Serum sirtuin 1 protein as a potential biomarker for type 2 diabetes: Increased expression of sirtuin 1 and the correlation with microRNAs
Ozlem Gok1, Zeynep Karaali2, Arzu Ergen3, Sema Sirma Ekmekci1, Neslihan Abaci1
1 Department of Genetics, Aziz Sancar Institute of Experimental Medicine (Aziz Sancar DETAE), Istanbul University, Istanbul, Turkey 2 Department of Internal Medicine, Haseki Training and Research Hospital, Istanbul, Turkey 3 Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine (Aziz Sancar DETAE), Istanbul University, Istanbul, Turkey
Date of Submission | 29-Nov-2018 |
Date of Decision | 22-Jan-2019 |
Date of Acceptance | 26-Mar-2019 |
Date of Web Publication | 25-Jun-2019 |
Correspondence Address: Dr. Neslihan Abaci Department of Genetics, Aziz Sancar Institute of Experimental Medicine (Aziz Sancar DETAE), Istanbul University, Vakif Gureba Caddesi, 34093, Sehremini, Istanbul Turkey
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jrms.JRMS_921_18
Background: Type 2 diabetes (T2DM) is characterized by hyperglycemia and insulin deficiency. Sirtuin 1 (SIRT1), serving as a deacetylase, is critical in the regulation of glucose and lipid metabolism. Recently, a number of studies have been conducted to investigate the role of SIRT1 in the pathogenesis of T2DM. However, there are no sufficient data about the relationship between SIRT1 and T2DM. The aim of this study was to analyze the expressions of microRNAs (miRNAs) (miR-34a, miR-9, miR-132, and miR-181a) involved in SIRT1 regulation and SIRT1 protein in the serum of T2DM patients and controls. Materials and Methods: miRNA expressions were determined by real-time polymerase chain reaction, and enzyme-linked immunosorbent assay was used to measure the SIRT1 protein levels in 25 T2DM patients and 25 controls. Results: Fasting blood glucose and glycated hemoglobin levels were significantly higher in patients when compared with controls (P < 0.001). There was no difference for miRNA expressions between the groups (P > 0.05). SIRT1 protein level was significantly increased in patients as compared to controls (P = 0.044). Moreover, SIRT1 was negatively correlated with miR-181a (r = −0.558,P = 0.005) and miR-132 (r = −0.435,P = 0.034) in patients. Conclusion: Obtained results indicate that serum SIRT1 may be a potentially new biomarker for T2DM and also miR-181a and miR-132 may be involved in the development of T2DM by targeting SIRT1. This is the first study reporting on the effects of SIRT1 and related miRNAs in Turkish T2DM patients.
Keywords: Diabetes mellitus, microRNA, serum, sirtuin 1
How to cite this article: Gok O, Karaali Z, Ergen A, Ekmekci SS, Abaci N. Serum sirtuin 1 protein as a potential biomarker for type 2 diabetes: Increased expression of sirtuin 1 and the correlation with microRNAs. J Res Med Sci 2019;24:56 |
How to cite this URL: Gok O, Karaali Z, Ergen A, Ekmekci SS, Abaci N. Serum sirtuin 1 protein as a potential biomarker for type 2 diabetes: Increased expression of sirtuin 1 and the correlation with microRNAs. J Res Med Sci [serial online] 2019 [cited 2023 Jun 10];24:56. Available from: https://www.jmsjournal.net/text.asp?2019/24/1/56/261208 |
Introduction | |  |
Diabetes is a progressive metabolic disease caused by the combination of genetic and environmental factors and characterized by hyperglycemia and poses a major threat to human health. According to the World Health Organization, there are over 400 million people worldwide suffering from diabetes and it is estimated that this figure will reach 552 million by 2030.[1],[2]
Diabetes can be classified into several categories, but the vast majority of cases of diabetes constitute type 1 diabetes and type 2 diabetes (T2DM).[3] T2DM seen in >90% of patients is characterized by insulin resistance and impaired insulin secretion, leading to macrovascular and microvascular complications.[4],[5] Defects in pancreatic β-cells and insulin resistance are the most important features involved in the pathogenesis of T2DM. Depending on the cell-receptor defect, glucose cannot enter into the cell. In particular, the effect of insulin on muscle and adipose tissue is insufficient. The pancreas cannot secrete enough insulin, and hence, glucose production in the liver increases. Furthermore, when insulin-producing β-cells cannot compensate for increased insulin resistance, glucose homeostasis is disturbed, and consequently, T2DM develops.[4],[6],[7]
