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Serum Metabolomics Study of Gliclazide Modifiedrelease Treated Type 2 Diabetes Mellitus Patients Using a Gas Chromatography-Mass Spectrometry Method Yang Zhou, Cheng Hu, Xinjie Zhao, Ping Luo, Jingyi Lu, Qing Li, Miao Chen, Dandan Yan, Xin Lu, Hongwei Kong, Weiping Jia, and Guowang Xu J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00866 • Publication Date (Web): 20 Feb 2018 Downloaded from http://pubs.acs.org on February 22, 2018

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Serum Metabolomics Study of Gliclazide Modified-release

2

Treated Type 2 Diabetes Mellitus Patients Using a Gas

3

Chromatography-Mass Spectrometry Method

4 5

Yang Zhou1,4#, Cheng Hu2,3#, Xinjie Zhao1,4, Ping Luo1,4, Jingyi Lu2, Qing Li2, Miao

6

Chen2, Dandan Yan2, Xin Lu1,4*, Hongwei Kong1,4, Weiping Jia2*, Guowang Xu1,4*

7

1

8

Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China

9

2

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian

Department of Endocrinology and Metabolism, Shanghai Jiao Tong University

10

Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical

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Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233,

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China.

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3

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Medical University, 6600 Nanfeng Road, Shanghai 201499, People’s Republic of

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China

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4

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* Address correspondence to:

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Prof. Dr. Guowang Xu, Tel/Fax: 0086-411-84379530. E-mail: [email protected].

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Prof. Dr. WeipingJia, Tel: 0086-21-24058260. E-mail: [email protected]

20

Prof. Dr. Xin Lu, Tel.: +86-411-84379532. E-mail: [email protected].

Institute for Metabolic Disease, Fengxian Central Hospital Affiliated to Southern

University of Chinese Academy of Sciences, Beijing 100049, China

21 22

#

Yang Zhou and Cheng Hu contributed equally to this work.

1


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ABSTRACT

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Sulfonylureas are one of the commonly used drugs in type 2 diabetes mellitus

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(T2DM), but with considerable incidence of monotherapy failure. However, the

4

mechanism of patients’ drug response is unclear and suitability evaluation biomarkers

5

are in urgent need for precision medicine. In this study, a pseudotargeted gas

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chromatography-mass spectrometry method was employed to investigate the serum

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metabolic profiling of 66 significant responders and 24 non-significant responders at

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baseline and 16-week after gliclazide modified-release (MR) monotherapy. Clinical

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improvements in blood glucose level and insulin sensitivity were closely associated

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with the alterations of TCA cycle, ketone body metabolism, lipid oxidation,

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branched-chain amino acids catabolism and gut flora metabolism. The different

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baseline metabolic profiling observed in the two groups implied patients with lower

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dyslipidemia level may be more suitable for sulfonylurea therapy. The biomarker

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panel

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8,11,14-eicosatrienoate and methyl hexadecanoate shows a very good prediction

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ability for the suitability of gliclazide treatment, it may be meaningful in personalized

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medicine of T2DM patients by sulfonylurea therapy.

consisting

of

HbA1c,

5,8,11,14,17-eicosapentaenoic

acid,

methyl

18 19

KEYWORDS: Metabolomics, Gliclazide modified-release, Sulfonylureas, Type 2

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diabetes mellitus, Gas chromatography-mass spectrometry, Biomarker

2



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INTRODUCTION

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Type 2 diabetes mellitus (T2DM) is an escalating public health problem worldwide,

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contributed considerably to social economical burdens.1 Sulfonylureas, which mainly

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stimulate endogenous insulin secretion via binding to sulfonylurea receptor in

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pancreatic β-cell,2 have been recognized as one of the major oral antidiabetic drugs in

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T2DM.3 Among sulfonylureas, gliclazide modified-release (MR) is commonly used in

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T2DM with its long and potent effect on glycemic level and low hypoglycemic

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events.4 Sulfonylurea monotherapy can reduce glycated hemoglobin (HbA1c) by

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1.51% more than placebo.5 Although most of T2DM patients responded well to

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sulfonylurea therapy, some patients failed in the clinical practice. According to

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previous cohorts, the incidence of sulfonylurea monotherapy failure reached nearly

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20% at 1 year6 and 34% at 5 years.7 Individual response to sulfonylurea may be

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affected by genetic8 and clinical factors.9 However, the potential mechanism of

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patients’ response is still unclear. Efforts have also been made to find indicators for

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predicting the outcome of sulfonylurea. It was reported that the higher baseline fasting

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plasma glucose (FPG) and HbA1c levels may predict the more reductions after oral

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agents (including sulfonylureas) treated.10 KCNQ1 polymorphisms of T2DM patients

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were found to be related to the therapeutic effect of gliclazide MR.11 Ren et al.

