DNA AND CELL BIOLOGY Volume 33, Number 11, 2014 ª Mary Ann Liebert, Inc. Pp. 816–822 DOI: 10.1089/dna.2014.2511
High Serum Level of Matrix Metalloproteinase 9 and Promoter Polymorphism - 1562 C:T as a New Risk Factor for Metabolic Syndrome Suraj S. Yadav,1 Raju K. Mandal,2 Manish K. Singh,1 Archna Verma,3 Pradeep Dwivedi,1 Rishi Sethi,4 Kauser Usman,5 and Sanjay Khattri1
The altered matrix metalloproteinases (MMPs) have been suggested in the pathophysiology of metabolic syndrome (MetS). Genetic variants in the promoter region of MMP1 and MMP9 genes may modulate an individual’s susceptibility to MetS. The aim of this study was to determine the frequency of MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms and the correlation with serum levels of MMP1 and MMP9 in MetS susceptibility. On the basis of anthropometric profile and laboratory investigations, 180 confirmed MetS patients and 190 unrelated healthy controls of similar ethnicity were genotyped for MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms by using the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) methods. In addition, serum levels of MMP1 and MMP9 were quantified by ELISA. We found that the serum level of MMP9 was significantly higher in MetS patients. Variant genotype TT of MMP9 - 1562 demonstrated increased risk (odds ratio [OR] = 3.70, p = 0.015) of MetS. Similarly, variant allele T (OR = 1.77, p = 0.002) and combined genotype CT + TT (OR = 1.81, p = 0.057) also showed a significantly higher risk. The CT and TT genotypes of MMP9 - 1562 polymorphism contributed to high serum levels of MMP9 in MetS patients. However, no such association was observed with the MMP1 serum level and - 519 A:G polymorphism. Our results suggest that a higher serum level of MMP9 in the presence of MMP9 polymorphism - 1562 C:T might be a risk factor for the development of MetS. The MMP9 enzyme activity might be a significant indicator in the screening of MetS patients.
Introduction
M
etabolic syndrome (MetS) is a major health problem around the world because of a modern lifestyle rising unexpectedly (Cornier et al., 2008). MetS is associated with a high mortality rate and plays a key role in cardiovascular disease (Isomaa et al., 2001; McNeill et al., 2005). The incidence rates of MetS vary worldwide, it affects an estimated 30% and 15% of the population in the United States and Europe, respectively (Cameron et al., 2004; Gallagher et al., 2011). The prevalence of MetS has significantly increased in India and affects an estimated 19.52% of the urban population (Sawant et al., 2011). Despite these dismal statistics, the etiology of MetS remains largely unknown. Therefore, finding a strategy for the prevention of MetS is a crucial medical challenge. Mets is characterized by a group of cardiovascular risk factors, including visceral obesity, hypertension, dyslipidemia, glucose intolerance, and insulin resistance (Eckel et al.,
2005). Considerable evidence demonstrated that genetic factors are the major contributors to MetS susceptibility (Pollex and Hegele, 2006). Moreover, genome-wide association studies (GWASs) have also identified various chromosomal regions that are associated with MetS risk (Francke et al., 2001). Thus, it is anticipated that the identification of host genetic factors for MetS risk would greatly assist in the control of this disease. Matrix metalloproteinases (MMPs) are a family of zincdependent endopeptidases, which are involved in physiological and pathological processes such as degradation and remodeling of the extracellular matrix (ECM) (Nagase et al., 2006). Earlier reports suggested the role of MMPs in the pathogenesis of MetS (Hopps et al., 2013; Yadav et al., 2014a, 2014b). Matrix metalloproteinase 1 (MMP1) (also known as interstitial collagenase) is a major proteolytic enzyme specifically to degrade type 1 collagen proteins, which are the main components of the interstitial matrix ( Jones et al., 2003). A single-nucleotide polymorphism (SNP) A:G found in the
1
Department of Pharmacology and Therapeutics, King George’s Medical University, Lucknow, India. College of Medicine, King Khalid University Hospital, Riyadh, Kingdom of Saudi Arabia. Department of Urology, Sanjay Gandhi Post Graduate Insitute of Medical Sciences, Lucknow, India. Departments of 4Cardiology and 5Internal Medicine, King George’s Medical University, Lucknow, India.
2 3
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promoter region of - 519 resulting in guanine to adenine substitution has been associated with altered MMP1 gene expression (Rutter et al., 1998). In addition, MMP9 (gelatinase B) has the ability to cleave type IV collagen, a major component of the basement membrane (Van den Steen et al., 2002). Several polymorphisms have been identified in the promoter regions, among them C:T polymorphism located in the - 1562 region has been shown to modulate the transcriptional activity of the MMP9 gene and associated with cardiovascular diseases (Peters et al., 1999; Po¨lla¨nen et al., 2001). Therefore, it is reasonable to suspect that functional genetic polymorphisms in the regulatory region of MMP1 and MMP9 genes may affect their circulating levels and predispose to MetS disease. To our knowledge, no study has addressed the association of these polymorphisms with MetS. Therefore, this study was aimed to compare the genotype and allelic frequencies of the functional polymorphisms of MMP1 and MMP9 between MetS and healthy controls. In addition, serum levels and functional relevance of MMP1 and MMP9 genes were also evaluated. Materials and Methods Study subjects
A total of 180 MetS patients were recruited from the Department of Medicine, King George Medical University, Lucknow, according to modified NCEP-ATP III criteria (Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, 2001; Misra et al., 2005) for Asian Indians. Age- and ethnicity-matched healthy individuals (n = 190) were recruited as controls who were without MetS, nonalcoholic, nondiabetic, and who had no cardiac, respiratory, inflammatory, endocrine, or other metabolic diseases. All the participants in the study were unrelated individuals of similar ethnicity from Lucknow and other adjoining cities of northern India. Information on demographic features was obtained through personal interview using a standard clinical pro forma. The study was approved by the ethics review board and written informed consent was obtained from all participants before entering the study. Anthropometric and laboratory investigations
The waist circumference (WC) was measured for determining obesity. We have followed the modified NCEP-ATP III (Misra et al., 2005) criteria for the Indian population. WC was measured midway between the margin of the lowest ribs and the iliac crest, at the point of minimal inspiration. The systolic and diastolic blood pressure (SDP and DBP) in subjects was measured for diagnosis of MetS. In biochemical investigations, we estimated fasting plasma glucose (FPG) in a blood sample without preliminary treatment by using a Cobas C-111analyzer (Roche) and related kit. Serum lipid profile was also investigated with estimation of total cholesterol (TC), high-density lipoprotein-cholesterol (HDLC), and triglycerides (TG) by using a Cobas C-111analyzer (Roche) and a related kit. DNA extraction
Blood samples (5.0 mL) from MetS patients and controls were collected in EDTA vials and stored at - 20C until required. Genomic DNA was extracted from peripheral
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whole blood according to a salting-out technique (Miller et al., 1988). Gene amplification and genotyping
The polymorphic sites in MMP1 - 519 A:G and MMP9 - 1562 C:T genes were amplified by polymerase chain reaction (PCR) combined with restriction fragment length polymorphism (RFLP) using primers implying conditions, as previously described (Drzewoski et al., 2008; Wang et al., 2011). The PCR cocktail contained 10 pmol of each primer; 100 ng genomic DNA; 0.25 mm, each of deoxyribonucleotide triphosphate; and a 1X PCR buffer containing 10 mM Tris HCl, pH 8.6, 50 mM KCl, 1.5 mM MgCl2, and 0.5 U of Taq polymerase (Bangalore Genei). The amplified products of MMP1 and MMP9 were digested with KpnI, SphI (New England Biolabs) overnight at 37C, respectively. Subsequently, fragments of these polymorphisms were visualized on 2% agarose gels and 10% polyacrylamide gel electrophoresis to identify the wild, heterozygous, and variant genotypes. Quality control
For quality control, positive and negative controls were used in each genotyping assay and 5% of randomly selected duplicates were included. No discrepancy between duplicates was observed in the genotyping, which ensured the absence of genotyping error. ELISA for serum MMP level
The serum MMP1 and MMP9 levels were measured by using a commercially available kit, according to the manufacturer’s protocol (Antagene) with sensitivity of < 5 pg/mL. Statistical analyses
SNPalyze software (Dynacom) was employed to calculate the Hardy–Weinberg equilibrium (HWE). Binary logistic regression was used to test the association of genotypes, alleles, and combined genotypes. Patients and controls were used as dependent variables and genotypes were used as covariates. Risk was expressed as odds ratio (OR) with 95% confidence intervals (CI). The wild-type genotype/allele of MMP1 and MMP9 polymorphisms was taken as reference for risk analysis. The distribution of MMP1 and MMP9 levels of genotypes was assessed by the D’Agostino and Pearson omnibus normality test. Based on the results of the normality test, the association of the genotype with the MMP level was analyzed by analysis of variance or the Kruskal–Wallis test followed by an appropriate posttest. All the statistical analyses were conducted by SPSS software, version 21 (SPSS). A p-value < 0.05 was taken as statistically significant. Power analysis was performed by G power software version 3.1 (Faul et al., 2007). Results Profiling of risk factors in MetS patients and control group
A total of 370 individuals (180 MetS and 190 controls) were analyzed in this study. Among the total patients, 68 (37.77%) were male and 112 (62.22%) were female, mean age 39 – 12.54 and 36 – 14.67 years, respectively. Clinical characteristics of
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Table 1. Clinical Components of Metabolic Syndrome Patients and Controls Metabolic risk factors
Controls (n = 190)
Patients (n = 180)
WC (cm) 71.27 – 15.13 88.67 – 10.38 FPG (mg/dL) 97.95 – 11.66 107.29 – 19.94 SBP (mmHg) 123.01 – 7.48 136.81 – 9.90 DBP (mmHg) 82.01 – 3.81 87.31 – 6.88 TG (mg/dL) 101.73 – 46.38 169.81 – 77.32 HDL-C (mg/dL) 54.62 – 8.95 39.25 – 12.05
p-Value < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
Data represented as mean – SD. Significant values (in boldface) showed increased risk. DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein-cholesterol; SBP, systolic blood pressure; TG, triglycerides; WC, waist circumference.
