KR101658134B1 - Diagnosis or screening in diabetes using PBMC metabolites or Lp-PLA2 activity - Google Patents

Abstract

The present invention relates to a method for diagnosing diabetes, prevention of diabetes, improvement of sensitivity to a therapeutic agent for diabetes mellitus including sensitivity to Lp-PLA ₂ activity using PBMC metabolism or PBMC activity, and a method for screening for a preventive, ameliorative or therapeutic agent for diabetes. By analyzing the levels of the four PBMC metabolites identified in the present invention or the activity of PBMC Lp-PLA ₂ , it is possible to diagnose the sensitivity or predict the prognosis of a subject diagnosed with pre-diabetes or diabetes mellitus for prevention, improvement or treatment of diabetes , Further screening for the prevention, improvement or treatment of diabetes.

Description

Diagnostic or screening in diabetes using PBMC metabolites or Lp-PLA2 activity in diabetes using PBMC metabolism or Lp-

The present invention relates to a method for preventing, ameliorating or diagnosing a therapeutic agent for diabetes in diabetes including prediabetes using a peripheral blood mononuclear cell (PBMC) metabolite or Lp-PLA ₂ (Lipoprotein-associated phospholipase A ₂ ) activity in PBMC And a method for screening for a preventive, ameliorative or therapeutic agent for diabetes.

With the coming of the 21st century, the eating habits have become more prosperous than ever before, and as the age of aging becomes longer due to the development of medical technology, interest in health longevity is increasing. Changes in dietary habits such as high-fat diets accompanied by economic growth have eroded the balance of the body, and the number of obese and diabetic complications is increasing, regardless of sex.

Unlike type 1 diabetes, which is called childhood diabetes, type 2 diabetes is caused by lack of exercise, obesity or stress, which causes insulin secretion to be regulated smoothly, but insulin does not function and blood glucose control fails. According to statistics from the Center for Disease Control and Prevention in 2008, the prevalence of diabetes in people over 30 years of age is 9.1%, and the prevalence rate increases sharply when it is over 40 years old, reaching 20% in their 50s. The rapid increase in prevalence rate is presumed to be caused by environmental factors such as improvement of nutritional status and lack of exercise.

Recent metabolic studies have shown that human plasma metabolites are associated with insulin resistance, type 2 diabetes, and blood glucose load resulting from pre-diabetes (Non-Patent Document 1).

On the other hand, Lp-PLA ₂ (Lipoprotein-associated phospholipase A ₂₎ has been reported, which is also associated to some extent and the can predict the occurrence of type 2 diabetes, independently, the pathogenesis of type 2 diabetes (non-patent reference 2) . In a recent study, inverse association between protein ingestion and circulating Lp-PLA ₂ activity was observed, suggesting that nutritional factors may influence Lp-PLA ₂ activity (Non-Patent Document 3). Dietary intervention studies in which whole grain and legumes were replaced with refined rice showed that glucose, insulin, Lp-PLA ₂ activity and cardiovascular risk factors could be reduced in patients with pre-diabetes or type 2 diabetes. However, the effects of this dietary intervention on plasma and PBMC metabolites have not yet been established.

PBMCs include monocytes and lymphocytes. Mononuclear cells play a key role in initiating or developing an inflammatory response by generating life-like molecules such as Lp-PLA ₂ in response to inflammatory stimuli (Non-Patent Document 4). Dietary interventions involve changes in PBMC gene expression, including downstream genes associated with inflammatory processes (Non-Patent Document 5). Thus, changes in PBMC metabolism and Lp-PLA ₂ activity following dietary intervention may reflect a dynamic response that can not be confirmed by plasma metabolism analysis.

Numerous papers and patent documents are referenced and cited throughout this specification. The disclosures of the cited papers and patent documents are incorporated herein by reference in their entirety to better understand the state of the art to which the present invention pertains and the content of the present invention.

United States Patent Application 13 / 693,306

 Zhang, X. et al., J.9 Proteome. Res., 8 (11), 5188-95 (2009).  Nelson TL, et al., J Clin Endocrinol Metab 2012; 97: 1695-1701.  Hatoum IJ, et al., Am J Clin Nutr 2010; 91: 786-793.  Dentan C, et al., Eur J Biochem 1996; 236: 48-55.  Brattbakk HR, et al., A Journal of integrative biology 2013; 17: 41-52.

Under these circumstances, the inventors of the present invention conducted a study on subjects diagnosed with pre-diabetes or type 2 diabetes and subjects with a general diet (refined rice) and diabetic improvement diets (whole foods and legumes) The study was conducted to confirm the difference. As a result, there was no significant difference in plasma metabolism between the two groups, but the PBMC metabolism L-leucine, oleamide, lysoPC (16: 0) and lysoPC (18: 0) and PBMC Lp-PLA ₂ activity , It is possible to apply the PBMC metabolites and Lp-PLA ₂ activity, which show significant differences, to the screening for the development of a preventive, ameliorative or therapeutic agent for diabetes, and further, The present invention can be applied to diagnosis (prediction) of the reactivity of diabetic patients including pre-diabetes for prevention, improvement, or therapeutic agent.

Accordingly, it is an object of the present invention to provide a method for providing information necessary for diagnosing sensitivity or predicting prognosis of a subject diagnosed with diabetes mellitus or diabetes mellitus for prevention, improvement or treatment of diabetes.

