Literature DB >> 26330106

Matrix Metalloproteinase-9 (MMP-9) Gene Polymorphism in Stroke Patients.

Kinga Buraczynska1, Jacek Kurzepa2, Andrzej Ksiazek3, Monika Buraczynska3, Konrad Rejdak3.   

Abstract

Matrix metalloproteinases (MMPs), endopeptidases degrading extracellular matrix, play an important role in the pathogenesis of atherosclerosis and vascular disease. The aim of this study was to evaluate the association between the C(-1562)T functional polymorphism in the MMP-9 gene and risk of stroke. We examined 322 patients with stroke and 410 controls. In the patient group, 52 % had type 2 diabetes. All subjects were genotyped for the C(-1562)T polymorphism by polymerase chain reaction and restriction analysis. A significant increase in T allele and CT + TT genotype frequencies was observed in patients compared with controls (OR 1.73, 95 % CI 1.34-2.23 and 1.89, 95 % CI 1.39-2.56, respectively). The T allele carriers were younger at the onset of stroke (63.5 ± 11.7 years) than patients with CC genotype (71 ± 14.1 years) (p = 0.0002). The comparison between patients with T2DM and without it showed that the T allele and CT + TT genotype were more frequent in T2DM patients (OR 1.48, 95 % CI 1.03-2.12 for T allele and 1.44, 95 % CI 1.93-2.24 for CT + TT genotype). In conclusion, our findings suggest that MMP-9 C(-1562)T polymorphism is significantly associated with risk of stroke in patients with and without T2DM.

Entities:  

Keywords:  C(-1562)T polymorphism; MMP-9; Risk allele; Stroke; Type 2 diabetes

Mesh:

Substances:

Year:  2015        PMID: 26330106      PMCID: PMC4643105          DOI: 10.1007/s12017-015-8367-5

Source DB:  PubMed          Journal:  Neuromolecular Med        ISSN: 1535-1084            Impact factor:   3.843


Introduction

Matrix metalloproteinases (MMPs), well-known inflammatory mediators, belong to a family of structurally related zinc-binding proteolytic enzymes that are widely distributed in human tissues. They degrade almost all components of extracellular matrix in both physiological and pathological processes (Visse and Nagase 2003). MMPs are involved in the pathogenesis of atherosclerosis by the activation of migration and proliferation of smooth muscle cells and by induction and destabilization of atherosclerotic plaques (Galis and Khatri 2002; Katakami et al. 2010). Imbalanced MMP activity has been reported in clinical conditions involving the cardiovascular and cerebrovascular diseases (Galis and Khatri 2002; Siefert and Sarkar 2012; Chen et al. 2013). Ischemic stroke (IS) and intracerebral hemorrhage (ICH) are both associated with activation and altered expression of MMPs, mainly MMP-2 and MMP-9. Several reports have shown that serum levels of MMP-9 increase in the acute phase of stroke and MMP-2 levels increase after several days (Romanic et al. 1998; Fatar et al. 2005). Dysregulated MMP activity leads to uncontrolled degradation of extracellular matrix and basal lamina proteins with serious effects for the blood–brain barrier integrity and neuroinflammatory consequences (Candelario-Jalil et al. 2009; Kurzepa et al. 2014). The high levels of MMP-9 in acute ischemic stroke confirm the involvement of this metalloproteinase in the regulation of inflammation in stroke (Cojocaru et al. 2012; Demir et al. 2012). The MMP-9 gene is located on chromosome 20q12.2–13.1. Sequence analysis revealed several single-nucleotide polymorphisms (SNPs) with some of them functionally important (Zhang et al. 1999a, b). Previous studies have demonstrated that MMP-9 activity is controlled by a functional -1562 C/T polymorphism in the promoter region of human MMP-9 gene (Zhang et al. 1999a, b; Blankenberg et al. 2003; Medley et al. 2004). Using a reporter assay technique, it was shown that the T -1562 allele has higher promoter activity in driving gene expression than the C -1562 allele (Zhang et al. 1999a, b). In human aortic samples, MMP-9 mRNA and protein expression were significantly higher in T allele carriers (Medley et al. 2004). There are only few studies that evaluated association of MMP-9 gene polymorphism with susceptibility to stroke (Kaplan et al. 2008; Katakami et al. 2010; Szczudlik and Borratynska 2010) or functional outcome after stroke (Manso et al. 2010). The aim of this study was to evaluate the association between the C(-1562)T MMP-9 gene polymorphism and risk of stroke.