the MetS patients and controls are represented in Table 1. As expected, there was a high degree of statistical difference between the metabolic risk factors of MetS and controls. WC (88.67 – 10.38 vs. 71.27 – 15.13 cm, p < 0.01), SBP (136.81 – 9.90 vs. 123.01 – 7.48 mmHg, p < 0.01), and DBP (87.31 – 6.88 vs. 82.01 – 3.81 mmHg, p < 0.01) were significantly different in MetS patients compared with healthy controls. Similarly, FPG (107.29 – 19.94 vs. 97.95 – 11.66 mg/dL, p < 0.01), HDL-C (39.25 – 12.05 vs. 54.62 – 8.95 mg/dL, p < 0.01), and TG (169.81 – 77.3 vs. 101.73 – 46.38 mg/dL, p < 0.01) were also significantly altered in MetS patients. Serum levels of MMP1 and MMP9 in MetS patients and controls
We compared the serum levels of MMP1 and MMP9 between controls and MetS patients (Fig. 1A). Our results demonstrated that the mean level of serum MMP9 was higher in MetS patients (73.93 – 33.59 ng/mL) compared with controls (34.78 – 12.06 ng/mL) and represented a significant difference p < 0.0001. However, the MMP1 level was almost similar in MetS patients (7.9 – 3.74 ng/mL) and controls (6.99 – 3.97 ng/mL) and did not reveal any significant risk. Correlation of the serum MMP1 and MMP9 levels with clinical characteristics of MetS
We performed a case-only analysis to investigate whether any possible association existed between the serum levels of MMP1 and MMP9 genes and clinical characteristics of MetS patients (Table 2). A statistically significant correlation was observed with WC, FPG, TC, TG, HDL-C, DBP, and the serum level of MMP9, while MMP1 was marginally correlated with WC only. Genotype and allelic frequency distribution of MMP1 - 519 A:G and MMP9 - 1562 C:T between MetS and controls
The frequency distributions of MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms were consistent with HWE in controls. Table 3 shows the distribution of genotypes and frequency of MMP1 and MMP9 polymorphisms in MetS patients and controls. The obtained results revealed a higher frequency of CT (37.2% vs. 28.5%) and TT (7.8% vs. 2.6%) genotypes in MetS patients compared with controls and showed a 1.6-fold (OR = 1.64, 95% CI = 1.05–2.55, p = 0.028)
FIG. 1. (A) Serum level of MMP9 and MMP1 genes in MetS and control. Data represented as mean – SD. (B) Association between MMP1 - 519 A:G polymorphism and the serum level in MetS and control. (C) Association between MMP9 - 1562 C:T polymorphism and the serum level in MetS and control. MetS, metabolic syndrome; NS, not significant. and 3.7-fold (OR = 3.70, 95% CI = 1.29–10.63, p = 0.015) increased risk of MetS. We combined the variant TT genotype with the heterozygous CT genotype (i.e., CT + TT), assuming a dominant genetic model, and found that the frequency of the combined genotype (CT + TT) was higher in MetS patients (45%) than in controls (31.1%); the result showed significant risk (OR = 1.81, 95% CI = 1.18–2.77, p = 0.006) for MetS. Similarly, the variant allele (T) was more frequent in MetS patients (26.4%) and demonstrated a 1.7-fold increased risk (OR = 1.77, 95% CI = 1.23–2.52, p = 0.002) for MetS. However, genotype and allelic frequency
MMP9 AND METABOLIC SYNDROME
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Table 2. Correlation (Pearson Correlation) Between Clinical Characteristics of Metabolic Syndrome Patients MMP1
MMP9
Clinical risk factors
r-Value
p-Value
r-Value
p-Value
WC (cm) FPG (mg/dL) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) SBP (mmHg) DBP (mmHg)
0.1843 0.1210 0.1284 0.1271 - 0.0430 0.0847 0.0863
0.005 0.096 0.089 0.081 0.556 0.245 0.255
0.3607 0.3269 0.2239 0.3937 - 0.3037 0.1276 0.3489
< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.507 < 0.01
Significant values (in boldface) showed increased risk. TC, total cholesterol.
distributions of the MMP1 - 519 A:G polymorphism were not found significant in patients and controls. A post hoc power of the study was calculated to detect the probability of association between MMP1 and MMP9 polymorphisms and MetS at the 0.05 level of significance, assuming a small effect size (w = 0.20). This analysis revealed that the current study has 86% power to detect the association. Combined effect of MMP9 - 1562 C:T and MMP1 - 519 A:G gene polymorphisms with MetS risk
In addition, we performed all possible interactions of MMP9 C:T and MMP1 A:G gene polymorphisms (Table 4). We found that interaction between the heterozygous genotype (CT-AG) of MMP9 and MMP1 polymorphisms showed a significant risk with MetS. Association of genotype–phenotype relationship of MMP1 and MMP9 serum level with MetS
A significant association of MMP9 - 1562 C:T polymorphism and serum MMP9 level was observed. The homozygous mutant TT ( p < 0.001) carrier showed higher
levels of MMP9 than wild-type CC and heterozygous CT genotypes. Similarly, heterozygous CT ( p < 0.001) genotype was significantly associated with higher serum MMP9 levels as compared to the wild-type CC (Fig. 1B). On the other hand, MMP1 - 519 A:G polymorphism failed to demonstrate any association (Fig. 1C). Discussion
Genetic association studies have been helpful in the detection of genetic susceptibility genes. SNPs may contribute greatly to the understanding of both interindividual and interpopulation differences, given the exposure to similar environmental and lifestyle factors. The expansion of the adipose tissue and enlargement of fat cells is accompanied by a remodeling of the stromal matrix performed mainly by MMPs (Halberg et al., 2008). Metalloproteinase are factors that regulate the composition of the ECM and they stimulate cytokines secreted by macrophages and endothelial cells (Lemaıˆtre et al., 2001). Pro- and anti-inflammatory cytokines secreted by the adipose tissue modulate the activity of MMPs and their inhibitors. Boden (2008) suggested that free fatty acid and insulin promote the activation of MAP-kinase activity, which is responsible for proinflammatory cytokines, and promote the activation of MMP2 and MMP9. The impaired glucose level affects the activity of MMPs through hyperproduction of advanced glycation end products (AGEs) with subsequent activation of AGE receptors and oxidative stress (Ishibashi et al., 2010; Kar et al., 2010). Moreover, oxidized LDL favors the inflammatory process and upregulates the expression of macrophage MMP9 (Xu et al., 1999; Kojima et al., 2010). MMPs also play a major role in vascular remodeling, interaction of the endothelial basement membrane, and the ECM actively participating in developing complications of MetS. The increased ECM accumulation in the basement membrane is linked with a variety of metabolic abnormalities and oxidative stress associated with MetS (Hayden et al., 2005). Recently, Lobmann (2006) reported altered levels of MMPs in the cultivated fibroblast of diabetic patients. So far, no association studies have been executed for MetS to evaluate
Table 3. MMP1 and MMP9 Gene Polymorphisms and Susceptibility to Metabolic Syndrome
Genotypes
Controls
Patients
n = 190 (%)
n = 180 (%)
MMP1 - 519 A:G (rs1144393) AA 104 (54.7) AG 68 (35.8) GG 18 (9.5) AG + GG 86 (45.3) Allele A 276 (72.6) Allele G 104 (27.4) MMP9 - 1562 C:T (rs3918242) CC 131 (68.9) CT 54 (28.5) TT 5 (2.6) CT + TT 59 (31.1) Allele C 316 (83.2) Allele T 64 (16.8)
OR (95% CI)
88 71 21 92 247 113
(48.9) (39.4) (11.7) (51.1) (68.6) (31.4)
Reference 1.23 (0.79–1.91) 1.37 (0.69–2.75) 1.26 (0.84–1.90) Reference 1.21 (0.88–1.66)
99 67 14 81 265 95
(55.0) (37.2) (7.8) (45.0) (73.6) (26.4)
Reference 1.64 (1.05–2.55) 3.70 (1.29–10.63) 1.81 (1.18–2.77) Reference 1.77 (1.23–2.52)
For allele, total number of chromosomes in controls-380 and MetS patients-360. Significant values (in boldface) showed increased risk. CI, confidence interval; MetS, metabolic syndrome; OR, odds ratio.