Another object of the present invention is to provide a method for screening for a preventive, ameliorative or therapeutic agent for diabetes.

Other objects and advantages of the present invention will become more apparent from the following detailed description of the invention, claims and drawings.

According to one aspect of the present invention, the present invention provides a method for providing information necessary for diagnosing the sensitivity or predicting the prognosis of a subject diagnosed with pre-diabetes or diabetes for the prevention, amelioration or treatment of diabetes comprising the steps of:

(a) measuring a metabolite level in peripheral blood mononuclear cells (PBMC) isolated from said subject that has received a diabetes prevention, improvement or treatment agent, said metabolite being L-leucine, oleamide, lysophosphatidylcholine 16: 0) and lyso-phosphatidylcholine (18: 0); And

(b) If the level of the metabolite measured is lower than that of the control sample, it is judged that the sensitivity to the prevention, improvement or treatment of diabetes is high.

According to another aspect of the present invention, the present invention provides a method for providing information necessary for diagnosing sensitivity or predicting the prognosis of a subject diagnosed with pre-diabetes or diabetes for a diabetes prevention, improvement or treatment agent comprising the following steps :

(a) measuring the activity of Lp-PLA ₂ (Lipoprotein-associated phospholipase A ₂ ) in peripheral blood mononuclear cells isolated from the subject to which the prevention, improvement or treatment of diabetes is administered; And

(b) If the activity of the measured Lp-PLA ₂ is lower than that of the control sample, it is judged that the sensitivity to the prevention, improvement or treatment of diabetes is high.

According to another aspect of the present invention, the present invention provides a method of screening for a preventive, ameliorative or therapeutic agent for diabetes comprising the steps of:

(a) measuring a metabolite level in peripheral blood mononuclear cells isolated from a subject diagnosed with a pre-diabetic or diabetic subject who has been administered a candidate substance, said metabolite being L-leucine, oleamide, lysophosphatidylcholine 16 : 0) and lyso-phosphatidylcholine (18: 0); And

(b) if the measured level of the metabolite is lower than that of the control sample, judging the candidate substance as a diabetes mellitus improving or treating agent.

According to another aspect of the present invention, the present invention provides a method of screening for a preventive, ameliorative or therapeutic agent for diabetes comprising the steps of:

(a) measuring the activity of Lp-PLA ₂ in peripheral blood mononuclear cells isolated from a subject diagnosed with diabetes or diabetes mellitus receiving the candidate substance; And

(b) if the activity of the measured Lp-PLA ₂ is lower than that of the control sample, judging the candidate substance to be a candidate for diabetes mellitus improvement or therapeutic agent.

The present inventors examined the metabolism difference between a subject who has been diagnosed with pre-diabetes or type 2 diabetes and a person who has a general diet (refined rice) and a diabetic improvement diet (whole lot and legume) The study was carried out. As a result, there was no significant difference in plasma metabolism between the two groups, but the PBMC metabolism L-leucine, oleamide, lysoPC (16: 0) and lysoPC (18: 0) and PBMC Lp-PLA ₂ activity , It is possible to apply the PBMC metabolites and Lp-PLA ₂ activity, which show significant differences, to the screening for the development of a preventive, ameliorative or therapeutic agent for diabetes, and further, (Prediction) of diabetic patients, including pre-diabetes, for the prevention, amelioration or treatment of diabetes mellitus.

The term " diagnosis ", as used herein, refers to the susceptibility to diabetes preventive, ameliorative or therapeutic agents administered to a subject diagnosed with a pre-diabetes or diabetes mellitus that has been administered with a preventive, ameliorative or therapeutic agent for diabetes such as drugs, determining whether the subject has pre-diabetes or diabetes mellitus (e.g., confirming the relief of diabetes mellitus or diabetes), determining the prognosis of the subject, determining susceptibility of the subject, , Or therametrics (e.g., monitoring the status of an object to provide information about the therapeutic efficacy).

According to an embodiment of the present invention, the subject diagnosed with the pre-diabetes represents impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), and the diabetes is type 2 diabetes. The onset of glucose tolerance refers to the case when the fasting blood glucose level is less than 126 mg / dL and the blood glucose level is between 140-199 mg / dL 2 hours after the glucose load. The fasting glucose tolerance is 100-125 mg / dL. < / RTI > The pre-diabetes stage is more likely to cause vascular complications than normal. In addition, type 2 diabetes means a fasting blood glucose level of 126 mg / dL or more.

According to one embodiment of the present invention, the subject is a non-obese subject. For example, non-obese subjects may be selected from those who have a value of 18.5 kg / m ² ≤ BMI <30 kg / m ² .

According to one embodiment of the present invention, the age of the subject and the control group of the present invention is 40-70 years old.

According to one embodiment of the present invention, the level of the PBMC metabolite of the present invention can be measured using an experimental apparatus known in the art (for example, chromatography, mass spectrometry, etc.).

Chromatography which can be used in the present invention can be carried out by liquid-solid chromatography (LSC), paper chromatography (PC), thin-layer chromatography (TLC), gas- Gas-Solid Chromatography (GSC), Liquid-Liquid Chromatography (LLC), Foam Chromatography (FC), Emulsion Chromatography (EC) Including, but not limited to, gel filtration chromatography (GLC), ion chromatography (IC), Gel Filtration Chromatography (GFC), or Gel Permeation Chromatography All chromatographies for routine use can be used.

