Skip to main content

Regulation of Adropin by Sitagliptin monotherapy in participants with newly diagnosed type 2 Diabetes

Abstract

Background

Adropin is a potent metabolic regulator of insulin sensitivity and glycolipid metabolism. The present study investigated the effects of sitagliptin on adropin and metabolic parameters in participants with newly diagnosed type 2 diabetes (T2D).

Methods

Thirty-five participants newly-diagnosed with T2D were prescribed sitagliptin 100 mg once daily for 17 weeks. Twenty-eight age-, sex-, and BMI-matched healthy subjects were included as the control group. Adropin and clinical parameters were assessed at baseline and after treatment.

Results

At baseline, serum adropin levels were lower in T2D participants than in the healthy individuals (3.12 ± 0.73 vs. 5.90 ± 1.22 ng/ml, P <  0.01). Serum adropin levels were significantly higher in T2D patients after sitagliptin treatment (4.97 ± 1.01 vs. 3.12 ± 0.73 ng/ml, P <  0.01). The changes in serum adropin levels after sitagliptin treatment were associated with the improvements of fasting blood glucose (FBG) (β = − 0.71, P <  0.01), glycosylated hemoglobin (HbA1c) (β = − 0.44, P <  0.01) and homeostatic model assessment of β-cell function (HOMA-β) (β = 9.02, P <  0.01).

Conclusions

Sitagliptin treatment could significantly increase serum adropin levels in participants with newly diagnosed T2D. The increase in serum adropin levels could be associated with the amelioration of glucose metabolism, which might be involved in beneficial glucose-lowering mechanisms of sitagliptin.

Trial registration

Clinicaltrials.gov, NCT04495881. Retrospectively registered on 03/08/2020.

Peer Review reports

Introduction

Adropin is a unique peptide hormone first reported in 2008. It contains 76 amino acids encoded by the Energy Homeostasis Associated (Enho) gene and is predominantly expressed in liver and brain [1]. Some animal studies have shown that adropin is involved in the control of glycolipid metabolism and the improvement of insulin sensitivity [1,2,3,4]. Lower serum adropin levels in human have been proved to be associated with multiple metabolic disorders such as type 2 diabetes (T2D), nonalcoholic fatty liver disease (NAFLD), polycystic ovary syndrome (PCOS) and metabolic syndrome [5,6,7,8].

T2D is a chronic metabolic disorder characterized by chronic hyperglycemia due to β-cell dysfunction and insulin resistance [9]. Sitagliptin is a potent and highly selective dipeptidyl peptidase-4 (DPP-4) inhibitor for T2D therapy and acts by inhibition of DPP-4 enzyme. Moreover, sitagliptin is the most widely used, because it was the first of DPP-4 inhibitors approved by the US Food and Drug Administration (FDA) [10], and it is effective, safe and generally well-tolerated in clinical practice [11]. DPP-4 is expressed in different tissues such as liver, brain and adipose tissue [12,13,14]. However, to our knowledge, no studies had focused on whether and how DPP-4 inhibitors regulate serum adropin. Therefore, we investigated the changes in serum adropin levels in participants newly-diagnosed with T2D following sitagliptin treatment.

Materials and methods

Study design

This was a phase 4, open-label, single-arm, interventional study to evaluate the effectiveness of sitagliptin for the treatment of newly diagnosed T2D. The study was conducted in accordance with the Declaration of Helsinki and was registered on Clinicaltrials.gov on 03/08/2020 (registration number NCT04495881). The protocol was approved by the Ethics Committee of Beijing Chao-yang Hospital affiliated with Capital Medical University (2020-#-182). All enrolled participants provided written informed consent.