Materials and Methods

Subjects

The study group consisted of 322 unrelated Caucasian adult patients with either a recent stroke (patients admitted to Stroke Unit of Department of Neurology) or a history of stroke (patients admitted to Departments of Neurology and Nephrology of Medical University, Lublin, Poland). There were 156 males and 166 females. Inclusion criteria were as follows: focal neurological deficit of sudden or rapid onset lasting more than 24 h (with or without acute lesion on cranial CT or MRI scans consistent with focal deficit) and a documented history of stroke. Stroke was classified into ischemic or hemorrhagic based on brain imaging. In the patient group, 290 patients had ischemic stroke and 32 intracerebral hemorrhage. Exclusion criteria included hereditary thrombotic disease and diagnosed brain tumor. For all individuals enrolled in the study, a medical history for the period prior to enrollment, including presence of hypertension, diabetes, coronary heart disease, atherosclerosis, kidney disease and pharmacological treatment was collected. Hypertension was defined as either a systolic blood pressure >140 mm Hg and diastolic blood pressure >90 mm Hg or current treatment with an antihypertensive drug. In the study group, 282 patients (88 %) were hypertensive. Type 2 diabetes was diagnosed according to American Diabetes Association criteria. One or more of the following conditions were met: the classic symptoms of hyperglycemia (polyuria, polydipsia, weight loss), fasting plasma glucose ≥126 mg/dl or random plasma glucose ≥200 mg/dl, the use of insulin or oral hypoglycemic agents. The mean duration of diabetes was 12.6 years (range 6–27). It was estimated from time of the first symptoms attributable to the disease or time of first detection of glycosuria. A total of 169 patients (52 %) had diabetes. Cardiovascular disease (CVD) was diagnosed and documented as one or the combination of several pathological states: congestive heart failure, left ventricular hypertrophy, angina pectoris, ischemic heart disease, myocardial infarction, ischemic cerebral stroke, vascular calcifications or atheromatous lesions. Each clinical manifestation of CVD was confirmed by appropriate biochemical, radiographic, echocardiographic and vascular diagnostic criteria. There was a substantial overlap between categories. Healthy control subjects (n = 410) with normal ECG and no clinical signs of renal, cardiovascular and neurological disease were randomly recruited among hospital staff and blood bank donors who underwent health examination. They were asked for risk factors, existing diseases and medication intake. Written informed consent for genotyping was obtained from all subjects in accordance with principles of the 1964 Declaration of Helsinki. The study protocol was approved by the institutional ethics committee.

Determination of MMP-9 Genotype

Genomic DNA was extracted from peripheral blood leukocytes obtained by the standard procedure. The -1562 C/T (rs3918242) polymorphism in the MMP-9 gene was analyzed by amplification of 435-bp DNA fragment by polymerase chain reaction (PCR). The following primers were used for amplification reaction: sense primer 5′-GCCTGGCACATAGTAGGCCC-3′ and antisense primer 5′-CTTCCTAGCCAGCCGGCATC-3′. Genomic DNA (300 ng) was amplified in a final volume of 30 μl using the following conditions: initial denaturation at 95 °C for 6 min, followed by 35 cycles of 94 °C for 30 s, annealing at 60 °C for 30 s and extension at 72 °C for 1 min. A final extension step was at 72 °C for 7 min. Ten microliters of the PCR product were digested overnight at 37 °C with 5 U of Sph I restriction endonuclease (Thermo Scientific, Waltham, MA), and resulting fragments were separated on a 2 % agarose gel. The fragment sizes were 435 bp (undigested) for the C allele and 247 bp + 188 bp for the polymorphic variant (T allele). The quality of genotyping was controlled by using blind DNA duplicates for random samples. In addition, 20 samples were randomly selected for each genotype and the PCR products were sequenced in CEQ 8000 Genetic Analysis System (Beckman Coulter, England). There was a 100 % concordance between genotyping assays.