According to one embodiment of the present invention, the chromatography used in the present invention is ultra performance liquid chromatography (UPLC).

The mass analyzer usable in the present invention is a Fourier transform mass spectrometer (FTMS), for example, LTQ-orbitrap MS.

The PBMC metabolite of the present invention can separate components from UPLC according to different mobility, and can confirm constituent components using molecular weight information as well as structural information (elemental composition) obtained through mass spectrometry.

According to the present invention, the level (concentration) of L-leucine, oleamide, lysophosphatidylcholine (16: 0), lysophosphatidylcholine (18: 0) And / or the activity of PBMC Lp-PLA ₂ is reduced as compared to the control, it indicates a high sensitivity to the administered diabetes preventive, ameliorating or therapeutic agent.

Also, according to the present invention, the level (concentration) of L-leucine, oleamide, lysophosphatidylcholine (16: 0), lysophosphatidylcholine (18: 0) And / or when the activity of PBMC Lp-PLA ₂ is reduced compared to the control, the administered candidate substance is used as a candidate substance for preventing, ameliorating or treating diabetes (or a candidate substance applicable to the development of diabetes prevention, improvement or therapeutic agent) ).

These four PBMC metabolites are PBMC metabolites with a variable importance in the projection (VIP) value of 1 or more, and are metabolites that show a large difference from the control or reference time point concentrations (see Table 2) and on the PLS-DA score plot Diabetes prevention, improvement, and a major factor that distinguishes between the control group that does not take the therapeutic agent and the group that ingested it (see FIG. 1). The reference time means a specific time point at which PBMC metabolism profiling, measurement of the concentration of the metabolite, and measurement of activity of Lp-PLA ₂ are started.

As confirmed in the following examples, the subjects (whole-grooming group) who were fed diets (diets containing whole grains and legumes instead of refined rice) for prevention, improvement and treatment of diabetes were PBMC L-leucine, oleamide, The levels of lysophosphatidylcholine (16: 0) and lysophosphatidylcholine (18: 0) and PBMC Lp-PLA ₂ activity were markedly decreased compared to those of the control group 2), PBMC Lp-PLA ₂ activity showed a positive correlation with L-leucine, oleamide, lysophosphatidylcholine (16: 0) and lysophosphatidylcholine (18: 0) . In addition, subjects subject to the above regimens were significantly more likely to have a glucose tolerance (HbA1c), HOMA-IR index, insulin, and plasma malondialdehyde levels than fasting blood glucose, glucose response area during oral glucose tolerance test (OGTT) , And showed lower fasting blood glucose, HOMA-IR index and plasma malondialdehyde levels compared to the control group (see Table 1).

These results show that diabetic symptoms are alleviated (alleviated) in a subject who has received dietary therapy, so that the dietary therapy shows activity as a preventive, ameliorative or therapeutic agent for diabetes. Thus, PBMC L-leucine, oleamide, lysophosphatidylcholine (16: 0) and lysophosphatidylcholine (18: 0) and PBMC Lp-PLA ₂ activity were significantly higher than those of the control group , The level of the four PBMC metabolites and the activity of PBMC Lp-PLA ₂ can be used to judge the reactivity (sensitivity) to prevent, ameliorate or treat diabetes of a subject diagnosed with pre-diabetes or diabetes, And can be used for screening candidate substances for improvement or therapeutic use.

As used herein, the term "decrease in PBMC metabolite levels or decrease in PBMC Lp-PLA ₂ activity" refers to a decrease in the activity of PBMCs compared to a control (a subject who has not received an anti- 15%, 20%, 30%, 40%, 50%, and 50%, respectively, of the PBMC Lp-PLA ₂ , , 60%, 70%, 80% or 90% or more.

According to one embodiment of the present invention, the measurements in the present invention are measured at a reference time point and after a lapse of 12 weeks from the reference time point.

According to one embodiment of the present invention, administration in the present invention is oral administration.

The term "candidate agent", as used, referring to the screening method of the present invention contains a substance (such as an unknown to be used in the screening to check whether it affects the level or PBMC Lp-PLA ₂ activity in PBMC metabolites, various Natural products including herbs and herbal medicines, compound libraries, etc.).

As used herein, the term "diabetes prevention, improvement or remedy" means a drug (pharmaceutical composition), a health functional food or a dietetic which is known to be exhibiting or exhibiting pharmacological activity against diabetes. For example, in the present invention, drugs and functional foods known in the art having pharmacological activity against diabetes can be used to diagnose the sensitivity of a subject diagnosed with pre-diabetes or diabetes, or to predict the prognosis. As another example, the present invention can be applied to screen for a substance having pharmacological activity against diabetes among candidate substances whose pharmacological activity against diabetes is not known.

The features and advantages of the present invention are summarized as follows:

(I) The present invention relates to a method for diagnosing diabetes prevention, improvement or sensitivity to diabetes mellitus including diabetes mellitus using Lp-PLA ₂ activity in PBMC metabolism or PBMC, and a method for screening for a preventive, ameliorative or therapeutic agent for diabetes will be.

(Ii) by analyzing the level of the four PBMC metabolites identified in the present invention or the activity of PBMC Lp-PLA ₂ , it is possible to diagnose the sensitivity or prognosis of a subject diagnosed with pre-diabetes or diabetes mellitus for the prevention, Predictable, and further screen for diabetes prevention, improvement or therapeutic agents.

