© 2015 APMIS. Published by John Wiley & Sons Ltd. DOI 10.1111/apm.12389
APMIS
Profiling peripheral microRNAs in obesity and type 2 diabetes mellitus LIANGPING WU,1 XIAOJIANG DAI,1 JUNFANG ZHAN,2 YUXIN ZHANG,1 HONGBIN ZHANG,1 HONGBING ZHANG,1 SONGHUA ZENG1 and WENBIN XI1 1
Surgical Center of Thyroid Diabetes, General Hospital of Guangzhou Military Command of PLA, Guangzhou; and 2Health Management Center, Guangzhou First People’s Hospital, Guangzhou Medical College, Guangzhou, China
Wu L, Dai X, Zhan J, Zhang Y, Zhang H, Zhang H, Zeng S, Xi W. Profiling peripheral microRNAs in obesity and type 2 diabetes mellitus. APMIS 2015. Mechanisms of type 2 diabetes mellitus (T2DM) remain elusive, in which obesity (OB) is considered as one of the major risk factors for the disease. A microRNA (miRNA) is a small non-coding RNA molecule functioning in RNA silencing and post-transcriptional regulation of gene expression. It has been demonstrated that some miRNAs can exist in serum stably and is closely related to various diseases. The goal of our study was to identify whether the deregulation of serum miRNAs was associated with T2DM and obesity. Twenty-five subjects with T2DM2, 25 healthy controls, 25 subjects with obesity, and 25 subjects with T2DM combined with obesity were included in the study. A total of 536 miRNA serum samples from these four groups were studied by miRNA polymerase chain reaction (PCR) panels. Data showed that miR-152 and miR-17 were significantly elevated in the OB group, whereas miR-138 was significantly decreased in OB group when compared to controls, T2DM, or T2DM+obesity group. In addition, level of MiR-593 was significantly lower in T2DM group and T2DM+obesity group when compared with controls. Further analysis revealed that the four miRNAs can be used as potential biomarkers to distinguish obesity from T2DM, OB+T2DM, and healthy subjects. Our study is one of the pioneer studies showing the differences in peripheral miRNA level in obesity, T2DM and T2DM combined with obesity. The study results suggest the potential utility of miRNAs in the prediction for obesity and T2DM. Key words: MicroRNA; obesity; diabetes. Junfang Zhan, Health Management Center, Guangzhou First People’s Hospital, Guangzhou Medical College, 1 Panfu Road, Guangzhou, Guangdong 510180, China. e-mail: [email protected] Yuxin Zhang, Surgical Center of Thyroid Diabetes, General Hospital of Guangzhou Military Command of PLA, 111 Liuhua Road, Guangzhou, Guangdong 510010, China. e-mail: [email protected]
Liangping Wu and Xiaojiang Dai contributed equally to the work.
Type 2 diabetes mellitus (T2DM) is a chronic disease characterized by hyperglycemia, pancreatic beta cell insufficiency, and insulin resistance, a suboptimal tissue response to insulin that is largely driven by obesity (1). Studies have suggested that about 400 million people in the world may be affected by diabetes, in which 90% would be T2DM by 2030 (1). Obesity (OB) is known as excessive fat accumulation in the body resulted from mismatch of energy intake and expenditure. Obesity-related insulin resistance is thought to be Received 18 January 2015. Accepted 23 February 2015
the major precursor driving the development of T2DM, which targets multiple tissues including the brain, liver, skeletal muscle, pancreas, and adipose tissue. There are many contributing factors associated with either obesity or T2DM (2). However, genetics is commonly thought as the most influential factor. Therefore, the study of genetics and its relation to obesity and T2DM has important meanings, which the information we obtain through our studies can potentially be apply to disease prevention, early diagnosis and interventions (3). MicroRNAs (miRNAs) are short noncoding RNAs of ~22 nucleotides that negatively regulate 1
WU et al.
