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Research Article

Matrix Metalloproteinase (MMP) Gene Polymorphisms in Chronic

Periodontitis: A Case Control Study in Indian Population

Poulami Majumder1*, Sujay Ghosh2, Subrata Kumar Dey1

1Department of Biotechnology, Centre for Genetic studies, School of Biotechnology and Biological

Sciences, Maulana Abul Kalam Azad University of Technology (Formerly West Bengal University of

Technology), BF-142, Sector I, Salt Lake City, Kolkata, West Bengal 70064, India.

2Cytogenetics and Genomics Research Unit, Department of Zoology, University of Calcutta, 35

Ballygunge Circular Road, Kolkata, West Bengal 700019, India.

*Correspondence author: Poulami Majumder

Email id: [email protected]

Abstract

Chronic periodontitis (CP), a commonest form of inflammatory oral disease. Matrix

metalloproteinases (MMPs) plays a pivotal role in progression of CP by degrading gingival tissue and

its remodeling. In this literature we conducted a case-control study to investigate a possible

association of single nucleotide polymorphism (SNP) of MMP genes and their interaction with

chronic periodontitis in Indian population. A total of 357 DNA samples from venous blood have been

isolated, 157 identified chronic periodontitis patients and 200 healthy individuals. Genotyping of six

MMP genes (MMP1, MMP3, MMP7, MMP8, MMP12 and MMP13) was done by PCR followed by

Sanger method of sequencing. All statistical analysis was performed by SPSS v16.0, R package

(SNPassoc). Gene-gene interaction was evaluated by MDR 3.0.2. Frequency of 6A allele of MMP3 -

1715A-6A gene polymorphism (36%) and G allele of MMP8 +17G-C gene polymorphisms (34%) are

higher in CP population compared to HC population (19% and 24% respectively). A significant

association of T allele of MMP8 -799C-T gene promoter polymorphism was found with CP (OR=

2.95, 95%CI= 2.16-4.04, p

Introduction

Chronic periodontitis (CP) is considered to be the most common multifactorial complex oral disease

(Sorsa et al. 2004). CP is the destructive form of periodontitis affecting adults can be explained as

bacterial infection induced inflammatory gingival tissue that attached and support teeth. The

phenotypic characteristics manifest tissue destruction, progressive irreversible bone loss, gingival

bleeding and tooth loss (Albander et al. 2005). This multifactorial disease is regulated by bacterial,

genetic and the environmental factors that affect the adult individuals (Rintakoski et al. 2010).

Although CP is initiated by dental plaque (microbial), host factor i.e. genetic factors sustain and

determine the pathogenesis and rate of progression of the disease. The mechanism by which an

individual may develop CP is not completely understood. Most of the cases, presence of pathogenic

subgingival microbes alone does not result in periodontal tissue destruction (Hajishengallis et al.

2015). The interplay between microbial and host factors causes the imbalance of potential microbial

level that intrigues the immunological as well as host response (Molander et al. 1998 and

Hajishengallis et al. 2015). This response is mostly regulated by the genetic factors which can be

modified by several other factors including demographic, behavioral, environmental, and systemic

aspects (Parmar et al. 2009). In respect to genetic factors, the extracellular matrix metalloproteinases

(MMPs) have an important role due to their proteases which are involved in physiological and

pathological processes including remodeling and destruction of extracellular matrix (ECM) (Li et al.

2012). Any disparity occurs in MMPs is secreted by neutrophils (Holla et al. 2004). Subjected tissue

inhibitors initiate the destruction of collagen in gum tissue, leading to chronic periodontitis. But in

case of CPs, this balance may be affected initially by microbial factors and slowly progressed by

genetic factors like MMPs with the help of other factors like behavioral factors (smoking, chewing

tobacco) etc which helps to enhance the risk of CP occurrence (Parmar et al. 2009).