Figure 1 shows the results of the identification of PBMC and plasma metabolites significantly changed after 12 weeks. A: Partial least squares discriminant analysis score plot (n = 40) of PBMC metabolite (n = 80) at baseline, whole meal intake group at 12 weeks (n = 40) and control group ). B shows PLS-DA score plots of PBMC metabolites in the whole blood intake group (n = 40) after 12 weeks and in the control group (n = 40) after 12 weeks. C shows a PLS-DA score plot of plasma metabolism at baseline (n = 80), whole blood intake group at 12 weeks (n = 40), and control group at 12 weeks (n = 40). D shows PLS-DA score plots of plasma metabolites of whole blood intake group (n = 40) after 12 weeks and control group (n = 40) after 12 weeks. ad: represents the S -plot for the covariance [p] and the confidence relationship [p (corr)] from the PLS-DA model.
Figure 2 shows the correlation matrix for the biochemical characteristics of all the subjects and PBMC metabolite changes. Supervised hierarchical clustering identified 10 most important metabolites and 9 biochemical features. Correlation was confirmed by deriving Spearman correlation coefficients. Red: Positive correlation. Purple: Negative correlation.

Hereinafter, the present invention will be described in more detail with reference to Examples. It is to be understood by those skilled in the art that these embodiments are only for describing the present invention in more detail and that the scope of the present invention is not limited by these embodiments in accordance with the gist of the present invention .

Example

Experimental Method

Experimental subject and experimental design

Yonsei University Nutritional Genetics / Nutritional Genomics The participant of this study was selected from the participants of clinical nutrition research conducted by the National Research Lab. Between January and June 2012, participants who were not obese at the age of 40-70 years (18.5 kg / m ² ≤ BMI <30 kg / m ²⁾ from a person who underwent routine health screening at the National Health Insurance Corporation Ilsan Hospital Health Check- Respectively. Based on the health screening data, persons with fasting glucose deficiency (IFG; 100 ≤ fasting glucose <126 mg / dL) or newly diagnosed with type 2 diabetes (fasting glucose ≥126 mg / dL) were selected. The criteria for exclusion are: (1) current and / or past history of cardiovascular disease, including angina, (2) liver or kidney dysfunction, (3) thyroid or pituitary disease, and (4) medium. Those who took drugs or supplements were excluded from the study. A total of 82 participants participated in the experiment. The mass nutritional composition of each participant's normal diet was consistent with a typical diet such as cooked refined rice. These diets represent approximately 64% energy from carbohydrate, approximately 21% energy from fat and approximately 17% energy from protein. All participants were informed about the purpose of the study and agreed upon, and the protocol of the study was approved by the Institutional Review Board of Yonsei University and Ilsan Hospital.

This experiment included a two-week run-in period of eating a regular diet of refined rice and a 12-week period of consuming whole grains and legumes as a general diet or carbohydrate source of refined rice It was carried out in two stages. During the entire study period, two experimental participants without energy intake were excluded from the experiment. The remaining 80 participants were randomly divided into two groups: a group (control group) that fed a regular refined rice diet at three meals a day for 12 weeks, and a group that consumed whole grains and legumes (whole group) instead of refined rice with carbohydrates Respectively.

Dietary education, dietary assessment and physical activity levels

For all participants, the dietitian instructed them to write and dictate the completion of the dietary record every two weeks for the duration of the experiment (2 days on weekdays and 1 weekends). Participants recorded and recorded on the diary the weight of the food before and after the meal. All participants continued their regular refined rice diet during the two-week pre-experimental phase. The reference point was measured at the beginning of the experiment. After the pre-experimental phase, the control group maintained the regular rice-fed diet, while the whole-ginseng group received a mixture of 1/3 beans, 1/3 barley and 1/3 wild rice instead of refined rice, Three times, and increased vegetable intake to at least 6 units per day (30-70 g / unit) for adequate dietary fiber intake. Dietitians monitored participants' compliance with the experimental guidelines and weight changes during the entire study period, either by direct visits or by telephone interviews. All participants maintained their usual lifestyle and did not make any changes to their daily eating habits.

Dietary energy values and nutrient intakes were calculated from the three-day food record using a computer-based nutritional analysis program (CAN-pro 3.0, Korean Nutrition Society). Based on total energy expenditure (kcal / day), basal metabolic rate, physical activity for 24 hours (Christian, JL, et al., In Nutrition for Living . 4th ed. Benjamin / Cummings Publishing Co., Redwood City, 242-266) and SDA (food dynamic action). Basal metabolic rate of each participant are Harris-Benedict equation (Butte, NF, Caballero B. Energy needs:... Assessment and requirements In Modern Nutrition In Health And Disease 10th ed Shils ME, Shike M, Ross AC, Cousins RJ, Eds. Lippincott Williams & Wilkins, Philadelphia, PA, 2006, p. 136-148).