gene expression at the post-transcriptional level (4). In general, miRNAs bind to the 3’-UTR of its target mRNA via sequence-guided recognition to trigger mRNA degradation or translational repression (4). A mature miRNA forms a RNA-protein complex called RNA-induced silencing complex by forming a survivin-XIAP complex (5). More than 1000 miRNAs have been identified in the human genome. The miRNA expression can be modulated through various pathways including transcription factors and processing precursors (6). Functions of miRNA are diversified. One individual miRNA can target and regulate hundreds of genes via interaction with partially complementary sites located at the 3’ UTR of mRNAs to destabilize, inhibit mRNA translation, and reduce protein production (7). In clinics, an ideal biomarker should be easily accessible by using a minimally invasive sampling procedure, making routine blood, urine, or saliva examination an excellent source of choice. Blood carries a wide array of biomolecules including nutrients, hormones, and molecules secreted by cells with specific biological functions. Among these molecules, circulating nucleic acids such as miRNAs have recently been recognized to be present in the circulation system, providing useful diagnostic indicators (8). The miRNAs in serum may serve as a promising target for identifying the development and progression of diseases. Studies have shown that this method can be used in cardiovascular diseases and cancers. It has been recently reported that miRNAs in serum may be greatly different in patients with diabetes and T2DM compared to those healthy controls. For instance, among 14 selected miRNAs in plasma from 19 Iraqis and 14 Swedes diagnosed with T2DM and 119 control patients, the expression of miR-24 and miR-29b was significantly different between the T2DM patients and the control group after adjustment for age, gender, waist circumference, a family history of T2DM, and a sedentary lifestyle (9). Another report has shown that miR-20b, miR-21, miR-24, miR-15a, miR-126, miR-191, miR-197, miR-223, miR-320, and miR-486 are downregulated, while miR-28-3p was upregulated in plasma of T2DM patients in comparison with non-DM individuals (10). However, researches about miRNA and T2DM combined with OB remain limited. The aim of our experiment was to study the expression of miRNAs from four different groups of samples (obese, non-obese diabetic, obese diabetic, and control). We hypothesized that miRNAs expression would show a significant difference between samples taken from obese subjects, diabetic subjects or obese diabetic subjects.
2
MATERIALS AND METHODS Study population A total of 100 subjects were included in our study. They were classified under our strict study criteria. Subjects with fasting glucose level ≥7.0 mmol/L were considered as diabetic. Subjects with BMI ≥ 30 kg/m2 were considered as obese. Four groups were created and each group contained 25 participants. The Ethics Committee of General Hospital of Guangzhou Military Command of PLA approved our study. All of our study participants signed a written consent. Blood serum samples from these participants were collected at least 12 h after their recent meals. Serum glucose was examined using autoanalyzer method (Boehringer Mannheim, Rhein, Germany). Clinical parameters including cholesterol, low-density lipoproteins, highdensity lipoprotein, and triglyceride levels were also evaluated (Life Technologies, Grand Island, NT, USA). After collection of the whole blood, the blood was left undisturbed at room temperature. The clot was removed by centrifuging at 1000 g for 10 min in a refrigerated centrifuge. The resulting supernatant is designated serum. We removed the supernatant part of the serum by transfer pipette. The samples were stored at 80 °C and they were thawed before use.
MiRNA isolation and measurement MiRNA isolation and measurement were performed based on previously described methods (11). Total miRNAs were extracted from serums using a modified version of Qiagen miRNeasy Mini Kit (Qiagen, Hilden, Germany). After this step, the RNAs were stored at 80 °C. To ensure the quality and integrity of our study, we used the endogenous miRNA assays to verify and assess the quality of the isolated products at this stage. Another procedure we used to ensure integrity of our samples was to test them with miR-191 and miR-423-3p, which can be typically found in serum. The samples tested must show Cp 0.05) and the OB+T2DM group (p > 0.05), whereas the control group and the OB+T2DM group remained very similar level of this miRNA (Fig. 1B). As for