MMP is a large family of zinc dependent extracellular proteinases which are responsible for the tissue

remodeling and degradation of the ECM, including collagens, elastins, gelatin, matrix glycoproteins,

and proteoglycans (Weng et al. 2016). Most of the member of MMPs family are secreted as its

inactive pro form (Holla et al. 2012). The proteolytic activities of MMPs are precisely regulated by

the involvement of key factors (like microbial and other environmental, behavioral factors etc.) and

MMPs getting activated from their precursors (Visse et al. 2003). Studies suggest that MMPs

comprise the most important pathway towards the tissue destruction and remodeling associated with

periodontal tissue (Letra et al. 2012). The dramatic changes in certain levels of MMPI, MMPII,

MMPIII, MMPVII, MMPVIII, MMPXII and MMPXIII have been observed in gingival crevicular

fluid and gingival tissue of periodontitis patients (Gurkan et al. 2007). Likewise, other studies have

also shown that transcript levels of MMPs are significantly increased in affected periodontal tissue

(Malemud et al. 2006). Accordingly, it can be premised that functional polymorphisms in MMP genes

may affect MMP proteins expression and may predispose to chronic periodontal disease conditions.

Several genotype analyses of single nucleotide polymorphisms (SNPs) in MMP genes have been done

to investigate the association between genetic factors and disease occurrence. Some remarkable

studies have shown the increased frequency of some common MMP SNPs in patients with

periodontitis (Li et al. 2012; Chou et al. 2011; Keles et al. 2006; Holla et.al., 2005, Loo et al. 2011,

Majumder et al. 2017). On the contrary, some other studies have demonstrated little or no association

of these SNPs in MMP genes with genopathoetiology of CP (Holla et.al., 2004; Itagaki et.al., 2004,

Astolfi et.al., 2006; Luczyszyn et al. 2012). In different population there are different outcomes

regarding the MMP gene SNP association. The different existence of polymorphisms in genes

determines the different levels of expression of the relevant protein at transcription level that leads to

different disease phenotypes. Several common single nucleotide polymorphisms (SNPs) have been

identified in MMP genes (Li et al. 2016). We selected those genes and their polymorphisms based on

their effect on immune system, ECM degradation, and gingival inflammation. We have selected six

genes from MMP gene family viz. MMP1, MMP3, MMP7, MMP8, MMP12 and MMP13. All of these

studied MMP genes are located on chromosome 11. The aim of our study is to investigate the possible

association of MMP genes (MMP1, MMP3, MMP7, MMP8, MMP12 and MMP13) with chronic

periodontitis in Indian population. In India, to the best of our knowledge, there was only one study

had been conducted to find out the association between MMP9 gene polymorphism and CP

prevalence (Majumder et al. 2017). This quantitative study may be implicated in the

genopathoetiology of CP.

Clinical Significance

India is a genetically diverse country. A large scale of individual is affected by periodontitis

but most of the cases are neglected which may leads to more severe inflammatory and other

related diseases.

MMP may act as a biomarker of chronic periodontitis due to its direct involvement with tissue

degradation.

Risk stratification of patients with chronic periodontitis remains unclear in everyday clinical

treatment.

MMP gene-gene interaction may conclude the chronic inflammatory pathway events in CP

patients.

This work may have contribution towards the genopathoetiology of CP and may impart a

theoretical basis for prevention and clinical treatment of chronic periodontitis.

Materials and Methods:

Participants

A case-control study was carried out with a total of 357 participants among them 157 patients with

chronic periodontitis (CP) and the rest 200 participants were considered as periodontal healthy control

(HC). All participants who voluntarily participate were agreed to informed consent in accordance with

Helsinki declaration & ICMR (Indian Council of Medical Research) guidelines and after being

informed about the purpose of the study; the confidentiality of the participants was preserved during

the study. All study methods were also performed in accordance to the above-mentioned guidelines. A

large scale of participants was residing in the eastern region of India, specifically from West Bengal,

though some of participants were from north eastern region. All study subjects were recruited over the

time period of one year between September 2014 to and January 2016. The study was approved by the

institutional ethics committee. All possible clinical and epidemiological data were taken for this study.

All study subjects were in age range of 21-65 years. We made some inclusion and exclusion criteria

during the sample collection. In Figure 1 a STARD flowchart has been done that represents the

selection process of whole study subjects.

Inclusion criteria: All participants must have at least 15 remaining teeth. For CP selection patients

must possess probing depth (PD) and clinical attachment loss (CAL) more than 3mm. Smoking status

of the participants were taken on the basis of number of cigarettes (≥10/day) for last five years.

Chewing tobacco users were also identified by defining their tobacco usage ≥3 times per day for 5

years (Page et al. 1997). The status of tea intake is divided into three categories viz., more than 4 cups

per day; less than 4 cups / day and no intake.

Exclusion criteria: Those who had systemic diseases which could modify the periodontal status (viz.

the cerebro-vascular disease, arthrosclerosis, hypertension, coronary heart disease etc.) were excluded.