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described a model built by clinical parameters and genes, which had the area under

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the receiving operator characteristic curve (AUC) of 0.77 for predicting the outcome

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of HbA1c target achievement.9 However, deep-going research is still required to

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uncover the potential mechanism of patients’ response, and new effective biomarkers 3


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for the assessment of sulfonylurea suitability are in urgent need.

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Metabolomics, as a powerful method to investigate the dynamic variation of

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endogenous metabolites, has been widely applied in disease mechanism,12,13

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biomarker discovery,14,15 therapeutic effect evaluation and prediction16 etc. Study

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reported that phosphatidylcholines were raised, sphingomyelins and cholesterol ester

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were reduced in T2DM patients after one year’s sulfonylurea treatment compared

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with baseline. And PC (O-34:1), SM (d18:0-24:1), and SM (d18:1-20:1) were related

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to the long-term cardiovascular events.17 Huo et al. observed that carnitines, urate,

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phenylalanine and tryptophan etc. were responsible for the urinary metabolic profiling

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separation of sulfonylurea - treated and untreated T2DM patients.18 For the outcomes

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prediction of drug treatment, baseline glucose and 1, 5-anhydroglucitol levels were

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found to be correlated with the HbA1c reduction after 5 years’ sulfonylurea treatment

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based on the plasma metabolic profiling study of T2DM patients before therapy.19

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In this study, we performed serum metabolic profiling of diabetes patients before and

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after gliclazide MR therapy using gas chromatography - mass spectrometry (GC-MS)

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to explore the effect of the drug on patients’ metabolism, determine the positive

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metabolic responses in patients well to gliclazide MR therapy, and screen potential

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biomarkers for assessing the patients’ suitability of gliclazide MR.

19 20

MATERIALS AND METHODS

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Participants

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This study was approved by the Institutional Review Board of Shanghai Jiao Tong 4



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University Affiliated Sixth People’s Hospital. All participants signed the informed

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consent. One hundred of newly diagnosed T2DM patients were recruited in 2012 -

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2013 from the outpatient department in Shanghai Jiao Tong University Affiliated

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Sixth People’s Hospital, Shanghai, China. The diagnosis of T2DM was based on the

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criteria of World Health Organization.20 Patients with Type 1 diabetes, mitochondrial

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diabetes, a history of any anti-diabetic medications, pregnant, cancer, cardiac failure,

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or renal failure were excluded from the study.

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After a 2-week run-in period (diet and exercise therapy only), 100 patients were given

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gliclazide MR, subsequent visits and designed clinical assessments were on weeks 2,

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4, 8, 12, and 16. Anthropometric traits, FPG and 2-h plasma glucose (2hPG) were

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determined at each visit. All patients were assigned to receive initial minimum dosage

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of gliclazide MR at 30 mg per day in the beginning, then dosage was added to 60, 90,

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or 120 mg daily in successively steps, if FPG and 2hPG were not achieved 7 mmol/L

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and 11 mmol/L (200 mg/dL). Considering the ethical issues, patients presenting

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FPG > 13 mmol/L (234 mg/dL) or 2hPG > 18 mmol/L (324 mg/dL) at two

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consecutive visits (at a maximal interval of 6 d) switched to other treatment options,

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and excluded from the study. Ten patients were excluded for losing follow-up. Finally,

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90 patients completed the 16 weeks gliclazide MR treatment. Serum lipid profile,

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fasting insulin (FINS) and 2-h insulin (2hINS), homeostasis model assessment

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(HOMA)21 for insulin resistance index (HOMA-IR) and β cell function (HOMA-β)

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were measured at baseline and 16-week visit. All clinical information was shown in

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Table 1. Their fasting sera of baseline and final visit (16-week) were used for 5


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metabolic profiling study. HbA1c level is an indicator of long-term glycemic control.

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After 16 weeks gliclazide MR treatment, patients with HbA1c level lower than 6.5%

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were defined as significant responder (SR1). As previously reported,11 at baseline

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some patients had higher levels of HbA1c, whose HbA1c levels decreased more than

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20% but did not achieve 6.5% after 16 weeks of treatment, were also considered to be

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significant responder (SR2) (Table 1). Patients who did not meet above criterions

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were treated as non-significant responder (NSR) and were advised to alter treatment

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protocols. On the basis of the criterions, 66 patients (male/female: 46/20) were SR, 24

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patients (male/female: 13/11) were NSR. In addition, another batch of subjects,

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containing 22 SR and four NSR patients as the external validation set, was sampled at

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the same conditions as described. The clinical information was shown in Supporting

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Information Table S1.

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Metabolic Profiling Analysis

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Sera were stored at -80 oC until sample preparation. After thawing on the ice, a 50 µL

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of sample was drawn and mixed with 200 µL of methanol containing internal

17

standards

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lyophilization-treated for subsequent oximation and silylation reactions. After

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reactions, the supernatant was obtained for GC-MS analysis. Quality control (QC)

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samples were prepared by pooling equal aliquot of each sample and pretreated as

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samples.