Recruitment

Thirty-eight participants with newly diagnosed T2D (T2D group) were recruited from outpatients at the Endocrinology Department of Beijing Chao-yang Hospital affiliated with Capital Medical University from January 2020 to March 2020. They met inclusion and exclusion criteria, which were similar to those used in our previous studies [15]. All participants underwent medical and laboratory screening including a 75 g oral glucose tolerance test (OGTT). Eligible participants aged 18 to 65 years were newly diagnosed with T2D within the previous 3 months according to the 2014 American Diabetes Association (ADA) diagnostic criteria and they were further selected when HbA1c ≥ 7.0% and ≤ 9.5% [16]. They did not use any hypoglycemic drugs before the enrolment. The healthy control group included twenty-eight age-, sex-, and body mass index (BMI)-matched healthy participants with normal glucose tolerance who received routine physical examination. We excluded all participants whose HbA1c levels were out of our selection range, those who had type 1 diabetes, pancreatitis, pregnancy or possible pregnancy, liver or renal function impairment, coronary heart disease, infectious disease, history of intestinal surgery, chronic hypoxic diseases, hematological disease, systemic inflammatory disease and cancer, and those who had medication use related to hypertension, hyperlipidemia, hyperglycemia and other metabolic-related disorders.

The T2D participants received sitagliptin 100 mg orally once daily for 17 weeks. Furthermore, all participants were given advice for lifestyle modifications consisting of diet and physical activity. Drug compliance, vital signs and adverse events were monitored by outpatient review or telephone follow-up. The patients who had poor glycemic control (FBG values > 10 mmol/L within four weeks) or could not accept the follow-up visit were withdrawn from the study.

Clinical and biochemical measurements

The newly diagnosed T2D participants were followed-up for 17 weeks. The fasting blood samples were taken before and after the 17-week sitagliptin treatment. The serum samples from all participants were collected in the morning after an overnight fast and stored at − 80 °C until analysis.

Anthropometric measurements and biochemical laboratory tests were performed at baseline (pre-treatment) and after 17 weeks of sitagliptin treatment (post-treatment). Weight and height were measured to the nearest 0.1 kg and 0.1 cm in the fasting state, respectively. FBG, HbA1c, fasting insulin (FINS), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) were measured at the central chemistry laboratory of Beijing Chao-yang Hospital affiliated with Capital Medical University. The primary outcome measure was the changes in HbA1c at baseline and after 17 weeks treatment, and the secondary outcome measures included changes in FBG, FINS, homeostasis model assessment of insulin resistance (HOMA-IR), HOMA-β, TC, HDL-C, TG and LDL-C.

Serum adropin levels were measured using commercial enzyme-linked immunosorbent assay (ELISA) kits (EK-032-35, Phoenix Pharmaceuticals, Inc., USA) for quantitative detection. The sensitivity of the assay was 0.32 ng/ml and the linear range of the standard was 0.32–5.80 ng/ml. BMI was calculated as the weight in kilograms divided by the height in meters squared (kg/m2). HOMA-IR and HOMA-β were calculated by the following formulas: HOMA-IR = FINS (μIU/mL) × FBG (mmol/L)/22.5; HOMA-β = 20 × FINS (μIU/mL)/FBG (mmol/L) − 3.5 [17, 18].

Statistical analysis

Data analyses were performed using the SPSS statistical software, version 23.0 (SPSS Inc., Chicago, IL, USA). The normality of distribution was tested by Shapiro–Wilk test. The data were expressed as means ± standard deviation (SD) or median (interquartile range). The Student’s t-test or nonparametric Mann-Whitney U-test for continuous variables was used to compare the differences between healthy control group and T2D group. Statistical differences versus baseline after 17 weeks of pharmacotherapy were tested using the paired Student’s t-test or nonparametric Wilcoxon test. Pearson and Spearman correlation coefficients were used to assess the correlations between serum adropin levels and other metabolic parameters at baseline as appropriate. We fit linear mixed-effects models using the STATA version 13.0 (STATA, College Station, TX), allowing for the inclusion of individual as a random effect, to examine the longitudinal relationships between serum adropin levels and insulin resistance/sensitivity indicators as well as the parameters of glucose metabolism and lipid metabolism over the study period. Mixed effects linear models can account for the associations between repeated measures owing to unobserved inter-individual heterogeneity by incorporating random effects. All statistical tests were two-tailed and P values < 0.05 were considered statistically significant.

