Lipid Metabolites and Markers in Men With New Diagnosed T2DM
Study participants included 53 men between 35 and 65 years of age. Participants were recruited during routine check-ups at a health promotion centre at the National Health Insurance Corporation Ilsan Hospital. Exclusion criteria included any diagnoses of diabetes, vascular, renal and liver diseases, or acute or chronic inflammatory disease. Patients taking any drugs or supplements were also excluded. Participants who met the inclusion criteria were recommended for participation in the study, and fasting serum glucose concentrations were measured again. Based on two measurements (from the routine health check-up and at entry to the study), participants with a fasting serum glucose concentration ≥7 mmol/l (126 mg/dl) were defined as newly diagnosed type 2 diabetes. Twenty-six men meeting this criterion and 27 age- and BMI-matched nondiabetic men were included. For nondiabetic subjects, a fasting glucose concentration <7 mmol/l (126 mg/dl) was considered the cut-off, but in actual, all the fasting glucose levels were <6·1 mmol/l (110 mg/dl).
Before participation, the purpose of the study was carefully explained to all patients who provided informed consent. The Institutional Review Board of Yonsei University provided ethical approval of study protocol.
Body weights and heights were used to calculate BMI (kg/m). Waist and hip circumferences were measured to calculate the waist-to-hip ratio. Blood pressures were measured in the left arm of seated participants with an automatic blood pressure monitor (TM-2654, A&D, Tokyo, Japan) after a 20-min rest. After a 12-h fasting period, venous blood specimens were collected in ethylenediaminetetraacetic acid-treated or plain tubes, centrifuged to yield plasma or serum and stored at ™70 °C until analysis.
Dietary intake was assessed with a 24-h recall method and semi-quantitative food frequency questionnaire. Dietary energy values and nutrient content were calculated using the Computer Aided Nutritional analysis program (CAN-pro 3.0; Korean Nutrition Society, Seoul, Korea). Total energy expenditure (TEE) was calculated from activity patterns, including basal metabolic rate, physical activity for 24 h and specific dynamic actions of food. The basal metabolic rate of each participant was calculated with the Harris–Benedict equation.
Fasting glucose levels were measured using a glucose oxidase method with a Beckman Glucose Analyzer (Beckman Instruments, Irvine, CA, USA). The intra-assay and interassay coefficients of variability (CVs) were 1·1% and 1·4%, respectively. Insulin levels were measured by radioimmunoassay using commercial kits from Immuno Nucleo Corporation (Stillwater, MN, USA). The intra-assay and interassay CVs were 5·7% and 6·5%, respectively. Insulin resistance (IR) was calculated by HOMA using the following equation: HOMA-IR = [fasting insulin (μIU/ml) × fasting glucose (mmol/l)]/22·5. β cell function was calculated as [20 × fasting insulin (μIU/ml)]/[fasting glucose (mmol/l) ™ 3·5).
Fasting serum total cholesterol and triglycerides were measured using commercially available kits on a Hitachi 7150 Autoanalyzer (Hitachi Ltd., Tokyo, Japan). The intra-assay and interassay CVs were 1·4% and 2·6% for total cholesterol, and 1·1% and 1·3% for triglycerides, respectively. After the precipitation of chylomicrons with dextran sulphate magnesium, concentrations of high-density lipoprotein (HDL) cholesterol in the supernatants were determined using ADVIA 2400 Chemistry System (Siemens Healthcare Diagnostics, Deerfield, IL, USA). The intra-assay and interassay CVs were 1·8% and 2·5%, respectively. Low-density lipoprotein (LDL) cholesterol was indirectly estimated in participants with serum triglyceride concentrations <400 mg/dl using the Friedewald formula.