Sirtuin (SIRT) genes have 7 variants (SIRT1–SIRT7) in mammals, and SIRT1 has the most stable deacetylase activity among these genes.[8],[9] SIRT1, which acts as a Class I histone deacetylase and helps to maintain the balance between acetylation and deacetylation in posttranslational modifications, plays an important role in the regulation of glucose and lipid metabolism. SIRT1 enhances β-cell protection and insulin secretion in the pancreas, gluconeogenesis and fatty acid oxidation in the liver, lipid mobilization in the adipose tissue, and mitochondrial biogenesis and glucose uptake in the skeletal muscle. In addition, it regulates biogenesis and fatty acid oxidation while reducing the production of reactive oxygen species in mitochondria.[6],[10],[11],[12]
It has recently been shown that microRNAs (miRNAs) can be secreted by cells and can be detectable in serum and other biological fluids. A number of studies have been conducted on whole blood, serum, plasma, urine, peripheral blood mononuclear cells, and endothelial progenitor cells to identify T2DM-related miRNAs.[13],[14] However, knowledge on how T2DM and SIRT1 expression is regulated is insufficient and it has not been fully understood yet.
In this study, we aimed to investigate the expressions of miRNAs (miR-34a, miR-9, miR-132, and miR-181a) involved in SIRT1 protein regulation and SIRT1 protein level in Turkish T2DM patient and control groups.
Materials and Methods | |  |
Study population
The study groups consisted of 25 T2DM patients (21 females and 4 males and mean age: 51.16 ± 6.82) and 25 controls (12 females and 13 males and mean age: 48.52 ± 9.67). The individuals were examined in (or treated in) the Haseki Training and Research Hospital, Department of Internal Medicine.
After overnight fasting, blood samples of the participants were drawn in plain tubes. The samples were centrifuged for 5 min at 4.500 rpm at +4°C, followed by the removal of serum, and then, serum was stored at −20°C for real-time polymerase chain reaction (real-time PCR) and enzyme-linked immunosorbent assay (ELISA). The following biochemical parameters were determined in both case and control groups by standard laboratory methods in the Haseki Training and Research Hospital: fasting blood glucose (FBG), glycated hemoglobin (HbA1c), total cholesterol, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol, triglyceride, urea, creatinine, total protein, albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), folate, Vitamin B12, 25-hydroxyvitamin D, white blood cell (WBC), red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), platelet (PLT), uric acid, sediment 1 h, sodium, potassium, calcium, glomerular filtration rate (eGFR), and C-reactive protein (CRP). Body mass index (BMI) values were calculated by dividing weight by height square (kg/m2) and categorized well according to the World Health Organization recommendations.
Determination of microRNA expressions
Total RNA was extracted from 200 μL of serum using miRNeasy serum/plasma kit (catalog no: 217184, Qiagen, USA) according to the manufacturer's protocol. The final elution volume was 14 μL. The concentration of all RNA samples was quantified by NanoDrop 2000 spectrophotometer (Thermo Scientific, USA), and 4 ng of serum RNA containing miRNA was reverse transcribed to cDNA using TaqMan MicroRNA Reverse Transcription Kit (catalog no: 4366596, Thermo Fisher, USA). Then, real-time PCR was performed using TaqMan MicroRNA Assays (catalog no: 4427975, Thermo Fisher, USA) in LightCycler 480 II (Roche, USA). Each sample was run in duplicate for analysis.