the miR-593, OB group was relatively higher than the control group (10.2 vs 8.3, p > 0.05, Fig. 1C). However, both of the controls and the OB group revealed significantly increased miR-593 expression than the T2DM group and the OB+T2DM group (Fig. 1C). Level of miR-593 was not significantly different between the T2DM group and the OB+T2DM group (Fig. 1C). In addition, we found that level of miR-138 in OB (relative expression: 5.5) was significantly lower than the controls (relative expression: 9.9, p < 0.001), T2DM (relative expression: 10.6, p < 0.001), and OB+T2DM group (relative expression: 9.3, p < 0.001, Fig. 1D), whereas level of this miRNA was similar among controls, T2DM, and OB+T2DM group (p > 0.05, Fig. 1D). These results suggest that the four miRNAs could be potential biomarkers to identify OB or T2DM at the genetic micro RNA level. The ability of each miRNA to distinguish OB from other groups
Analysis of ROC showed that the AUC values of miR-152, miR-17, and miR-138 were 0.99 (95% CI 0.97–1.00), 0.95 (95% CI 0.91–0.98), 0.93 (95% CI 0.88–0.96) respectively (Table 2). These data indicate that miR-152, miR-17, and miR-138 alone can be used as biomarkers to distinguish obese subjects from healthy controls based on its discriminating difference shown in our study. Furthermore, we investigated the differences of miRNAs between patient groups. When compared OB with T2DM, miR-152, miR-17, miR-593, and miR-138 had
T2DM 25 46.7 23.5 7.9 22.4 183.2 122.5 54.6 132.2 79.2
8.6 2.1 0.5 7.8 35.5 23.2 11.5 15.4 10.5
OB 25 42.6 34.2 4.5 26.5 195.1 106.7 50.8 135.7 81.6
11.8 1.5 0.6 11.6 30.2 22.5 11.6 12.1 8.6
OB+ T2DM 25 46.1 12.6 33.1 1.9 8.2 0.7 27.7 12.5 199.3 38.4 125.9 28.9 48.6 8.9 136.8 17.8 85.5 12.1
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A
B
C
D
Fig. 1. Comparison of the serum levels of miR-152(A), miR-17 (B), miR-593 (C), and miR-138 (D) in controls, T2DM, obesity (OB), and OB+T2DM groups. Graphs show mean level with SD. The serum levels were determined using quantitative reverse transcription polymerase chain reaction following RNA extraction. Comparisons were performed between each two groups. Only data with significant difference are shown in the figure. ***p < 0.001. Table 2. The ability of each miRNA to distinguish obesity from controls Controls vs OB AUC 95% CI miR-152 0.98 0.97–1.00 miR-17 0.95 0.91–0.98 miR-593 0.59 0.32–0.77 miR-138 0.93 0.88–0.96
Table 3. The ability of each miRNA to distinguish obesity from T2DM patients OB vs T2DM AUC 95% CI miR-152 0.91 0.81–0.95 miR-17 0.97 0.94–0.99 miR-593 0.98 0.96–1.00 miR-138 0.93 0.85–0.96
AUC values of 0.91 (95% CI 0.81–0.95), 0.97 (95% CI 0.94–0.99), 0.98 (95% CI 0.96–1.00), 0.93 (95% CI 0.85–0.96) respectively (Table 3). Such results indicate that the four miRNAs can be used to distinguish OB from T2DM. Similarly, we compared the ROC curve between OB vs OB+T2DM. Results revealed that miR-152, miR-17, miR-593, and miR138 had AUC values of 0.88, 0.94, 0.97, and 0.93 respectively (Table 4). Together, the data suggest that the four miRNAs can be used as potential biomarkers to distinguish OB from T2DM, OB+T2DM, and healthy subjects.
Table 4. The ability of each miRNA to distinguish obesity (OB) from OB+T2DM patients OB vs OB+T2DM AUC 95% CI miR-152 0.88 0.80–0.93 miR-17 0.94 0.89–0.97 miR-593 0.97 0.93–0.99 miR-138 0.93 0.87–0.96
DISCUSSION Evidence have shown that miRNA in serum can be used as novel diagnostic biomarkers in different diseases such as cancers and autoimmune diseases. In this study, we screened and analyzed miRNAs in OB patients, T2DM patients, OB+T2DM patients, and healthy subjects, and identified that miR-152 4
and miR-17 were significantly elevated in the OB group, whereas miR-138 was significantly decreased in OB group when compared to controls, T2DM, or T2DM+OB group. In addition, level of MiR-593 was significantly lower in T2DM group and T2DM+OB group when compared with controls. Using the four miRNAs alone can effectively distinguish OB from T2DM, OB+T2DM and healthy subjects. These results indicate the diagnostic value of circulating miRNAs in OB and T2DM. Functions of miR-152 are very complicated. MiR-152 can mediate the tumor-suppressive effects in human glioblastoma stem cells through long © 2015 APMIS. Published by John Wiley & Sons Ltd
MICRORNA AND OBESITY