Anthropometric and blood pressure analysis

In order to calculate BMI (kg / m ² ), the weight and height of the participants who disappeared without shoes were measured in the morning. The waist circumference was measured around the navel of the standing person after breathing. The blood pressure of the left arm of the true branch was measured while sitting after 20 minutes rest using an automatic blood pressure meter (FT-200S, Jawon Medical). After fasting for 12 hours, venous blood samples were collected in EDTA-treated tubes and centrifuged to obtain plasma or serum, respectively, and stored at -70 ° C.

hole Analysis of clear lipid profiles and free fatty acids

Fasting total cholesterol and triglyceride levels were analyzed using a Hitachi 7600 automatic analyzer (Hitachi Ltd.). The ApoB-containing lipoprotein was precipitated with dextran-magnesium sulfate and the HDL-cholesterol concentration in serum samples was determined by enzyme reaction. LDL-cholesterol concentrations were indirectly estimated using the Pre-Debalts formula: LDL cholesterol = total cholesterol - [HDL cholesterol + (triglyceride / 5)] for participants who had serum triglyceride levels <400 mg / dL Respectively. LDL-cholesterol levels were measured directly for participants who had serum triglyceride levels ≥400 mg / dL. Free fatty acids (FFA) were analyzed using acyl CoA synthetase-acyl-CoA oxidase (ACS-ACOD) enzyme assay and Hitachi 7600 automatic analyzer.

Oral glucose tolerance test, fasting glucose, insulin and hemoglobin A _1c , And the homeostatic model of insulin resistance

The oral glucose tolerance test (OGTT) was performed at 0 and 12 weeks after ingesting 75 g glucose solution after 12 hour night fasting to all participants. To determine serum glucose levels and glucose response, venous samples were collected before, during, and after 30, 60, and 120 minutes of glucose loading. Fasting blood glucose levels were analyzed by the hexokinase method using a Hitachi 7600 automatic analyzer. Insulin levels were measured using a radioimmunoassay kit (DIAsource Immuno Assays SA). Hemoglobin A _1c (HbA _1c ) was measured by immunoturbidimetric analysis. Insulin resistance (IR) was calculated by the homeostasis-model assessment (HOMA) using the equation HOMA-IR = [fasting insulin (μIU / mL) x fasting glucose (mmol / L)] / 22.5.

Serum-sensitive C-reactive protein, Lp-PLA ₂  Evaluation of active, plasma malondialdehyde, LDL particle size and oxidized LDL

High-Sensitivity C-Reactive Protein (hs-C) was amplified by ADVIA 2400 clinical chemistry system (Siemens Ltd.) using a high-sensitivity CRP-Latex (II) X2 kit (Denka-Seiken Co., CRP) were measured. Lp-PLA ₂ activity was measured using a modified high-throughput radiometric activity assay (Wilensky RL, et al., Nat Med 2008; 14: 1059-1066). Plasma malondialdehyde (MDA) was measured from thiobarbituric acid-reactive substances (TBARS) using a TBARS assay kit (ZeptoMetrix Co.). The LDL particles were separated by sequential flotation ultracentrifugation and the particle size distribution (1.019-1.063 g / mL) was analyzed using a linear 2-16% acrylamide gradient (CBS Scientific Company) And examined using a gel-pore-gradient lipoprotein system (CBS Scientific Company). Thioglobulin (17 nm), ferritin (12.2 nm) and catalase (10.4 nm) standards conjugated to latex beads (30 nm) were used to estimate the relative band mobility. The gel was scanned using a GS-800 calibrated imaging densitometer (GS-800 Calibrated Imaging Densitometer; Bio-Rad Laboratories). Enzyme immunoassay kit using (Mercodia AB) and measuring the plasma oxidized (ox) -LDL, the derived color reaction Wallac Victor ² multi-label instrument; at 450 nm in ^{(Wallac Victor 2 multilabel counter Perkin-} Elmer Life Sciences) Color reaction results were read.

Overall (non-targeted) plasma metabolism profiling

Preparation of Plasma Extraction Samples

Before analysis, 800 쨉 l of 80% acetonitrile was added to 100 쨉 l of plasma, mixed by vortexing, and centrifuged at 10,000 rpm for 5 minutes at 4 째 C. The supernatant was dried with N ₂ , dissolved in 10% methanol, vortexed, and centrifuged at 10,000 rpm for 5 minutes at 4 ° C. The supernatant was then transferred to a new vial.

Ultra high performance liquid chromatography

Plasma extraction samples (4 μl) were injected into a coupled in-line Acquity UPLC-BEH-C18 column (2.1 × 50 mm, 1.7 μm; Waters) coupled with UPLC-LTQ-Orbitrap XL (Thermo Fisher Scientific). Samples injected with water containing 0.1% formic acid were equilibrated. The sample was eluted for 20 minutes using an acetonitrile gradient containing 0.1% formic acid at a flow rate of 0.35 ml / min. Metabolites were separated by UPLC (Thermo Fisher Scientific) and analyzed using LTQ-Orbitrap-XL (Thermo Fisher Scientific). The mass spectrometer was operated in an ESI-positive mode. The spray voltage was set at 5 kV. The flow rates of nitrogen sheath gas and auxiliary gas were 50 and 5 (arbitrary units). The capillary voltage (V), tube-lens voltage (V) and capillary temperature (캜) were kept constant at 35V, 80V and 370 ° C, respectively. Orbitrap data were collected in the m / z 50-1,000 range. The MS / MS spectra of the metabolites were measured using a collision-energy ramp at 55-65 eV and analyzed using Excalibur 2.1 and MS Frontier software (Thermo Fisher Scientific).