As the internal control gene, noncoding small RNA RNU6B (U6) was used, and expression levels of miR-34a, miR-9, miR-132, and miR-181a were calculated using the computed tomography (cycle threshold) method.
Measurement of sirtuin 1 protein levels
Serum samples of individuals were analyzed for the levels of SIRT1 protein using ELISA kit (catalog no: E2557Hu, BT Labs, China) according to the manufacturer's protocol. Briefly, standards and serum samples were added into a 96-well plate. After adding biotin-conjugated anti-SIRT1 antibody and streptavidin-horseradish peroxidase, the plate was incubated for 60 min at 37°C. The wells were then washed five times with wash buffer. Substrate solutions A and B were added, and the plate was incubated for 10 min at 37°C for color development. Finally, the reaction was stopped by the stop solution. The intensity of color in each well was measured in a microplate reader (Multiskan Spectrum, Thermo Electron Corporation) at 450 nm.
Statistical analysis
Statistical analyses were conducted using a standard software package (SPSS 18 for Windows; SPSS Inc., Chicago, IL, USA). Differences in demographic and clinical characteristics were analyzed using Chi-square, Fisher's exact, and Student's t-tests. miRNA expression levels and SIRT1 protein levels were compared by Student's t-test. Pearson's correlation was used for correlation between SIRT1 and other parameters in groups, and Mann–Whitney test was used for analysis of risk factors. Student's t-test was also used for comparative analyzes in the control group. Fisher's exact test was used if the number in any cell of the 2 × 2 contingency table was <5. P < 0.05 was regarded as being statistically significant.
Results | |  |
Clinical and biochemical characteristics of type 2 diabetes patients and controls
Clinical and biochemical characteristics of study groups were presented in [Table 1]. The patients and controls had similar distributions of age. There was no significant difference in age, BMI, total cholesterol, LDL cholesterol, HDL cholesterol, total cholesterol/HDL cholesterol, triglyceride, urea, total protein, AST, ALT, ALP, folate, Vitamin B12, 25-hydroxyvitamin D, RBC, HGB, HCT, PLT, uric acid, sediment 1 h, sodium, potassium, calcium, and eGFR levels (P > 0.05). However, FBG (P < 0.001), HbA1c (P < 0.001), GGT (P = 0.020), WBC (P = 0.002), and CRP (P = 0.002) levels were significantly increased in patients with T2DM compared to controls. Creatinine (P = 0.004) and sodium (P = 0.006) levels were significantly lower in the patient group, as well. When the study groups were evaluated for smoking (P = 0.012), hypertension (P < 0.001), and family history (P = 0.050), statistical significance was found in the patient group.
MicroRNA expressions and sirtuin 1 protein levels
There was no statistically significant difference when miR-181a, miR-132, miR-9, and miR-34a expression levels were evaluated between the patient and control groups (P > 0.05) [Figure 1]. On the other hand, SIRT1 protein level significantly increased in patients as compared to controls (P = 0.044) [Figure 2]. | Figure 1: Relative expression of microRNAs in patient and control groups. Statistical evaluation by Student's t-test. The results are shown as mean ± standard error of mean in log2 scale. miR-181a (P = 0.249), miR-132 (P = 0.523), miR-34a (P = 0.976), and miR-9 (P = 0.813)
Click here to view |
 | Figure 2: Sirtuin 1 protein levels in patient and control groups. Statistical evaluation by Student's t-test. The results are shown as mean ± standard error of mean. *Significant difference between patients and controls (P = 0.044)
Click here to view |
Correlation analysis
Pearson's correlation analysis between serum SIRT1 and other factors is summarized in [Table 2]. Serum SIRT1 was negatively correlated with miR-181a (r = −0.558, P = 0.005) and miR-132 (r = −0.435, P = 0.034) in patients and FBG (r = −0.414, P = 0.040) in controls as well. However, there was no significant correlation between SIRT1 and other parameters (P > 0.05). | Table 2: Results of Pearson's correlation between expression level of sirtuin 1 and other parameters
