Introduction
Periodontitis can be defined as an inflammatory disorder that causes tissue and bone
loss as a consequence of various interactions between the host immune response and
pathogenic bacteria.[1] These interactions are modified by several genetic and environmental factors together
with the presence of systemic diseases and habits such as smoking.[2]
Knowledge of how immune mechanisms—inflammatory responses—are regulated is critical
for understanding the pathogenesis of complex diseases, such as periodontitis.[3] As part of the immune system, cytokines and chemokine signals regulate the immune
response to infection. Cytokines are highly important peptide mediators responsible
for cell signaling and communication. Functions of cytokines vary to include the control
of cell proliferation, cell differentiation, immune responses, and inflammatory responses.[4] In periodontal diseases, the balance between the proinflammatory and anti-inflammatory
cytokines is generally tipped toward the proinflammatory activity.[5] Among the proinflammatory cytokines is interleukin-17 (IL-17); this cytokine appears
to be of particular interest in the pathogenesis of periodontitis because of its involvement
in both inflammation and protective antimicrobial immunity.[6] Another host-derived mediator is IL-10, which possesses a potent anti-inflammatory
activity to suppress the expression of several proinflammatory mediators such as tumor
necrosis factor-α, IL-6, or IL-1.[7]
Risk factors are part of the causal chain for a particular disease or can lead to
an individual's exposure to disease. For periodontal disease, smoking, in particular,
has a consistent, positive association with loss of periodontal attachment, which
is confirmed in many studies.[8]
Despite the improvements in the classification system since the introduction of the
2017 classification of periodontal and peri-implant diseases and conditions, the problems
associated with the existing clinical diagnostic methods (inspection, palpation, periodontal
probing, and radiography) are still present such as sensitivity of probing technique
to the applied force, dimensions of the probe, and the limitations of conventional
radiograph.[9] This has increased the urge to develop a more sophisticated and precise predictors
for periodontal disease; one of them is using biomarkers present in oral fluids such
as Gingival crevicular fluid (GCF) and saliva.
Keeping these observations in mind, rapid chair-side tests, which rely on biomarkers
present in biological fluids, are developed to diagnose periodontal disease, and are
called point of care (POC) diagnostics that simplifies diagnosis and helps improve
the prognosis. The use of saliva in (POC) diagnostics offers many advantages as it
is readily available, and contains a rich array of diagnostic biomarker molecules
with the ability to obtain rapid and reliable results.[10] Based on the facts mentioned above, detecting a biomarker that can reliably be used
to establish an accurate periodontitis diagnosis has become pivotal.
Materials and Methods
An observational case–control study is a design that was applied to this study. The
potential patients were recruited from individuals seeking periodontal therapy at
the College of dentistry hospital/the University of Baghdad. The study started in
January 2022 and finished in August 2022. Each patient was requested to sign an informed
consent form after providing all the information describing the study's aim. This
study was also conducted following ethical principles, including the World Medical
Association Declaration of Helsinki.
Sample Size and Study Population
The sample size was calculated by using one of the biomarkers (IL-17) as the study's
primary outcome. The concentration of this biomarker during health was estimated to
be equal to 4.29 pg/mL, whereas, during periodontitis, its concentration was regulated
as up to 12.68 pg/mL.[11] This yields an expected odds ratio of 3 between periodontal health and periodontitis,
which was used to calculate sample size using online tool (https://epitools.ausvet.com.au/samplesize) at a 95% confidence interval and 5% error margin. The estimated sample size for
the periodontitis group is 106, rounded up to 150 to avoid drop out of the sample
and attrition bias, while it was 25 for healthy control. Accordingly, each periodontitis
group (stage I, II, III) with and without smoking received around 50 patients, following
allocation ratio of 1:2:2:2(control: smoker and non-smoker periodontitis stage I:
smoker and non-smoker periodontitis stage II: smoker and non-smoker periodontitis
stage III, respectively).
The 175 systemically healthy subjects were divided into four groups:
-
Periodontally healthy with intact periodontium as the control group.
-
Periodontitis stage I (bone loss involving 1–2mm of the root).