Statistical Analysis

Statistical calculations were performed using SPSS version 11.0 for Windows (SPSS, Inc., Chicago, IL, USA). For baseline characteristics, the normally distributed continuous variables are presented as mean ± SD. The Hardy–Weinberg equilibrium was assessed using a Chi-squared test with 1 degree of freedom. Genotype distribution and allele frequencies were compared between groups using a Pearson’s Chi-squared test of independence with 2 × 2 contingency and z statistics. ANOVA was used to compare average values of biochemical parameters. Pearson’s Chi-squared test and Mann–Whitney test were used for comparing discrete and continuous variables. For significant allelic and genotyping associations, the adjusted odds ratios (ORs) with corresponding 95 % confidence intervals (CI) were calculated. Since the number of the homozygous patients TT was small, we combined the TT and CT into a single group to improve the statistical power. Power calculations were performed with the program of Purcell et al. (Purcell et al. 2003) (available at http://pngu.mgh.harvard.edu/~purcell/gpc/). In the stroke patient group, the frequency of the MMP-9 T allele was 0.25. The study had 91.3 % power (α = 0.05) to detect an association (OR vs controls 1.73, 95 % CI 1.34–2.23). An interaction of the polymorphism with various risk factors was examined with multiple logistic regression analysis. The Bonferroni correction was applied for multiple comparisons with control type 1 error. Statistical significance was set at p < 0.05.

Results

The -1562 C/T (rs3918242) polymorphism in the MMP-9 gene was genotyped in 322 patients with stroke (90 % had ischemic stroke) and 410 healthy control subjects. The demographic and clinical characteristics of all studied subjects are summarized in Table 1. The stroke patients presented an average age 10 years older than controls. Gender did not statistically differ between patients and controls (p = 0.31). Compared with controls, the stroke patient group had a higher prevalence of conventional risk factors for stroke, including higher levels of total cholesterol and triglycerides (p < 0.01 and p < 0.001, respectively). BMI in stroke patient group was also higher than in controls (p < 0.001).
Table 1

Demographic and clinical profile of studied subjects

VariableStroke patients(n = 322)Controls(n = 410) p valuea
Male/female156/166217/1930.31
Age at study (years)67.3 ± 16.256.8 ± 19.20.012
Age at stroke (years)64.3 ± 12.7NA
Diabetes mellitus (%)169 (52)0
Cardiac disease (%)219 (68)0
Hypertension (%)282 (88)0
Atrial fibrillation (%)90 (28)0
Total cholesterol (mmol/l)4.9 ± 1.34.2 ± 1.7<0.01
HDL cholesterol (mmol/l)1.2 ± 0.6ND
LDL cholesterol (mmol/l)2.91 ± 1.02ND
Triglycerides (mmol/l)1.9 ± 1.31.21 ± 0.86<0.001
BMI (kg/m2)27.1 ± 4.225.8 ± 4.6<0.001

Values are presented as mean ± SD (continuous characteristics) or as numbers with percent in parentheses (discrete characteristics)

NA not applicable, ND not determined

aPearson’s Chi-squared test for categorical variables and Mann–Whitney test for continuous variables

Demographic and clinical profile of studied subjects Values are presented as mean ± SD (continuous characteristics) or as numbers with percent in parentheses (discrete characteristics) NA not applicable, ND not determined aPearson’s Chi-squared test for categorical variables and Mann–Whitney test for continuous variables The prevalence of MMP-9 -1562 genotype and allele frequencies in stroke patients and controls is presented in Table 2. The genotype distribution among the controls and stroke patients was in Hardy–Weinberg equilibrium (p = 0.536 and p = 0.359, respectively). A significant increase in the T allele and CT + TT genotype frequencies was observed in stroke patients compared with healthy controls (OR 1.73, 95 % CI 1.34–2.23 and 1.89, 95 % CI 1.39–2.56, respectively). Multivariate logistic regression analysis was used to assess the role of the rs3918242 genotype and other coexisting factors in stroke. These adjustments did not substantially affect the OR estimates. After confounding effects of age, gender, BMI and lipid profile were adjusted, the T allele and TT genotype were significantly associated with stroke in our study population.
Table 2

Genotype and allele distribution of C(-1562)T gene polymorphism in MMP-9 gene in patients and controls

N GenotypesAllelesOR (95 % CI)
CCCTTTCT + TTCTCT + TT genotypeT allele
Stroke patients
 322174 (54)132 (41)16 (5)148 (46)0.750.251.89 (1.39–2.56) p < 0.00011.73 (1.34–2.23) p < 0.0001
Controls
 410283 (69)119 (29)8 (2)127 (31)0.840.16Ref.Ref.

