Endocrine Research
201
Authors
J. Zhou1, Q. Zheng1, T. Xu2, D. Liao2, Y. Zhang2, S. Yang2, J. Hu2
Affiliations
1
Department of Cardiology, Wuhan 1st Hospital (Wuhan Hospital of Integrated Chinese and Western Medicine), Wuhan, China 2 Department of Endocrinology, Affiliated Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Key words ▶ exercise ● ▶ epigenetic ● ▶ metabolic syndrome ●
Abstract
received 16.07.2013 accepted 12.09.2013 Bibliography DOI http://dx.doi.org/ 10.1055/s-0033-1357139 Published online: October 17, 2013 Horm Metab Res 2014; 46: 201–205 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0018-5043 Correspondence J. Hu, MD Department of Endocrinology Affiliated Liyuan Hospital Tongji Medical College Huazhong University of Science and Technology Liyuan Village Wuhan 430077 Hubei China Tel.: + 86/27/83692 347 Fax: + 86/27/86779 910 [email protected]
▼
The aim of the study was to investigate the associations between physical activity (PA)-related miRNAs and metabolic syndrome (MetS). A casecontrol study was conducted in 209 subjects with MetS and 234 controls. The MetS was defined by the International Diabetes Foundation (IDF) criteria of 2005. Serum PA-related miRNAs were detected by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays. Association analysis was performed by logistic regression models. The expression levels of miR-126 and miR-130a were lower in the highest metabolic equivalent hours per week (MET-h/week) quartile than in the lowest quartile [miR-126: Q5 vs. Q1, median (5–95 %), 1.67 (0.54, 2.45) vs. 1.35 (0.45, 2.45), p = 0.012; miR130a: Q5 vs. Q1, median (5–95 %), 0.90 (0.44, 1.35) vs. 0.53 (0.26, 1.01), p < 0.001]. However,
Introduction
▼
Metabolic syndrome (MetS), a sub-health state comprising a cluster of risk factors including hypertension, altered glucose metabolism, dyslipidemia, and abdominal obesity, confers an individual at risk for type 2 diabetes (T2D) and cardiovascular disease (CVD) [1]. In addition, results from meta-analysis showed MetS was associated with increased risk of common cancers [2]. The persistent increased prevalence made MetS a serious public health concern [3]. In order to improve the preventive and therapeutic strategies, researchers need to revert back to elucidating the molecular mechanisms underlying MetS. Lifestyle modification is the most appealing approach for MetS because of its nontoxicity and high efficacy, and physical activity (PA) is a fundamental component [4]. Epidemiological
miR-197 exhibited a trend with increased MET-h/ week [Q5 vs. Q1, median (5–95 %), 1.35 (0.45, 2.63) vs. 2.18 (0.87, 4.77), p = 0.009]. MiR-126 increased MetS risk significantly while the effect of miR-197 was opposite (miR-126: OR = 1.37, 95 % CI 1.07–1.75; p = 0.012; miR-197: OR = 0.68, 95 % CI 0.51–0.92; p = 0.010). Individuals in the highest MET-h/week quartile had lower prevalence and odds rate of MetS compared with those in the lowest quartile (Q4 vs. Q1: OR = 0.58, 95 % CI 0.33–1.05; p for trend = 0.026). However, further adjustment of both PA associated miRNAs abolished that association. All these results suggested that the association between PA and MetS risk might partly depend on miR-126 and miR197. Supporting Information for this article is available online at http://www.thieme-connect.de/ ejournals/toc/hmr
evidence showed that PA could reduce the risk of MetS [5] and its components: obesity [6], hypertension [7], dyslipidemia [8, 9], and prediabetes/ diabetes [10]. MicroRNAs (miRNAs) are short (ranging from 19 to 22 nucleotides), endogenous, noncoding RNAs that negatively regulate gene expression at the posttranscriptional level by binding to the 3′ untranslated regions of messenger RNA targets [11]. Published studies have provided evidence for the significance role of circulating miRNAs in MetS [12, 13]. In addition, considerable evidence showed that PA could alert the miRNA expression [14–16]. Thus, we hypothesize that PA might influence the MetS risk by impacting on the expression levels of miRNAs. To address this hypothesis, we investigated the associations between PA-associated miRNAs and MetS risk in 209 persons with MetS and 234 controls.
Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Associations Between Physical Activity-related miRNAs and Metabolic Syndrome
202 Endocrine Research Subjects and Methods
▼
calculated by the equation 2 − ΔCT, in which ΔCT = cycle threshold (CT) miRNA – CT (cel-miR-39).