-
Periodontitis stage II (bone loss involves the coronal ⅓ of the root).
-
Periodontitis stage III (bone loss extends to the middle ⅓ of the root).
Periodontal health was defined by the presence of pocket probing depth (PPD) less
than or equal to 3mm, bleeding on probing less than 10% and no clinical attachment
loss (CAL) due to periodontitis.[1]
However, all periodontitis cases exhibited generalized form (≥30% of teeth involved)
and unstable status (PPD ≥5mm or PPD 4mm with bleeding on probing [BOP]).[12]
Then each of the three periodontitis group was subcategorized into two group:
-
Smokers (stage I, II, III)
-
Non-smokers (stage I, II, III)
The following data were obtained from subjects belonging to the smokers' group: (1)
number of cigarettes consumed daily, (2) frequency of smoking, and (3) number of years
of smoking. The criteria for smoking status included in this study were applied according
to Centers for Disease Control and Prevention (CDC) heavier smokers, defined as those
who smoked more than 16 cigarettes per day within the past 30 days.[13]
Eligibility Criteria
Inclusion Criteria
Systemically healthy patients (excluding the case definition criteria) eligible to
be included in the study have a minimum of 20 teeth.
Exclusion Criteria
Patients with medical disorders such as diabetes mellitus, immunologic diseases and
hepatitis, and those who had received antibiotic or periodontal treatment in the previous
3 months, diabetes mellitus, previous history of organ transplant or cancer therapy,
or had any cardiovascular disease excluded. Additional exclusion criteria include
obese patients with body mass index (BMI) more than or equal to 30.
Clinical Findings
A complete mouth examination was performed using a periodontal probe (UCN-15 probe)
by a calibrated periodontist. Clinical periodontal recordings were performed on all
dentition, including dichotomous plaque index (PLI) (±) by using disclosing agents,[14] bleeding on probing (BOP %), pocket probing depth (PPD), and CAL. BMI index was
also added to the above clinical measurements to exclude obese patients. The third
molars were also excluded.
Salivary Collection Procedure
Unstimulated saliva samples were collected from all patients before clinical evaluation;
the patients were instructed not to consume any food or drink at least 1 hour before
the saliva collection. And while they were sitting straight and their heads bent forward,
the saliva was emptied from the bottom lip into a plastic cup during a 5-minute period.
Then, the total saliva collected was aspirated from the disposable cup using a micropipette
to aspirate a measured volume of the saliva of 500μl into a plastic Eppendorf tube.
After collection, samples were centrifuged at 3000 rpm for 10 minutes to separate
the cellular debris from the salivary supernatants. After being centrifuged and separated
from the cellular debris, the salivary fluid was aspirated again, stored in a clean
and labeled Eppendorf tube, and frozen at -40°C until the day of analysis by enzyme-linked
immunosorbent assay (ELISA) kits for IL-10 and IL-17.
Enzyme-Linked Immunosorbent Assay
Salivary samples were added in triplicate to the wells of microtiter plates to determine
the concentrations of human IL-17 and IL-10 using Shanghai YL Biotech ELISA Kits.
The IL-10 and IL-17 levels were calculated from the standard curves included in each
assay. The levels in the saliva were expressed as ng/mL.
Statistical Analysis
Data description, analysis, and presentation were performed using Statistical Package
for Social Science (SPSS version 21). The Shapiro–Wilk test was used to check the
distribution of data that indicated normal distribution; thus, multigroup comparisons
were conducted using the analysis of variance test. In case of significance, additional
intergroup comparisons were performed using Bonferroni posthoc test. The diagnostic
accuracy of the biomarkers was determined using ROC (receiver operating characteristic)
and AUC (area under curve). A level of the p-value of less than 0.05 was considered statistically significant.
Results
Demographic Characteristics
The highest mean of age was seen in stage III smokers (46.280), while the youngest
were in the control group (37.440), with no significant differences ([Table 1]). Additionally, gender distribution ([Table 2]) also showed no significant differences among the groups.