p-Value
0.346 0.362 0.261 0.230 0.028 0.015 0.006 0.002
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Table 4. Interaction Between MMP9 - 1562 C:T and MMP1 - 519 A:G Gene Polymorphisms in Metabolic Syndrome Patients and Healthy Controls Controls Cases Combined genotype n = 190 (%) n = 180 (%) CC-AA CC-AG CC-GG CT-AA CT-AG CT-GG TT-AA TT-AG TT-GG
100 19 12 4 49 1 0 0 5
(52.6) (10) (6.3) (2.1) (25.8) (0.5) (2.6)
74 14 12 9 57
(41.1) (7.8) (6.7) (5) (31.7) — 4 (2.2) 1 (0.6) 9 (5.0)
OR (95% CI)
p-Value
Reference 0.99 (0.46–2.11) 1.35 (0.57–3.17) 3.04 (0.90–10.25) 1.57 (0.96–2.55) NC NC NC 2.43 (0.78–7.55)
0.991 0.490 0.902 0.049 NC NC NC 0.124
Significant values (in boldface) showed increased risk. NC, not calculated.
MMP9 and MMP1 polymorphisms. Functional polymorphisms in a coding region of the gene may result in deformed proteins. Similarly, variants in promoter regions affect binding of the transcription factor and possibly reduce transcript levels (Pastinen et al., 2004). In the present study, we found an increased serum level of MMP9 in MetS patients and a significant correlation with clinical characteristics. We also investigated the role of MMP9 - 1562 C:T polymorphism in the serum level of MMP9 in MetS. The - 1562 C:T polymorphism has shown a significant association with serum MMP9 levels and - 1562 C:T genotypes, suggesting that the increased frequency of the minor allele of the - 1562 C:T polymorphism may function as a significant risk factor of MetS. Together, these findings indicated that the MMP9 polymorphism has important effects on MMP9 serum levels and MetS risk. In vitro studies have shown that C:T substitution at the - 1562 position results in the loss of binding of a nuclear repressor protein and thus leading to increased MMP9 expression (Zhang et al., 1999). Our results were consistent with earlier studies, Andrade et al. (2012) found a strong association of the - 1562 C:T polymorphism with obesity and also reported higher levels of MMP9 in obese patients. Similar effects of MMP9 polymorphism were reported by Belo et al. (2012) in obese children. Blankenberg et al. (2003) reported higher plasma MMP9 levels with - 1562T allele carriers in cardiovascular disease. Besides, functional studies have revealed that the T allele of this SNP has significantly higher mRNA expression and protein levels compared with the C allele (Medley et al., 2004). Moreover, altered plasma levels of MMP9 were significantly observed in MetS and hypertension patients (Derosa et al., 2006; Hopps and Caimi, 2012). On the other hand, we did not find any difference in the level of MMP1 in MetS patients. MMP1 - 519 A:G polymorphism did not reveal any significant risk for MetS, indicating that this polymorphism might not be a major determinant of MMP1 levels and MetS risk. It is likely that some other unidentified polymorphisms may affect the gene expression and MMP1 levels. However, effects of - 519 A:G polymorphism have been reported in other diseases like coronary artery disease (Xu et al., 2013) and myocardial infarction (Pearce et al., 2005). Thus, further study may be necessary to elucidate the role of MMP1 SNPs/levels in the progress of MetS. In our
study, we found that the combination (CT-AG) of MMP9 and MMP1polymorphisms had a multiplicative effect on the risk of MetS. In conclusion, these results suggest that MetS is associated with elevated serum levels of MMP9. Moreover, our study also revealed that - 1562 C:T polymorphism of the MMP9 gene increased the risk of MetS and expression of MMP9 levels. Hence, it can be considered as a potential prognostic marker for MetS patients. It is biologically possible that these findings may benefit from the use of an inhibitor of MMPs to prevent MetS disease. Additionally, further research is needed to understand the molecular mechanisms and regulation of MMPs in the pathophysiology of MetS. Acknowledgment
The authors wish to thank the technical staff of the Department of Pharmacology and Medicine, KGMU, Lucknow. The author S.S.Y. is thankful to the Indian Council of Medical Research (ICMR) for providing a senior research fellowship (SRF) during the course of study. Funding
This study was supported by the research grant No. 52/15/ 2008-BMS of the Indian Council of Medical Research (ICMR) New Delhi, India. Disclosure Statement
No competing financial interests or other conflicts of interests exist. References
Andrade, V.L., Fernandes, K.S., Bosco, A.A., Tanus-Santos, J.E., and Sandrim, V.C. (2012). Functional polymorphism located in MMP-9 gene promoter is strongly associated with obesity. DNA Cell Biol 31, 1054–1057. Belo, V.A., Souza-Costa, D.C., Luizon, M.R., Lanna, C.M., Carneiro, P.C., Izidoro-Toledo, TC., Ferraz, K.C., and TanusSantos, J.E. (2012). Matrix metalloproteinase-9 genetic variations affect MMP-9 levels in obese children. Int J Obes (Lond) 36, 69–75. Blankenberg, S., Rupprecht, H.J., Poirier, O., Collins, A., and Ye, S. (2003). Plasma concentrations and genetic variation of matrix metalloproteinase 9 and prognosis of patients with cardiovascular disease. Circulation 107, 1579–1585. Boden, G. (2008). Obesity and free fatty acids. Endocrinol Metab Clin North Am 37, 635–646. Cameron, A.J., Shaw, J.E., and Zimmet, P.Z. (2004). The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am 33, 351–375. Cornier, M.A., Dabelea, D., Hernandez, T.L., Lindstrom, R.C., Steig, A.J., Stob, N.R., Van, Pelt, R.E., Wang, H., and Eckel, R.H. (2008). The metabolic syndrome. Endocr Rev 29, 777– 822. Derosa, G., D’Angelo, A., Ciccarelli, L., Piccinni, M.N., Pricolo, F., Salvadeo, S., Montagna, L., Gravina, A., Ferrari, I., Galli, S., Paniga, S., Tinelli, C., and Cicero, A.F. (2006). Matrix metalloproteinase-2, -9, and tissue inhibitor of metalloproteinase1 in patients with hypertension. Endothelium 13, 227–2231. Drzewoski, J., Sliwin´ska, A., Przyby1owska, K., Sliwin´ski, T., Kasznicki, J., Zurawska-Klis, M., Kosmalski, M., and Majsterek, I. (2008). Gene polymorphisms and antigen levels of
MMP9 AND METABOLIC SYNDROME