Data processing and identification of metabolites

All MS data, including retention time, m / z and ionic strength, were extracted using SIEVE software (Thermo Fisher Scientific) and the resulting MS data results were collected into a matrix. The SIEVE parameters were set as follows: m / z range 50-1,000; m / z width 0.02; Retention time width 2.5; m / z resistance 0.005. Metabolites were searched using the following databases: ChemSpider (www.chemspider.com), Human Metabolome (www.hmdb.ca), Lipid MAPS (www.lipidmaps.org), KEGG (www.genome.jp/kegg ) And MassBank (www.massbank.jp). Metabolites selected based on retention time and mass spectra were compared to standard samples.

Statistical analysis

SPSS v. Statistical analysis was performed using 21.0 (IBM SPSS Statistics 21). Skewed variables were transformed logarithmically for statistical analysis. For descriptive purposes, the mean values are presented as untransformed values. Results are expressed as mean ± standard error (SE). A two-tailed P-value <0.05 was considered statistically significant. Differences in biochemical parameters between baseline and 12-week follow-up periods were measured using Student's independent t -test. A GLM (General Linear Model) test was applied to compare the parameter changes between the two groups by calibrating to baseline time values. A Paired t-test was used to assess the level difference between baseline for each group and the follow-up period of 12 weeks. In order to investigate the relationship between variables over time, simple and partial correlation coefficients were used. R package 'fdrtool' was used to calculate the corrected discovery rate (FDR) and the corrected q-value. A heat map was generated to visualize and evaluate the correlation between metabolites and conventional risk factors.

Multivariate statistical analyzes were performed using SIMCA-P + software version 12.0 (Umetrics). Partial least-squares discriminant analysis (PLS-DA) was used as a classification method to model differences between groups. In order to check the validity of the model, seven-fold validation was applied to the PLS-DA model and the reliability of the model was rigorously tested with a permutation test (n = 200). The chi-square goodness-of-fit was quantified as R ² Y , and the predictive power was quantified as Q ² Y. In general, R ² Y shows how well the data is mathematically generated in the training set and varies between 0-1 (1 means that the model is perfectly matched). The model with Q ² Y ≥ 0.5 was considered to have good predictive power.

Experiment result

After an entire period of time in the laboratory, 80 participants in the energy intake participated in a 12-week experiment, randomly divided into control or whole-food groups. (57.5 ± 1.2 years vs. 57.5 ± 1.3 years; P = 0.995), male / female ratio (25/15 vs. 25/15), education level, smoking and alcohol consumption between the control and whole- There were no significant differences in initial characteristics.

Clinical characteristics, lipid profiles and nutrient intake after baseline and after 12 weeks

No significant changes in physical activity level were observed during the experimental period. At baseline, BMI (24.2 ± 0.5 kg / m ² versus 24.2 ± 0.4 kg / m ² P = 0.902), waist: hip ratio (WHR; 0.89 ± 0.01 versus 0.90 ± 0.01; P = 0.292), systolic blood pressure ), Serum triglyceride (115 ± 10 mg / dL versus 126 ± 9 mmHg), diastolic blood pressure (78 ± 1 mm Hg versus 78 ± 1 mm Hg; P = 0.827) LDL-cholesterol (115 ± 5 mg / dL versus 109 ± 5 mg / dL; P (mg / dL), P = 0.287), total cholesterol (192 ± 5 mg / dL versus 188 ± 6 mg / (485 ± 38 μEq / L versus 464 ± 29 μEq / L; P = 0.919) and hs (p = There was no significant difference between the control group and the whole-gross intake group in -CRP (2.0 ± 0.5 mg / dL versus 1.4 ± 0.3 mg / dL; P = 0.371). Both groups were similar before and after the experiment on BMI, WHR, blood pressure, serum lipid profile, hs-CRP, total energy expenditure and total energy intake.

The ratio of energy (%) of protein (16.3 ± 0.1% versus 20.5 ± 0.1%; P <0.001) and fat (22.2 ± 0.2% versus 24.9 ± 0.2; P <0.001) in the case of replacing whole rice with whole grains and legumes intake) and a significant reduction in the energy intake rate of carbohydrates (61.9 ± 0.2% versus 54.6 ± 0.1; P <0.001). The energy uptake rates of the two groups of protein, fat and carbohydrates were significantly different ( p <0.001 for all) before calibration to baseline, but not after calibration. Total ingestion showed a significant increase in fiber intake and polyunsaturated-to-saturated fatty acids ratio (PUFA / SFA). After 12 weeks of experimentation, the whole-gang intake group showed lower percent carbohydrate percent energy, higher percentage of protein and fat calories, and higher fiber intake than the control group (Table 1).

Each value is expressed as mean ± standard error.

^∮ is checked through log conversion.

P ^a values were derived from an independent t-test at baseline.

P ^b values were derived from independent t-tests after 12 weeks.

P ^c values were derived from independent t-tests at varying values.

P ^d values were derived from independent t-tests at adjusted values after adjustment to baseline.

^* P <0.05, ^** P <0.01, ^*** P <0.001 were derived from the paired t-test.