Table 1
Descriptive and statistical test of age (years) among groups
|
Stages
|
Groups
|
Mean (y)
|
± SD
|
± SE
|
Min. years
|
Max. years
|
F
|
p
-Value
|
|
Control
|
37.440
|
10.239
|
2.048
|
20.000
|
55.000
|
2.019
|
0.066 NS
|
|
Stage I
|
Nonsmoker
|
39.640
|
9.630
|
1.926
|
22.000
|
55.000
|
|
Smoker
|
40.680
|
8.669
|
1.734
|
27.000
|
55.000
|
|
Stage II
|
Nonsmoker
|
40.720
|
8.820
|
1.764
|
27.000
|
58.000
|
|
Smoker
|
43.120
|
11.487
|
2.297
|
20.000
|
65.000
|
|
Stage III
|
Nonsmoker
|
41.640
|
10.527
|
2.105
|
28.000
|
63.000
|
|
Smoker
|
46.280
|
8.928
|
1.786
|
20.000
|
62.000
|
Abbreviations: F, F test; Max, maximum; Min, minimum; NS, nonsignificant; SD, standard
deviation; SE, standard error.
Table 2
Association between gender and groups
|
|
Stage I
|
Stage II
|
Stage III
|
|
|
Total
|
|
Control
|
Nonsmoker
|
Smoker
|
Nonsmoker
|
Smoker
|
Nonsmoker
|
Smoker
|
Chi-squared test
|
p-Value
|
|
M
|
N.
|
15
|
18
|
10
|
10
|
10
|
10
|
10
|
10.405
|
0.109 NS
|
83
|
|
%
|
60
|
72
|
40
|
40
|
40
|
40
|
40
|
47.43
|
|
F
|
N.
|
10
|
7
|
15
|
15
|
15
|
15
|
15
|
92
|
|
%
|
40
|
28
|
60
|
60
|
60
|
60
|
60
|
52.57
|
Abbreviations: F, female; M, male; N, number; NS, nonsignificant.
Clinical Periodontal Parameters
Clinical periodontal parameters in terms of the PLI ([Fig. 1]) and BOP ([Fig. 2]) scores were significantly higher in all case groups compared with the control group
(p-value= 0.00000) for both indicators.
Fig. 1 Comparison of mean percentage of plaque index (PLI) among all groups. Periodontitis
(stage I–III) smoker (SM) and nonsmoker (NS) groups exhibited significantly higher
percentage of PLI than control group. BOP, bleeding on probing, *p <0.05. CI, confidence interval.
Fig. 2 Comparison of mean percentage of bleeding on probing (BOP) among groups, all periodontitis
groups exhibited significantly greater mean percentage of BOP compared with the control
group. Additionally, mean percentage of BOP was lower for the smoker's group than
non-smokers for all three stages of periodontitis, * p < 0.05. CI, confidence interval.
The mean of BOP% in the smokers' group was significantly lower than that of the nonsmokers
in both stages II (p-value= 0.026) and III (p-value= 0.000; [Table 3]).
Table 3
Descriptive and statistical test of BOP percentage among groups
|
Groups
|
Control
|
Mean
|
± SD
|
± SE
|
Minimum
|
Maximum
|
F
|
p
-Value
|
|
2.667
|
1.743
|
0.349
|
0.595
|
6.548
|
|
|
|
Stage I nonsmoker
|
23.720
|
9.276
|
1.855
|
10.714
|
59.333
|
0.022
|
0.883
|
|
Stage I smoker
|
23.156
|
7.353
|
1.471
|
11.333
|
39.744
|
|
Stage II nonsmoker
|
34.797
|
15.923
|
3.185
|
17.164
|
78.030
|
5.062
|
0.026
|
|
Stage II smoker
|
26.178
|
11.453
|
2.291
|
13.043
|
66.000
|
|
Stage III nonsmoker
|
41.228
|
18.462
|
3.692
|
14.198
|
79.710
|
13.039
|
0.000
|
|
Stage III smoker
|
27.396
|
15.324
|
3.065
|
5.952
|
70.238
|
|
Nonsmoker stages
|
F
|
10.690
|
|
|
|
p-Value
|
0.000047
|
|
|
|
Smoker stages
|
F
|
0.650
|
|
|
|
p-Value
|
0.524
|
|
|
Abbreviations: BOP, bleeding on probing; F, F test; Max, maximum; Min, minimum; SD,
standard deviation; SE, standard error.