Results

Baseline characteristics of control subjects and participants with T2D

Among thirty-eight enrolled participants with T2D, thirty-five completed the follow-up and three dropped out of this study because of poor glycemic control. No hypoglycemia occurred during the follow-up period. The baseline characteristics of the study participants were summarized in Table 1. Comparative analysis of baseline characteristics showed that there were no significant differences as regards age, sex, BMI, TC, LDL-C, TG and FINS levels between healthy control group and T2D group (all P > 0.05). Nevertheless, higher FBG, HbA1c and HOMA-IR as well as lower HDL-C and HOMA-β were observed in the T2D group compared with the healthy individuals (all P <  0.05). Serum adropin levels were significantly lower in the T2D group than in the control group (3.12 ± 0.73 vs. 5.90 ± 1.22 ng/ml, P <  0.01).

Table 1 Baseline characteristics of the study participants

Correlations between serum adropin levels and the baseline parameters

In addition, the correlations between serum adropin levels and the baseline parameters were investigated in all participants. The serum adropin levels were significantly negatively correlated with TG, FBG, HbA1c and HOMA-IR (TG: r = − 0.271; P <  0.05; FBG: r = − 0.750, P <  0.01; HbA1c: r = − 0.770, P <  0.01; HOMA-IR: r = − 0.441, P <  0.01). Serum adropin levels were significantly positively correlated with HDL-C and HOMA-β (HDL-C: r = 0.280, P <  0.05; HOMA-β: r = 0.596, P <  0.01) (Table 2).

Table 2 Simple correlation analyses of serum adropin levels associated with other biochemical parameters in baseline

Effect of sitagliptin monotherapy on serum adropin levels and other metabolic parameters in T2D group

Changes in clinical parameters after sitagliptin treatment in the T2D group are summarized in Table 3. BMI, FBG, HbA1c and HOMA-IR after sitagliptin treatment were significantly decreased compared with the baseline (all P <  0.01). Moreover, HOMA-β was significantly increased after sitagliptin treatment (P <  0.01). But no obvious changes in lipid profiles (TC, LDL-C, HDL-C and TG) and FINS were observed (all P > 0.05). Importantly, the increases in serum adropin levels were observed after sitagliptin treatment compared to baseline (4.97 ± 1.01 vs. 3.12 ± 0.73 ng/ml, P <  0.01).

Table 3 Pre-treatment and post-treatment clinical characteristics of T2D participants treated with sitagliptin

Association between serum adropin levels and metabolic parameters after sitagliptin treatment

Longitudinal analyses over the study period using linear mixed-effects models were displayed in Figs. 1 and 2. In multivariable models adjusted for sex, age, BMI and lipid profiles (TC, HDL-C, LDL-C and TG), higher serum adropin levels were associated with lower FBG (β = − 0.71, P <  0.01, Fig. 1A), lower HbA1c (β = − 0.44, P <  0.01, Fig. 1B), and higher HOMA-β (β = 9.02, P <  0.01, Fig. 1D). The associations between HOMA-IR (β = − 0.35, P > 0.05, Fig. 1C), FINS (β = − 0.06, P > 0.05, Fig. 1E) and serum adropin levels were not statistically significant. Using other regression models adjusted for sex, age, BMI, FBG, HbA1c and FINS, lipid profiles were not significantly associated with serum adropin levels (all P > 0.05, Fig. 2A-D).