non-coding RNA XIST (12). Serum miR-152 together with miR-148a and miR-148b are significantly downregulated in non-small cell lung cancer (NSCLC) (13). Also, miR-152-5p may discriminate benign from malignant ovarian disease. Study has shown that Mir-152 inhibits cell proliferation and colony formation of CD133 + liver cancer stem cells by targeting KIT (14). In addition, miR-152 can modulate the canonical Wnt pathway activation by targeting DNA methyltransferase 1 in arthritic rat model (15). The miRNA has been observed to show increased expression in children with newly diagnosed type 1 diabetes (16). Here, we identified elevated level of miR-152 in OB patients but not in T2DM cases (Fig. 1A). As for miR-17, study has shown that ectopic expression of miR-17, which controls RUNX1 level by targeting RUNX1-3 UTR, in human U937 cells leads to deregulation of a core RUNX1-regulated miRNA mechanism that is similarly affected by the t (8, 17) RUNX1-MTG8 and inv (16) CBFBMYH11 fusion proteins (18). Also, MiR-17 may inhibit melanoma growth by stimulating CD8 + T cells mediated host immune response, which is due to its regulation of STAT3 (19). We found that level of miR-17 was increased in OB patients but not in OB+T2DM cases (Fig. 1B). Compared with other miRNAs, researches about miR-593 remain limited. It has been reported that he levels of miR-593 in the serum of children with combined pituitary hormone deficiency were increased compared with those in the control subjects (20). Our results revealed that OB group was relatively higher than the control group (p > 0.05, Fig. 1C). However, both of the controls and the OB group had significantly increased miR-593 expression than the T2DM group and the OB+T2DM group (Fig. 1C). MiR-138 has been widely researched. MiR-138 downregulation can be associated with prognosis in patients with hepatocellular carcinoma (21). Overexpression of miR-138 resulted in reduced cell invasion and migration, while silencing of miR-138 led to enhancement of the invasion and migration of ovarian cancer cells (17). In addition, miR-138 has been demonstrated to target the 3’UTR of EID-1, an interacting inhibitor of differentiation that can interact with SHP, an endogenous enhancer of adipogenic PPARc2. A recent report has shown that level of miR-138 is significantly diminished in OB patients compared to healthy controls, T2DM alone, and OB+T2DM in a Spanish population (11). Data also suggest that the miRNA is significantly lower in OB+T2DM group than in T2DM alone (11, 18). Our study found downregulated expression of serum miR-138 in OB cases. However, we did
© 2015 APMIS. Published by John Wiley & Sons Ltd
not identify significant difference between the OB+T2DM group and the T2DM group (Fig. 1D), which might be due to the different population investigated between these studies. In conclusion, our study identified four miRNAs (miR-152, miR-17, and miR-138, miR-593) that showed differences in peripheral miRNA level in OB, T2DM and T2DM combined with OB. The study results suggest the potential utility of miRNAs in the prediction for OB and T2DM.
CONFLICT OF INTEREST None.
This work was supported by Science and Technology Planning Project of Guangdong Province, China (No.2011B050400041), and Natural Science Foundation of Guangdong Province, China (No.S2011010000472).
REFERENCES 1. Park MH, Falconer C, Viner RM, Kinra S. The impact of childhood obesity on morbidity and mortality in adulthood: a systematic review. Obes Rev 2012;13:985–1000. 2. Chen X, Wei S, Yang F. Mitochondria in the pathogenesis of diabetes: a proteomic view. Protein Cell 2012;3:648–60. 3. Avrahami D, Kaestner KH. Epigenetic regulation of pancreas development and function. Semin Cell Dev Biol 2012;23:693–700. 4. Liu J, Albrecht AM, Ni X, Yang J, Li M. Glioblastoma tumor initiating cells: therapeutic strategies targeting apoptosis and microRNA pathways. Curr Mol Med 2013;13:352–7. 5. Pers YM, Jorgensen C. MicroRNA in 2012: biotherapeutic potential of microRNAs in rheumatic diseases. Nat Rev Rheumatol 2013;9:76–8. 6. Fernandez-Hernando C, Ramirez CM, Goedeke L, Suarez Y. MicroRNAs in metabolic disease. Arterioscler Thromb Vasc Biol 2013;33:178–85. 7. Ishida M, Shimabukuro M, Yagi S, Nishimoto S, Kozuka C, Fukuda D, et al. MicroRNA-378 regulates adiponectin expression in adipose tissue: a new plausible mechanism. PLoS ONE 2014;9:e111537. 8. Ortega FJ, Mercader JM, Catalan V, Moreno-Navarrete JM, Pueyo N, Sabater M, et al. Targeting the circulating microRNA signature of obesity. Clin Chem 2013;59:781–92. 9. Wang X, Sundquist J, Zoller B, Memon AA, Palmer K, Sundquist K, et al. Determination of 14 circulating microRNAs in Swedes and Iraqis with and without diabetes mellitus type 2. PLoS ONE 2014;9:e86792. 10. Zampetaki A, Kiechl S, Drozdov I, Willeit P, Mayr U, Prokopi M, et al. Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes. Circ Res 2010;107:810–7.
