2.1 Patients
Newly diagnosed T2DM patients treated at the MMC of the Tianjin 4th Central Hospital from April to August 2018 were recruited as the research subjects, and healthy people were recruited as the control group at the same time. In this study, healthy people were referred to as volunteers who had no diabetes and had a low risk of diabetes when they entered the group (China Diabetes Risk Score < 25) [21]. We collected information on the patient’s name, sex, smoking and drinking history, family history of diabetes, waist circumference, age, diabetes course, and blood pressure from the MMC system. The body mass index (BMI) was calculated and recorded according to the height and body weight. Blood was taken in a fasting state for the detection of plasma glucose and blood lipids. The patients were examined for proteinuria, the fundus was photographed, and serum samples were taken for metabolomic analysis.
2.2 Ethical statement
The clinical study protocol was approved by the Institutional Review Board (IRB) of Tianjin 4th Central Hospital, and all steps were conducted in accordance with the principles of the World Medical Association Declaration of Helsinki (trial registration code: ChiCTR2000037652). The IRB approved the collection and use of patient records according to the regulations for clinical trials in humans (IRB approval no.2017-SZXLL017). Written informed consent was obtained from each patient, and serum samples were collected during medical examinations.
2.3 Inclusion and exclusion criteria
Due to the occult onset of T2DM, there might be a large gap between the time of diagnosis and the time of real onset [22]. In this study, the diagnosed age of LatT2DM was ≥ 50 years, and the diagnosed age of EarT2DM was < 40 years. In order to avoid the influence of drugs on the metabolic spectrum results, the subjects did not take any drugs or health products in the recent period (within 1 month). Each participant recently had regular rest and diet, and there was no stress such as excessive exercise, trauma and emotional excitement. All diabetic patients were screened for insulin antibodies, glutamic acid decarboxylase antibodies and islet cell antibodies, all of which were negative. The inclusion criteria: (a) The diagnosis of T2DM was based on the 2017 Chinese diabetes treatment guidelines, as fasting peripheral blood glucose (FPG)≥7.0 mmol/l, postprandial blood glucose≥11.1 mmol/l at 2 h, or a confirmed diagnosis as type 2 diabetes by hospitals with Grade 2 or above [1]. (b) The duration of diabetes was less than 1 year. (c) Patients did not have diabetic microvascular complications, such as proteinuria or diabetic retinopathy. (d) Each patient volunteered to participate in the study.
The exclusion criteria were as follows: (a) type 1 and other special types of diabetes, gestational diabetes, or diabetes mellitus with pregnancy; (b) patients with severe mental illness and unclear consciousness; and (c) patients with active tuberculosis and other infectious diseases.
Group description: According to the age at diabetes diagnosis, the study divided patients with diabetes into EarT2DM and LatT2DM groups, and matched healthy individuals with age and sex as corresponding healthy control groups. They were successively named healthy control group 1 (HeaCG1) and healthy control group 2 (HeaCG 2).
2.4 UPLC-Q-TOF/MS analysis [15]
2.4.1 Sample collection and preparation
Serum collection: Blood samples were processed by spinning the blood at 3000 rpm for 10 min at 4 °C and freezing at −80 °C prior to analysis. The samples were thawed at 4 °C and 100 μL aliquots were mixed with 400 μL of cold methanol/acetonitrile (1:1, v/v) to remove the protein. The mixture was centrifuged for 20 min at 14,000 × g and 4 °C. The supernatant was then dried using a vacuum centrifuge. For the UPLC-MS analysis, the samples were redissolved in 100 μL of cold methanol/acetonitrile (1:1, v/v).
2.4.2 Requirements, operation and analysis of experimental platform
Platform requirements: triple TOF 5600+mass spectrometer (AB SCIEX), Agilent 1290 infinity LC ultra high pressure liquid chromatograph (Agilent), chromatographic column: waters, acquity UPLC beh amide 1.7 μm, 2.1 mm × 100 mm column.
Chromatographic conditions and process: the samples were separated by Agilent 1290 infinity LC ultra high performance liquid chromatography system (UHPLC) HILIC column; Column temperature 25 ℃; Flow rate: 0.3 ml / min; Injection volume 2 μL; Mobile phase composition a: water + 25 mM ammonium acetate + 25 mm ammonia, B: acetonitrile; The gradient elution procedure is as follows: 0-1 min, 95% B; 1-14 minutes, B changes linearly from 95% to 65%; 14-16 minutes, B changes linearly from 65% to 40%; 16-18 minutes, B maintained at 40%; 18 --- 18.1 minutes, B changes linearly from 40% to 95%; 18.1 --- 23 minutes, B maintained at 95%; During the whole analysis process, the samples were placed in a 4 ℃ automatic sampler. In order to avoid the influence caused by the fluctuation of instrument detection signal, the random sequence is used for continuous analysis of samples.