The socio demographic data of participants were included in this study. Clinical assessment of study

subjects was as follows: CP subjects with signs of clinical inflammation consistent with local

etiological factors, GI score >1, PD ≥4 mm, CAL ≥4 mm, with radiographic evidence of bone loss

were included in this study (Zeng et al. 2015). HC subjects have ‘healthy periodontium’ with no

evidence of loss of connective tissue attachment or supporting bone or other signs of disease activity.

All CP patients were diagnosed according to their physical, medical and dental history, tooth mobility

and radiographs. Clinical parameters include probing depth (PD), clinical attachment loss (CAL),

plaque index (PI), gingival index (GI).

Genotyping

4 ml blood were taken by venipuncture from the arm vein of each subject and kept in

Ethylenediaminetetraacetic acid (EDTA) vacuitner. Genomic DNA from each sample was isolated by

Genomic DNA Mini Kit (DSRGT DNA Isolation Kit, India) based on the instructions of the protocol.

DNA was purified by sequential phenol/chloroform extraction and salt/ethanol precipitation and

purity was measured by the ratio of OD260/ OD280. Extracted pure DNA was labeled and stored in

TE buffer at − 20 °C until use. Polymerase chain reaction (PCR) was performed for amplification of

following SNPs: MMP1 -519A-G, MMP1 -16071G-2G, MMP3 -11715A-6A, MMP7 -181A-G,

MMP8 -799C-T, MMP8 +17G-C, MMP12 -82A-G and MMP13 -77A-G. All PCR was carried out in

50µl containing 0.1 µg of DNA, 5µl of 10x buffer (Invitrogen®, Sao Paulo Brazil), 5µl of 0.5mM

MgCl2 (Invitrogen®), 1µl of 10mM dNTPs (Himedia®, India), 1µl of 0.5 µM of each primer (Sigma-

Aldrich®, India), 2.5U Taq DNA polymerase (Invitrogen®). The designed primers for each SNPs and

the thermal cycling parameters for the PCR amplification of those polymorphisms of MMPs gene

were detailed in Table 1. All PCR products were sequenced (Sanger method of sequencing) by Prism

3100 DNA Genetic Analyzer (Applied Biosystems, Carlsbad, CA, USA).

Statistical analysis

Statistical analysis was performed using SPSS version 16.0 (SPSS, Chicago, IL, USA). Continuous

variables with normal distribution are shown as mean ± standard deviation (SD). Conformity to Hardy

–Weinberg equilibrium was determined by χ2 analysis. All categorical nonparametric data were

evaluated by using chi-square test and fisher exact test. One-way analysis of variance (ANOVA) was

performed to evaluate the parametric data. The chi-square test was also used to evaluate whether

genotype and allele frequencies were in Hardy-Weinberg equilibrium (HWE). All genotyping

distribution and statistical analysis was assessed by SNPassoc version 3.4.1 in R package. The

association of each SNP with the risk for CP was analyzed by multivariate logistic regression using

the stepwise backward approach; odds ratios (OR), and 95% confidence intervals (95% CI) were also

calculated. Differences were considered statistically significant when p value is less than 0.05. For

quantitative data, the mean and 95% confidence interval (95% CI) were calculated. Bonferroni

correction was done and used only for multiple genotypic comparisons of studied genes (Pc≤0.006).

MDR 3.0.2 software (multifactor dimensionality reduction) was used to determine the gene-gene

interactions. The ‘protective alleles’ and ‘risk alleles’ combinations were determined by the same

method.

Results:

Baseline characteristics

In this study there are 157 chronic periodontitis patients were enrolled and their mean age is

41.59±11.12 years. There is no such drastic difference in mean age between patients and control

population (38.41±9.48). The basal characteristics and clinical parameters are tabulated in Table 2.

Among CP population 62% participants are regular smoker which is significantly higher than control

group (20.5%). The frequency of smoker and chewing tobacco users in CP are 62% and 62.67%. Both

the smokers and chewing tobacco users are significantly greater than controls (Fisher exact test

p

than control group (

high degree of synergy whilst the light-green line indicates a redundancy (Sinitsky et al. 2017).

MMP8 -799C-T SNP has independently strong effect (7.51%) on CP risk while MMP1 -519A-G and

MMP7 -181A-G are representing synergistic interaction effect (9.04%) towards CP susceptibility.