Click here to view |
Pearson's correlation test showed that there was a significant positive correlation between miR-181a with miR-132 (r = 0.826, P < 0.001), miR-9 (r = 0.434, P = 0.030), miR-34a (r = 0.603, P = 0.001), and triglyceride (r = 0.494, P = 0.012) and also miR-132 with miR-9 (r = 0.412, P = 0.041), miR-34a (r = 0.792, P < 0.001), and HbA1c (r = 0.443, P = 0.027) in patients. There was a negative correlation between miR-181a with creatinine (r = −0.489, P = 0.013) and a positive correlation between miR-132 with miR-34a (r = 0.688, P < 0.001) and miR-181a (r = 0.565, P = 0.003) in control group. In addition, it was found that miR-34a was positively correlated with AST (r = 0.631, P = 0.001), ALT (r = 0.698, P < 0.001), and GGT (r = 0.605, P = 0.013) in patients and also AST (r = 0.550, P = 0.004) and ALT (r = 0.434, P = 0.030) in controls.
Discussion | |  |
In recent years, T2DM and understanding its molecular mechanisms have gained great importance worldwide. The circulating miRNAs and related proteins have strong potential as novel biomarkers for early diagnosis and pathogenesis of various metabolic diseases such as T2DM. In literature, some miRNAs have been reported to be abundant and stable in serum and also potentially disease specific by targeting SIRT1. However, there are limited data worldwide and no such study in Turkey related to the effects of SIRT1 and miRNAs involved in SIRT1 regulation in T2DM. Therefore, in the present study, we performed our experiments on SIRT1 protein and related miRNAs.
Recently, a number of studies have been carried out on the potential use of serum SIRT1 and related miRNAs as biomarkers for elucidating the molecular mechanism of T2DM. In a previous study, researchers determined that 7 miRNAs including miR-9, miR-29a, miR-30d, miR34a, miR-124a, miR146a, and miR375 (P < 0.05) were significantly upregulated in T2DM patients compared to normal glucose levels individuals.[15] In another previous study, Liu et al. showed that expression levels of miR-34a (P < 0.05) and miR-34c (P < 0.01) were significantly higher in the T2DM group. Thus, these miRNAs had a potency to be used as biomarkers for T2DM diagnosis.[16] Zhou et al. observed that the level of serum miR-181a was significantly increased in patients (P < 0.01). They reported that miR-181a regulated SIRT1 and improved hepatic insulin sensitivity. Therefore, that miR-181a inhibition may be a potential new strategy for insulin resistance and T2DM treatment.[17] However, in the current study, no statistically significant difference was found for expression levels of miR-181a, miR-132, miR-9, and miR-34a between the groups (P > 0.05).
According to a study performed by Shao et al., SIRT1 levels were significantly decreased (P < 0.01) and miR-217 levels were significantly increased in the serum of T2DM patients (P < 0.01). miR-217 was negatively correlated with SIRT1 (P = 0.002). Moreover, there was a significant association between Ln (albumin/creatinine ratio) with SIRT1 and miR-217 (P < 0.05).[18] In another study by Fathy et al., serum SIRT1 levels were significantly lower in the normoalbuminuric group (P < 0.05). SIRT1 demonstrated a positive correlation with FBG in normoalbuminuric patients (P < 0.05) and also a negative correlation with microalbumin in macroalbuminuric patients (P < 0.05).[19] Collectively, these investigations suggest that serum miR-217 may be involved in the development of diabetic kidney disease by promoting chronic inflammation, renal fibrosis, and angiogenesis, and serum SIRT1 might be associated with minimal renal insufficiency in patients with type 2 diabetic nephropathy. However, these results are in controversy with our results in that SIRT1 protein level was significantly increased in patients with T2DM compared to controls (P = 0.044). Furthermore, we determined a negative correlation between SIRT1 protein with miR-181a (P = 0.005) and miR-132 (P = 0.034) in the patient group. This may be due to differences in the development of T2DM among populations and epigenetic regulation.