At baseline and after 12 weeks glucose, insulin and malondialdehyde

At the end of the experiment, the fasting glucose, HbA _1c and plasma MDA levels were significantly increased in the control group, but after adjusting to baseline, all of the glucose tolerance groups showed fasting glucose, OGTT sugar reactive region, HbA _1c , HOMA-IR index, insulin and plasma MDA were significantly decreased (Table 1). The whole meal intake group was significantly different from the control group before and after adjusting for baseline levels of fasting glucose (P <0.001), glucose tolerance during OGTT, HbA _1c , HOMA-IR index and plasma MDA. The fasting blood glucose, HOMA-IR index and plasma MDA were significantly lower in the whole-gang intake group than in the control group after 12 weeks (Table 1).

Plasma ox-LDL, LDL particle size, plasma and inactivation at baseline and after 12 weeks Lp-PLA in PBMC ₂  activation

At the end of the experiment, the whole-gonadal group showed lower plasma ox-LDL and Lp-PLA ₂ activity and higher LDL particle size in unstimulated PBMC supernatants, while the control group showed higher Lp-PLA ₂ (Table 1). These changes in plasma ox-LDL, LDL particle size, plasma Lp-PLA ₂ activity, and PBMC Lp-PLA ₂ activity were significantly different from the control group in the whole blood intake group before and after calibrating to baseline level. After 12 weeks, the whole-calorie group had lower plasma ox-LDL and PBMC Lp-PLA ₂ activity and larger LDL particle size than the control group (Table 1).

Profiling of PBMC and plasma metabolites using UPLC-LTQ-Orbitrap mass spectrometer

Nontargeted Metabolic Pattern Analysis

The mass spectrometry (MS) data of PBMC and serum metabolites obtained at baseline and after 12 weeks were analyzed using a PLS-DA score plot for the following two combinations: (1) control group at the reference time point, Control group after 12 weeks, and whole blood intake group after 12 weeks (A, PBMC in Figure 1; C, plasma in Figure 1); (2) Control group after 12 weeks and whole blood intake group (B, PBMC in Figure 1; D, plasma in Figure 1). PBMC metabolism score plots showed distinct clustering and distinct clustering of participants: a control group at the baseline time point, a whole-gross intake group, a control group at 12 weeks, and a whole-body intake group at 12 weeks ( R ² X (cum) 0.124, R ² Y (cum) = 0.34, Q ² Y (cum) = 0.218; This distinct clustering shows that the PBMC profile detected changes in metabolites induced by dietary intervention. The PLS-DA model was verified using a permutation test with an R ² Y intercept value of 0.159 and a Q ² Y intercept value of -0.149. PBMC metabolite score plots showed distinct clustering for the control group and all gonadal groups after 12 weeks ( R ² X (cum) = 0.125, R ² Y (cum) = 0.809, Q ² Y (cum) = 0.525; 1B). The PLS-DA model was verified using a permutation test with R ² Y intercept values of 0.391 and Q ² Y intercept values of -0.183.

Plasma metabolite score plots did not show clear clustering as did PBMC metabolites ( R ² X (cum) = 0.124, R ² Y (cum) = 0.376, Q ² Y (cum) = 0.127; ). The PLS-DA model was verified using a permutation test with R ² Y intercept values of 0.312 and Q ² Y intercept values of -0.105. Plasma metabolism score plots did not show clear clustering as in PBMC metabolism ( R ² X (cum) = 0.201, R ² Y (cum) = 0.704, Q ² Y (cum) = 0.414; Fig. 1D). The PLS-DA model was verified using a permutation test with R ² Y intercept values of 0.491 and Q ² Y intercept values of -0.148. The S-plot (1) of p and p (corr) was derived using centroid scaling to identify metabolites that differentially determined data at baseline and at 12 weeks (Figure 1 a , b, c, and d). The S-plot showed that metabolites with higher or lower p (corr) values showed a more distinct difference between the two groups.

Identification of PBMC Metabolites

Based on the parameters of variable importance in the projection (VIP), metabolites that play an important role in the differentiation of each group among 1,923 PBMC metabolites were selected: a VIP value of> 1.0 was highly related to the differences between the groups Respectively. 51 metabolites showed a VIP value of> 1.0, among which 10 metabolites were previously identified and 41 metabolites were unknown. Table 2 shows the 10 PBMC metabolites (VIP> 1.0) at baseline and after 12 weeks. There was no significant difference in baseline metabolites between the control and all groups. After 12 weeks, the control group showed a significant change in the following PBMC metabolite levels: three metabolites (cyclopentanone dimethylhydrazone, lysoPC (C16: 0) and lysoPC (C18: 0) increased (Table 2) and the three metabolites (L-pyroglutamic acid, dihydrobiopterin and ribothymidine) decreased. After 12 weeks, the whole-ginkgo group showed significant changes at the following PBMC levels: six metabolites (L-leucine, dihydrobiopterin, palmitic amide, oleamide, lysoPC C16: 0) and lysoPC (C18: 0)] decreased and one type of metabolite (cyclopentanone dimethyl hydrazone) increased.

The change in PBMC metabolism (change from baseline) was compared between the control and whole-meal groups. A greater reduction in (q = 0.003) whole grain intake group L- leucine (q = 0.031), oleamide (q = 0.032), lysoPC ( 16:: 0) (q = 0.003) and lysoPC (0 18) (Table 2). After 12 weeks, the whole-intakes group showed a higher peak intensity of pyrrolidonecarboxylic acid and ribothymidine and a lower peak intensity of palmitic amide, oleamide and lysoPC (C16: 0 and C18: 0) compared to the control group (Table 2).