Study subjects and data collection Definition of the metabolic syndrome MetS was defined using the updated National Cholesterol Education Program/Adult treatment Panel III criteria for Asian Americans as having ≥ 3 of the following components: (1) waist circumference ≥ 90 cm for men or ≥ 80 cm for women; (2) TG ≥ 1.7 mmol/l; (3) HDL cholesterol < 1.03 mmol/l for men or < 1.30 mmol/l for women; (4) blood pressure ≥ 130/85 mm Hg (5); and fasting glucose ≥ 5.6 mmol/l [19].
Statistical analysis All statistical analyses were performed using SPSS 13.0 software. Categorical variables were expressed in percentages and continuous variables were expressed in means ± SD for normally distributed data or medians (5–95 %) for skewed parameters. Differences in the variables between MetS and controls were assessed by Student’s t-test (or Kruskal-Wallis test) for continuous variables and chi-square test for categorical variables. Confidence intervals (CIs) 95 % and β for miRNAs were tested by generalized linear models. Odds ratios (ORs) and 95 % CI for MetS risk were obtained by the logistic regression models. A 2-sided p-value < 0.05 was considered significant.
Assessment of PA Type, frequency, and average duration of the PA were obtained by the questionnaires. Separate metabolic equivalent (MET) hours per week were calculated for each activity to estimate energy expenditure for total PA using the formula: MET coefficient of activity × duration (hours per time) × frequency (times per week). MET coefficient used for leisure activities were: 3 for walking, 4 for biking, 4.5 for tai chi [17], 7.5 for jogging or swimming, 6 for playing ball games or doing exercise in gym, 5 for dancing, 4.5 for climbing [18], according to the compendium of physical fitness [18].
MiRNA selections and detections A total of 55 reported PA-associated miRNAs [14, 15] were selected in this study: miR-126, miR-130a, miR-151–5p, miR223, miR-363, let-7e, let-7i, miR-106a, miR-107, miR-1225–5p, miR-1238, miR-125a-5p, miR-130b, miR-142–3p, miR-142–5p, miR-145, miR-16, miR-17, miR-181b, miR-185, miR-18a, miR18b, miR-192, miR-193a-3p, miR-194, miR-197, miR-199a-3p, miR-199a-5p, miR-20a, miR-20b, miR-212, miR-22, miR-221, miR-29a, miR-29b, miR-29c, miR-30e, miR-326, miR-328, miR338–3p, miR-340, miR-365, miR-485–3p, miR-505, miR520d-3p, miR-590–5p, miR-629, miR-638, miR-652, miR-660, miR-7, miR-93, miR-939, miR-940, and miR-96. Total RNA was isolated from 200 μl of serum sample, according to the manufacturer’s instructions using the mirVana PARIS miRNA Isolation Kit (Ambion 1556, Austin, TX). The qRT-PCR assay was carried out using a Taqman miRNA PCR kit (Applied BioSystems, Foster City, CA) according to the manufacturer’s instructions. The input RNAs were reverse transcribed (RT) at 16 °C for 30 min, 42 °C for 30 min, and 85 °C for 5 min, using the miRNA specific stem-loop primers provided in the kit. RT products were 1:5 diluted and subjected to quantitative PCR in TaqMan miRNA probes on the Applied Biosystems 7 900 Sequence Detection System (Applied Biosystems). The reaction was carried out at 95 °C for 10 min, 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. Cel-miR-39 was selected as internal reference for qRT-PCR analysis. Levels of miRNAs were all normalized to cel-miR-39 and Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
Fig. 1 MiRNA expression levels in plasma according to the quartiles of MET. The cutoff values of MET (h/week) were < 2.40, 2.40–15.60, 15.75–30.60, and ≥ 31.20, respectively. p-Value was obtained by KruskalWallis test.
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A total of 209 persons with MetS and 234 age- and sex-matched controls were recruited from a garment factory in Wuhan (Hubei, China). All of them were retired employees who agreed to answer the questionnaires and provide blood samples. Information on general characteristics was collected by face to face interviews. According to the respondents’ self-reported smoking status and alcohol consumption, participants were grouped as current smokers, ex-smokers, nonsmokers, drinker, ex-drinker, and nondrinker. Family history of coronary heart disease (CHD), stroke, and diabetes were dichotomized as yes or no on the basis of the responses to questionnaires. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. A 5 ml fast blood was drawn into a coded vacuum coagulation tube after 24–48 h of the completion of the last physical activity. Serum triglyceride (TG), blood glucose, and high-density lipoprotein (HDL) cholesterol were measured by the laboratory in Affiliated Liyuan Hospital (Wuhan, China) using ARCHITECT ci8200, Abbott, USA. All participants provided informed consent. The ethical committees in the Tongji Medical College had approved this study.