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11. Pescador N, Perez-Barba M, Ibarra JM, Corbaton A, Martinez-Larrad MT, Serrano-Rios M. Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers. PLoS ONE 2013;8:e77251. 12. Yao Y, Ma J, Xue Y, Wang P, Li Z, Liu J, et al. Knockdown of long non-coding RNA XIST exerts tumor-suppressive functions in human glioblastoma stem cells by up-regulating miR-152. Cancer Lett 2015;359:75–86. 13. Yang JS, Li BJ, Lu HW, Chen Y, Lu C, Zhu RX, et al. Serum miR-152, miR-148a, miR-148b, and miR21 as novel biomarkers in non-small cell lung cancer screening. Tumour Biol 2014; doi: 10.1007/s13277014-2938-1. 14. Huang H, Hu M, Li P, Lu C, Li M. Mir-152 inhibits cell proliferation and colony formation of CD133 liver cancer stem cells by targeting KIT. Tumour Biol 2014;36:921–8. 15. Miao CG, Yang YY, He X, Huang C, Huang Y, Qin D, et al. MicroRNA-152 modulates the canonical Wnt pathway activation by targeting DNA methyltransferase 1 in arthritic rat model. Biochimie 2014;106:149–56. 16. Nielsen LB, Wang C, Sorensen K, Bang-Berthelsen CH, Hansen L, Andersen ML, et al. Circulating levels
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of microRNA from children with newly diagnosed type 1 diabetes and healthy controls: evidence that miR-25 associates to residual beta-cell function and glycaemic control during disease progression. Exp Diabetes Res 2012;2012:896362. Chen P, Zeng M, Zhao Y, Fang X. Upregulation of Limk1 caused by microRNA-138 loss aggravates the metastasis of ovarian cancer by activation of Limk1/ cofilin signaling. Oncol Rep 2014;32:2070–6. Fischer J, Rossetti S, Datta A, Eng K, Beghini A, Sacchi N. miR-17 deregulates a core RUNX1-miRNA mechanism of CBF acute myeloid leukemia. Mol Cancer 2015;14:7. Li H, Gupta S, Du WW, Yang BB. MicroRNA-17 inhibits tumor growth by stimulating T-cell mediated host immune response. Oncoscience 2014;1:531–9. Hu Y, Wang Q, Wang Z, Wang F, Guo X, Li G. Circulating microRNA profiles and the identification of miR-593 and miR-511 which directly target the PROP1 gene in children with combined pituitary hormone deficiency. Int J Mol Med 2015;35: 358–66. Huang B, Li H, Huang L, Luo C, Zhang Y. Clinical significance of microRNA 138 and cyclin D3 in hepatocellular carcinoma. J Surg Res 2015;193:718–23.
© 2015 APMIS. Published by John Wiley & Sons Ltd
APMIS
Profiling peripheral microRNAs in obesity and type 2 diabetes mellitus LIANGPING WU,1 XIAOJIANG DAI,1 JUNFANG ZHAN,2 YUXIN ZHANG,1 HONGBIN ZHANG,1 HONGBING ZHANG,1 SONGHUA ZENG1 and WENBIN XI1 1
Surgical Center of Thyroid Diabetes, General Hospital of Guangzhou Military Command of PLA, Guangzhou; and 2Health Management Center, Guangzhou First People’s Hospital, Guangzhou Medical College, Guangzhou, China
Wu L, Dai X, Zhan J, Zhang Y, Zhang H, Zhang H, Zeng S, Xi W. Profiling peripheral microRNAs in obesity and type 2 diabetes mellitus. APMIS 2015. Mechanisms of type 2 diabetes mellitus (T2DM) remain elusive, in which obesity (OB) is considered as one of the major risk factors for the disease. A microRNA (miRNA) is a small non-coding RNA molecule functioning in RNA silencing and post-transcriptional regulation of gene expression. It has been demonstrated that some miRNAs can exist in serum stably and is closely related to various diseases. The goal of our study was to identify whether the deregulation of serum miRNAs was associated with T2DM and obesity. Twenty-five subjects with T2DM2, 25 healthy controls, 25 subjects with obesity, and 25 subjects with T2DM combined with obesity were included in the study. A total of 536 miRNA serum samples from these four groups were studied by miRNA polymerase chain reaction (PCR) panels. Data showed that miR-152 and miR-17 were significantly elevated in the OB group, whereas miR-138 was significantly decreased in OB group when compared to controls, T2DM, or T2DM+obesity group. In addition, level of MiR-593 was significantly lower in T2DM group and T2DM+obesity group when compared with controls. Further analysis revealed that the four miRNAs can be used as potential biomarkers to distinguish obesity from T2DM, OB+T2DM, and healthy subjects. Our study is one of the pioneer studies showing the differences in peripheral miRNA level in obesity, T2DM and T2DM combined with obesity. The study results suggest the potential utility of miRNAs in the prediction for obesity and T2DM. Key words: MicroRNA; obesity; diabetes. Junfang Zhan, Health Management Center, Guangzhou First People’s Hospital, Guangzhou Medical College, 1 Panfu Road, Guangzhou, Guangdong 510180, China. e-mail: [email protected] Yuxin Zhang, Surgical Center of Thyroid Diabetes, General Hospital of Guangzhou Military Command of PLA, 111 Liuhua Road, Guangzhou, Guangdong 510010, China. e-mail: [email protected]
Liangping Wu and Xiaojiang Dai contributed equally to the work.