Figure 4 demonstrates the risk allele (dark-grey cells) and protective alleles (light-grey cells) while

combination the three factor model alleles.

Discussion:

A good periodontal health needs a balance between tissue destruction enzymes, i.e. MMPs and its

inhibitors. As we said earlier that chronic periodontitis is a multifactorial disease where genetic

factors play an important role in disease susceptibility. The reason behind the study of these genes of

periodontitis is to find out the etiology of disease genetically (Malemud et al. 2006). It is an

inflammatory oral disease henceforth, it is obvious to presence of inflammatory response in host cells.

If we going deeper, it is clear that inflammatory responses are regulated by immune responses. All the

studied genes are acting like a collaborating network of genes and their regulatory system. Our

present study reveals the findings as follows: 1) we found 6A allele of MMP3 -11715A-6A gene

polymorphism and G allele of MMP8 +17G-C gene polymorphisms are acting as protective allele in

studied CP population. It is found to be as protective as these mutant allele frequencies are also higher

in control healthy groups. 2) a significant association of MMP8-799C-T gene promoter polymorphism

with increased susceptibility to CP prevalence. 3) we found no significant association of MMP1 -

519A-G, MMP1 -16071G-2G, and MMP13 -77A-G gene polymorphisms with CP. 4) the allelic

distribution of MMP1 -519A-G, MMP1 -16071G-2G, MMP12 -82A-G and MMP13 -77A-G are non-

significantly associated to CP susceptibility. 5) Codominant and dominant model of MMP12 -82A-G

polymorphism is associated to CP increasing risk. 6) while combining the mutant genotypes of all

gene polymorphisms from those three factor models, the CP risk is seemed to be increased. 7) the best

gene-gene interaction model is MMP1 -519A-G X MMP7 -181A-G X MMP8 -799C-T

polymorphisms with CV consistency of 9/10. We have tried our best to manage and analyze this small

data statistically. Actually, the promoter of the gene responds to various stimuli, including growth

factors, cytokines, tumor promoters, and oncogene products. In our study we found no association

with MMP1 gene with CP susceptibility. There are several studies revealed that some inhibitors such

as tissue inhibitor, COX inhibitor, even anti-inflammatory interleukins may suppress the effect of

MMP1 -519A-G and MMP1 -16071G-2G polymorphisms which help to decrease the severity of CP

(Visse et al. 2003; Fontana et al. 2012). 6A polymorphism in the promoter of the MMP3 gene is

caused by a variation in the number of adenosines located at position -1171 of MMP3 relative to the

transcription start site, resulting in one allele having five adenosines (5A) and the other allele having

six adenosines (6A). It has been shown in different studies that individuals carrying the 6A allele have

decreased susceptibility to this disease (Astolfi et al. 2006 and Li et al. 2012). In this study we have

found the frequency of 6A variants more than 5A in diseased group so 6A variant of MMP3 gene can

be act as protective factor and has decreased susceptibility to the disease. The same event happens in

case of MMP8 +17G-C polymorphism. G allele is the rare allele but found dominant in both diseased

and control group which means G allele has protective shield for CP. MMP8 -799C-T polymorphism

has direct effect on tissue degradation. Result shows a significant association of MMP8 gene

polymorphism with the increasing susceptibility to CP. So, MMP8 polymorphisms may act as disease

marker for the early diagnosis of periodontitis specially of CP (Chou et al. 2011). MMP13 -77A-G

polymorphism is seemed to be negatively associated to CP progression that means the presence of

variant in lower frequency decrease the CP severity (Rossa et al. 2007). In chronic periodontitis group

the two polymorphisms of MMP8 gene are linked as they were showing D value more than 0.8 i.e.

0.92. This linkage somehow reveals that if a periodontitis patient carries MMP8 gene polymorphisms

then there is a possibility to inherit the polymorphisms together to next generation. While we studied

on gene-gene interaction we found strong effect of MMP8 -799C-T polymorphism separately but

when it interacts with another gene polymorphism entropy value become reduced and the redundancy

found between MMP8 -799C-T with MMP1 -519A-G and MMP7 -181A-G. On the contrast way, we

found synergistic interaction (red line) between MMP1 -519A-G and MMP7 -181A-G gene

polymorphisms (9.04%) while their separate effects bring no impact on CP occurrence. The dark grey

cells containing the risk allele frequency and the light grey cells indicates protective alleles

combinations (Wang et al. 2016; Sinitskyet al. 2017). It is interesting that separately polymorphisms

in MMP1 -519A-G and MMP7 -181A-G gene polymorphisms have no effects on CP susceptibility but

while combined with MMP8 -799C-T they show a significant increase susceptibility towards CP risk