Endocrine Research
MiRNAs
Expression levels of miRNA
Crude OR (95 % CI)
p-Value
Adjusted OR
(mean ± SD) miR-126 miR-197 miR-130a a
p-Value
a
(95 % CI)
Controls
MetS
1.64 ± 0.77 1.55 ± 0.65 0.90 ± 0.36
1.83 ± 0.86 1.39 ± 0.74 0.89 ± 0.39
1.37 (1.07, 1.75) 0.68 (0.51, 0.92) 0.88 (0.53, 1.46)
0.012 0.010 0.627
1.40 (1.08, 1.82) 0.66 (0.48, 0.9) 0.83 (0.48, 1.42)
203
Table 1 Association between physical activity-associated miRNAs and MetS risk.
0.012 0.009 0.499
Logistic regression model adjustments for age (continuous), gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke
Sample size Univariate model Multivariate model 1a Multivariate model 2b a
p-Trend
Q2
Q3
Q4
109 1.00 1.00 1.00
116 0.94 (0.56, 1.58) 0.94 (0.54, 1.65) 0.91 (0.54, 1.61)
108 0.67 (0.39, 1.15) 0.56 (0.32, 1.00) 0.56 (0.31, 1.01)
110 0.58 (0.34, 1.00) 0.58 (0.33, 1.05) 0.64 (0.35, 1.16)
Table 2 Odds ratio and 95 % CI for MetS according to the quartiles of MET (h/week).
0.015 0.026 0.083
Logistic regression model adjustments for age (continuous), gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke
b
Logistic regression model adjustments for co-variants mentioned above pulse miR-197 and miR-126
Results
▼
Descriptive characteristics of the subjects A total of 209 subjects with MetS and 234 controls were recruited in this cross-sectional study. The general characteristics of the subjects are summarized in Table S1. Briefly, MetS group has higher levels of BMI, waist, TG, HDL, blood pressure, fasting blood glucose, and past history of stroke, and diabetes (rate), but lower MET-h/week and smoking rate. No significant differences were observed between MetS and controls in terms of the distribution of age, sex, drinking status, and past history of CHD.
Relationship between PA and miRNA expression levels in plasma Serum expression levels of 55 miRNAs were detected and 3 miRNAs including miR-197, miR-126, and miR-130a were significantly related with PA. The expression levels of miR-126, and miR-130a were lower in the highest MET-h/week quartile than in the lowest quartile [miR-126: Q5 vs. Q1, median (5–95 %), 1.67 (0.54, 2.45) vs. 1.35 (0.45, 2.45), p = 0.012; miR-130a: Q5 vs. Q1, median (5–95 %), 0.90 (0.44, 1.35) vs. 0.53 (0.26, 1.01), ▶ Fig. 1). However, miR-197 exhibited a trend with p < 0.001, ● increased MET-h/week [Q5 vs. Q1, median (5–95 %), 1.35 (0.45, ▶ Fig. 1. 2.63) vs. 2.18 (0.87, 4.77), p = 0.009, ●
Associations between PA-related miRNAs and MetS risk We further analyzed the associations between PA-associated miRNAs mentioned above and MetS risk. MiR-126 increased MetS risk significantly while the effect of miR-197 was opposite (miR-126: OR = 1.37, 95 % CI 1.07–1.75; p = 0.012; miR-197: OR = 0.68, 95 % CI 0.51–0.92; p = 0.010). Similar results were obtained after adjustment for age, gender, smoking, alcohol con▶ Table 1). sumption and history of CHD, diabetes, and stroke (● No significant association was found between miR-130a and ▶ Table 1). MetS risk (●
Association between PA and MetS risk Individuals in the highest MET-h/week quartile had lower preva▶ Fig. 2) and odds rate of MetS compared with those in lence (● the lowest quartile (Q4 vs. Q1: OR = 0.58, 95 % CI 0.33–1.05; p for ▶ Table 2) after adjustment for age (continuous), trend = 0.026, ●
Fig. 2 Prevalence of the metabolic syndrome by quartile of MET (h/ week). The cutoff values of MET (h/week) were < 2.40, 2.40–15.60, 15.75–30.60, and ≥ 31.20, respectively.
gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke. When MET-h/week was entered in the logistic regression model as a continuous variable, the full adjustment OR was 0.997 and 95 % CI was 0.978–0.999 (data not shown). However, that association was abolished when miR-197 and ▶ Table 2). miR-126 were included in the model (p = 0.083, ●
Discussion
▼
In this case-control study, we explored the associations between PA-related miRNAs and MetS risk. MiR-126 was significantly associated with increased MetS risk while miR-197 served as a protective role in the development of MetS. PA could reduce the MetS risk. Further adjustment of miRNA-126 and miRNA-197 abolished the association between PA and MetS risk. All these results suggested that PA might decrease MetS risk partly by regulating the expression levels of miRNA. Previous studies supported the roles of miRNAs in response to PA in neutrophil [15], peripheral blood mononuclear cells [20], natural killer cells [14], and in the plasma [16] and serum [21]. Bye et al. found the expression levels of miR-210, miR-222, and miR-21 in serum were higher in participants with low maximal
Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Quartiles of MET Q1
204 Endocrine Research Acknowledgements
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The authors would like to thank all study subjects for participating in this study as well as all volunteers for assisting in collecting the samples and data.