Mass spectrum condition setting and process: The ESI source conditions were set as follows: Ion Source Gas1 (Gas1) as 60, Ion Source Gas2 (Gas2) as 60, curtain gas (CUR) as 30, source temperature, 600 °C; and IonSpray voltage floating (ISVF) ± 5500 V. On MS acquisition, the instrument was set to acquire over the m/z range 60–1000 Da, and the accumulation time for TOF MS scan was set at 0.2 s/spectra. In the auto MS/MS acquisition, the instrument was set to acquire over the m/z range of 25–1000 Da, and the accumulation time for the product ion scan was set at 0.05 s/spectra. The product ion scan was acquired using information-dependent acquisition (IDA) with a high sensitivity mode. The parameters were set as follows: the collision energy (CE) was fixed at 35 V with ± 15 eV; declustering potential (DP),60 V (+), and −60 V (−), excluding isotopes within 4 Da, candidate ions to monitor per cycle: 6.
In the HILIC separation, samples were analysed using a 2.1 mm ×100 mm ACQUIY UPLC BEH 1.7 µm column (Waters, Ireland). In both ESI positive and negative modes, the mobile phase contained 25 mM ammonium acetate and 25 mM ammonium hydroxide in water and B = acetonitrile. The gradient was 95% eluent B for 1 min and was linearly reduced to 65% in 14 min, and then reduced to 40% in 2 min, maintained for t2 min, and then increased to 95% in 0.1 min, with a 5 min re-equilibration period. The gradients were at a flow rate of 0.3 mL/min, and the column temperatures were kept constant at 25 °C. A 2 µL aliquot of each sample was injected. During the analysis, quality control samples (QC) were inserted into the sample queue to monitor and evaluate the stability of the system and the reliability of the experimental data.
2.4.3 Metabolite data analysis
The raw MS data (wiff. scan files) were converted to mzXML files using the Proteo Wizard MS Convert before importing into freely available XCMS software. For peak picking, the following parameters were used: centre-wave m/z = 25 ppm, peak width = c (10, 60), and prefilter = c (10, 100). For peak grouping, bw = 5, mzwid = 0.025, and minfrac = 0.5. In the extracted ion features, only the variables with more than 50% of the nonzero measurement values in at least one group were retained. The identification of the metabolites using MS/MS with an in-house database was established using available authentic standards. After the normalisation to total peak intensity, the processed data were uploaded before importing into SIMCA-P (version 14.1, Umetrics, Umea, Sweden), where the data were subjected to multivariate data analyses, including Pareto-scaled principal component analyses (PCAs) and orthogonal partial least-squares discriminant analyses (OPLS-DAs). The variable importance in the projection (VIP) value of each variable in the PLS-DA model was calculated to indicate its contribution to the classification. Metabolites with a VIP value > 1 were further subjected to Student’s t-tests at the univariate level to measure the significance of each metabolite, and P values less than 0.05, were considered to be statistically significant. The hierarchical cluster algorithm was used to cluster the differentially expressed proteins among groups, and the data were displayed in the form of a heat map.
The hierarchical cluster algorithm was used to cluster the differentially expressed proteins among groups, and the data were displayed in the form of a heat map. Taking the KEGG pathway as a unit and taking the metabolic pathway participated by this species or species with close genetic relationships as the background, the significance level of metabolite enrichment of each pathway was analysed and calculated using the Fisher's exact test to make a preliminary determination of the significantly affected metabolic and signal transduction pathways.
2.5 Flow chart of the study (Figure 1).
2.6 Statistical analysis
Statistical Program for Social Sciences software (version 20.0; SPSS, Inc., Chicago, IL, USA) was used for data collation and analysis. The Kolmogorov-Smirnov normal test was performed on the measurement data. Means ± standard deviations were used for the statistical description of the variables that conformed to a normal distribution, and percentages (%) was used for counting data. An independent sample t-test was used to compare the measurement data. The chi-squared test was used for the comparison of the counting data. All the statistical tests were performed using bilateral tests with alpha = 0.05.