Genotype distributions are shown as numbers (%). HWE test for controls X 2 = 1.25, p = 0.536; for stroke patients X 2 = 2.05, p = 0.359

Genotype and allele distribution of C(-1562)T gene polymorphism in MMP-9 gene in patients and controls Genotype distributions are shown as numbers (%). HWE test for controls X 2 = 1.25, p = 0.536; for stroke patients X 2 = 2.05, p = 0.359 Mean age at the onset of stroke was compared in patients with CT + TT versus CC genotype. The T allele carriers (CT + TT) were younger at the onset of stroke (63.5 ± 11.7 years) than patients with CC genotype (71 ± 14.1 years) (z = 3.7167, p = 0.0002). The patients were divided into subgroups with and without T2DM (n = 169 and n = 153, respectively). The comparison between these subgroups showed that the T allele and CT + TT genotype were more frequent in patients with T2DM compared with those without diabetes, with the OR 1.48 (95 % CI 1.03–2.12) for T allele and 1.44 (95 % CI 1.93–2.24) for CT + TT genotype (Table 3).
Table 3

Genotype and allele distribution of C(-1562)T gene polymorphism in MMP-9 gene in stroke patients with and without T2DM

N GenotypesAllelesOR (95 % CI)
CCCTTTCT + TTCTCT + TT genotypeT allele
STR + T2DM
 16984 (50)72 (43)13 (7)85 (50)0.710.291.44 (1.93–2.24) p = 0.1011.48 (1.03–2.12) p = 0.031
STR no T2DM
 15390 (59)60 (39)3 (2)63 (41)0.780.22Ref.Ref.
Controls
 410283 (69)119 (29)8 (2)127 (31)0.840.16

Genotype distribution is shown as numbers (%). For STR + T2DM subgroup compared with control group, OR is 2.07 (95 % CI 1.53–2.79) for T allele and 2.25 (95 % CI 1.56–3.25) for CT + TT genotype

STR stroke, T2DM type 2 diabetes

Genotype and allele distribution of C(-1562)T gene polymorphism in MMP-9 gene in stroke patients with and without T2DM Genotype distribution is shown as numbers (%). For STR + T2DM subgroup compared with control group, OR is 2.07 (95 % CI 1.53–2.79) for T allele and 2.25 (95 % CI 1.56–3.25) for CT + TT genotype STR stroke, T2DM type 2 diabetes

Discussion

In the present study, we identified an association between genetic polymorphism in matrix metalloproteinase-9 gene and the risk of ischemic stroke. The main finding is that the T allele of the -1562 C/T polymorphism might increase risk of stroke. Compared with control group, the increase was 1.9-fold for stroke patients carrying T allele and 2.3-fold for diabetic T allele carriers. The similar result was obtained by Nie et al. (2014) in a recently published study of 396 Chinese patients with ischemic stroke. The TT genotype and T allele frequencies of MMP-9 C/T polymorphism were significantly increased in stroke patients. The stroke incidence was increased 1.5-fold in patients carrying the T allele. Our results are not consistent with a previous study performed in a Polish population that showed no association between the MMP-9 -1562 C/T polymorphism and increased risk of ischemic stroke (Szczudlik and Borratynska 2010). The authors studied 418 patients with ischemic stroke of various etiologies. Statistical analysis did not show a significant difference in distribution of CC, CT and TT genotypes or C and T alleles between ischemic stroke patients and controls. The association of the MMP-9 -1562 C/T polymorphism with cardiovascular disease was found in another Polish study of 110 patients with coronary atherosclerosis (Goracy et al. 2003). The results suggested that C(-1562)T MMP-9 transition is associated with premature ischemic heart disease in Polish patients. It is difficult to explain the discrepancy between our results and those of Szczudlik et al. (Szczudlik and Borratynska 2010) since both studies involved similar number of stroke patients from Polish population. Stroke is a complex disease in which it might be difficult to demonstrate an impact of a single polymorphism. An interactive effect of several factors may lead to underestimation or overestimation of a role of given polymorphism in determining the phenotype. There are some limitations in this type of study that might account for differences in obtained results. Control subjects are considered free of cerebrovascular disease by medical history, lack of neurological deficits and laboratory examinations. However, without brain imaging studies, some control subjects might have been affected by silent stroke. This could reduce the statistical power. Another limitation is that some interactions between MMP-9 and other candidate genes might be different between different studies, but these interactions are usually not taken under consideration. The -1562 C/T polymorphism in MMP-9 gene was analyzed in a study of four SNPs in patients with myocardial infarction (854 patients) and those with ischemic stroke (367 patients) (Kaplan et al. 2008). All studied MMP-9 SNPs or haplotypes were not associated with myocardial infarction or ischemic stroke. Diabetes mellitus is a well-recognized risk factor for coronary and cerebrovascular diseases (Banerjee 2012; Djelilovic-Vranic et al. 2013). They share many characteristics, due to the fact that diabetes affects blood vessels and stroke is a disease of blood vessels. Moreover, diabetes is commonly associated with other cardiovascular risk factors, such as hyperlipidemia and increased low-density lipoprotein levels (Taylor et al. 2013). Therefore, MMP-9 might be one of the potential candidate genes for the link between T2DM and ischemic stroke. The allele frequencies of different polymorphisms in diabetic patients might be different from those in nondiabetic subjects. Also, different polymorphisms could be related to different risk factors in patients with type 2 diabetes. In our study, the T allele and CT + TT genotype were more frequent in patients with T2DM compared with those without diabetes, with the OR 1.48 (95 % CI 1.03–2.12) for T allele and 1.44 (95 % CI 1.93–2.24) for CT + TT genotype. This indicates that there might be a different mechanism for the effect of -1562 polymorphism in diabetic patients. This effect might depend on the population studied. Katakami et al. (2010) evaluated the -1562 MMP-9 polymorphism in 3094 Japanese type 2 diabetes subjects. They did not observe a statistically significant association between this polymorphism and the prevalence of cerebral infarction. The mechanism of the observed effect of studied polymorphism on susceptibility to stroke is unknown. The -1562 C/T polymorphism is located in the promoter region of MMP-9 gene. Transcriptional activity of the T allele was found to be significantly higher than that of the C allele (Blankenberg et al. 2003). Increased expression of MMP-9 may increase plaque instability. The disruption of vulnerable atherosclerotic plaque and subsequent thrombus formation play critical role in the pathogenesis of cerebrovascular disease. In conclusion, our findings suggest that MMP-9 -1562 genotypes are significantly associated with the risk of ischemic stroke in patients with and without T2DM. These results require replication in future studies. The effect on observed genetic susceptibility is modest but might be important in the presence of other genetic factors. The study provides new clinically relevant information regarding genetic determinants of susceptibility to stroke.
  24 in total