Fig. 1
figure 1

Forest plots demonstrating associations between adropin and FBG (A), HbA1c (B), HOMA-IR (C), HOMA-β (D) and FINS (E) in mixed-effect linear models adjusted for potential confounders. Abbreviations: FBG: fasting blood glucose; HbA1c: glycosylated hemoglobin; HOMA-IR: homeostasis model assessment of insulin resistance; HOMA-β: homeostasis model assessment of β-cell function; FINS: fasting insulin; BMI: body mass index; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; TG: triglyceride

Fig. 2
figure 2

Forest plots demonstrating associations between adropin and TC (A), HDL-C (B), LDL-C (C) and TG (D) in mixed-effect linear models adjusted for potential confounders. Abbreviations: TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; TG: triglyceride; BMI: body mass index; FBG: fasting blood glucose; HbA1c: glycosylated hemoglobin; FINS: fasting insulin

Discussion

The present study showed that serum adropin levels were lower in participants with newly diagnosed T2D than in the healthy controls. At baseline, serum adropin levels were negatively correlated with TG, FBG, HbA1c and HOMA-IR while positively correlated with HDL-C and HOMA-β. Importantly, sitagliptin treatment could significantly increase serum adropin levels with the improvement of metabolic parameters. Furthermore, the associations of adropin with FBG, HbA1c and HOMA-β still existed after sitagliptin treatment.

Adropin is a regulatory hormone produced mainly in the liver and brain, which is involved in glucolipid metabolism and insulin sensitivity [2, 3]. Our study showed that the T2D participants had significantly lower adropin levels. Meanwhile, serum adropin levels were negatively correlated with TG, FBG, HbA1c and HOMA-IR while positively correlated with HDL-C and HOMA-β. These results were similar with other studies [8, 19]. In animal studies, adropin overexpression or adropin treatment significantly ameliorated insulin resistance, enhanced glucose tolerance and improved glycolipid metabolism in diet-induced obese mice with insulin resistance [3, 4, 20]. In streptozotocin (STZ)-induced diabetic rats, adropin administration could improve glycemic levels, body weight, insulin levels, hepatic glycogen and carbohydrate enzymes in a dose-dependent manner, which were almost close to those of the normal control [21]. Mechanistically, several studies have found that adropin can exert beneficial metabolic effects through different mechanisms. Firstly, it was reported that adropin had a direct role in the regulation of glucose metabolism. Adropin enhanced glucose uptake via increased translocation of peroxisome proliferator-activated receptor γ (PPARγ) and glucose transpoter-4 (GLUT-4) to the plasma membrane. Secondly, adropin exerted antidiabetic effect through the AMPK pathway, which was mainly reflected in the elevations of AMPK levels and acetyl CoA carboxylase (ACC) phosphorylation in diabetic rat liver [21]. Furthermore, adropin enhanced hepatic intracellular signaling actions that were involved in insulin-mediated glucose homeostasis. Adropin inhibited cAMP-PKA signaling pathway, leading to reduce the inositol triphosphate receptor (IP3R) phosphorylation and suppress the expression of cAMP-responsive element-binding protein (CREB) and CREB-regulated transcription co-activator 2 (CRTC2), which are two key factors in hepatic glucose metabolism [3, 4, 20]. Additionally, adropin reduced the expression of genes involved in lipogenesis such as stearoyl-CoA desaturase-1 (SCD-1) and fatty acid synthase (Fas) in both liver and adipose tissue [1]. Therefore, these findings indicated that decreased adropin was closely related to the occurrence and development of T2D.

Consistent with previous studies [22,23,24], FBG and HbA1c significantly decreased, and lipid metabolism was not appreciably altered in T2D participants following sitagliptin treatment. However, sitagliptin treatment exhibited a greater reduction of BMI and HbA1c, and could improve indices of insulin resistance or sensitivity in our study, which are inconsistent with several previous studies [25,26,27,28]. Several possible reasons that could explain these inconsistences. In the first place, sitagliptin was employed as the initial therapy, meanwhile, lifestyle modifications were used as an add-on treatment. As a result, the above-mentioned effects might be overlapped by the combination of both. These findings are similar to those of previous studies [29, 30]. In the second place, Chinese adults with T2D have higher postprandial plasma glucose levels compared with Western participants [31]. Sitagliptin stimulates glucose-dependent insulin secretion and inhibits postprandial glucagon effectively, thus significantly lowering the postprandial glucose levels [32]. Moreover, sitagliptin has been shown various glucose-lowering efficacies but these different effects varied from ethnic differences. A meta-analysis demonstrated that sitagliptin could increase insulin sensitivity among in Asian T2D patients than in Caucasian T2D patients [33]. These results are supported by animal studies showing that DPP-4 inhibitors can improve insulin resistance and increase insulin sensitivity [34,35,36,37].