Conflict of Interest
▼
The authors declare no potential conflicts of interest with respect to the authorship and/or publication of this article.
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Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
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oxygen uptake, suggesting that a potential value of measuring circulating miRNAs as biomarkers of aerobic fitness [21]. It assumed that release of these 3 miRNAs from the endothelium in healthy subjects with low maximal oxygen uptake could be related to subclinical artherosclerosis, hypoxia or inflammation [21]. In this study, we successfully validate the relationship between 3 miRNAs (miR-197, miR-126, and miR-130a) and PA. Future studies are needed to further investigate the potential mechanism on how PA impacts circulating expression of miRNAs. Circulating miRNAs are widely reported as potential biomarkers for disease development [13, 22, 23], although their exact mechanism of release is largely unclear. To our knowledge, miR-126 received wide concern in epidemiology studies. Prospective study found that circulating miR-126 showed a positive association with incidence of myocardial infarction (MI) [24] and a negative association with type 2 diabetes (DM) [13]. Data from meta-analysis showed miR-126 was significantly downregulated in patients with lung cancer [25]. In addition, the experimental study provided evidence that miR-126 is downregulated in endothelial progenitor cells from diabetic patients [26]. In this study, Serum miR-126 was significantly associated with increased MetS risk, consistent with its role in MI. MiR-197 in blood was reported to be correlated with BMI, suggesting its potential contribution to dyslipidemia in MetS [12]. In addition, evidence from published research found that plasma miR-197 was inversely related to MI [24] and DM [13]. In this study, miR-197 was associated with increased MetS risk. As MetS serves as a critical role in the development of DM and CHD [1], our results provided the potential mechanism for the role of miR-126 and miR-197 in the development of noninfectious chronic diseases. However, little is known about the cellular origin of both miRNAs in the circulation. Thus, it is necessary to investigate the potential mechanism of the associations between miRNA-126 and miRNA-197 and MetS risk. Previous study has established the role of PA on reduction of MetS risk [5]. In this study, we validated that association successfully, consistent with the role of PA in the expression levels of miR-126 and miR-197. However, further adjustment of both miRNAs abolished that association. We speculated that the association between PA and MetS might partly dependant on the expression levels of miR-126 and miR-197. Our results should be explained with caution. First, the casecontrol study design has limited ability to investigate the causal roles of PA and miRNAs in the developments of MetS. Second, the modest sample size of this study may limit its statistical power. Third, a part of participants in this study were patients with cardiovascular diseases (CHD, stroke, and diabetes). Thus, the findings presented herein should be replicated in independent cohorts. In summary, this study validated the association between PA and MetS risk and established the roles for PA-related miRNAs (miR-126 and miR-197) in the development of MetS, suggesting that the association between PA and MetS risk might be partly mediated by miRNAs. Future studies are warranted to validate these results.
Endocrine Research
23 Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ. Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Ann Surg 2010; 251: 499–505 24 Zampetaki A, Willeit P, Tilling L, Drozdov I, Prokopi M, Renard JM, Mayr A, Weger S, Schett G, Shah A, Boulanger CM, Willeit J, Chowienczyk PJ, Kiechl S, Mayr M. Prospective study on circulating MicroRNAs and risk of myocardial infarction. J Am Coll Cardiol 2012; 60: 290–299 25 Vosa U, Vooder T, Kolde R, Vilo J, Metspalu A, Annilo T. Meta-analysis of microRNA expression in lung cancer. Int J Cancer 2013; 132: 2884–2893 26 Meng S, Cao JT, Zhang B, Zhou Q, Shen CX, Wang CQ. Downregulation of microRNA-126 in endothelial progenitor cells from diabetes patients, impairs their functional properties, via target gene Spred-1. J Mol Cell Cardiol 2012; 53: 64–72
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19 Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F. American Heart A, National Heart L, Blood I. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112: 2735–2752 20 Radom-Aizik S, Zaldivar F Jr, Leu SY, Adams GR, Oliver S, Cooper DM. Effects of exercise on microRNA expression in young males peripheral blood mononuclear cells. Clin Transl Sci 2012; 5: 32–38 21 Bye A, Rosjo H, Aspenes ST, Condorelli G, Omland T, Wisloff U. Circulating microRNAs and aerobic fitness – the HUNT-Study. PLoS One 2013; 8: e57496 22 Creemers EE, Tijsen AJ, Pinto YM. Circulating microRNAs: novel biomarkers and extracellular communicators in cardiovascular disease? Circ Res 2012; 110: 483–495