1.  Genetic variation at the matrix metalloproteinase-9 locus on chromosome 20q12.2-13.1.

Authors:  B Zhang; A Henney; P Eriksson; A Hamsten; H Watkins; S Ye
Journal:  Hum Genet       Date:  1999-11       Impact factor: 4.132

2.  Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits.

Authors:  S Purcell; S S Cherny; P C Sham
Journal:  Bioinformatics       Date:  2003-01       Impact factor: 6.937

3.  Duration of diabetes and risk of ischemic stroke: the Northern Manhattan Study.

Authors:  Chirantan Banerjee; Yeseon P Moon; Myunghee C Paik; Tatjana Rundek; Consuelo Mora-McLaughlin; Julio R Vieira; Ralph L Sacco; Mitchell S V Elkind
Journal:  Stroke       Date:  2012-03-01       Impact factor: 7.914

4.  Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis.

Authors:  B Zhang; S Ye; S M Herrmann; P Eriksson; M de Maat; A Evans; D Arveiler; G Luc; F Cambien; A Hamsten; H Watkins; A M Henney
Journal:  Circulation       Date:  1999-04-13       Impact factor: 29.690

Review 5.  Matrix metalloproteinases in vascular remodeling and atherogenesis: the good, the bad, and the ugly.

Authors:  Zorina S Galis; Jaikirshan J Khatri
Journal:  Circ Res       Date:  2002-02-22       Impact factor: 17.367

6.  Changes in plasma matrix metalloproteinase-9 levels in patients with acute ischemic stroke.

Authors:  Inimioara Mihaela Cojocarui; M Cojocaru; Violeta Sapira; Gabriela Socoliuc; Cristina Hertea; S Paveliu
Journal:  Rom J Intern Med       Date:  2012 Apr-Jun

7.  Variants of the Matrix Metalloproteinase-2 but not the Matrix Metalloproteinase-9 genes significantly influence functional outcome after stroke.

Authors:  Helena Manso; Tiago Krug; João Sobral; Isabel Albergaria; Gisela Gaspar; José M Ferro; Sofia A Oliveira; Astrid M Vicente
Journal:  BMC Med Genet       Date:  2010-03-11       Impact factor: 2.103

8.  Relationship between plasma metalloproteinase-9 levels and volume and severity of infarct in patients with acute ischemic stroke.

Authors:  Recep Demir; Hızır Ulvi; Lütfi Özel; Gökhan Özdemir; Metin Güzelcik; Recep Aygül
Journal:  Acta Neurol Belg       Date:  2012-05-12       Impact factor: 2.396

9.  Accumulation of gene polymorphisms related to plaque disruption and thrombosis is associated with cerebral infarction in subjects with type 2 diabetes.

