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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
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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
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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
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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
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than control group (
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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
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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
1 cycle 96°C for 5 min; 30
cycles (96°C for 30 sec, 60°C
for 1 min, 72°C for 1 min); final
extension at 72°C for 7 min
MMP3 -11715A-6A
(rs35068180)
GAAGGAATTAGAGCTG
CCACA
AAGGGATTTCTCTGTGG
CAA
1 cycle 94°C for 5 min; 30
cycles (94°C for 30 sec, 58°C
for 1 min, 72°C for 1 min); final
extension at 72°C for 7 min
MMP7 -181A-G
(rs11568818)
CCTGCCATCTTTCCCCT
GTA
ACGGTGAGTCGCATAGC
TG
1 cycle 96°C for 5 min; 35
cycles (96°C for 30 sec, 56°C
for 2 min, 72°C for 30 sec); final
extension at 72°C for 7 min
MMP8 -799C-T
(rs11225395)
TCTGGAGGATGTGGTTT
GGT
TCAGAATAAGTGGGACC
AGGT
1 cycle 96°C for 5 min; 27
cycles (96°C for 30 sec, 63°C
for 1 min, 72°C for 1 min); final
extension at 72°C for 7 min
+17C-G
(rs2155052)
GGCCTAGTCCTTACCA
GCTT
CCTTGTTCCTTTTCCTCA
ACCA
1 cycle 96°C for 6 min; 30
cycles (96°C for 30 sec, 60°C
for 1 min, 72°C for 1 min); final
extension at 72°C for 7 min
MMP12 -82A-G
(rs2276109)
GAAAGCACTCATTTAC
TCCAGGA
AGTGTCCATACTTACTTC
ACCAA
1 cycle 96°C for 6 min; 30
cycles (96°C for 30 sec, 58°C
for 1 min, 72°C for 1 min); final
extension at 72°C for 7 min
MMP13 -77A-G
(rs2252070)
TGGGTAAACATGCCAT
CTTGA
TCATCTTCATCACCACC
ACTG
1 cycle 96°C for 5 min; 27
cycles (96°C for 30 sec, 59°C
for 1 min, 72°C for 30 sec); final
extension at 72°C for 7 min
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Table2. Sociodemographic and clinical characteristics in study population
*Statistically significant #Fisher exact test p value
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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.