Each value is expressed as mean ± standard error.

^* q <0.05, ^** q <0.01, ^*** q <0.001 were derived from the corresponding sample t-test.

^† q <0.05, ^†† q <0.01, ^††† q <0.001 was derived from independent t-test after 12 weeks.

^{‡ q <0.05, ‡‡ q <} 0.01, ‡‡‡ q <0.001 was derived from the changed values of the control and whole-grain intake group.

Identification of plasma metabolites

Of the 4,121 plasma metabolites, the metabolites that play an important role in distinguishing each group were selected with a VIP value> 1.0. 122 species of plasma metabolites were selected, of which 20 were previously identified and 102 were unknown metabolites (Table 3). There was no significant difference in baseline metabolic rate between control and whole meal intake group. After 12 weeks, C17 sphinganine was significantly increased in the control group. After 12 weeks, there was no significant difference in plasma metabolism between the control and whole-meal groups, and there was no significant difference in plasma metabolism changes at baseline (Table 3).

Each value is expressed as mean ± standard error.

^* q <0.05, ^** q <0.01, ^*** q <0.001 were derived from the corresponding sample t-test.

^† q <0.05, ^†† q <0.01, ^††† q <0.001 was derived from independent t-test after 12 weeks.

^{‡ q <0.05, ‡‡ q <} 0.01, ‡‡‡ q <0.001 was derived from the changed values of the control and whole-grain intake group.

^{Since 1} PC was detected with Obitrap MS, all detected PC values were combined.

SM: sphingomyelin

Fasting blood glucose, plasma and PBMC Lp-PLA ₂  Activity, biochemical parameters and correlation of major PBMC metabolites

The correlation matrix of fasting plasma glucose, Lp-PLA ₂ activity in plasma and PBMC, biochemical parameters, and PBMC major metabolites were calculated (FIG. 2). Analysis of metabolic changes including all subjects ( n = 80) confirmed the following correlations: After adjusting for age, sex, BMI, smoking and alcohol consumption, fasting glucose levels were measured using insulin, HOMA-IR, plasma Lp- PLA ₂ activity (r = 0.454, P <0.001 ), MDA, plasma ox-LDL, PBMC supernatants _{Lp-PLA 2 (r = 0.511} , P <0.001), OGTT curve, C- peptide, HbA1c, PBMC lysoPC (16: 0) and PBMC lysoPC (18: 0), respectively. Plasma Lp-PLA ₂ activity was significantly correlated with Lp-PLA ₂ activity ( r = 0.516, P <0.001), OGTT curve, HOMA-IR, plasma ox-LDL, PBMC supernatant Amide and PBMC oleamide. PBMC Lp-PLA ₂ activity was assessed by the fasting glucose, HOMA-IR, plasma Lp-PLA ₂ activity, plasma ox-LDL, PBMC L-leucine, PBMC oleamide, PBMC lysoPC (16: Showed a positive correlation with PBMC lysoPC (18: 0) and a negative correlation with LDL particle size (Fig. 2).

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the present invention. Accordingly, the actual scope of the present invention will be defined by the appended claims and their equivalents.

Claims (5)

A method for providing information necessary for diagnosing or predicting the sensitivity of a subject diagnosed with prediabetes or diabetes for the prevention, amelioration or treatment of diabetes comprising the steps of:
(16: 0) and lyso-phosphatidylcholine (18: 0) in peripheral blood mononuclear cells (PBMC) isolated from the subject receiving diabetes prevention, Measuring the metabolite level selected from the group consisting of; And
(b) determining that the measured level of the metabolite is lower than that of the control sample, that the sensitivity to the prevention, improvement, or treatment of diabetes is high.
The method of claim 1, wherein the step (a) further comprises measuring the activity of Lp-PLA ₂ (Lipoprotein-associated phospholipase A ₂ )
Wherein the step (b) determines that the level of the metabolite and the activity of Lp-PLA ₂ are lower than that of the control sample, and that the diabetic patient is susceptible to diabetes prevention, improvement, A method for providing information necessary for the diagnosis of a sensitivity or prediction of prognosis of a subject diagnosed with pre-diabetes or diabetes for prevention, improvement or treatment.
A screening method for preventing, ameliorating or treating a diabetes comprising the steps of:
oleamide, lyso-phosphatidylcholine (16: 0) and lyso-phosphatidylcholine (18: 0) in peripheral blood mononuclear cells isolated from subjects diagnosed with diabetes or diabetes mellitus receiving the candidate substance, Measuring the level of the metabolite selected from the group consisting of; And
(b) determining the candidate substance as a candidate for diabetes mellitus improvement or therapeutic agent if the measured level of the metabolite is lower than that of the control sample.
The method of claim 3, wherein the step (a) additionally measure the _{Lp-PLA 2 (Lipoprotein-associated} phospholipase A 2) with the activity of the metabolite level,
Wherein the candidate substance is judged to be a candidate for diabetes mellitus improvement or treatment when the level of the metabolite and the activity of Lp-PLA ₂ are lower than that of the control sample. , Or a method for screening a therapeutic agent.
The method of any one of claims 1 to 4, wherein the subject diagnosed with the pre-diabetes represents impaired fasting glucose or impaired glucose tolerance, wherein the diabetes is type 2 diabetes &Lt; / RTI &gt;

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