Sitagliptin treatment significantly increased serum adropin levels, which were associated with the improvements in FBG, HbA1c and HOMA-β. In animal studies, adropin overexpression significantly reduced insulin resistance and improved glucose tolerance in obese high-fat-fed mice [1]. Besides, adropin treatment reduced blood glucose levels, HbA1c and HOMA-IR and increased HOMA-β in a rat model of T2D [20]. However, the exact mechanism by which sitagliptin increases serum adropin levels remains unclear. We found that sitagliptin and adropin had similar effects on the regulation of glucose metabolism in previous studies. DPP-4 inhibitor could suppress gluconeogenic gene expression through the inhibition of CREB phosphorylation and CRTC2 expression in mice with diabetes [4, 37]. Based on these previous findings, we believe that the upregulation of adropin might be a potential novel mechanism for beneficial effects of sitagliptin in T2D.

But several limitations in the present study should be noted. First, our study was not a randomized controlled trial, the causality between adropin and sitagliptin cannot infer. Well-designed randomized controlled trials are needed to further confirm the beneficial effects we reported. Second, our findings are limited by a relatively small sample size, so we need to expand the sample size to support. Lastly, more animal and cell experiments are needed to reveal the underlying molecular mechanism of sitagliptin on adropin.

Conclusion

In conclusion, our study demonstrated that serum adropin levels were lower in newly diagnosed T2D participants than in healthy controls. Sitagliptin treatment could significantly increase serum adropin levels in participants with newly diagnosed T2D. The increase in serum adropin levels could be associated with the amelioration of glucose metabolism, which might be involved in underlying anti-diabetic mechanism of sitagliptin.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

T2D:

Type 2 diabetes

FBG:

fasting blood glucose

HbA1c:

glycosylated hemoglobin

HOMA-β:

homeostasis model assessment of β-cell function

Enho:

Energy Homeostasis Associated

NAFLD:

nonalcoholic fatty liver disease

PCOS:

polycystic ovary syndrome

DPP-4:

dipeptidyl peptidase-4

FDA:

Food and Drug Administration

OGTT:

oral glucose tolerance test

ADA:

American Diabetes Association

BMI:

body mass index

FINS:

fasting insulin

TC:

total cholesterol

LDL-C:

low-density lipoprotein cholesterol

HDL-C:

high-density lipoprotein cholesterol

TG:

triglyceride

HOMA-IR:

homeostasis model assessment of insulin resistance

ELISA:

enzyme-linked immunosorbent assay

SD:

standard deviation

STZ:

streptozotocin

PPARγ:

peroxisome proliferator-activated receptor γ

GLUT-4:

glucose transpoter-4

ACC:

acetyl CoA carboxylase

IP3R:

inositol triphosphate receptor

CREB:

cAMP-responsive element-binding protein

CRTC 2:

CREB-regulated transcription co-activator 2

SCD-1:

stearoyl-CoA desaturase-1

Fas:

fatty acid synthase

GLP-1 RA:

GLP-1 receptor agonist

References

  1. Kumar KG, Trevaskis JL, Lam DD, Sutton GM, Koza RA, Chouljenko VN, et al. Identification of adropin as a secreted factor linking dietary macronutrient intake with energy homeostasis and lipid metabolism. Cell Metab. 2008;8(6):468–81.

    Article  CAS  Google Scholar 

  2. Ganesh Kumar K, Zhang J, Gao S, Rossi J, McGuinness OP, Halem HH, et al. Adropin deficiency is associated with increased adiposity and insulin resistance. Obesity (Silver Spring). 2012;20(7):1394–402.