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Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
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201
Authors
J. Zhou1, Q. Zheng1, T. Xu2, D. Liao2, Y. Zhang2, S. Yang2, J. Hu2
Affiliations
1
Department of Cardiology, Wuhan 1st Hospital (Wuhan Hospital of Integrated Chinese and Western Medicine), Wuhan, China 2 Department of Endocrinology, Affiliated Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Key words ▶ exercise ● ▶ epigenetic ● ▶ metabolic syndrome ●
Abstract
received 16.07.2013 accepted 12.09.2013 Bibliography DOI http://dx.doi.org/ 10.1055/s-0033-1357139 Published online: October 17, 2013 Horm Metab Res 2014; 46: 201–205 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0018-5043 Correspondence J. Hu, MD Department of Endocrinology Affiliated Liyuan Hospital Tongji Medical College Huazhong University of Science and Technology Liyuan Village Wuhan 430077 Hubei China Tel.: + 86/27/83692 347 Fax: + 86/27/86779 910 [email protected]
▼
The aim of the study was to investigate the associations between physical activity (PA)-related miRNAs and metabolic syndrome (MetS). A casecontrol study was conducted in 209 subjects with MetS and 234 controls. The MetS was defined by the International Diabetes Foundation (IDF) criteria of 2005. Serum PA-related miRNAs were detected by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays. Association analysis was performed by logistic regression models. The expression levels of miR-126 and miR-130a were lower in the highest metabolic equivalent hours per week (MET-h/week) quartile than in the lowest quartile [miR-126: Q5 vs. Q1, median (5–95 %), 1.67 (0.54, 2.45) vs. 1.35 (0.45, 2.45), p = 0.012; miR130a: Q5 vs. Q1, median (5–95 %), 0.90 (0.44, 1.35) vs. 0.53 (0.26, 1.01), p < 0.001]. However,
Introduction
▼
Metabolic syndrome (MetS), a sub-health state comprising a cluster of risk factors including hypertension, altered glucose metabolism, dyslipidemia, and abdominal obesity, confers an individual at risk for type 2 diabetes (T2D) and cardiovascular disease (CVD) [1]. In addition, results from meta-analysis showed MetS was associated with increased risk of common cancers [2]. The persistent increased prevalence made MetS a serious public health concern [3]. In order to improve the preventive and therapeutic strategies, researchers need to revert back to elucidating the molecular mechanisms underlying MetS. Lifestyle modification is the most appealing approach for MetS because of its nontoxicity and high efficacy, and physical activity (PA) is a fundamental component [4]. Epidemiological
miR-197 exhibited a trend with increased MET-h/ week [Q5 vs. Q1, median (5–95 %), 1.35 (0.45, 2.63) vs. 2.18 (0.87, 4.77), p = 0.009]. MiR-126 increased MetS risk significantly while the effect of miR-197 was opposite (miR-126: OR = 1.37, 95 % CI 1.07–1.75; p = 0.012; miR-197: OR = 0.68, 95 % CI 0.51–0.92; p = 0.010). Individuals in the highest MET-h/week quartile had lower prevalence and odds rate of MetS compared with those in the lowest quartile (Q4 vs. Q1: OR = 0.58, 95 % CI 0.33–1.05; p for trend = 0.026). However, further adjustment of both PA associated miRNAs abolished that association. All these results suggested that the association between PA and MetS risk might partly depend on miR-126 and miR197. Supporting Information for this article is available online at http://www.thieme-connect.de/ ejournals/toc/hmr
evidence showed that PA could reduce the risk of MetS [5] and its components: obesity [6], hypertension [7], dyslipidemia [8, 9], and prediabetes/ diabetes [10]. MicroRNAs (miRNAs) are short (ranging from 19 to 22 nucleotides), endogenous, noncoding RNAs that negatively regulate gene expression at the posttranscriptional level by binding to the 3′ untranslated regions of messenger RNA targets [11]. Published studies have provided evidence for the significance role of circulating miRNAs in MetS [12, 13]. In addition, considerable evidence showed that PA could alert the miRNA expression [14–16]. Thus, we hypothesize that PA might influence the MetS risk by impacting on the expression levels of miRNAs. To address this hypothesis, we investigated the associations between PA-associated miRNAs and MetS risk in 209 persons with MetS and 234 controls.
Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Associations Between Physical Activity-related miRNAs and Metabolic Syndrome
202 Endocrine Research Subjects and Methods
▼
calculated by the equation 2 − ΔCT, in which ΔCT = cycle threshold (CT) miRNA – CT (cel-miR-39).
Study subjects and data collection Definition of the metabolic syndrome MetS was defined using the updated National Cholesterol Education Program/Adult treatment Panel III criteria for Asian Americans as having ≥ 3 of the following components: (1) waist circumference ≥ 90 cm for men or ≥ 80 cm for women; (2) TG ≥ 1.7 mmol/l; (3) HDL cholesterol < 1.03 mmol/l for men or < 1.30 mmol/l for women; (4) blood pressure ≥ 130/85 mm Hg (5); and fasting glucose ≥ 5.6 mmol/l [19].