As far as PPD and CAL are concerned, both were highest in stage III smokers' group,
as seen in [Figs. 3] and [4], respectively, with PPD having a statistical significance between stage I and III
(p-value= 0.006) only among the nonsmokers' periodontitis stages, while in the smoker's
periodontitis stages a significant difference was found between stage I and III (p-value= 0.000), stage II and III as well (p-value= 0.022).
Fig. 3 Comparison of the mean PPD scores among periodontitis stage I, II, III. Periodontitis
stage III exhibited the highest PPD mean compared with stage II and I. NS, nonsmoker;
PPD, pocket probing depth; SM, smoker, * p < 0.05. CI, confidence interval.
Fig. 4 Comparison of mean clinical attachment loss (CAL) among periodontitis stage I, II,
III, stage III group exhibited significantly higher CAL than stage II and I. CI, confidence
interval; NS, nonsmoker; SM, smoker.
Salivary Biomarkers Levels
The results showed a statistically significant difference, with higher levels of the
biomarkers in all periodontitis groups compared with controls except for stage III,
where the levels of IL-17 dropped significantly ([Table 4], [Fig. 5]), while for IL-10, there showed to be a difference between stage III and the controls;
however, it is of no statistical significance ([Table 5], [Fig. 6]).
Table 4
Comparison of IL-17 of each group with control using Dunnett two-sided
|
F
|
p-Value
|
(I) Interaction
|
(J) Interaction
|
Mean difference (I-J)
|
p-Value
|
|
73.207
|
0.000
|
Stage I nonsmoker
|
Control
|
97.122
|
0.00000
|
|
Stage I smoker
|
Control
|
79.859
|
0.00000
|
|
Stage II nonsmoker
|
Control
|
78.324
|
0.00000
|
|
Stage II smoker
|
Control
|
62.714
|
0.00000
|
|
Stage III nonsmoker
|
Control
|
− 30.496-
|
0.00534
|
|
Stage III smoker
|
Control
|
− 29.398-
|
0.00789
|
Abbreviation: IL-17, interleukin-17.
Fig. 5 Comparison of mean interleukin-17 (IL-17) levels among groups, the highest mean seen
in stage I nonsmokers (NS) group and the lowest in stage III smokers' (SM) group.
* p < 0.05. CI, confidence interval.
Table 5
Comparisons of IL-10 of each group with control using Dunnett two-sided
|
F
|
p-Value
|
(I) Interaction
|
(J) Interaction
|
Mean difference (I-J)
|
p-Value
|
|
40.075
|
0.000
|
Stage I non smoker
|
Control
|
165.149
|
0.000
|
|
Stage I smoker
|
Control
|
113.405
|
0.000
|
|
Stage II nonsmoker
|
Control
|
110.385
|
0.000
|
|
Stage II smoker
|
Control
|
57.404
|
0.001
|
|
Stage III nonsmoker
|
Control
|
3.363
|
1.000
|
|
Stage III smoker
|
Control
|
− 0.009
|
1.000
|
Abbreviation: IL-10, interleukin-10.
Fig. 6 Comparing the mean levels of interleukin-10 (IL-10) among all study groups, the highest
mean was associated with stage I nonsmokers (NS) and the lowest seen in stage III
smokers (SM). CI, confidence interval * p <0.05.
For IL-17, there was no difference between the smokers and nonsmokers periodontitis
of each stage ([Table 6]); meanwhile, a statistically significant difference between stage I and III, stage
II and III (p-value= 0.000) in both smoker's periodontitis stages and nonsmokers ([Table 7]). On the contrary, IL-10 shows a significant difference between the smokers and
nonsmokers of stages I and II (p-value= 0.001; [Table 8]); additionally, a statistical significance was found among stages of periodontitis
in both smokers and nonsmokers detailed in [Table 9].