(Figure 4). We therefore conclude these genotype combinations as key players in modulating the CP

risk in Indian population. Cumulatively these all genes and their polymorphism give contribution to

the periodontitis progression. The way of their expression impacts the signs of CP that results of

emergence of different types of periodontal destruction and oral diseases. Our study faced limitations

such as, the small sample size, mostly Indians from eastern zone were included. Hence, further studies

in a larger, ethnically diverse population are necessary to elucidate the role of MMP genes in CP risk.

Conclusion:

Our study concludes the significant association of MMP8 -799C-T polymorphism with CP increased

susceptibility while MMP8 +17G-C and MMP3 -11715A-6A mutant alleles are associated with the

decreased susceptibility to CP. MMP1 -519A-G and MMP7 -181A-G polymorphisms are showing

combinatorial synergistic effect on CP risk. Oral habits such as smoking, chewing tobacco are also

higher the CP susceptibility.

Acknowledgement

We would like to thank Dr. Vineet Nair and all participants of this study. This work was supported by

DBT, India (102/IFD/SAN/1699/2015-2016).

Conflict of Interest

Authors declare no conflict of interest.

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Table1. Primers and PCR conditions used in this study

Gene SNP

(rs number)

Forward Primers (5ʹ-3ʹ) Reverse Primes (5ʹ-3ʹ) PCR condition

MMP1 -519A-G

(rs494379)

AGTCCTTGCCCTTCCAG

AAA

CAGGCAGCTTAACAAAG

GCA

1 cycle 94°C for 5 min; 30

cycles (94°C for 30 sec, 60°C

for 1 min, 72°C for 1 min); final

extension at 72°C for 7 min

-16071G-2G

(rs1799750)

TGCTGCTTTCCTGAGTT

AACC

CCCCACTCTCCTTCCTTG

G





MMP3 -11715A-6A

(rs35068180)

GAAGGAATTAGAGCTG

CCACA

AAGGGATTTCTCTGTGG

CAA





MMP7 -181A-G

(rs11568818)

CCTGCCATCTTTCCCCT

GTA

ACGGTGAGTCGCATAGC

TG



for 2 min, 72°C for 30 sec); final


MMP8 -799C-T

(rs11225395)

TCTGGAGGATGTGGTTT

GGT

TCAGAATAAGTGGGACC

AGGT





+17C-G

(rs2155052)

GGCCTAGTCCTTACCA

GCTT

CCTTGTTCCTTTTCCTCA

ACCA





MMP12 -82A-G

(rs2276109)

GAAAGCACTCATTTAC

TCCAGGA

AGTGTCCATACTTACTTC

ACCAA





MMP13 -77A-G

(rs2252070)

TGGGTAAACATGCCAT

CTTGA

TCATCTTCATCACCACC

ACTG



for 1 min, 72°C for 30 sec); final


Table2. Sociodemographic and clinical characteristics in study population

*Statistically significant #Fisher exact test p value

Table3. Genotypic distribution of MMP genes variants

Gene SNPs Genotype CP (%) HC (%) Model AOR (95%CI) P value

MMP1 -519A-G AA

AG

GG

68 (43.3)

62 (39.5)

27 (17.2)

91 (45.5)

86 (43.0)

23 (11.5)

Co-dominant AA vs AG 1.05 (0.63-1.75)

0.258 AA vs GG 1.78 (0.88-3.60)

Dominant AA vs

AG+GG

1.20 (0.75-1.94) 0.44

Recessive AA+AG vs

GG

1.74 (0.9-3.37) 0.101

Over dominant AA+GG vs

AG

0.91 (0.56-1.46) 0.688

-16071G-2G 1G1G

1G2G

2G2G

81 (51.6)

58 (36.9)

18 (11.5)

101 (50.5)

73 (36.5)

26 (13.0)

Co-dominant 11 vs 12 0.95 (0.57-1.58)

0.839 11 vs 22 0.8 (0.38-1.67)

Dominant 11 vs 12+22 0.91 (0.57-1.46) 0.702

Recessive 11+12 vs 22 0.82 (0.4-1.65) 0.573

Over dominant 11+22 vs 12 1.0 (0.62-1.62) 0.997

MMP3 -11715A-6A 5A5A

5A6A

6A6A

72 (45.9)