Plasma MDA was measured from thiobarbituric acid–reactive substances (TBARS Assay Kit; Zepto-Metrix Co., Buffalo, NY, USA). The intra-assay and interassay CVs were 2·9% and 5·2%, respectively. Plasma oxidized LDL (ox-LDL) was measured using an enzyme immunoassay (Mercodia, Uppsala, Sweden). The intra-assay and interassay CVs were 5·4% and 6·3%, respectively. Urine was collected in polyethylene bottles containing 1% butylated hydroxytoluene after a 12-h fast. Bottles were immediately covered with aluminium foil and stored at ™70 °C until analysis. 8-epi-PGF2α was measured using an enzyme immunoassay (Oxford Biomedical Research Inc., Oxford, MI, USA). Urinary 8-epi-PGF2α concentrations were expressed as pmol/mmol creatinine. The intra-assay and interassay CVs were 2·5% and 7·6%, respectively.
Serum hs-CRP concentrations were measured with an Express autoanalyzer (Chiron Diagnostics Co., Walpole, MA, USA) using high-sensitivity CRP-Latex (II) X2 kit (Seiken Laboratories Ltd., Tokyo, Japan). Serum IL-1ß, IL-6 and TNF-α concentrations were measured with a Bio-plex suspension array system (Bio-Rad, Hercules, CA, USA) using a human cytokine panel kit. The intra-assay and interassay CVs were 5·5% and 9·8% for IL-1β; 4·5% and 7·8% for IL-6; and 4·9% and 7·4% for TNF-α, respectively.
Plasma ICAM-1 and VCAM-1 concentrations were measured using a soluble ICAM-1/CD54 immunoassay kit and a soluble VCAM-1 Immunoassay kit (R&D Systems, Inc., Minneapolis, MN, USA) according to the manufacturer's instructions. The intra-assay and interassay CVs were 3·3% and 6·0% for ICAM-1, and 3·5% and 7·7% for VCAM-1, respectively. Urinary albumin concentrations were measured using the turbidimetric immunoassay method with an Integra 800 chemistry analyzer (Roche Diagnostics, Rotkreuz, Switzerland). The intra-assay and interassay CVs were 3·0% and 7·0%, respectively.
The activity of lipoprotein-associated phospholipase A2 (Lp-PLA2) was measured using a previously described modified method. The CVs for intra- and interobserver variability were 3·8% and 5·3%, respectively. Plasma adiponectin concentrations were measured using an enzyme immunoassay (Human Adiponectin ELISA kit; B-Bridge International Inc., Cupertino, CA, USA). The CVs for intra- and interobserver variability were 3·3% and 4·2%, respectively.
Brachial-ankle pulse wave velocity was measured using an automatic waveform analyzer (model VP-1000; Nippon Colin Ltd., Komaki, Japan) using a previously described method. The average ba-PWV from both left and right sides was used for analysis (correlation between the right and left ba-PWVs: r = 0·925, P < 0·001).
Total lipids were extracted with chloroform/methanol (2:1, v/v) as described by Folch et al. Phospholipids were methylated after separation using thin-layer chromatography. Fatty acid methyl esters were analysed by gas chromatography (HP 7890A; Agilent Technologies, Santa Clara, CA, USA). Percentages of individual fatty acids were calculated according to the peak areas relative to the total area.
Plasma samples were prepared and injected into the UPLC/Q-TOF MS (Waters, Milford, MA, USA) using previously described methods. All MS data-related information including retention times, m/z and ion intensities was extracted by MarkerLynx software (Waters) incorporated in the instrument, and the resulting MS data were assembled into a matrix. Metabolites were identified with the Chemspider (www.chemspider.com) and Human Metabolome (www.hmdb.ca) databases. Identified compounds were matched by authentic standards based on both retention time and mass spectra. Authentic standards were purchased from Sigma Chemical (St. Louis, MO, USA), Crystal Chem (Chicago, IL, USA) and Avanti Polar Lipids (Alabaster, AL, USA). MS/MS fragmentation data of identified compounds were obtained by collision energy ramp from 10 to 30 eV and matched to authentic standards.