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A QP 2010 GC-MS system (Shimadzu, Japan) with a DB-5 MS fused-silica capillary

(ISs)

(Table

S2).

As

previously

reported,22

supernatants

were

6



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column (30 m × 0.25 mm × 0.25 µm, Agilent Technologies, USA) was used for

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metabolic profiling analysis. A pseudotargeted GC-MS metabolomics method, that

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uses selected ion monitoring mode to realize non-targeted data acquisition, was

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established as previously report.22 Total of 289 characteristic ions were defined for

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data collection and quantification. A QC sample was inserted every ten samples to

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evaluate the data quality.

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Data Processing and Statistics

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A peak table was obtained using GCMS Postrun Analysis (Software, Shimadzu, Japan)

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based on a quantitative table (containing retention time and characteristic ions). The

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intensities of features were normalized to the corresponding ISs, and multiplied by the

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average responses of corresponding ISs in QC samples. Principal component analysis

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(PCA) was conducted by SIMCA-P 11.0 (Umetrics, Sweden). The significantly

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changed clinical parameters and metabolites after therapy compared with baseline

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were defined by paired non-parametric tests (Wilcoxon signed rank two-sided test)

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and false discovery rate (FDR) correction23 using MATLAB (MathWorks, USA). The

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clinical parameters and metabolites in inter-group comparison at baseline (p < 0.05)

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were screened by Mann-Whitney U test using SPSS 18.0 (IBM, USA). A heat map of

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the differential metabolites was obtained using the MultiExperiment Viewer 4.8.1

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(http://www.tm4.org). Correlation analysis between clinical parameters and the

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differential metabolites was performed by using SPSS 18.0. The significantly altered

22

pathways

were

defined

via

enrichment

analysis

on

MetaboAnalyst

2.0 7


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(http://www.metaboanalyst.ca). To predict the suitability of gliclazide MR, the

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potential biomarkers were defined via binary logistic regression analysis and

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evaluated via receiver operating characteristic curve (ROC) using SPSS 18.0.

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RESULTS

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Clinical Parameters of Cohort

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In the study, 90 T2DM patients (male/female: 59/31) with age of 58.1 ± 10.0 years old

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completed the 16-week follow-up. It was observed that the clinical features of patients

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were significantly changed at 16-week visit compared with baseline (Table 1). After

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gliclazide MR treatment, systolic and diastolic blood pressures (SBP and DBP),

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alanine aminotransferase (ALT) and aspartate transaminase (AST) were all

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significantly reduced. The significant alterations of serum lipid profile were also

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observed, including the decrease of total cholesterol, triglyceride, low-density

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lipoprotein cholesterol (LDL-c) and apolipoprotein B (ApoB). FPG, 2hPG and HbA1c

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were reduced sharply, while FINS was distinctly improved. Moreover, it was

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observed that HOMA–IR was significantly decreased, conversely HOMA-β was

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significantly increased. DBP, total cholesterol, LDL-c, ApoB, FPG, 2hPG and HbA1c

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were significantly down-regulated, while HOMA-β was significantly up-regulated in

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both SR and NSR groups at final visit compared with baseline. Nevertheless, SBP,

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triglyceride, HOMA–IR and ALT were remarkably decreased only in SR group after

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gliclazide MR therapy.

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At 16-week visit, LDL-c, FPG and HbA1c were significantly lower in SR group than 8



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those of in NSR group. At baseline, SBP, high-density lipoprotein cholesterol

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(HDL-c), LDL-c and ApoB were significantly lower, while HbA1c was significantly

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higher in SR group than that of in NSR group.

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The clinical features of patients in the external validation set were given in Table S1.

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AST, total cholesterol, LDL-c, ApoB, ApoE, FPG, 2hPG, HbA1c and HOMA-IR were

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significantly decreased only in SR group at final visit compared with baseline. At

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16-week visit, HbA1c was significantly lower in SR group than that of in NSR group.

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Global Metabolic Response to Gliclazide MR Treatment

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For pseudotargeted GC-MS metabolic profiling, the score scatter plots of QC samples

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were clustered closely in the PCA model (Figure S1A). And 91.3% and 98.3% of

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features in QC samples had RSD distributions less than 20% and 30%, respectively

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(Figure S1B), demonstrating a good data quality of the study. Qualitative analysis was

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following our previous reports,22,24 mainly based on similarity search in commercial

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mass spectral library (Mainlib, NIST, Wiley, and Fiehn) and a home-made library. A

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total of 187 metabolites were identified, and among them 140 metabolites were

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verified using available standards. Finally, 183 identified metabolites with RSD

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