Type 2 diabetes mellitus (T2DM) is a chronic disease characterized by hyperglycemia, pancreatic beta cell insufficiency, and insulin resistance, a suboptimal tissue response to insulin that is largely driven by obesity (1). Studies have suggested that about 400 million people in the world may be affected by diabetes, in which 90% would be T2DM by 2030 (1). Obesity (OB) is known as excessive fat accumulation in the body resulted from mismatch of energy intake and expenditure. Obesity-related insulin resistance is thought to be Received 18 January 2015. Accepted 23 February 2015
the major precursor driving the development of T2DM, which targets multiple tissues including the brain, liver, skeletal muscle, pancreas, and adipose tissue. There are many contributing factors associated with either obesity or T2DM (2). However, genetics is commonly thought as the most influential factor. Therefore, the study of genetics and its relation to obesity and T2DM has important meanings, which the information we obtain through our studies can potentially be apply to disease prevention, early diagnosis and interventions (3). MicroRNAs (miRNAs) are short noncoding RNAs of ~22 nucleotides that negatively regulate 1
WU et al.
gene expression at the post-transcriptional level (4). In general, miRNAs bind to the 3’-UTR of its target mRNA via sequence-guided recognition to trigger mRNA degradation or translational repression (4). A mature miRNA forms a RNA-protein complex called RNA-induced silencing complex by forming a survivin-XIAP complex (5). More than 1000 miRNAs have been identified in the human genome. The miRNA expression can be modulated through various pathways including transcription factors and processing precursors (6). Functions of miRNA are diversified. One individual miRNA can target and regulate hundreds of genes via interaction with partially complementary sites located at the 3’ UTR of mRNAs to destabilize, inhibit mRNA translation, and reduce protein production (7). In clinics, an ideal biomarker should be easily accessible by using a minimally invasive sampling procedure, making routine blood, urine, or saliva examination an excellent source of choice. Blood carries a wide array of biomolecules including nutrients, hormones, and molecules secreted by cells with specific biological functions. Among these molecules, circulating nucleic acids such as miRNAs have recently been recognized to be present in the circulation system, providing useful diagnostic indicators (8). The miRNAs in serum may serve as a promising target for identifying the development and progression of diseases. Studies have shown that this method can be used in cardiovascular diseases and cancers. It has been recently reported that miRNAs in serum may be greatly different in patients with diabetes and T2DM compared to those healthy controls. For instance, among 14 selected miRNAs in plasma from 19 Iraqis and 14 Swedes diagnosed with T2DM and 119 control patients, the expression of miR-24 and miR-29b was significantly different between the T2DM patients and the control group after adjustment for age, gender, waist circumference, a family history of T2DM, and a sedentary lifestyle (9). Another report has shown that miR-20b, miR-21, miR-24, miR-15a, miR-126, miR-191, miR-197, miR-223, miR-320, and miR-486 are downregulated, while miR-28-3p was upregulated in plasma of T2DM patients in comparison with non-DM individuals (10). However, researches about miRNA and T2DM combined with OB remain limited. The aim of our experiment was to study the expression of miRNAs from four different groups of samples (obese, non-obese diabetic, obese diabetic, and control). We hypothesized that miRNAs expression would show a significant difference between samples taken from obese subjects, diabetic subjects or obese diabetic subjects.
2
MATERIALS AND METHODS Study population A total of 100 subjects were included in our study. They were classified under our strict study criteria. Subjects with fasting glucose level ≥7.0 mmol/L were considered as diabetic. Subjects with BMI ≥ 30 kg/m2 were considered as obese. Four groups were created and each group contained 25 participants. The Ethics Committee of General Hospital of Guangzhou Military Command of PLA approved our study. All of our study participants signed a written consent. Blood serum samples from these participants were collected at least 12 h after their recent meals. Serum glucose was examined using autoanalyzer method (Boehringer Mannheim, Rhein, Germany). Clinical parameters including cholesterol, low-density lipoproteins, highdensity lipoprotein, and triglyceride levels were also evaluated (Life Technologies, Grand Island, NT, USA). After collection of the whole blood, the blood was left undisturbed at room temperature. The clot was removed by centrifuging at 1000 g for 10 min in a refrigerated centrifuge. The resulting supernatant is designated serum. We removed the supernatant part of the serum by transfer pipette. The samples were stored at 80 °C and they were thawed before use.