Statistical analyses were performed with spss ver12.0 (Statistical Package for the Social Sciences; SPSS Inc., Chicago, IL, USA). The Kolmogorov–Smirnov test was used to determine the normality of the distribution, and skewed variables were logarithmically transformed for statistical analysis. For descriptive purposes, mean values are presented using untransformed values. Results are expressed as the mean ± standard error (SE). A two-tailed P value < 0·05 was considered statistically significant. Pearson's and partial correlation coefficients were used to examine the relationships between variables. Differences in clinical variables, including mass intensities of plasma metabolites between the two groups, were tested by independent t-test with the Mann–Whitney U-test. To estimate whether the selected metabolites adequately predicted the risk of diabetes, the receiver operating characteristic (ROC) curve was estimated. In addition, multivariate statistical analysis was performed using simca-p software version 12.0 (Umetrics, Umeå, Sweden). Partial least-squares discriminant analysis (PLS-DA) was used as the classification method for modelling the discrimination between the diabetes and control subjects by visualizing the score plot or S-plot using the first and second PLS components. To validate the model, a seven-fold validation was applied to the PLS-DA model, and the reliabilities of the model were rigorously validated by a permutation test (n = 200). The goodness of the fit was quantified by RY, while the predictive ability was indicated by QY. Generally, RY, which describes how well data in the training set are mathematically reproduced, varies between 0 and 1, with 1 indicating a model with a perfect fit.
Methods
Participants
Study participants included 53 men between 35 and 65 years of age. Participants were recruited during routine check-ups at a health promotion centre at the National Health Insurance Corporation Ilsan Hospital. Exclusion criteria included any diagnoses of diabetes, vascular, renal and liver diseases, or acute or chronic inflammatory disease. Patients taking any drugs or supplements were also excluded. Participants who met the inclusion criteria were recommended for participation in the study, and fasting serum glucose concentrations were measured again. Based on two measurements (from the routine health check-up and at entry to the study), participants with a fasting serum glucose concentration ≥7 mmol/l (126 mg/dl) were defined as newly diagnosed type 2 diabetes. Twenty-six men meeting this criterion and 27 age- and BMI-matched nondiabetic men were included. For nondiabetic subjects, a fasting glucose concentration <7 mmol/l (126 mg/dl) was considered the cut-off, but in actual, all the fasting glucose levels were <6·1 mmol/l (110 mg/dl).
Before participation, the purpose of the study was carefully explained to all patients who provided informed consent. The Institutional Review Board of Yonsei University provided ethical approval of study protocol.
Anthropometric Parameters, Blood Pressure and Blood Collection
Body weights and heights were used to calculate BMI (kg/m). Waist and hip circumferences were measured to calculate the waist-to-hip ratio. Blood pressures were measured in the left arm of seated participants with an automatic blood pressure monitor (TM-2654, A&D, Tokyo, Japan) after a 20-min rest. After a 12-h fasting period, venous blood specimens were collected in ethylenediaminetetraacetic acid-treated or plain tubes, centrifuged to yield plasma or serum and stored at ™70 °C until analysis.
Assessment of Dietary Intake
Dietary intake was assessed with a 24-h recall method and semi-quantitative food frequency questionnaire. Dietary energy values and nutrient content were calculated using the Computer Aided Nutritional analysis program (CAN-pro 3.0; Korean Nutrition Society, Seoul, Korea). Total energy expenditure (TEE) was calculated from activity patterns, including basal metabolic rate, physical activity for 24 h and specific dynamic actions of food. The basal metabolic rate of each participant was calculated with the Harris–Benedict equation.