56 (35.7)

29 (18.5)

134 (67.0)

56 (28.0)

10 (5.0)

Co-dominant 55 vs 56 2.01 (1.18-3.42)

Table4. Allele frequency of studied MMP genes variants

Gene SNPs Allele Allele frequency

Chi-squarea

(p value)

Odds ratio

(95% CI)

P valueb

CP (N=157) HC (N=200)

MMP1 -519A-G A

G

198 (0.63)

116 (0.37)

268 (0.67)

132(0.33)

1.21

(0.272)

1.189

(0.87-1.62)

0.303

-16071G-2G 1G

2G

220 (0.7)

94 (0.3)

276 (0.69)

124 (0.31)

0.09

(0.764)

0.951

(0.689-1.31)

0.806

MMP3 -11715A-6A 5A

6A

201 (0.64)

113 (0.36)

324 (0.81)

76 (0.19)

26.08

(

Table 5. Characteristics of the model of MMP gene–gene interactions associated with CP risk in

compared to control group.

Model Training

balance

accuracy

Testing

balance

accuracy

Sensitivity Specificity CV

consistency

AOR#

10.1007/s

12041-

018-

1028-3

(95%CI)

P for

permutation

test

MMP8-799C-T 0.6381 0.638 0.726 0.55 10/10 3.2403

(2.0208-

5.1957)

Fig1: STARD (Standards for reporting diagnostic accuracy study) flowchart for study population selection

Potentially eligible participants

(n = 437)

Excluded for not getting

participants’ consent

n= 13

Eligible participants

(n = 424)

Clinical test

Based on CAL, PPD, GI

(n = 403)

Excluded

(n = 21)

Due to having systemic

diseases like diabetes, flu,

blood pressure etc.

Healthy Control

(n = 200)Case

(n = 199)

Final diagnosis

Healthy Control

(n = 200)

Final diagnosis (Chronic

inflammation, accumulation of

dental plaque)

Chronic Periodontitis

(n= 157)

Inconclusive

(n = 0)

Excluded (n = 42; 40

diagnosed with AgP and 2

were inconclusive)

Fig2. Chromatograms showing genotypic variants: A. variants for MMP1 -519A-G; B. variants for MMP1 -

16071G-2G; C. variants for MMP3 -11715A-6A; D. variants for MMP7 -181A-G.

-519A-A -519A-G -519G-G

-16071G-1G -16071G-2G -16072G-2G

-11715A-5A -11715A-6A -11716A-6A

-181A-A -181A-G -181G-G

A.

B.

C.

D.

Fig2. (Contd.) Chromatograms showing genotypic variants: E. variants for MMP8 -799C-T; F. variants for

MMP8 +17G-C; G. variants for MMP12 -82A-G; H. MMP13 -77A-G.

+17 +17 +17

-799C-C -799C-T -799T-T

-82A-A -82A-G -82G-G

-77A-A -77A-G -77G-G

E.

F.

G.

H.

+17 G-G +17 G-C +17 C-C

Fig3. Entropy-based circle graph of gene–gene interactions in CP population Entropy values in cells reflect

independent effects of indicated allelic variants whereas those in connecting lines represent the effect of

interaction. The red lines reflect a high degree of synergy whilst the light-green line indicates a redundancy.

Note: The figure was generated by MDRv.3.0.2 (Computational genetics laboratory; Dartmouth).

*The expression of polymorphisms in this figure viz. MMP1(-519A-G) [which is software generated] is same as mention in text as MMP1 -

519A-G and onwards.

Fig4: Allele combinations of indicated SNPs associated with high (dark-grey cells) and low (light-grey cells)

susceptibility risk in CP patients.

Note: The figure was generated by MDRv.3.0.2 (Computational genetics laboratory; Dartmouth). The most

high-risk cells have been found in third interaction block (six high-risk cells out of nine cells) i.e. T allele of

MMP8 -799C-T with MMP1 -519A-G and MMP7 -181A-G. Hence, the effect of rare allele of MMP8 -799C-T

polymorphism causing more risk towards CP prevalence.

*The expression of polymorphisms in this figure viz. MMP1(-519A-G) [which is software generated] is same as mention in text as MMP1 -

519A-G and onwards.

matrix metalloproteinase (mmp) gene polymorphisms in ... · research article matrix...

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