Statistical analysis All statistical analyses were performed using SPSS 13.0 software. Categorical variables were expressed in percentages and continuous variables were expressed in means ± SD for normally distributed data or medians (5–95 %) for skewed parameters. Differences in the variables between MetS and controls were assessed by Student’s t-test (or Kruskal-Wallis test) for continuous variables and chi-square test for categorical variables. Confidence intervals (CIs) 95 % and β for miRNAs were tested by generalized linear models. Odds ratios (ORs) and 95 % CI for MetS risk were obtained by the logistic regression models. A 2-sided p-value < 0.05 was considered significant.
Assessment of PA Type, frequency, and average duration of the PA were obtained by the questionnaires. Separate metabolic equivalent (MET) hours per week were calculated for each activity to estimate energy expenditure for total PA using the formula: MET coefficient of activity × duration (hours per time) × frequency (times per week). MET coefficient used for leisure activities were: 3 for walking, 4 for biking, 4.5 for tai chi [17], 7.5 for jogging or swimming, 6 for playing ball games or doing exercise in gym, 5 for dancing, 4.5 for climbing [18], according to the compendium of physical fitness [18].
MiRNA selections and detections A total of 55 reported PA-associated miRNAs [14, 15] were selected in this study: miR-126, miR-130a, miR-151–5p, miR223, miR-363, let-7e, let-7i, miR-106a, miR-107, miR-1225–5p, miR-1238, miR-125a-5p, miR-130b, miR-142–3p, miR-142–5p, miR-145, miR-16, miR-17, miR-181b, miR-185, miR-18a, miR18b, miR-192, miR-193a-3p, miR-194, miR-197, miR-199a-3p, miR-199a-5p, miR-20a, miR-20b, miR-212, miR-22, miR-221, miR-29a, miR-29b, miR-29c, miR-30e, miR-326, miR-328, miR338–3p, miR-340, miR-365, miR-485–3p, miR-505, miR520d-3p, miR-590–5p, miR-629, miR-638, miR-652, miR-660, miR-7, miR-93, miR-939, miR-940, and miR-96. Total RNA was isolated from 200 μl of serum sample, according to the manufacturer’s instructions using the mirVana PARIS miRNA Isolation Kit (Ambion 1556, Austin, TX). The qRT-PCR assay was carried out using a Taqman miRNA PCR kit (Applied BioSystems, Foster City, CA) according to the manufacturer’s instructions. The input RNAs were reverse transcribed (RT) at 16 °C for 30 min, 42 °C for 30 min, and 85 °C for 5 min, using the miRNA specific stem-loop primers provided in the kit. RT products were 1:5 diluted and subjected to quantitative PCR in TaqMan miRNA probes on the Applied Biosystems 7 900 Sequence Detection System (Applied Biosystems). The reaction was carried out at 95 °C for 10 min, 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. Cel-miR-39 was selected as internal reference for qRT-PCR analysis. Levels of miRNAs were all normalized to cel-miR-39 and Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
Fig. 1 MiRNA expression levels in plasma according to the quartiles of MET. The cutoff values of MET (h/week) were < 2.40, 2.40–15.60, 15.75–30.60, and ≥ 31.20, respectively. p-Value was obtained by KruskalWallis test.
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A total of 209 persons with MetS and 234 age- and sex-matched controls were recruited from a garment factory in Wuhan (Hubei, China). All of them were retired employees who agreed to answer the questionnaires and provide blood samples. Information on general characteristics was collected by face to face interviews. According to the respondents’ self-reported smoking status and alcohol consumption, participants were grouped as current smokers, ex-smokers, nonsmokers, drinker, ex-drinker, and nondrinker. Family history of coronary heart disease (CHD), stroke, and diabetes were dichotomized as yes or no on the basis of the responses to questionnaires. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. A 5 ml fast blood was drawn into a coded vacuum coagulation tube after 24–48 h of the completion of the last physical activity. Serum triglyceride (TG), blood glucose, and high-density lipoprotein (HDL) cholesterol were measured by the laboratory in Affiliated Liyuan Hospital (Wuhan, China) using ARCHITECT ci8200, Abbott, USA. All participants provided informed consent. The ethical committees in the Tongji Medical College had approved this study.
Endocrine Research
MiRNAs
Expression levels of miRNA
Crude OR (95 % CI)
p-Value
Adjusted OR
(mean ± SD) miR-126 miR-197 miR-130a a
p-Value
a
(95 % CI)
Controls
MetS
1.64 ± 0.77 1.55 ± 0.65 0.90 ± 0.36
1.83 ± 0.86 1.39 ± 0.74 0.89 ± 0.39
1.37 (1.07, 1.75) 0.68 (0.51, 0.92) 0.88 (0.53, 1.46)
0.012 0.010 0.627
1.40 (1.08, 1.82) 0.66 (0.48, 0.9) 0.83 (0.48, 1.42)
203
Table 1 Association between physical activity-associated miRNAs and MetS risk.