Serum Glucose Concentration, Insulin Concentration, Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) and β Cell Function
Fasting glucose levels were measured using a glucose oxidase method with a Beckman Glucose Analyzer (Beckman Instruments, Irvine, CA, USA). The intra-assay and interassay coefficients of variability (CVs) were 1·1% and 1·4%, respectively. Insulin levels were measured by radioimmunoassay using commercial kits from Immuno Nucleo Corporation (Stillwater, MN, USA). The intra-assay and interassay CVs were 5·7% and 6·5%, respectively. Insulin resistance (IR) was calculated by HOMA using the following equation: HOMA-IR = [fasting insulin (μIU/ml) × fasting glucose (mmol/l)]/22·5. β cell function was calculated as [20 × fasting insulin (μIU/ml)]/[fasting glucose (mmol/l) ™ 3·5).
Serum Lipid Profile
Fasting serum total cholesterol and triglycerides were measured using commercially available kits on a Hitachi 7150 Autoanalyzer (Hitachi Ltd., Tokyo, Japan). The intra-assay and interassay CVs were 1·4% and 2·6% for total cholesterol, and 1·1% and 1·3% for triglycerides, respectively. After the precipitation of chylomicrons with dextran sulphate magnesium, concentrations of high-density lipoprotein (HDL) cholesterol in the supernatants were determined using ADVIA 2400 Chemistry System (Siemens Healthcare Diagnostics, Deerfield, IL, USA). The intra-assay and interassay CVs were 1·8% and 2·5%, respectively. Low-density lipoprotein (LDL) cholesterol was indirectly estimated in participants with serum triglyceride concentrations <400 mg/dl using the Friedewald formula.
Lipid Peroxidation: Plasma Malondialdehyde (MDA), Oxidized LDL and Urinary 8-epi-Prostaglandin F2α (8-epi-PGF2α)
Plasma MDA was measured from thiobarbituric acid–reactive substances (TBARS Assay Kit; Zepto-Metrix Co., Buffalo, NY, USA). The intra-assay and interassay CVs were 2·9% and 5·2%, respectively. Plasma oxidized LDL (ox-LDL) was measured using an enzyme immunoassay (Mercodia, Uppsala, Sweden). The intra-assay and interassay CVs were 5·4% and 6·3%, respectively. Urine was collected in polyethylene bottles containing 1% butylated hydroxytoluene after a 12-h fast. Bottles were immediately covered with aluminium foil and stored at ™70 °C until analysis. 8-epi-PGF2α was measured using an enzyme immunoassay (Oxford Biomedical Research Inc., Oxford, MI, USA). Urinary 8-epi-PGF2α concentrations were expressed as pmol/mmol creatinine. The intra-assay and interassay CVs were 2·5% and 7·6%, respectively.
Serum High-Sensitivity C-reactive Protein (hs-CRP), Interleukin (IL)-1ß, IL-6 and Tumour Necrosis Factor-alpha (TNF-α) Concentrations
Serum hs-CRP concentrations were measured with an Express autoanalyzer (Chiron Diagnostics Co., Walpole, MA, USA) using high-sensitivity CRP-Latex (II) X2 kit (Seiken Laboratories Ltd., Tokyo, Japan). Serum IL-1ß, IL-6 and TNF-α concentrations were measured with a Bio-plex suspension array system (Bio-Rad, Hercules, CA, USA) using a human cytokine panel kit. The intra-assay and interassay CVs were 5·5% and 9·8% for IL-1β; 4·5% and 7·8% for IL-6; and 4·9% and 7·4% for TNF-α, respectively.
Intercellular Adhesion Molecule (ICAM)-1, Vascular Cell Adhesion Molecule (VCAM)-1 and Urinary Albumin Concentrations
Plasma ICAM-1 and VCAM-1 concentrations were measured using a soluble ICAM-1/CD54 immunoassay kit and a soluble VCAM-1 Immunoassay kit (R&D Systems, Inc., Minneapolis, MN, USA) according to the manufacturer's instructions. The intra-assay and interassay CVs were 3·3% and 6·0% for ICAM-1, and 3·5% and 7·7% for VCAM-1, respectively. Urinary albumin concentrations were measured using the turbidimetric immunoassay method with an Integra 800 chemistry analyzer (Roche Diagnostics, Rotkreuz, Switzerland). The intra-assay and interassay CVs were 3·0% and 7·0%, respectively.