    Article  CAS  Google Scholar 

  3. Gao S, McMillan RP, Zhu Q, Lopaschuk GD, Hulver MW, Butler AA. Therapeutic effects of adropin on glucose tolerance and substrate utilization in diet-induced obese mice with insulin resistance. Mol Metab. 2015;4(4):310–24.

    Article  CAS  Google Scholar 

  4. Gao S, Ghoshal S, Zhang L, Stevens JR, McCommis KS, Finck BN, et al. The peptide hormone adropin regulates signal transduction pathways controlling hepatic glucose metabolism in a mouse model of diet-induced obesity. J Biol Chem. 2019;294(36):13366–77.

    Article  CAS  Google Scholar 

  5. Sayin O, Tokgoz Y, Arslan N. Investigation of adropin and leptin levels in pediatric obesity-related nonalcoholic fatty liver disease. J Pediatr Endocrinol Metab. 2014;27(5–6):479–84.

    CAS  Google Scholar 

  6. Kume T, Calan M, Yilmaz O, Kocabas GU, Yesil P, Temur M, et al. A possible connection between tumor necrosis factor alpha and adropin levels in polycystic ovary syndrome. J Endocrinol Investig. 2016;39(7):747–54.

    Article  CAS  Google Scholar 

  7. Yosaee S, Khodadost M, Esteghamati A, Speakman JR, Shidfar F, Nazari MN, et al. Metabolic syndrome patients have lower levels of Adropin when compared with healthy overweight/obese and lean subjects. Am J Mens Health. 2017;11(2):426–34.

    Article  Google Scholar 

  8. Zang H, Jiang F, Cheng X, Xu H, Hu X. Serum adropin levels are decreased in Chinese type 2 diabetic patients and negatively correlated with body mass index. Endocr J. 2018;65(7):685–91.

    Article  CAS  Google Scholar 

  9. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2018;14(2):88–98.

    Article  Google Scholar 

  10. Drucker D, Easley C, Kirkpatrick P. Sitagliptin. Nat Rev Drug Discov. 2007;6(2):109–10.

    Article  CAS  Google Scholar 

  11. Plosker GL. Sitagliptin: a review of its use in patients with type 2 diabetes mellitus. Drugs. 2014;74(2):223–42.

    Article  CAS  Google Scholar 

  12. Zillessen P, Celner J, Kretschmann A, Pfeifer A, Racke K, Mayer P. Metabolic role of dipeptidyl peptidase 4 (DPP4) in primary human (pre)adipocytes. Sci Rep. 2016;6:23074.

    Article  CAS  Google Scholar 

  13. Baumeier C, Saussenthaler S, Kammel A, Jahnert M, Schluter L, Hesse D, et al. Hepatic DPP4 DNA methylation associates with fatty liver. Diabetes. 2017;66(1):25–35.

    Article  CAS  Google Scholar 

  14. Mi DH, Fang HJ, Zheng GH, Liang XH, Ding YR, Liu X, et al. DPP-4 inhibitors promote proliferation and migration of rat brain microvascular endothelial cells under hypoxic/high-glucose conditions, potentially through the SIRT1/HIF-1/VEGF pathway. CNS Neurosci Ther. 2019;25(3):323–32.

    Article  CAS  Google Scholar 

  15. Wang Q, Ma L, Zhang Y, Zhang L, An Y, Liu J, et al. Effect of Sitagliptin on serum Irisin levels in patients with newly diagnosed type 2 Diabetes mellitus. Diabetes Ther. 2021;12(4):1029–39.

    Article  CAS  Google Scholar 

  16. American Diabetes A. Standards of medical care in diabetes--2014. Diabetes Care. 2014;37(Suppl 1):S14–80.

    Article  Google Scholar 

  17. Katsuki A, Sumida Y, Gabazza EC, Murashima S, Furuta M, Araki-Sasaki R, et al. Homeostasis model assessment is a reliable indicator of insulin resistance during follow-up of patients with type 2 diabetes. Diabetes Care. 2001;24(2):362–5.

