophilized liver powder (20 mg) was extracted with cold assotonitrile (ACN) using a homogenizer. After centrifugation the supernatant was completely dried and the dry sample was dissolved in 40% methanol for UPLC-Q-TOF analysis. Dry liver ACN extract containing caprylic acid, an internal standard for GC / MS analysis, and derivatize with a mixed solvent of 50 μl of BSTFA, 100 μl of ACN, 100 μl of DMSO, and 50 μl of pyridine for 2 hours at 70 ° C. It was made. After cooling the derivatized sample was diluted with methanol.

Serum proteins were precipitated by the addition of cold ACN. After centrifugation, the supernatant was dissolved in 20% methanol for UPLC-Q-TOF analysis. Dry plasma samples containing internal standards were derivatized for GC / MS analysis and diluted under the same conditions as the preparation of liver samples.

UPLC-Q-TOF MS Analysis of Liver and Serum Extracts

Liver and serum metabolites were analyzed using a UPLC system (Waters, Milford, USA) equipped with a solvent delivery system and an autosampler detector. Extracts of liver and serum were injected into an Acquity UPLC BEH C18 column (2.1 × 50 mm, 1.7 μm; Waters) mounted on an UPLC system and equilibrated with water containing 0.1% TFA. Samples were eluted with acetonitrile containing 0.1% TFA at a concentration rate of 0.35 ml / min for 14.5 minutes and analyzed by Q-TOF MS (Waters) after analyzing the metabolites separated by C18-UPLC.

Q-TOF was conducted in ESI positive mode and the capillary and sampling cone voltages were set to 2.78 kV and 26 V, respectively. The desolvation flow rate was set to 300 L / h at 300 ° C. and the temperature of the source was set to 110 ° C. TOF MS data were obtained in the range of m / z 50-1000 with a scan time of 0.2 seconds. All analyzes were obtained using rock spray to ensure accuracy and reproducibility; As the lac mass, leucine-enkephalin (556.2771 Da in ESI positive mode) was used at a concentration of 200 pmole and a flow rate of 3 μl / min. The lock spray frequency was set to 10 seconds. Five standard compounds (caffeine, sulfadimethoxine, terfenadine, 4-acetoaminophenol, and resorpine) were injected after every 5 samples for quality control (QC). MS / MS spectra of metabolites were obtained using a collision energy ramp of 10-30 eV. Accurate masses and compositions were calculated for precursor ions and fragment ions and sequenced using MassLynx (waters) mounted in the device. All information of MS data including retention time, m / z, and ionic strength was extracted using MarkerLynx (Waters) mounted in the device, and the resulting MS data was assembled into a data matrix.

GC / MS Analysis of Liver and Serum Extracts

Derivatized Overlook Using GC System (7890A; Agilent Technologies, CA) with Mass Select Detector (MSD) and DB-5MS Capillary Column (30m × 0.25mm × 0.25µm; J & W Scientific, Folsom, CA) Samples of serum were analyzed. The temperature of the oven was programmed from 60 ° C. to 250 ° C. at 10 ° C. per minute and held at 60 ° C. and 250 ° C. for 3 minutes and 10 minutes, respectively. The detector voltage was 70 eV and the MS spectra were obtained in the mass range of m / z 50-550. The flow rate of helium, which is a carrier gas, was 1 ml / min, and the solvent delay time was 7.5 minutes. The injection volume was 1 μl and the split ratio was 1:20.

[Experiment result]

Animal characteristics

The characteristics of mice fed a high fat diet or a normal diet are shown in FIG. 1. Body weight (33.2 ± 1.8 g) of the high-fat diet mice was significantly heavier than that of the control diet mice. Fat weight and its cell size were increased by high fat diet and fatty liver was observed histologically, but liver weight was not significantly different. Mice fed high-fat diets also had high levels of triglyceride (TG) and cholesterol in serum, 143.0 ± 12.7 mg / dL and 260.4 ± 79.6 mg / dL, respectively, and in the liver, 331.5 ± 8.4 mg / g and 518.8, respectively. TG and cholesterol contents of the mice leaned to ± 216.8 mg / dg were 116.4 ± 15.8 mg / dL and 184.5 ± 89.0 mg / dL in serum, respectively, and 295.2 ± 17.0 mg / g and 389.9 ± 180.7 mg / dg in liver. It was high in comparison. In addition, blood sugar content increased by 20% in the high-fat diet group. The liver NAD / NADH ratio (2.1 ± 0.4) in obese mice was twice as low as 4.8 ± 1.1 in lean mice. These characteristics indicate that the high fat diet caused obesity induction in c57BL / 6J mice.