Plasma Lp-PLA2 Activity and Adiponectin Concentration
The activity of lipoprotein-associated phospholipase A2 (Lp-PLA2) was measured using a previously described modified method. The CVs for intra- and interobserver variability were 3·8% and 5·3%, respectively. Plasma adiponectin concentrations were measured using an enzyme immunoassay (Human Adiponectin ELISA kit; B-Bridge International Inc., Cupertino, CA, USA). The CVs for intra- and interobserver variability were 3·3% and 4·2%, respectively.
Brachial-ankle Pulse Wave Velocity
Brachial-ankle pulse wave velocity was measured using an automatic waveform analyzer (model VP-1000; Nippon Colin Ltd., Komaki, Japan) using a previously described method. The average ba-PWV from both left and right sides was used for analysis (correlation between the right and left ba-PWVs: r = 0·925, P < 0·001).
Fatty Acid Composition in Serum Phospholipids
Total lipids were extracted with chloroform/methanol (2:1, v/v) as described by Folch et al. Phospholipids were methylated after separation using thin-layer chromatography. Fatty acid methyl esters were analysed by gas chromatography (HP 7890A; Agilent Technologies, Santa Clara, CA, USA). Percentages of individual fatty acids were calculated according to the peak areas relative to the total area.
Metabolic Profiling of Plasma Samples by UPLC/Q-TOF MS Analysis
Plasma samples were prepared and injected into the UPLC/Q-TOF MS (Waters, Milford, MA, USA) using previously described methods. All MS data-related information including retention times, m/z and ion intensities was extracted by MarkerLynx software (Waters) incorporated in the instrument, and the resulting MS data were assembled into a matrix. Metabolites were identified with the Chemspider (www.chemspider.com) and Human Metabolome (www.hmdb.ca) databases. Identified compounds were matched by authentic standards based on both retention time and mass spectra. Authentic standards were purchased from Sigma Chemical (St. Louis, MO, USA), Crystal Chem (Chicago, IL, USA) and Avanti Polar Lipids (Alabaster, AL, USA). MS/MS fragmentation data of identified compounds were obtained by collision energy ramp from 10 to 30 eV and matched to authentic standards.
Statistical Analysis
Statistical analyses were performed with spss ver12.0 (Statistical Package for the Social Sciences; SPSS Inc., Chicago, IL, USA). The Kolmogorov–Smirnov test was used to determine the normality of the distribution, and skewed variables were logarithmically transformed for statistical analysis. For descriptive purposes, mean values are presented using untransformed values. Results are expressed as the mean ± standard error (SE). A two-tailed P value < 0·05 was considered statistically significant. Pearson's and partial correlation coefficients were used to examine the relationships between variables. Differences in clinical variables, including mass intensities of plasma metabolites between the two groups, were tested by independent t-test with the Mann–Whitney U-test. To estimate whether the selected metabolites adequately predicted the risk of diabetes, the receiver operating characteristic (ROC) curve was estimated. In addition, multivariate statistical analysis was performed using simca-p software version 12.0 (Umetrics, Umeå, Sweden). Partial least-squares discriminant analysis (PLS-DA) was used as the classification method for modelling the discrimination between the diabetes and control subjects by visualizing the score plot or S-plot using the first and second PLS components. To validate the model, a seven-fold validation was applied to the PLS-DA model, and the reliabilities of the model were rigorously validated by a permutation test (n = 200). The goodness of the fit was quantified by RY, while the predictive ability was indicated by QY. Generally, RY, which describes how well data in the training set are mathematically reproduced, varies between 0 and 1, with 1 indicating a model with a perfect fit.
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