    Article  CAS  Google Scholar 

  18. Bermudez V, Cano R, Cano C, Bermudez F, Leal E, Acosta K, et al. Homeostasis model assessment (HOMA) as surrogate insulinization criteria in patients with type 2 diabetes. Am J Ther. 2008;15(4):409–16.

    Article  Google Scholar 

  19. Wu L, Fang J, Chen L, Zhao Z, Luo Y, Lin C, et al. Low serum adropin is associated with coronary atherosclerosis in type 2 diabetic and non-diabetic patients. Clin Chem Lab Med. 2014;52(5):751–8.

    Article  CAS  Google Scholar 

  20. Akcilar R, Kocak FE, Simsek H, Akcilar A, Bayat Z, Ece E, et al. Antidiabetic and hypolipidemic effects of adropinin streoptozotocin-induced type 2 diabetic rats. Bratisl Lek Listy. 2016;117(2):100–5.

    CAS  Google Scholar 

  21. He L, Zhang FJ, Li HY, Li L, Song LG, Mao Y, et al. Anti-diabetic role of Adropin in Streptozotocin induced diabetic rats via alteration of PI3K/Akt and insulin signaling pathway. J Oleo Sci. 2021;70(5):657–64.

    Article  CAS  Google Scholar 

  22. Rosenstock J, Brazg R, Andryuk PJ, Lu K, Stein P, Sitagliptin Study G. Efficacy and safety of the dipeptidyl peptidase-4 inhibitor sitagliptin added to ongoing pioglitazone therapy in patients with type 2 diabetes: a 24-week, multicenter, randomized, double-blind, placebo-controlled, parallel-group study. Clin Ther. 2006;28(10):1556–68.

    Article  CAS  Google Scholar 

  23. Aschner P, Katzeff HL, Guo H, Sunga S, Williams-Herman D, Kaufman KD, et al. Efficacy and safety of monotherapy of sitagliptin compared with metformin in patients with type 2 diabetes. Diabetes Obes Metab. 2010;12(3):252–61.

    Article  CAS  Google Scholar 

  24. Iwamoto Y, Tajima N, Kadowaki T, Nonaka K, Taniguchi T, Nishii M, et al. Efficacy and safety of sitagliptin monotherapy compared with voglibose in Japanese patients with type 2 diabetes: a randomized, double-blind trial. Diabetes Obes Metab. 2010;12(7):613–22.

    Article  CAS  Google Scholar 

  25. Nonaka K, Kakikawa T, Sato A, Okuyama K, Fujimoto G, Kato N, et al. Efficacy and safety of sitagliptin monotherapy in Japanese patients with type 2 diabetes. Diabetes Res Clin Pract. 2008;79(2):291–8.

    Article  CAS  Google Scholar 

  26. Ahren B. Use of DPP-4 inhibitors in type 2 diabetes: focus on sitagliptin. Diabetes Metab Syndr Obes. 2010;3:31–41.

    Article  CAS  Google Scholar 

  27. Kobayashi K, Yokoh H, Sato Y, Takemoto M, Uchida D, Kanatsuka A, et al. Efficacy and safety of the dipeptidyl peptidase-4 inhibitor sitagliptin compared with alpha-glucosidase inhibitor in Japanese patients with type 2 diabetes inadequately controlled on sulfonylurea alone (SUCCESS-2): a multicenter, randomized, open-label, non-inferiority trial. Diabetes Obes Metab. 2014;16(8):761–5.

    Article  CAS  Google Scholar 

  28. Kutoh E, Kuto AN, Wada A, Hayashi J, Kurihara R. Sitagliptin as an initial therapy and differential regulations of metabolic parameters depending on its glycemic response in subjects with type 2 Diabetes. Drug Res (Stuttg). 2021;71(3):157–65.