Conclusions | |  |
Our findings suggest that the increase in the SIRT1 protein expression in patients with T2DM may be considered as a compensatory mechanism in the body. miR-181a and miR-132 may be involved in the development of T2DM by targeting SIRT1. Therefore, SIRT1 has the potential to be a new noninvasive biomarker for T2DM. This is the first study to investigate the effects of SIRT1 and miRNAs involved in SIRT1 regulation in Turkish T2DM patients. Further research is needed to better understand the association between SIRT1 and T2DM in large cases.
Acknowledgments
We would like to thank the people who participated in this study, the reviewers for their comments, and the editors for their kind work on this paper. This study was supported by the Scientific Research Projects Coordination Unit of Istanbul University (Research project number: 23646), and Istanbul University Ethical Board approval was taken. All participants, after giving written informed consent, completed a structured questionnaire to collect their demographic data.
Financial support and sponsorship
This study was funded by a grant from Istanbul University.
Conflicts of interest
There are no conflicts of interest.
References | |  |
1. | Olokoba AB, Obateru OA, Olokoba LB. Type 2 diabetes mellitus: A review of current trends. Oman Med J 2012;27:269-73. |
2. | Jin W, Patti ME. Genetic determinants and molecular pathways in the pathogenesis of type 2 diabetes. Clin Sci (Lond) 2009;116:99-111. |
3. | American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2014;37 Suppl 1:S81-90. |
4. | Turkey Endocrinology and Metabolism Association. Diagnosis, Treatment and Follow up Guide of Diabetes Mellitus and its Complications. Turkey: Turkey Endocrinology and Metabolism Association; 2017. |
5. | Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet 2017;389:2239-51. |
6. | Kitada M, Kume S, Kanasaki K, Takeda-Watanabe A, Koya D. Sirtuins as possible drug targets in type 2 diabetes. Curr Drug Targets 2013;14:622-36. |
7. | NCD Risk Factor Collaboration. Worldwide trends in diabetes since 1980: A pooled analysis of 751 population-based studies with 4.4 million participants. Lancet 2016;387:1513-30. |
8. | Bayram A, Igci M. Sirtuin genes and functions. Firat Med J 2013;18:136-40. |
9. | Morris BJ. Seven sirtuins for seven deadly diseases of aging. Free Radic Biol Med 2013;56:133-71. |
10. | Michishita E, Park JY, Burneskis JM, Barrett JC, Horikawa I. Evolutionarily conserved and nonconserved cellular localizations and functions of human SIRT proteins. Mol Biol Cell 2005;16:4623-35. |
11. | Kitada M, Koya D. SIRT1 in type 2 diabetes: Mechanisms and therapeutic potential. Diabetes Metab J 2013;37:315-25. |
12. | Perovic A, Unic A, Dumic J. Recreational scuba diving: Negative or positive effects of oxidative and cardiovascular stress? Biochem Med (Zagreb) 2014;24:235-47. |
13. | Sebastiani G, Nigi L, Spagnuolo I, Morganti E, Fondelli C, Dotta F. MicroRNA profiling in sera of patients with type 2 diabetes mellitus reveals an upregulation of miR-31 expression in subjects with microvascular complications. J Biomed Sci Eng 2013;6:58-64. |