Multivariate statistical analysis of metabolites in serum and liver

PLS-DA score plot of MS data of serum and liver metabolites obtained from dry and obese mice analyzed using UPLC0-Q-TOF and hydrophilic and hydrophobic metabolites analyzed using GC / MS (FIG. 2A) -D). The first two-component PLS-DA score plots of serum and liver metabolites showed good grouping between dry and obese mice. Two groups are a Q2 (cum) the value of R ² X (cum), and R ² Y (cum) value indicating that the data is applied to well represent the predictability of each of from 0.49 to 0.95 and from 0.54 to 0.97, 0.54 to 0.91 and a model On the basis of the phosphorus model, they are clearly distinguished from each other by the primary component t (1) or the secondary component t (2) (see Table 1).

In addition, the PLS-DA model was verified by permutation. The R intercept values of all models except livers analyzed using LC / MS were lower than 0.3 and their Q intercept values were lower than −0.2, indicating that these models were not overfit. In addition, the P values obtained from 7 batch cross-validation showed that all groups to which different models were applied were significantly different (see Table 1).

S-plots of p (1) and p (corr) (1) were generated using centroid scaling to identify metabolites that contributed to the difference (FIG. 3). S-plot shows that metabolites with high or low p (corr) values are more suitable ions to account for the difference between the two groups. The metabolite content at positive p (corr) values decreased in the high fat diet, while those with negative values increased. However, the model of hydrophobicity analyzed using GC / MS was reversed. For many metabolites, the number of metabolites shown in the s-plot was confirmed and their fold change was calculated (see Tables 2-4).

Qualitative and quantitative analysis of serum and liver metabolites

Normalization of all metabolites detected by UPLS-Q-TOF (339 and 137 respectively in serum and liver) or all metabolites detected by GC / MS (64 and 34 respectively in hydrophilic and hydrophobic liver extracts) Intensities were statistically analyzed using a nonparametric t-test. All metabolites, 206 and 91 metabolites in serum and liver, and 14 and 3 metabolites in hydrophilic and hydrophobic liver extracts, respectively, were significantly affected by the high fat diet. However, only a few metabolites were identified and the results obtained using UPLS-Q-TOF and GC / MS are shown in Tables 2-4, respectively.

Serum contains 15 metabolites (arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, serotonin, L-carnitine, steroyl carnitine, PCs) , And three lysoPCs, C17: 0, C18: 0, and C18: 3) were significantly increased. While 5 acylcarnitines (including C14: 0, C16: 1, C18: 0, C18: 1, and C18: 2), 10 lysoPCs (C14: 0, C15: 0, C16: 0, C16: 1 , C17: 1, C18: 1, and C18: 2, C19: 0, C20: 1, and C20: 4) and two lysoPEs (including C18: 2, C20: 4). Among these, lysoPCs with VIP values of 2.3 or higher, containing C16: 0, C18: 0, C18: 1, and C18: 2, and C18: 2, and highly correlated in explaining the difference between sample groups, PLS On the -DA score plot (Table 2), the normal diet and the high fat diet were identified as the major serum metabolites that contributed to the distinction between mice.