MiRNA isolation and measurement MiRNA isolation and measurement were performed based on previously described methods (11). Total miRNAs were extracted from serums using a modified version of Qiagen miRNeasy Mini Kit (Qiagen, Hilden, Germany). After this step, the RNAs were stored at 80 °C. To ensure the quality and integrity of our study, we used the endogenous miRNA assays to verify and assess the quality of the isolated products at this stage. Another procedure we used to ensure integrity of our samples was to test them with miR-191 and miR-423-3p, which can be typically found in serum. The samples tested must show Cp 0.05) and the OB+T2DM group (p > 0.05), whereas the control group and the OB+T2DM group remained very similar level of this miRNA (Fig. 1B). As for the miR-593, OB group was relatively higher than the control group (10.2 vs 8.3, p > 0.05, Fig. 1C). However, both of the controls and the OB group revealed significantly increased miR-593 expression than the T2DM group and the OB+T2DM group (Fig. 1C). Level of miR-593 was not significantly different between the T2DM group and the OB+T2DM group (Fig. 1C). In addition, we found that level of miR-138 in OB (relative expression: 5.5) was significantly lower than the controls (relative expression: 9.9, p < 0.001), T2DM (relative expression: 10.6, p < 0.001), and OB+T2DM group (relative expression: 9.3, p < 0.001, Fig. 1D), whereas level of this miRNA was similar among controls, T2DM, and OB+T2DM group (p > 0.05, Fig. 1D). These results suggest that the four miRNAs could be potential biomarkers to identify OB or T2DM at the genetic micro RNA level. The ability of each miRNA to distinguish OB from other groups
Analysis of ROC showed that the AUC values of miR-152, miR-17, and miR-138 were 0.99 (95% CI 0.97–1.00), 0.95 (95% CI 0.91–0.98), 0.93 (95% CI 0.88–0.96) respectively (Table 2). These data indicate that miR-152, miR-17, and miR-138 alone can be used as biomarkers to distinguish obese subjects from healthy controls based on its discriminating difference shown in our study. Furthermore, we investigated the differences of miRNAs between patient groups. When compared OB with T2DM, miR-152, miR-17, miR-593, and miR-138 had
T2DM 25 46.7 23.5 7.9 22.4 183.2 122.5 54.6 132.2 79.2
8.6 2.1 0.5 7.8 35.5 23.2 11.5 15.4 10.5
OB 25 42.6 34.2 4.5 26.5 195.1 106.7 50.8 135.7 81.6
11.8 1.5 0.6 11.6 30.2 22.5 11.6 12.1 8.6
OB+ T2DM 25 46.1 12.6 33.1 1.9 8.2 0.7 27.7 12.5 199.3 38.4 125.9 28.9 48.6 8.9 136.8 17.8 85.5 12.1
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A
B
C
D
Fig. 1. Comparison of the serum levels of miR-152(A), miR-17 (B), miR-593 (C), and miR-138 (D) in controls, T2DM, obesity (OB), and OB+T2DM groups. Graphs show mean level with SD. The serum levels were determined using quantitative reverse transcription polymerase chain reaction following RNA extraction. Comparisons were performed between each two groups. Only data with significant difference are shown in the figure. ***p < 0.001. Table 2. The ability of each miRNA to distinguish obesity from controls Controls vs OB AUC 95% CI miR-152 0.98 0.97–1.00 miR-17 0.95 0.91–0.98 miR-593 0.59 0.32–0.77 miR-138 0.93 0.88–0.96
Table 3. The ability of each miRNA to distinguish obesity from T2DM patients OB vs T2DM AUC 95% CI miR-152 0.91 0.81–0.95 miR-17 0.97 0.94–0.99 miR-593 0.98 0.96–1.00 miR-138 0.93 0.85–0.96
AUC values of 0.91 (95% CI 0.81–0.95), 0.97 (95% CI 0.94–0.99), 0.98 (95% CI 0.96–1.00), 0.93 (95% CI 0.85–0.96) respectively (Table 3). Such results indicate that the four miRNAs can be used to distinguish OB from T2DM. Similarly, we compared the ROC curve between OB vs OB+T2DM. Results revealed that miR-152, miR-17, miR-593, and miR138 had AUC values of 0.88, 0.94, 0.97, and 0.93 respectively (Table 4). Together, the data suggest that the four miRNAs can be used as potential biomarkers to distinguish OB from T2DM, OB+T2DM, and healthy subjects.