matrix metalloproteinase-1 in type 2 diabetes mellitus coexisting with coronary heart disease. Kardiol Pol 66, 1042–1048. Eckel, R.H., Grundy, S.M., and Zimmet, P.Z. (2005). The metabolic syndrome. Lancet 365, 1415–1428. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. (2001). Executive summary of the Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 285, 2486–2497. Faul, F., Erdfelder, E., Lang, A.G., and Buchner, A.G. (2007). Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39, 175. Francke, S., Manraj, M., Lacquemant, C., Lecoeur, C., Lepreˆtre, F., Passa, P., Hebe, A., Corset, L., Yan, S.L., Lahmidi, S., Jankee, S., Gunness, T.K., Ramjuttun, U.S., Balgobin, V., Dina, C., and Froguel, P. (2001). A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27. Hum Mol Genet 10, 2751–2765. Gallagher, E.J., Leroith, D., and Karnieli, E. (2011). The metabolic syndrome—from insulin resistance to obesity and diabetes. Med Clin North Am 95, 855–873. Halberg, N., Wernstedt-Asterholm, I., and Scherer, P.E. (2008). The adipocyte as an endocrine cell. Endocrinol Metab Clin North Am 3, 753–768. Hayden, M.R., Sowers, J.R., and Tyagi, S.C. (2005). The central role of vascular extracellular matrix and basement membrane remodeling in metabolic syndrome and type 2 diabetes: the matrix preloaded. Cardiovasc Diabetol 4, 9. Hopps, E., and Caimi, G. (2012). Matrix metalloproteinases in metabolic syndrome. Eur J Int Med 23, 99–104. Hopps, E., Lo Presti, R., Montana, M., Noto, D., Averna, M.R., and Caimi, G. (2013). Gelatinases and their tissue inhibitors in a group of subjects with metabolic syndrome. J Invest Med 61, 978–983. Ishibashi, T., Kawaguchi, M., Sugimoto, K., Uekita, H., Sakamoto, N., Yokoyama, K., Maruyama, Y., and Takeishi, Y. (2010). Advanced glycation end product-mediated matrix metalloproteinases-9 and apoptosis via renin-angiotensin system in type 2 diabetes. J Atheroscler Thromb 17, 578–589. Isomaa, B., Almgren, P., Tuomi, T., Forse´n, B., Lahti, K., Nisse´n, M., Taskinen, M.R., and Groop, L. (2001). Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24, 683–689. Jones, C.B., Sane, D.C., and Herrington, D.M. (2003). Matrix metalloproteinases: a review of their structure and role in acute coronary syndrome. Cardiovasc Res 59, 812–823. Kar, S., Subbaram, S., Carrico, P.M., and Melendez, J.A. (2010). A critical link between free radicals, matrix remodeling and degenerative disease. Respir Physiol Neurobiol 174, 299–306. Kojima, C., Ino, J., Ishii, H., Nitta, K., and Yoshida, M. (2010). MMP-9 inhibition by ACE inhibitor reduces oxidized LDLmediated foam-cell formation. J Atheroscler Thromb 17, 97–105. Lemaıˆtre, V., O’Byrne, T.K., Borczuk, A.C., Okada, Y., Tall, A.R., and D’Armiento, J. (2001). ApoE knockout mice expressing human matrix metalloproteinase-1 in macrophages have less advanced atherosclerosis. J Clin Invest 107, 1227–1234. Lobmann, R. (2006). Differential effects of PDGF-BB on matrix metalloproteinases and cytokines release in fibroblasts of Type 2 diabetic patients and normal controls in vitro. J Diabetes Complications 20, 105–112.
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McNeill, A.M., Rosamond, W.D., Girman, C.J., Golden, S.H., Schmidt, M.I., East, H.E., Ballantyne, C.M., and Heiss, G. (2005). The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 28, 385–390. Medley, T.L., Cole, T.J., Dart, A.M., Gatzka, C.D., and Kingwell, B.A. (2004). Matrix metalloproteinase-9 genotype influences large artery stiffness through effects on aortic gene and protein expression. Arterioscler Thromb Vasc Biol 24, 1479–1484. Miller, S.A., Dykes, D.D., and Polesky, H.F. (1988). Simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 3, 1215. Misra, A.1., Wasir, J.S., and Pandey, R.M. (2005). An evaluation of candidate definitions of the metabolic syndrome in adult Asian Indians. Diabetes Care 28, 398–403. Nagase, H., Visse, R., and Murphy, G. (2006). Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc Res 69, 562–573. Pastinen, T., Sladek, R., Gurd, S., Sammak, A., Ge, B., Lepage, P., Lavergne, K., Villeneuve, A., Gaudin, T., Bra¨ndstro¨m, H., Beck, A., Verner, A., Kingsley, J., Harmsen, E., Labuda, D., Morgan, K., Vohl, M.C., Naumova, A.K., Sinnett, D., and Hudson, T.J. (2004). A survey of genetic and epigenetic variation affecting human gene expression. Physiol Genomics 16, 184–193. Pearce, E., Tregouet, D.A., Samnega˚rd, A., Morgan, A.R., Cox, C., Hamsten, A., Eriksson, P., and Ye, S. (2005). Haplotype effect of the matrix metalloproteinase-1 gene on risk of myocardial infarction. Circ Res 97, 1070–1076. Peters, D.G., Kassam, A., St Jean, P.L., Yonas, H., and Ferrell, R.E. (1999). Functional polymorphism in the matrix metalloproteinase-9 promoter as a potential risk factor for intracranial aneurysm. Stroke 30, 2612–2616. Po¨lla¨nen, P.J., Karhunen, P.J., Mikkelsson, J., Laippala, P., Perola, M., Penttila¨, A., Mattila, K.M., Koivula, T., and Lehtima¨ki, T. (2001). Coronary artery complicated lesion area is related to functional polymorphism of matrix metalloproteinase 9 gene: an autopsy study. Arterioscler Thromb Vasc Biol 21, 1446–1450. Pollex, R.L., and Hegele, R.A. (2006). Genetic determinants of the metabolic syndrome. Nat Clin Pract Cardiovasc Med 3, 482–489. Rutter, J.L., Mitchell, T.I., Buttice`, G., Meyers, J., Gusella, J.F., Ozelius, L.J., and Brinckerhoff, C.E. (1998). A single nucleotide polymorphism in the matrix metalloproteinase-1 promoter creates an Ets binding site and augments transcription. Cancer Res 58, 5321–5325. Sawant, A., Mankeshwar, R., Shah, S., Raghavan, R., Dhongde, G., Raje, H., D’souza, S., Subramanium, A., Dhairyawan, P., Todur, S., and Ashavaid, T.F. (2011). Prevalence of metabolic syndrome in urban India. Cholesterol 2011, 920983. Van den Steen, P.E., Dubois, B., Nelissen, I., Rudd, P.M., Dwek, R.A., and Opdenakker, G. (2002). Biochemistry and molecular biology of gelatinase B or matrix metalloproteinase-9 (MMP-9). Crit Rev Biochem Mol Biol 37, 375– 536. Wang, L., Ma, Y.T., Xie, S., Yang, Y., Fu, Z., Liu, F., Li, X.M., and Chen, B. (2011). Association of MMP-9 gene polymorphisms with acute coronary syndrome in the Uygur population of China. World J Emerg Med 2, 104–110. Xu, X., Wang, L., Xu, C., Zhang, P., Yong, F., Liu, H., Wang, J., and Shi, Y. (2013). Variations in matrix metalloproteinase1, -3, and -9 genes and the risk of acute coronary syndrome
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and coronary artery disease in the Chinese Han population. Coron Artery Dis 24, 259–265. Xu, X.P., Meisel, S.R., Ong, J.M., Kaul, S., Cercek, B., Rajavashisth, T.B., Sharifi, B., and Shah, P.K. (1999). Oxidized low-density lipoprotein regulates matrix metalloproteinase-9 and its tissue inhibitor in human monocyte-derived macrophages. Circulation 99, 993–998. Yadav, S.S., Mandal, R.K., Singh, M.K., Usman, K., and Khattri, S. (2014a). Genetic variants of matrix metalloproteinase (MMP2) gene influence metabolic syndrome susceptibility. Genet Test Mol Biomarkers 18, 88–92 Yadav, S.S., Singh, M.K., Dwivedi, P., Mandal, R.K., Usman, K., and Pant, K.K. (2014b). Significance of impaired serum gelatinases activities in metabolic syndrome. Toxicol Int 21, 107–111. Zhang, B., Ye, S., Herrmann, S.M., Eriksson, P., de, Maat, M., Evans, A., Arveiler, D., Luc, G., Cambien, F., Hamsten, A.,
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Watkins, H., and Henney, A.M. (1999). Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis. Circulation 13, 1788–1794.
Address correspondence to: Sanjay Khattri, MD Department of Pharmacology and Therapeutics King George’s Medical University Lucknow 226003 India E-mail: [email protected] Received for publication May 7, 2014; received in revised form July 3, 2014; accepted July 3, 2014.