Authors:  Naoto Katakami; Mitsuyoshi Takahara; Hideaki Kaneto; Ikki Shimizu; Keizo Ohno; Fukashi Ishibashi; Takeshi Osonoi; Atsunori Kashiwagi; Ryuzo Kawamori; Iichiro Shimomura; Munehide Matsuhisa; Yoshimitsu Yamasaki
Journal:  Diabetes Care       Date:  2009-11-23       Impact factor: 19.112

Review 10.  Matrix metalloproteinases: inflammatory regulators of cell behaviors in vascular formation and remodeling.

Authors:  Qishan Chen; Min Jin; Feng Yang; Jianhua Zhu; Qingzhong Xiao; Li Zhang
Journal:  Mediators Inflamm       Date:  2013-06-12       Impact factor: 4.711

View more
  10 in total

1.  Optimization of time for neural stem cells transplantation for brain stroke in rats.

Authors:  Seyyed Mohyeddin Ziaee; Parisa Tabeshmehr; Khawaja Husnain Haider; Majidreza Farrokhi; Abdolhamid Shariat; Atena Amiri; Seyed Mojtaba Hosseini
Journal:  Stem Cell Investig       Date:  2017-04-14

2.  Clinical study of different doses of atorvastatin combined with febuxostat in patients with gout and carotid atherosclerosis.

Authors:  Zheng Zhang; Ming-Hua Xu; Feng-Ju Wei; Li-Na Shang
Journal:  Pak J Med Sci       Date:  2020 Sep-Oct       Impact factor: 1.088

3.  Cerebral Autoregulation in Hypertension and Ischemic Stroke: A Mini Review.

Authors:  Shashank Shekhar; Ruen Liu; Olivia K Travis; Richard J Roman; Fan Fan
Journal:  J Pharm Sci Exp Pharmacol       Date:  2017-10-27

4.  The β-fibrinogen gene 455G/A polymorphism associated with cardioembolic stroke in atrial fibrillation with low CHA2DS2-VaSc score.

Authors:  Xiaofeng Hu; Junjun Wang; Yaguo Li; Jiong Wu; Song Qiao; Shanhu Xu; Jun Huang; Linhui Chen
Journal:  Sci Rep       Date:  2017-12-13       Impact factor: 4.379

5.  Lysophosphatidic Acid Is Associated with Atherosclerotic Plaque Instability by Regulating NF-κB Dependent Matrix Metalloproteinase-9 Expression via LPA2 in Macrophages.

Authors:  Chun Gu; Fang Wang; Zhenwen Zhao; Hongyue Wang; Xiangfeng Cong; Xi Chen
Journal:  Front Physiol       Date:  2017-04-27       Impact factor: 4.566

6.  Association between Increased Matrix Metalloproteinase-9 (MMP-9) Levels with Hyperglycaemia Incidence in Acute Ischemic Stroke Patients.

Authors:  Ismail Setyopranoto; Rusdy Ghazali Malueka; Andre Stefanus Panggabean; I Putu Eka Widyadharma; Ahmad Hamim Sadewa; Rusdi Lamsudin; Samekto Wibowo
Journal:  Open Access Maced J Med Sci       Date:  2018-11-18

7.  Matrix Metalloproteinase-9 Gene Polymorphism and Its Methylation in Stroke Patients.

Authors:  Omkar Kalidasrao Choudhari; Anita Rani; Geeta Kampani; Charanjeet Kaur; Ananya Sengupta
Journal:  Malays J Med Sci       Date:  2021-12-22

Review 8.  Matrix Metalloproteinase-9 as an Important Contributor to the Pathophysiology of Depression.

Authors:  Hongmin Li; Zhaofu Sheng; Suliman Khan; Ruiyi Zhang; Yang Liu; Yan Zhang; V Wee Yong; Mengzhou Xue
Journal:  Front Neurol       Date:  2022-03-18       Impact factor: 4.003

Review 9.  The Role of Matrix Metalloproteinase Polymorphisms in Ischemic Stroke.

Authors:  Jason J Chang; Ansley Stanfill; Tayebeh Pourmotabbed
Journal:  Int J Mol Sci       Date:  2016-08-12       Impact factor: 5.923

10.  Matrix Metalloproteinases as a Pleiotropic Biomarker in Medicine and Biology.

Authors:  Jacek Kurzepa; Fatma M El-Demerdash; Massimiliano Castellazzi
Journal:  Dis Markers       Date:  2016-11-09       Impact factor: 3.434

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.