    Article  CAS  Google Scholar 

  29. Du Q, Wu B, Wang YJ, Yang S, Zhao YY, Liang YY. Comparative effects of sitagliptin and metformin in patients with type 2 diabetes mellitus: a meta-analysis. Curr Med Res Opin. 2013;29(11):1487–94.

    Article  CAS  Google Scholar 

  30. Le TD, Nguyen NTP, Nguyen ST, Tran HTT, Nguyen LTH, Duong HH, et al. Sitagliptin increases Beta-cell function and decreases insulin resistance in newly diagnosed Vietnamese patients with type 2 Diabetes mellitus. Diabetes Metab Syndr Obes. 2020;13:2119–27.

    Article  CAS  Google Scholar 

  31. Herman WH, Dungan KM, Wolffenbuttel BH, Buse JB, Fahrbach JL, Jiang H, et al. Racial and ethnic differences in mean plasma glucose, hemoglobin A1c, and 1,5-anhydroglucitol in over 2000 patients with type 2 diabetes. J Clin Endocrinol Metab. 2009;94(5):1689–94.

    Article  CAS  Google Scholar 

  32. Deacon CF. Physiology and pharmacology of DPP-4 in glucose homeostasis and the treatment of type 2 Diabetes. Front Endocrinol (Lausanne). 2019;10:80.

    Article  Google Scholar 

  33. Cai X, Han X, Luo Y, Ji L. Efficacy of dipeptidyl-peptidase-4 inhibitors and impact on beta-cell function in Asian and Caucasian type 2 diabetes mellitus patients: a meta-analysis. J Diabetes. 2015;7(3):347–59.

    Article  CAS  Google Scholar 

  34. Kulkarni RN, Bruning JC, Winnay JN, Postic C, Magnuson MA, Kahn CR. Tissue-specific knockout of the insulin receptor in pancreatic beta cells creates an insulin secretory defect similar to that in type 2 diabetes. Cell. 1999;96(3):329–39.

    Article  CAS  Google Scholar 

  35. Shirakawa J, Amo K, Ohminami H, Orime K, Togashi Y, Ito Y, et al. Protective effects of dipeptidyl peptidase-4 (DPP-4) inhibitor against increased beta cell apoptosis induced by dietary sucrose and linoleic acid in mice with diabetes. J Biol Chem. 2011;286(29):25467–76.

    Article  Google Scholar 

  36. Shirakawa J, Fujii H, Ohnuma K, Sato K, Ito Y, Kaji M, et al. Diet-induced adipose tissue inflammation and liver steatosis are prevented by DPP-4 inhibition in diabetic mice. Diabetes. 2011;60(4):1246–57.

    Article  CAS  Google Scholar 

  37. Kim TH, Kim MK, Cheong YH, Chae YN, Lee Y, Ka SO, et al. Hepatic role in an early glucose-lowering effect by a novel dipeptidyl peptidase 4 inhibitor, evogliptin, in a rodent model of type 2 diabetes. Eur J Pharmacol. 2016;771:65–76.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was financially supported by the Chinese National Natural Science Foundation [No. 81770792] and Key Projects of Science and Technology Planning of Beijing Municipal Education Commission [KZ201810025038] to G.W. and the Beijing Talents foundation [2018–12] to J.L.

Author information

Authors and Affiliations

Authors

Contributions

J.L. and G.W. conceived and designed the study, Q.W. conducted the experiments, performed the analyses and wrote the manuscript. Y.A., L.Z. and Y.Z. helped collect and analyze the data. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Guang Wang or Jia Liu.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Beijing Chao-yang Hospital affiliated with Capital Medical University (2020-#-182) and was registered at Clinicaltrials.gov (NCT number: NCT04495881). The protocol was implemented in accordance with provisions of the Declaration of Helsinki. All enrolled participants provided written informed consent in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Q., An, Y., Zhang, L. et al. Regulation of Adropin by Sitagliptin monotherapy in participants with newly diagnosed type 2 Diabetes. BMC Endocr Disord 22, 306 (2022). https://doi.org/10.1186/s12902-022-01233-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12902-022-01233-x

Keywords