High Serum Level of Matrix Metalloproteinase 9 and Promoter Polymorphism - 1562 C:T as a New Risk Factor for Metabolic Syndrome Suraj S. Yadav,1 Raju K. Mandal,2 Manish K. Singh,1 Archna Verma,3 Pradeep Dwivedi,1 Rishi Sethi,4 Kauser Usman,5 and Sanjay Khattri1
The altered matrix metalloproteinases (MMPs) have been suggested in the pathophysiology of metabolic syndrome (MetS). Genetic variants in the promoter region of MMP1 and MMP9 genes may modulate an individual’s susceptibility to MetS. The aim of this study was to determine the frequency of MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms and the correlation with serum levels of MMP1 and MMP9 in MetS susceptibility. On the basis of anthropometric profile and laboratory investigations, 180 confirmed MetS patients and 190 unrelated healthy controls of similar ethnicity were genotyped for MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms by using the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) methods. In addition, serum levels of MMP1 and MMP9 were quantified by ELISA. We found that the serum level of MMP9 was significantly higher in MetS patients. Variant genotype TT of MMP9 - 1562 demonstrated increased risk (odds ratio [OR] = 3.70, p = 0.015) of MetS. Similarly, variant allele T (OR = 1.77, p = 0.002) and combined genotype CT + TT (OR = 1.81, p = 0.057) also showed a significantly higher risk. The CT and TT genotypes of MMP9 - 1562 polymorphism contributed to high serum levels of MMP9 in MetS patients. However, no such association was observed with the MMP1 serum level and - 519 A:G polymorphism. Our results suggest that a higher serum level of MMP9 in the presence of MMP9 polymorphism - 1562 C:T might be a risk factor for the development of MetS. The MMP9 enzyme activity might be a significant indicator in the screening of MetS patients.
Introduction
M
etabolic syndrome (MetS) is a major health problem around the world because of a modern lifestyle rising unexpectedly (Cornier et al., 2008). MetS is associated with a high mortality rate and plays a key role in cardiovascular disease (Isomaa et al., 2001; McNeill et al., 2005). The incidence rates of MetS vary worldwide, it affects an estimated 30% and 15% of the population in the United States and Europe, respectively (Cameron et al., 2004; Gallagher et al., 2011). The prevalence of MetS has significantly increased in India and affects an estimated 19.52% of the urban population (Sawant et al., 2011). Despite these dismal statistics, the etiology of MetS remains largely unknown. Therefore, finding a strategy for the prevention of MetS is a crucial medical challenge. Mets is characterized by a group of cardiovascular risk factors, including visceral obesity, hypertension, dyslipidemia, glucose intolerance, and insulin resistance (Eckel et al.,
2005). Considerable evidence demonstrated that genetic factors are the major contributors to MetS susceptibility (Pollex and Hegele, 2006). Moreover, genome-wide association studies (GWASs) have also identified various chromosomal regions that are associated with MetS risk (Francke et al., 2001). Thus, it is anticipated that the identification of host genetic factors for MetS risk would greatly assist in the control of this disease. Matrix metalloproteinases (MMPs) are a family of zincdependent endopeptidases, which are involved in physiological and pathological processes such as degradation and remodeling of the extracellular matrix (ECM) (Nagase et al., 2006). Earlier reports suggested the role of MMPs in the pathogenesis of MetS (Hopps et al., 2013; Yadav et al., 2014a, 2014b). Matrix metalloproteinase 1 (MMP1) (also known as interstitial collagenase) is a major proteolytic enzyme specifically to degrade type 1 collagen proteins, which are the main components of the interstitial matrix ( Jones et al., 2003). A single-nucleotide polymorphism (SNP) A:G found in the
1
Department of Pharmacology and Therapeutics, King George’s Medical University, Lucknow, India. College of Medicine, King Khalid University Hospital, Riyadh, Kingdom of Saudi Arabia. Department of Urology, Sanjay Gandhi Post Graduate Insitute of Medical Sciences, Lucknow, India. Departments of 4Cardiology and 5Internal Medicine, King George’s Medical University, Lucknow, India.
2 3
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MMP9 AND METABOLIC SYNDROME
promoter region of - 519 resulting in guanine to adenine substitution has been associated with altered MMP1 gene expression (Rutter et al., 1998). In addition, MMP9 (gelatinase B) has the ability to cleave type IV collagen, a major component of the basement membrane (Van den Steen et al., 2002). Several polymorphisms have been identified in the promoter regions, among them C:T polymorphism located in the - 1562 region has been shown to modulate the transcriptional activity of the MMP9 gene and associated with cardiovascular diseases (Peters et al., 1999; Po¨lla¨nen et al., 2001). Therefore, it is reasonable to suspect that functional genetic polymorphisms in the regulatory region of MMP1 and MMP9 genes may affect their circulating levels and predispose to MetS disease. To our knowledge, no study has addressed the association of these polymorphisms with MetS. Therefore, this study was aimed to compare the genotype and allelic frequencies of the functional polymorphisms of MMP1 and MMP9 between MetS and healthy controls. In addition, serum levels and functional relevance of MMP1 and MMP9 genes were also evaluated. Materials and Methods Study subjects
A total of 180 MetS patients were recruited from the Department of Medicine, King George Medical University, Lucknow, according to modified NCEP-ATP III criteria (Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, 2001; Misra et al., 2005) for Asian Indians. Age- and ethnicity-matched healthy individuals (n = 190) were recruited as controls who were without MetS, nonalcoholic, nondiabetic, and who had no cardiac, respiratory, inflammatory, endocrine, or other metabolic diseases. All the participants in the study were unrelated individuals of similar ethnicity from Lucknow and other adjoining cities of northern India. Information on demographic features was obtained through personal interview using a standard clinical pro forma. The study was approved by the ethics review board and written informed consent was obtained from all participants before entering the study. Anthropometric and laboratory investigations
The waist circumference (WC) was measured for determining obesity. We have followed the modified NCEP-ATP III (Misra et al., 2005) criteria for the Indian population. WC was measured midway between the margin of the lowest ribs and the iliac crest, at the point of minimal inspiration. The systolic and diastolic blood pressure (SDP and DBP) in subjects was measured for diagnosis of MetS. In biochemical investigations, we estimated fasting plasma glucose (FPG) in a blood sample without preliminary treatment by using a Cobas C-111analyzer (Roche) and related kit. Serum lipid profile was also investigated with estimation of total cholesterol (TC), high-density lipoprotein-cholesterol (HDLC), and triglycerides (TG) by using a Cobas C-111analyzer (Roche) and a related kit. DNA extraction
Blood samples (5.0 mL) from MetS patients and controls were collected in EDTA vials and stored at - 20C until required. Genomic DNA was extracted from peripheral
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whole blood according to a salting-out technique (Miller et al., 1988). Gene amplification and genotyping
The polymorphic sites in MMP1 - 519 A:G and MMP9 - 1562 C:T genes were amplified by polymerase chain reaction (PCR) combined with restriction fragment length polymorphism (RFLP) using primers implying conditions, as previously described (Drzewoski et al., 2008; Wang et al., 2011). The PCR cocktail contained 10 pmol of each primer; 100 ng genomic DNA; 0.25 mm, each of deoxyribonucleotide triphosphate; and a 1X PCR buffer containing 10 mM Tris HCl, pH 8.6, 50 mM KCl, 1.5 mM MgCl2, and 0.5 U of Taq polymerase (Bangalore Genei). The amplified products of MMP1 and MMP9 were digested with KpnI, SphI (New England Biolabs) overnight at 37C, respectively. Subsequently, fragments of these polymorphisms were visualized on 2% agarose gels and 10% polyacrylamide gel electrophoresis to identify the wild, heterozygous, and variant genotypes. Quality control
For quality control, positive and negative controls were used in each genotyping assay and 5% of randomly selected duplicates were included. No discrepancy between duplicates was observed in the genotyping, which ensured the absence of genotyping error. ELISA for serum MMP level
The serum MMP1 and MMP9 levels were measured by using a commercially available kit, according to the manufacturer’s protocol (Antagene) with sensitivity of < 5 pg/mL. Statistical analyses
SNPalyze software (Dynacom) was employed to calculate the Hardy–Weinberg equilibrium (HWE). Binary logistic regression was used to test the association of genotypes, alleles, and combined genotypes. Patients and controls were used as dependent variables and genotypes were used as covariates. Risk was expressed as odds ratio (OR) with 95% confidence intervals (CI). The wild-type genotype/allele of MMP1 and MMP9 polymorphisms was taken as reference for risk analysis. The distribution of MMP1 and MMP9 levels of genotypes was assessed by the D’Agostino and Pearson omnibus normality test. Based on the results of the normality test, the association of the genotype with the MMP level was analyzed by analysis of variance or the Kruskal–Wallis test followed by an appropriate posttest. All the statistical analyses were conducted by SPSS software, version 21 (SPSS). A p-value < 0.05 was taken as statistically significant. Power analysis was performed by G power software version 3.1 (Faul et al., 2007). Results Profiling of risk factors in MetS patients and control group
A total of 370 individuals (180 MetS and 190 controls) were analyzed in this study. Among the total patients, 68 (37.77%) were male and 112 (62.22%) were female, mean age 39 – 12.54 and 36 – 14.67 years, respectively. Clinical characteristics of
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YADAV ET AL.