In the liver, five metabolites (7-ketodeoxycholine acid, pantothenic acid, PCs, and lysoPCs with C20: 4 and C22: 6) were increased by the high-fat diet, and nine metabolites (valine, beta Phosphorus, L-carnitine, 3-methylgutarylcarnitine, and lysoPCs, including C14: 0, C16: 0, C16: 1, C18: 0, and C18: 3). Although some identified metabolites have high p-values (p> 0.1), 7-ketodeoxycholine acid, betaine, L-carnitine, C16: 0, C16: 1, C18: 0, C20: LysoPCs with 4, and C22: 6 appeared to be the most important metabolites of livers with a VIP value of 1.2 or higher to assess the difference between normal and high-fat mice (Table 3). Furthermore, seven fatty acids (palmitelliidic acid, palmitic acid, linoleic acid, oleic acid, stearic acid, and two unidentified substances) in the liver analyzed using GC / MS, five sugars (glucose, melibiose, maltose) Oz, and two unidentified substances), glycerol, and tyrosine have been shown to be affected by high fat diet, of which glucose with a VIP value of more than 1.8, two unidentified monosaccharides, palmitellidic acid, palmitic acid, linol Reinic acid and oleic acid were identified as major metabolites contributing to the distinction (Table 4).

As described above, it has been described with reference to a preferred embodiment of the present invention, but those skilled in the art various modifications and changes of the present invention without departing from the spirit and scope of the invention described in the claims below I can understand that you can.

Claims (6)

Arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, in blood isolated from subjects to provide information necessary for the diagnosis and treatment of obesity or obesity-related diseases. Serotonin, L-carnitine, decanoylcarnitine, myristoylcarnitine, hexadekenoylcarnitine, linoleyl carnitine, basenylcarnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16) : 0), lysoPC (C16: 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), at least one selected from lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), lysoPE (C20: 4) and PCs Glucose, glycerol, tyrosine, valine, 7-ketodeoxycholine acid, pantothenic acid, betaine, L-carnitine, 3-methylgutarylcarnitine, palmitellidine acid, palmitate, linoleine Mountain Range, Reinic acid, stearic acid, melibioz, lysoPC (C14: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4) , lysoPC (C22: 6), and a method for detecting the concentration of at least one marker selected from the group of PCs. The method of claim 1,
Detecting from the blood a concentration of at least one marker selected from the group of lysoPC (C16: 0), lysoPC (C18: 0), lysoPC (C18: 1), and lysoPC (C18: 2). The method of claim 1,
From liver extracts, 7-ketodeoxycholine acid, betaine, L-carnitine, lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C20: 4), and lysoPC (C22) Detecting the concentration of at least one marker selected from the group of: 6). (1) Arginine, tyrosine, pipecolinic acid, benzoic acid, pantothenic acid, uric acid, phenylpyruvic acid, phenylacetamide, serotonin, L-carnitine, deca in blood isolated from a subject taking a particular food or drug. Noyl carnitine, myristoyl carnitine, hexadekenoyl carnitine, linoleyl carnitine, basenyl carnitine, stearoyl carnitine, lysoPC (C14: 0), lysoPC (C15: 0), lysoPC (C16: 0), lysoPC (C16 : 1), lysoPC (C17: 0), lysoPC (C17: 1), lysoPC (C18: 0), lysoPC (C18: 1), lysoPC (C18: 2), lysoPC (C18: 3), lysoPC (C19: 0), lysoPC (C20: 1), lysoPC (C20: 4), lysoPC (C20: 5), lysoPE (C18: 2), at least one marker selected from lysoPE (C20: 4) and PCs, or extracts of liver Glucose, Glycerol, Tyrosine, Valine, 7-Ketodeoxycholine Acid, Pantothenic Acid, Betaine, L-Carnitine, 3-Methylgutarylcarnitine, Palmitellidine Acid, Palmitic Acid, Linoleic Acid, Oleic Acid, Stearic Acid, Melli Biose, lysoPC (C1 4: 0), lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C18: 3), lysoPC (C20: 4), lysoPC (C22: 6), and PCs A method for screening a food or drug having anti-obesity activity, comprising detecting a concentration of at least one marker selected from the group. The method of claim 4, wherein
Detecting from the blood a concentration of at least one marker selected from the group of lysoPC (C16: 0), lysoPC (C18: 0), lysoPC (C18: 1), and lysoPC (C18: 2). The method of claim 4, wherein
From liver extracts, 7-ketodeoxycholine acid, betaine, L-carnitine, lysoPC (C16: 0), lysoPC (C16: 1), lysoPC (C18: 0), lysoPC (C20: 4), and lysoPC (C22) Detecting the concentration of at least one marker selected from the group of: 6).

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