0.012 0.009 0.499
Logistic regression model adjustments for age (continuous), gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke
Sample size Univariate model Multivariate model 1a Multivariate model 2b a
p-Trend
Q2
Q3
Q4
109 1.00 1.00 1.00
116 0.94 (0.56, 1.58) 0.94 (0.54, 1.65) 0.91 (0.54, 1.61)
108 0.67 (0.39, 1.15) 0.56 (0.32, 1.00) 0.56 (0.31, 1.01)
110 0.58 (0.34, 1.00) 0.58 (0.33, 1.05) 0.64 (0.35, 1.16)
Table 2 Odds ratio and 95 % CI for MetS according to the quartiles of MET (h/week).
0.015 0.026 0.083
Logistic regression model adjustments for age (continuous), gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke
b
Logistic regression model adjustments for co-variants mentioned above pulse miR-197 and miR-126
Results
▼
Descriptive characteristics of the subjects A total of 209 subjects with MetS and 234 controls were recruited in this cross-sectional study. The general characteristics of the subjects are summarized in Table S1. Briefly, MetS group has higher levels of BMI, waist, TG, HDL, blood pressure, fasting blood glucose, and past history of stroke, and diabetes (rate), but lower MET-h/week and smoking rate. No significant differences were observed between MetS and controls in terms of the distribution of age, sex, drinking status, and past history of CHD.
Relationship between PA and miRNA expression levels in plasma Serum expression levels of 55 miRNAs were detected and 3 miRNAs including miR-197, miR-126, and miR-130a were significantly related with PA. The expression levels of miR-126, and miR-130a were lower in the highest MET-h/week quartile than in the lowest quartile [miR-126: Q5 vs. Q1, median (5–95 %), 1.67 (0.54, 2.45) vs. 1.35 (0.45, 2.45), p = 0.012; miR-130a: Q5 vs. Q1, median (5–95 %), 0.90 (0.44, 1.35) vs. 0.53 (0.26, 1.01), ▶ Fig. 1). However, miR-197 exhibited a trend with p < 0.001, ● increased MET-h/week [Q5 vs. Q1, median (5–95 %), 1.35 (0.45, ▶ Fig. 1. 2.63) vs. 2.18 (0.87, 4.77), p = 0.009, ●
Associations between PA-related miRNAs and MetS risk We further analyzed the associations between PA-associated miRNAs mentioned above and MetS risk. MiR-126 increased MetS risk significantly while the effect of miR-197 was opposite (miR-126: OR = 1.37, 95 % CI 1.07–1.75; p = 0.012; miR-197: OR = 0.68, 95 % CI 0.51–0.92; p = 0.010). Similar results were obtained after adjustment for age, gender, smoking, alcohol con▶ Table 1). sumption and history of CHD, diabetes, and stroke (● No significant association was found between miR-130a and ▶ Table 1). MetS risk (●
Association between PA and MetS risk Individuals in the highest MET-h/week quartile had lower preva▶ Fig. 2) and odds rate of MetS compared with those in lence (● the lowest quartile (Q4 vs. Q1: OR = 0.58, 95 % CI 0.33–1.05; p for ▶ Table 2) after adjustment for age (continuous), trend = 0.026, ●
Fig. 2 Prevalence of the metabolic syndrome by quartile of MET (h/ week). The cutoff values of MET (h/week) were < 2.40, 2.40–15.60, 15.75–30.60, and ≥ 31.20, respectively.
gender, smoking, alcohol consumption and history of CHD, diabetes, and stroke. When MET-h/week was entered in the logistic regression model as a continuous variable, the full adjustment OR was 0.997 and 95 % CI was 0.978–0.999 (data not shown). However, that association was abolished when miR-197 and ▶ Table 2). miR-126 were included in the model (p = 0.083, ●
Discussion
▼
In this case-control study, we explored the associations between PA-related miRNAs and MetS risk. MiR-126 was significantly associated with increased MetS risk while miR-197 served as a protective role in the development of MetS. PA could reduce the MetS risk. Further adjustment of miRNA-126 and miRNA-197 abolished the association between PA and MetS risk. All these results suggested that PA might decrease MetS risk partly by regulating the expression levels of miRNA. Previous studies supported the roles of miRNAs in response to PA in neutrophil [15], peripheral blood mononuclear cells [20], natural killer cells [14], and in the plasma [16] and serum [21]. Bye et al. found the expression levels of miR-210, miR-222, and miR-21 in serum were higher in participants with low maximal
Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
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Quartiles of MET Q1
204 Endocrine Research Acknowledgements
▼
The authors would like to thank all study subjects for participating in this study as well as all volunteers for assisting in collecting the samples and data.