Table 1. Clinical Components of Metabolic Syndrome Patients and Controls Metabolic risk factors
Controls (n = 190)
Patients (n = 180)
WC (cm) 71.27 – 15.13 88.67 – 10.38 FPG (mg/dL) 97.95 – 11.66 107.29 – 19.94 SBP (mmHg) 123.01 – 7.48 136.81 – 9.90 DBP (mmHg) 82.01 – 3.81 87.31 – 6.88 TG (mg/dL) 101.73 – 46.38 169.81 – 77.32 HDL-C (mg/dL) 54.62 – 8.95 39.25 – 12.05
p-Value < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
Data represented as mean – SD. Significant values (in boldface) showed increased risk. DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein-cholesterol; SBP, systolic blood pressure; TG, triglycerides; WC, waist circumference.
the MetS patients and controls are represented in Table 1. As expected, there was a high degree of statistical difference between the metabolic risk factors of MetS and controls. WC (88.67 – 10.38 vs. 71.27 – 15.13 cm, p < 0.01), SBP (136.81 – 9.90 vs. 123.01 – 7.48 mmHg, p < 0.01), and DBP (87.31 – 6.88 vs. 82.01 – 3.81 mmHg, p < 0.01) were significantly different in MetS patients compared with healthy controls. Similarly, FPG (107.29 – 19.94 vs. 97.95 – 11.66 mg/dL, p < 0.01), HDL-C (39.25 – 12.05 vs. 54.62 – 8.95 mg/dL, p < 0.01), and TG (169.81 – 77.3 vs. 101.73 – 46.38 mg/dL, p < 0.01) were also significantly altered in MetS patients. Serum levels of MMP1 and MMP9 in MetS patients and controls
We compared the serum levels of MMP1 and MMP9 between controls and MetS patients (Fig. 1A). Our results demonstrated that the mean level of serum MMP9 was higher in MetS patients (73.93 – 33.59 ng/mL) compared with controls (34.78 – 12.06 ng/mL) and represented a significant difference p < 0.0001. However, the MMP1 level was almost similar in MetS patients (7.9 – 3.74 ng/mL) and controls (6.99 – 3.97 ng/mL) and did not reveal any significant risk. Correlation of the serum MMP1 and MMP9 levels with clinical characteristics of MetS
We performed a case-only analysis to investigate whether any possible association existed between the serum levels of MMP1 and MMP9 genes and clinical characteristics of MetS patients (Table 2). A statistically significant correlation was observed with WC, FPG, TC, TG, HDL-C, DBP, and the serum level of MMP9, while MMP1 was marginally correlated with WC only. Genotype and allelic frequency distribution of MMP1 - 519 A:G and MMP9 - 1562 C:T between MetS and controls
The frequency distributions of MMP1 - 519 A:G and MMP9 - 1562 C:T polymorphisms were consistent with HWE in controls. Table 3 shows the distribution of genotypes and frequency of MMP1 and MMP9 polymorphisms in MetS patients and controls. The obtained results revealed a higher frequency of CT (37.2% vs. 28.5%) and TT (7.8% vs. 2.6%) genotypes in MetS patients compared with controls and showed a 1.6-fold (OR = 1.64, 95% CI = 1.05–2.55, p = 0.028)
FIG. 1. (A) Serum level of MMP9 and MMP1 genes in MetS and control. Data represented as mean – SD. (B) Association between MMP1 - 519 A:G polymorphism and the serum level in MetS and control. (C) Association between MMP9 - 1562 C:T polymorphism and the serum level in MetS and control. MetS, metabolic syndrome; NS, not significant. and 3.7-fold (OR = 3.70, 95% CI = 1.29–10.63, p = 0.015) increased risk of MetS. We combined the variant TT genotype with the heterozygous CT genotype (i.e., CT + TT), assuming a dominant genetic model, and found that the frequency of the combined genotype (CT + TT) was higher in MetS patients (45%) than in controls (31.1%); the result showed significant risk (OR = 1.81, 95% CI = 1.18–2.77, p = 0.006) for MetS. Similarly, the variant allele (T) was more frequent in MetS patients (26.4%) and demonstrated a 1.7-fold increased risk (OR = 1.77, 95% CI = 1.23–2.52, p = 0.002) for MetS. However, genotype and allelic frequency
MMP9 AND METABOLIC SYNDROME
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Table 2. Correlation (Pearson Correlation) Between Clinical Characteristics of Metabolic Syndrome Patients MMP1
MMP9
Clinical risk factors
r-Value
p-Value
r-Value
p-Value
WC (cm) FPG (mg/dL) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) SBP (mmHg) DBP (mmHg)
0.1843 0.1210 0.1284 0.1271 - 0.0430 0.0847 0.0863
0.005 0.096 0.089 0.081 0.556 0.245 0.255
0.3607 0.3269 0.2239 0.3937 - 0.3037 0.1276 0.3489
< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.507 < 0.01
Significant values (in boldface) showed increased risk. TC, total cholesterol.
distributions of the MMP1 - 519 A:G polymorphism were not found significant in patients and controls. A post hoc power of the study was calculated to detect the probability of association between MMP1 and MMP9 polymorphisms and MetS at the 0.05 level of significance, assuming a small effect size (w = 0.20). This analysis revealed that the current study has 86% power to detect the association. Combined effect of MMP9 - 1562 C:T and MMP1 - 519 A:G gene polymorphisms with MetS risk
In addition, we performed all possible interactions of MMP9 C:T and MMP1 A:G gene polymorphisms (Table 4). We found that interaction between the heterozygous genotype (CT-AG) of MMP9 and MMP1 polymorphisms showed a significant risk with MetS. Association of genotype–phenotype relationship of MMP1 and MMP9 serum level with MetS
A significant association of MMP9 - 1562 C:T polymorphism and serum MMP9 level was observed. The homozygous mutant TT ( p < 0.001) carrier showed higher
levels of MMP9 than wild-type CC and heterozygous CT genotypes. Similarly, heterozygous CT ( p < 0.001) genotype was significantly associated with higher serum MMP9 levels as compared to the wild-type CC (Fig. 1B). On the other hand, MMP1 - 519 A:G polymorphism failed to demonstrate any association (Fig. 1C). Discussion
Genetic association studies have been helpful in the detection of genetic susceptibility genes. SNPs may contribute greatly to the understanding of both interindividual and interpopulation differences, given the exposure to similar environmental and lifestyle factors. The expansion of the adipose tissue and enlargement of fat cells is accompanied by a remodeling of the stromal matrix performed mainly by MMPs (Halberg et al., 2008). Metalloproteinase are factors that regulate the composition of the ECM and they stimulate cytokines secreted by macrophages and endothelial cells (Lemaıˆtre et al., 2001). Pro- and anti-inflammatory cytokines secreted by the adipose tissue modulate the activity of MMPs and their inhibitors. Boden (2008) suggested that free fatty acid and insulin promote the activation of MAP-kinase activity, which is responsible for proinflammatory cytokines, and promote the activation of MMP2 and MMP9. The impaired glucose level affects the activity of MMPs through hyperproduction of advanced glycation end products (AGEs) with subsequent activation of AGE receptors and oxidative stress (Ishibashi et al., 2010; Kar et al., 2010). Moreover, oxidized LDL favors the inflammatory process and upregulates the expression of macrophage MMP9 (Xu et al., 1999; Kojima et al., 2010). MMPs also play a major role in vascular remodeling, interaction of the endothelial basement membrane, and the ECM actively participating in developing complications of MetS. The increased ECM accumulation in the basement membrane is linked with a variety of metabolic abnormalities and oxidative stress associated with MetS (Hayden et al., 2005). Recently, Lobmann (2006) reported altered levels of MMPs in the cultivated fibroblast of diabetic patients. So far, no association studies have been executed for MetS to evaluate
Table 3. MMP1 and MMP9 Gene Polymorphisms and Susceptibility to Metabolic Syndrome
Genotypes
Controls
Patients
n = 190 (%)
n = 180 (%)
MMP1 - 519 A:G (rs1144393) AA 104 (54.7) AG 68 (35.8) GG 18 (9.5) AG + GG 86 (45.3) Allele A 276 (72.6) Allele G 104 (27.4) MMP9 - 1562 C:T (rs3918242) CC 131 (68.9) CT 54 (28.5) TT 5 (2.6) CT + TT 59 (31.1) Allele C 316 (83.2) Allele T 64 (16.8)
OR (95% CI)
88 71 21 92 247 113
(48.9) (39.4) (11.7) (51.1) (68.6) (31.4)
Reference 1.23 (0.79–1.91) 1.37 (0.69–2.75) 1.26 (0.84–1.90) Reference 1.21 (0.88–1.66)
99 67 14 81 265 95
(55.0) (37.2) (7.8) (45.0) (73.6) (26.4)
Reference 1.64 (1.05–2.55) 3.70 (1.29–10.63) 1.81 (1.18–2.77) Reference 1.77 (1.23–2.52)
For allele, total number of chromosomes in controls-380 and MetS patients-360. Significant values (in boldface) showed increased risk. CI, confidence interval; MetS, metabolic syndrome; OR, odds ratio.