14. | Chien HY, Lee TP, Chen CY, Chiu YH, Lin YC, Lee LS, et al. Circulating microRNA as a diagnostic marker in populations with type 2 diabetes mellitus and diabetic complications. J Chin Med Assoc 2015;78:204-11. |
15. | Kong L, Zhu J, Han W, Jiang X, Xu M, Zhao Y, et al. Significance of serum microRNAs in pre-diabetes and newly diagnosed type 2 diabetes: A clinical study. Acta Diabetol 2011;48:61-9. |
16. | Liu H, Jin M, Tian H, Li J, Li N, Yan S. MiR-34a and miR-34c are involved in the pathogenesis of type-2 diabetes by modulating the cell cycle of pancreatic beta-cell. Int J Clin Exp Pathol 2016;9:5340-5. |
17. | Zhou B, Li C, Qi W, Zhang Y, Zhang F, Wu JX, et al. Downregulation of Mir-181a upregulates sirtuin-1 (SIRT1) and improves hepatic insulin sensitivity. Diabetologia 2012;55:2032-43. |
18. | Shao Y, Ren H, Lv C, Ma X, Wu C, Wang Q. Changes of serum Mir-217 and the correlation with the severity in type 2 diabetes patients with different stages of diabetic kidney disease. Endocrine 2017;55:130-8. |
19. | Fathy SA, Ibrahim DM, Elkhayat WA, Ahmed HS. Association between serum sirt 1 and advanced glycation end products levels in type 2 diabetic nephropathy patients. Int J Biosci 2017;10:398-404. |
[Figure 1], [Figure 2]
[Table 1], [Table 2]
This article has been cited by | 1 |
Decreased Serum Levels of SIRT1 and SIRT3 Correlate with Severity of Skin and Lung Fibrosis and Peripheral Microvasculopathy in Systemic Sclerosis |
|
| Mirko Manetti, Irene Rosa, Bianca Saveria Fioretto, Marco Matucci-Cerinic, Eloisa Romano | | Journal of Clinical Medicine. 2022; 11(5): 1362 | | [Pubmed] | [DOI] | | 2 |
Estimation of Fluoride and Sirtuin1 in Patients with Diabetic Nephropathy in Kolar District of Karnataka, India |
|
| Sai Deepika R.,KN Shashidhar,Raveesha A.,Muninarayana C. | | Journal of Laboratory Physicians. 2021; | | [Pubmed] | [DOI] | | 3 |
Sirtuin 1, Visfatin and IL-27 Serum Levels of Type 1 Diabetic Females in Relation to Cardiovascular Parameters and Autoimmune Thyroid Disease |
|
| Magdalena Lukawska-Tatarczuk,Edward Franek,Leszek Czupryniak,Ilona Joniec-Maciejak,Agnieszka Pawlak,Ewa Wojnar,Jakub Zielinski,Dagmara Mirowska-Guzel,Beata Mrozikiewicz-Rakowska | | Biomolecules. 2021; 11(8): 1110 | | [Pubmed] | [DOI] | | 4 |
MicroRNA-34a promotes apoptosis of retinal vascular endothelial cells by targeting SIRT1 in rats with diabetic retinopathy |
|
| Qingshan Ji,Jing Han,Lisong Wang,Jiajia Liu,Yiran Dong,Kai Zhu,Lei Shi | | Cell Cycle. 2020; : 1 | | [Pubmed] | [DOI] | | 5 |
Association Between SIRT1, Cytokines, and Metabolic Syndrome in Schizophrenia Patients With Olanzapine or Clozapine Monotherapy |
|
| Xinyu Fang,Lingfang Yu,Dandan Wang,Yan Chen,Yewei Wang,Zenan Wu,Ruimei Liu,Juanjuan Ren,Wei Tang,Chen Zhang | | Frontiers in Psychiatry. 2020; 11 | | [Pubmed] | [DOI] | | 6 |
Mapping Research in the Obesity, Adipose Tissue, and MicroRNA Field: A Bibliometric Analysis |
|
| João Manoel Alves,Ramon Handerson Gomes Teles,Camila do Valle Gomes Gatto,Vitor Rosetto Muñoz,Márcia Regina Cominetti,Ana Cláudia Garcia de Oliveira Duarte | | Cells. 2019; 8(12): 1581 | | [Pubmed] | [DOI] | |
|
 |
 |
|