Conflict of Interest
▼
The authors declare no potential conflicts of interest with respect to the authorship and/or publication of this article.
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Zhou J et al. miRNAs and Metabolic Syndrome … Horm Metab Res 2014; 46: 201–205
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oxygen uptake, suggesting that a potential value of measuring circulating miRNAs as biomarkers of aerobic fitness [21]. It assumed that release of these 3 miRNAs from the endothelium in healthy subjects with low maximal oxygen uptake could be related to subclinical artherosclerosis, hypoxia or inflammation [21]. In this study, we successfully validate the relationship between 3 miRNAs (miR-197, miR-126, and miR-130a) and PA. Future studies are needed to further investigate the potential mechanism on how PA impacts circulating expression of miRNAs. Circulating miRNAs are widely reported as potential biomarkers for disease development [13, 22, 23], although their exact mechanism of release is largely unclear. To our knowledge, miR-126 received wide concern in epidemiology studies. Prospective study found that circulating miR-126 showed a positive association with incidence of myocardial infarction (MI) [24] and a negative association with type 2 diabetes (DM) [13]. Data from meta-analysis showed miR-126 was significantly downregulated in patients with lung cancer [25]. In addition, the experimental study provided evidence that miR-126 is downregulated in endothelial progenitor cells from diabetic patients [26]. In this study, Serum miR-126 was significantly associated with increased MetS risk, consistent with its role in MI. MiR-197 in blood was reported to be correlated with BMI, suggesting its potential contribution to dyslipidemia in MetS [12]. In addition, evidence from published research found that plasma miR-197 was inversely related to MI [24] and DM [13]. In this study, miR-197 was associated with increased MetS risk. As MetS serves as a critical role in the development of DM and CHD [1], our results provided the potential mechanism for the role of miR-126 and miR-197 in the development of noninfectious chronic diseases. However, little is known about the cellular origin of both miRNAs in the circulation. Thus, it is necessary to investigate the potential mechanism of the associations between miRNA-126 and miRNA-197 and MetS risk. Previous study has established the role of PA on reduction of MetS risk [5]. In this study, we validated that association successfully, consistent with the role of PA in the expression levels of miR-126 and miR-197. However, further adjustment of both miRNAs abolished that association. We speculated that the association between PA and MetS might partly dependant on the expression levels of miR-126 and miR-197. Our results should be explained with caution. First, the casecontrol study design has limited ability to investigate the causal roles of PA and miRNAs in the developments of MetS. Second, the modest sample size of this study may limit its statistical power. Third, a part of participants in this study were patients with cardiovascular diseases (CHD, stroke, and diabetes). Thus, the findings presented herein should be replicated in independent cohorts. In summary, this study validated the association between PA and MetS risk and established the roles for PA-related miRNAs (miR-126 and miR-197) in the development of MetS, suggesting that the association between PA and MetS risk might be partly mediated by miRNAs. Future studies are warranted to validate these results.
Endocrine Research
23 Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ. Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Ann Surg 2010; 251: 499–505 24 Zampetaki A, Willeit P, Tilling L, Drozdov I, Prokopi M, Renard JM, Mayr A, Weger S, Schett G, Shah A, Boulanger CM, Willeit J, Chowienczyk PJ, Kiechl S, Mayr M. Prospective study on circulating MicroRNAs and risk of myocardial infarction. J Am Coll Cardiol 2012; 60: 290–299 25 Vosa U, Vooder T, Kolde R, Vilo J, Metspalu A, Annilo T. Meta-analysis of microRNA expression in lung cancer. Int J Cancer 2013; 132: 2884–2893 26 Meng S, Cao JT, Zhang B, Zhou Q, Shen CX, Wang CQ. Downregulation of microRNA-126 in endothelial progenitor cells from diabetes patients, impairs their functional properties, via target gene Spred-1. J Mol Cell Cardiol 2012; 53: 64–72
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19 Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F. American Heart A, National Heart L, Blood I. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112: 2735–2752 20 Radom-Aizik S, Zaldivar F Jr, Leu SY, Adams GR, Oliver S, Cooper DM. Effects of exercise on microRNA expression in young males peripheral blood mononuclear cells. Clin Transl Sci 2012; 5: 32–38 21 Bye A, Rosjo H, Aspenes ST, Condorelli G, Omland T, Wisloff U. Circulating microRNAs and aerobic fitness – the HUNT-Study. PLoS One 2013; 8: e57496 22 Creemers EE, Tijsen AJ, Pinto YM. Circulating microRNAs: novel biomarkers and extracellular communicators in cardiovascular disease? Circ Res 2012; 110: 483–495
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