Table 4. The ability of each miRNA to distinguish obesity (OB) from OB+T2DM patients OB vs OB+T2DM AUC 95% CI miR-152 0.88 0.80–0.93 miR-17 0.94 0.89–0.97 miR-593 0.97 0.93–0.99 miR-138 0.93 0.87–0.96
DISCUSSION Evidence have shown that miRNA in serum can be used as novel diagnostic biomarkers in different diseases such as cancers and autoimmune diseases. In this study, we screened and analyzed miRNAs in OB patients, T2DM patients, OB+T2DM patients, and healthy subjects, and identified that miR-152 4
and miR-17 were significantly elevated in the OB group, whereas miR-138 was significantly decreased in OB group when compared to controls, T2DM, or T2DM+OB group. In addition, level of MiR-593 was significantly lower in T2DM group and T2DM+OB group when compared with controls. Using the four miRNAs alone can effectively distinguish OB from T2DM, OB+T2DM and healthy subjects. These results indicate the diagnostic value of circulating miRNAs in OB and T2DM. Functions of miR-152 are very complicated. MiR-152 can mediate the tumor-suppressive effects in human glioblastoma stem cells through long © 2015 APMIS. Published by John Wiley & Sons Ltd
MICRORNA AND OBESITY
non-coding RNA XIST (12). Serum miR-152 together with miR-148a and miR-148b are significantly downregulated in non-small cell lung cancer (NSCLC) (13). Also, miR-152-5p may discriminate benign from malignant ovarian disease. Study has shown that Mir-152 inhibits cell proliferation and colony formation of CD133 + liver cancer stem cells by targeting KIT (14). In addition, miR-152 can modulate the canonical Wnt pathway activation by targeting DNA methyltransferase 1 in arthritic rat model (15). The miRNA has been observed to show increased expression in children with newly diagnosed type 1 diabetes (16). Here, we identified elevated level of miR-152 in OB patients but not in T2DM cases (Fig. 1A). As for miR-17, study has shown that ectopic expression of miR-17, which controls RUNX1 level by targeting RUNX1-3 UTR, in human U937 cells leads to deregulation of a core RUNX1-regulated miRNA mechanism that is similarly affected by the t (8, 17) RUNX1-MTG8 and inv (16) CBFBMYH11 fusion proteins (18). Also, MiR-17 may inhibit melanoma growth by stimulating CD8 + T cells mediated host immune response, which is due to its regulation of STAT3 (19). We found that level of miR-17 was increased in OB patients but not in OB+T2DM cases (Fig. 1B). Compared with other miRNAs, researches about miR-593 remain limited. It has been reported that he levels of miR-593 in the serum of children with combined pituitary hormone deficiency were increased compared with those in the control subjects (20). Our results revealed that OB group was relatively higher than the control group (p > 0.05, Fig. 1C). However, both of the controls and the OB group had significantly increased miR-593 expression than the T2DM group and the OB+T2DM group (Fig. 1C). MiR-138 has been widely researched. MiR-138 downregulation can be associated with prognosis in patients with hepatocellular carcinoma (21). Overexpression of miR-138 resulted in reduced cell invasion and migration, while silencing of miR-138 led to enhancement of the invasion and migration of ovarian cancer cells (17). In addition, miR-138 has been demonstrated to target the 3’UTR of EID-1, an interacting inhibitor of differentiation that can interact with SHP, an endogenous enhancer of adipogenic PPARc2. A recent report has shown that level of miR-138 is significantly diminished in OB patients compared to healthy controls, T2DM alone, and OB+T2DM in a Spanish population (11). Data also suggest that the miRNA is significantly lower in OB+T2DM group than in T2DM alone (11, 18). Our study found downregulated expression of serum miR-138 in OB cases. However, we did
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not identify significant difference between the OB+T2DM group and the T2DM group (Fig. 1D), which might be due to the different population investigated between these studies. In conclusion, our study identified four miRNAs (miR-152, miR-17, and miR-138, miR-593) that showed differences in peripheral miRNA level in OB, T2DM and T2DM combined with OB. The study results suggest the potential utility of miRNAs in the prediction for OB and T2DM.
CONFLICT OF INTEREST None.
This work was supported by Science and Technology Planning Project of Guangdong Province, China (No.2011B050400041), and Natural Science Foundation of Guangdong Province, China (No.S2011010000472).
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