Table 6
Descriptive and statistical test of IL-17 means among groups
|
Groups
|
Control
|
Mean
|
± SD
|
± SE
|
Minimum
|
Maximum
|
F
|
p
-Value
|
|
90.825
|
32.861
|
6.572
|
33.047
|
158.221
|
|
|
|
Stage I nonsmoker
|
187.947
|
33.514
|
6.703
|
129.218
|
287.766
|
3.633
|
0.059
|
|
Stage I smoker
|
170.684
|
21.438
|
4.288
|
131.961
|
212.276
|
|
Stage II nonsmoker
|
169.149
|
25.211
|
5.042
|
100.262
|
228.970
|
2.970
|
0.087
|
|
Stage II smoker
|
153.539
|
27.646
|
5.529
|
86.657
|
193.963
|
|
Stage III nonsmoker
|
60.329
|
50.138
|
10.028
|
11.124
|
192.174
|
0.015
|
0.904
|
|
Stage III smoker
|
61.428
|
25.620
|
5.124
|
19.672
|
100.607
|
|
Nonsmoker stages
|
F
|
115.726
|
|
|
|
p-Value
|
0.000
|
|
|
|
smoker stages
|
F
|
84.171
|
|
|
|
p-Value
|
0.000
|
|
|
Abbreviations: F, F test; IL-17, interleukin-17; SD, standard deviation; SE, standard
error.
Table 7
Multiple pairwise comparisons of IL-17 among stages using Bonferroni test
|
Smoking
|
Stage
|
Stage
|
Mean difference
|
p-Value
|
|
Nonsmoker
|
Stage I
|
Stage II
|
18.798
|
0.119
|
|
Stage III
|
127.619
|
0.000
|
|
Stage II
|
Stage III
|
108.820
|
0.000
|
|
Smoker
|
Stage I
|
Stage II
|
17.144
|
0.181
|
|
Stage III
|
109.256
|
0.000
|
|
Stage II
|
Stage III
|
92.112
|
0.000
|
Abbreviation: IL-17, interleukin-17.
Table 8
Descriptive and statistical test of IL-10 among groups
|
Groups
|
Control
|
Mean
|
± SD
|
± SE
|
Minimum
|
Maximum
|
F
|
p
-Value
|
|
56.786
|
25.882
|
5.176
|
17.441
|
124.696
|
|
|
|
Stage I nonsmoker
|
221.935
|
95.335
|
19.067
|
48.145
|
399.261
|
10.688
|
0.001
|
|
Stage I smoker
|
170.191
|
52.276
|
10.455
|
77.312
|
277.898
|
|
Stage II nonsmoker
|
167.171
|
56.388
|
11.278
|
62.664
|
245.365
|
11.205
|
0.001
|
|
Stage II smoker
|
114.190
|
41.345
|
8.269
|
58.305
|
196.250
|
|
Stage III nonsmoker
|
60.149
|
44.209
|
8.842
|
20.835
|
230.306
|
0.045
|
0.832
|
|
Stage III smoker
|
56.777
|
11.135
|
2.227
|
42.271
|
78.910
|
|
Nonsmoker stages
|
F
|
54.058
|
|
|
|
p-Value
|
0.000
|
|
|
|
Smoker stages
|
F
|
25.674
|
|
|
|
p-Value
|
0.000
|
|
|
Abbreviations: F, F test; IL-10, interleukin-10; SD, standard deviation; SE, standard
error.
Table 9
Multiple pairwise comparison of IL-10 among stages by groups using Bonferroni posthoc
test
|
Smoking
|
Stage
|
Stage
|
Mean difference
|
p-Value
|
|
Nonsmoker
|
Stage I
|
Stage II
|
54.765
|
0.002
|
|
Stage III
|
161.786
|
0.000
|
|
Stage II
|
Stage III
|
107.022
|
0.000
|
|
Smoker
|
Stage I
|
Stage II
|
56.001
|
0.002
|
|
Stage III
|
113.414
|
0.000
|
|
Stage II
|
Stage III
|
57.413
|
0.001
|
Abbreviation: IL-10, interleukin-10.