p-Value
0.346 0.362 0.261 0.230 0.028 0.015 0.006 0.002
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Table 4. Interaction Between MMP9 - 1562 C:T and MMP1 - 519 A:G Gene Polymorphisms in Metabolic Syndrome Patients and Healthy Controls Controls Cases Combined genotype n = 190 (%) n = 180 (%) CC-AA CC-AG CC-GG CT-AA CT-AG CT-GG TT-AA TT-AG TT-GG
100 19 12 4 49 1 0 0 5
(52.6) (10) (6.3) (2.1) (25.8) (0.5) (2.6)
74 14 12 9 57
(41.1) (7.8) (6.7) (5) (31.7) — 4 (2.2) 1 (0.6) 9 (5.0)
OR (95% CI)
p-Value
Reference 0.99 (0.46–2.11) 1.35 (0.57–3.17) 3.04 (0.90–10.25) 1.57 (0.96–2.55) NC NC NC 2.43 (0.78–7.55)
0.991 0.490 0.902 0.049 NC NC NC 0.124
Significant values (in boldface) showed increased risk. NC, not calculated.
MMP9 and MMP1 polymorphisms. Functional polymorphisms in a coding region of the gene may result in deformed proteins. Similarly, variants in promoter regions affect binding of the transcription factor and possibly reduce transcript levels (Pastinen et al., 2004). In the present study, we found an increased serum level of MMP9 in MetS patients and a significant correlation with clinical characteristics. We also investigated the role of MMP9 - 1562 C:T polymorphism in the serum level of MMP9 in MetS. The - 1562 C:T polymorphism has shown a significant association with serum MMP9 levels and - 1562 C:T genotypes, suggesting that the increased frequency of the minor allele of the - 1562 C:T polymorphism may function as a significant risk factor of MetS. Together, these findings indicated that the MMP9 polymorphism has important effects on MMP9 serum levels and MetS risk. In vitro studies have shown that C:T substitution at the - 1562 position results in the loss of binding of a nuclear repressor protein and thus leading to increased MMP9 expression (Zhang et al., 1999). Our results were consistent with earlier studies, Andrade et al. (2012) found a strong association of the - 1562 C:T polymorphism with obesity and also reported higher levels of MMP9 in obese patients. Similar effects of MMP9 polymorphism were reported by Belo et al. (2012) in obese children. Blankenberg et al. (2003) reported higher plasma MMP9 levels with - 1562T allele carriers in cardiovascular disease. Besides, functional studies have revealed that the T allele of this SNP has significantly higher mRNA expression and protein levels compared with the C allele (Medley et al., 2004). Moreover, altered plasma levels of MMP9 were significantly observed in MetS and hypertension patients (Derosa et al., 2006; Hopps and Caimi, 2012). On the other hand, we did not find any difference in the level of MMP1 in MetS patients. MMP1 - 519 A:G polymorphism did not reveal any significant risk for MetS, indicating that this polymorphism might not be a major determinant of MMP1 levels and MetS risk. It is likely that some other unidentified polymorphisms may affect the gene expression and MMP1 levels. However, effects of - 519 A:G polymorphism have been reported in other diseases like coronary artery disease (Xu et al., 2013) and myocardial infarction (Pearce et al., 2005). Thus, further study may be necessary to elucidate the role of MMP1 SNPs/levels in the progress of MetS. In our
study, we found that the combination (CT-AG) of MMP9 and MMP1polymorphisms had a multiplicative effect on the risk of MetS. In conclusion, these results suggest that MetS is associated with elevated serum levels of MMP9. Moreover, our study also revealed that - 1562 C:T polymorphism of the MMP9 gene increased the risk of MetS and expression of MMP9 levels. Hence, it can be considered as a potential prognostic marker for MetS patients. It is biologically possible that these findings may benefit from the use of an inhibitor of MMPs to prevent MetS disease. Additionally, further research is needed to understand the molecular mechanisms and regulation of MMPs in the pathophysiology of MetS. Acknowledgment
The authors wish to thank the technical staff of the Department of Pharmacology and Medicine, KGMU, Lucknow. The author S.S.Y. is thankful to the Indian Council of Medical Research (ICMR) for providing a senior research fellowship (SRF) during the course of study. Funding
This study was supported by the research grant No. 52/15/ 2008-BMS of the Indian Council of Medical Research (ICMR) New Delhi, India. Disclosure Statement
No competing financial interests or other conflicts of interests exist. References
Andrade, V.L., Fernandes, K.S., Bosco, A.A., Tanus-Santos, J.E., and Sandrim, V.C. (2012). Functional polymorphism located in MMP-9 gene promoter is strongly associated with obesity. DNA Cell Biol 31, 1054–1057. Belo, V.A., Souza-Costa, D.C., Luizon, M.R., Lanna, C.M., Carneiro, P.C., Izidoro-Toledo, TC., Ferraz, K.C., and TanusSantos, J.E. (2012). Matrix metalloproteinase-9 genetic variations affect MMP-9 levels in obese children. Int J Obes (Lond) 36, 69–75. Blankenberg, S., Rupprecht, H.J., Poirier, O., Collins, A., and Ye, S. (2003). Plasma concentrations and genetic variation of matrix metalloproteinase 9 and prognosis of patients with cardiovascular disease. Circulation 107, 1579–1585. Boden, G. (2008). Obesity and free fatty acids. Endocrinol Metab Clin North Am 37, 635–646. Cameron, A.J., Shaw, J.E., and Zimmet, P.Z. (2004). The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am 33, 351–375. Cornier, M.A., Dabelea, D., Hernandez, T.L., Lindstrom, R.C., Steig, A.J., Stob, N.R., Van, Pelt, R.E., Wang, H., and Eckel, R.H. (2008). The metabolic syndrome. Endocr Rev 29, 777– 822. Derosa, G., D’Angelo, A., Ciccarelli, L., Piccinni, M.N., Pricolo, F., Salvadeo, S., Montagna, L., Gravina, A., Ferrari, I., Galli, S., Paniga, S., Tinelli, C., and Cicero, A.F. (2006). Matrix metalloproteinase-2, -9, and tissue inhibitor of metalloproteinase1 in patients with hypertension. Endothelium 13, 227–2231. Drzewoski, J., Sliwin´ska, A., Przyby1owska, K., Sliwin´ski, T., Kasznicki, J., Zurawska-Klis, M., Kosmalski, M., and Majsterek, I. (2008). Gene polymorphisms and antigen levels of
MMP9 AND METABOLIC SYNDROME
matrix metalloproteinase-1 in type 2 diabetes mellitus coexisting with coronary heart disease. Kardiol Pol 66, 1042–1048. Eckel, R.H., Grundy, S.M., and Zimmet, P.Z. (2005). The metabolic syndrome. Lancet 365, 1415–1428. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. (2001). Executive summary of the Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 285, 2486–2497. Faul, F., Erdfelder, E., Lang, A.G., and Buchner, A.G. (2007). Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39, 175. Francke, S., Manraj, M., Lacquemant, C., Lecoeur, C., Lepreˆtre, F., Passa, P., Hebe, A., Corset, L., Yan, S.L., Lahmidi, S., Jankee, S., Gunness, T.K., Ramjuttun, U.S., Balgobin, V., Dina, C., and Froguel, P. (2001). A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27. Hum Mol Genet 10, 2751–2765. Gallagher, E.J., Leroith, D., and Karnieli, E. (2011). The metabolic syndrome—from insulin resistance to obesity and diabetes. Med Clin North Am 95, 855–873. Halberg, N., Wernstedt-Asterholm, I., and Scherer, P.E. (2008). The adipocyte as an endocrine cell. Endocrinol Metab Clin North Am 3, 753–768. Hayden, M.R., Sowers, J.R., and Tyagi, S.C. (2005). The central role of vascular extracellular matrix and basement membrane remodeling in metabolic syndrome and type 2 diabetes: the matrix preloaded. Cardiovasc Diabetol 4, 9. Hopps, E., and Caimi, G. (2012). Matrix metalloproteinases in metabolic syndrome. Eur J Int Med 23, 99–104. Hopps, E., Lo Presti, R., Montana, M., Noto, D., Averna, M.R., and Caimi, G. (2013). Gelatinases and their tissue inhibitors in a group of subjects with metabolic syndrome. J Invest Med 61, 978–983. Ishibashi, T., Kawaguchi, M., Sugimoto, K., Uekita, H., Sakamoto, N., Yokoyama, K., Maruyama, Y., and Takeishi, Y. (2010). Advanced glycation end product-mediated matrix metalloproteinases-9 and apoptosis via renin-angiotensin system in type 2 diabetes. J Atheroscler Thromb 17, 578–589. Isomaa, B., Almgren, P., Tuomi, T., Forse´n, B., Lahti, K., Nisse´n, M., Taskinen, M.R., and Groop, L. (2001). Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24, 683–689. Jones, C.B., Sane, D.C., and Herrington, D.M. (2003). Matrix metalloproteinases: a review of their structure and role in acute coronary syndrome. Cardiovasc Res 59, 812–823. Kar, S., Subbaram, S., Carrico, P.M., and Melendez, J.A. (2010). A critical link between free radicals, matrix remodeling and degenerative disease. Respir Physiol Neurobiol 174, 299–306. Kojima, C., Ino, J., Ishii, H., Nitta, K., and Yoshida, M. (2010). MMP-9 inhibition by ACE inhibitor reduces oxidized LDLmediated foam-cell formation. J Atheroscler Thromb 17, 97–105. Lemaıˆtre, V., O’Byrne, T.K., Borczuk, A.C., Okada, Y., Tall, A.R., and D’Armiento, J. (2001). ApoE knockout mice expressing human matrix metalloproteinase-1 in macrophages have less advanced atherosclerosis. J Clin Invest 107, 1227–1234. Lobmann, R. (2006). Differential effects of PDGF-BB on matrix metalloproteinases and cytokines release in fibroblasts of Type 2 diabetic patients and normal controls in vitro. J Diabetes Complications 20, 105–112.
821
McNeill, A.M., Rosamond, W.D., Girman, C.J., Golden, S.H., Schmidt, M.I., East, H.E., Ballantyne, C.M., and Heiss, G. (2005). The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 28, 385–390. Medley, T.L., Cole, T.J., Dart, A.M., Gatzka, C.D., and Kingwell, B.A. (2004). Matrix metalloproteinase-9 genotype influences large artery stiffness through effects on aortic gene and protein expression. Arterioscler Thromb Vasc Biol 24, 1479–1484. Miller, S.A., Dykes, D.D., and Polesky, H.F. (1988). Simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 3, 1215. Misra, A.1., Wasir, J.S., and Pandey, R.M. (2005). An evaluation of candidate definitions of the metabolic syndrome in adult Asian Indians. Diabetes Care 28, 398–403. Nagase, H., Visse, R., and Murphy, G. (2006). Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc Res 69, 562–573. Pastinen, T., Sladek, R., Gurd, S., Sammak, A., Ge, B., Lepage, P., Lavergne, K., Villeneuve, A., Gaudin, T., Bra¨ndstro¨m, H., Beck, A., Verner, A., Kingsley, J., Harmsen, E., Labuda, D., Morgan, K., Vohl, M.C., Naumova, A.K., Sinnett, D., and Hudson, T.J. (2004). A survey of genetic and epigenetic variation affecting human gene expression. Physiol Genomics 16, 184–193. Pearce, E., Tregouet, D.A., Samnega˚rd, A., Morgan, A.R., Cox, C., Hamsten, A., Eriksson, P., and Ye, S. (2005). Haplotype effect of the matrix metalloproteinase-1 gene on risk of myocardial infarction. Circ Res 97, 1070–1076. Peters, D.G., Kassam, A., St Jean, P.L., Yonas, H., and Ferrell, R.E. (1999). Functional polymorphism in the matrix metalloproteinase-9 promoter as a potential risk factor for intracranial aneurysm. Stroke 30, 2612–2616. Po¨lla¨nen, P.J., Karhunen, P.J., Mikkelsson, J., Laippala, P., Perola, M., Penttila¨, A., Mattila, K.M., Koivula, T., and Lehtima¨ki, T. (2001). Coronary artery complicated lesion area is related to functional polymorphism of matrix metalloproteinase 9 gene: an autopsy study. Arterioscler Thromb Vasc Biol 21, 1446–1450. Pollex, R.L., and Hegele, R.A. (2006). Genetic determinants of the metabolic syndrome. Nat Clin Pract Cardiovasc Med 3, 482–489. Rutter, J.L., Mitchell, T.I., Buttice`, G., Meyers, J., Gusella, J.F., Ozelius, L.J., and Brinckerhoff, C.E. (1998). A single nucleotide polymorphism in the matrix metalloproteinase-1 promoter creates an Ets binding site and augments transcription. Cancer Res 58, 5321–5325. Sawant, A., Mankeshwar, R., Shah, S., Raghavan, R., Dhongde, G., Raje, H., D’souza, S., Subramanium, A., Dhairyawan, P., Todur, S., and Ashavaid, T.F. (2011). Prevalence of metabolic syndrome in urban India. Cholesterol 2011, 920983. Van den Steen, P.E., Dubois, B., Nelissen, I., Rudd, P.M., Dwek, R.A., and Opdenakker, G. (2002). Biochemistry and molecular biology of gelatinase B or matrix metalloproteinase-9 (MMP-9). Crit Rev Biochem Mol Biol 37, 375– 536. Wang, L., Ma, Y.T., Xie, S., Yang, Y., Fu, Z., Liu, F., Li, X.M., and Chen, B. (2011). Association of MMP-9 gene polymorphisms with acute coronary syndrome in the Uygur population of China. World J Emerg Med 2, 104–110. Xu, X., Wang, L., Xu, C., Zhang, P., Yong, F., Liu, H., Wang, J., and Shi, Y. (2013). Variations in matrix metalloproteinase1, -3, and -9 genes and the risk of acute coronary syndrome
822
and coronary artery disease in the Chinese Han population. Coron Artery Dis 24, 259–265. Xu, X.P., Meisel, S.R., Ong, J.M., Kaul, S., Cercek, B., Rajavashisth, T.B., Sharifi, B., and Shah, P.K. (1999). Oxidized low-density lipoprotein regulates matrix metalloproteinase-9 and its tissue inhibitor in human monocyte-derived macrophages. Circulation 99, 993–998. Yadav, S.S., Mandal, R.K., Singh, M.K., Usman, K., and Khattri, S. (2014a). Genetic variants of matrix metalloproteinase (MMP2) gene influence metabolic syndrome susceptibility. Genet Test Mol Biomarkers 18, 88–92 Yadav, S.S., Singh, M.K., Dwivedi, P., Mandal, R.K., Usman, K., and Pant, K.K. (2014b). Significance of impaired serum gelatinases activities in metabolic syndrome. Toxicol Int 21, 107–111. Zhang, B., Ye, S., Herrmann, S.M., Eriksson, P., de, Maat, M., Evans, A., Arveiler, D., Luc, G., Cambien, F., Hamsten, A.,
YADAV ET AL.
Watkins, H., and Henney, A.M. (1999). Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis. Circulation 13, 1788–1794.
Address correspondence to: Sanjay Khattri, MD Department of Pharmacology and Therapeutics King George’s Medical University Lucknow 226003 India E-mail: [email protected] Received for publication May 7, 2014; received in revised form July 3, 2014; accepted July 3, 2014.