Finally, the findings in [Table 10] explain how the two biomarkers are correlated to one another.
Table 10
Correlation between IL-10 and IL-17
|
Interaction
|
IL-10
|
|
r
|
p-Value
|
|
Control
|
IL-17
|
−0.428
|
0.033
|
|
Stage I nonsmoker
|
IL-17
|
0.040
|
0.850
|
|
Stage I smoker
|
IL-17
|
−0.270
|
0.192
|
|
Stage II nonsmoker
|
IL-17
|
−0.070
|
0.740
|
|
Stage II smoker
|
IL-17
|
−0.460
|
0.021
|
|
Stage III nonsmoker
|
IL-17
|
0.613
|
0.001
|
|
Stage III smoker
|
IL-17
|
−0.162
|
0.439
|
Abbreviation: IL-17, interleukin-17.
There seems to be a significantly negative correlation in the controls group (p-value= 0.033), and stage II smoker's group (p-value= 0.021).
The biomarkers correlated significantly and positively to each other only in nonsmoker's
group of stage III (p-value= 0.001)
Diagnostic Accuracy of IL-17 and IL-10 in Discriminating Periodontal Health and Disease
Diagnostic accuracy was determined by using ROC to evaluate the sensitivity and specificity
of each biomarker to differentiate periodontal health from periodontitis and between
the different stages of periodontitis. [Fig. 7] shows that AUC for salivary IL-17 and IL-10 was 0.727 and 0.793, respectively, suggesting
a potential to discriminate between periodontal health and periodontitis. Additionally,
the above-stated biomarkers showed high diagnostic accuracy in differentiating the
different stages of periodontitis.
Fig. 7 Receiver operating characteristic (ROC) curves of interleukin-17 (IL-17) and IL-10.
(A) Periodontitis versus healthy control. (B) Stage I versus healthy control, (C) stage I versus stage II, (D) stage I versus stage III, and (E) stage II versus stage III. AUC, area under curve.
Generally, IL-17 showed a higher degree of sensitivity and specificity than IL-10,
with the highest observed association with IL-17 at a cutoff point of 127.985 ([Table 11]).
Table 11
ROC between control and periodontitis and among different stages of periodontitis
|
Test result variable(s)
|
AUC
|
p-Value
|
Optimal cutoff point
|
%Sensitivity
|
%Specificity
|
|
PD X control
|
IL-17
|
0.727
|
Good
|
0.000
|
128.164
|
65.3
|
88
|
|
IL-10
|
0.793
|
Good
|
0.000
|
63.1120
|
70.7
|
72
|
|
Stage I X control
|
IL-17
|
0.987
|
Excellent
|
0.000
|
139.728
|
92
|
96
|
|
IL-10
|
0.966
|
Excellent
|
0.000
|
94.732
|
92
|
96
|
|
Stage I–stage II
|
IL-17
|
0.670
|
Sufficient
|
0.003
|
178.564
|
82
|
54
|
|
IL-10
|
0.703
|
Good
|
0.000
|
151.867
|
62
|
70
|
|
Stage I–stage III
|
IL-17
|
0.980
|
Excellent
|
0.000
|
127.985
|
96
|
100
|
|
IL-10
|
0.951
|
Excellent
|
0.000
|
77.26
|
92
|
96
|
|
Stage II–stage III
|
IL-17
|
0.962
|
Excellent
|
0.000
|
119.547
|
92
|
94
|
|
IL-10
|
0.937
|
Excellent
|
0.000
|
78.563
|
94
|
86
|
Abbreviations: AUC, area under curve; IL-17, interleukin-17; ROC, receiver operating
characteristic.
The ROC analysis for determining the diagnostic potential of the two biomarkers in
differentiating each group of periodontitis from stage I to III smokers and nonsmokers
from the healthy controls is illustrated in [Fig. 8]. The biomarkers have shown good-to-excellent AUC values in discriminating between
all smokers and non-smokers periodontitis stages from periodontal health ([Table 12]), except for IL-10, which failed to distinguish the smokers and nonsmokers of stage
III from the healthy controls.
Fig. 8 Receiver operating characteristic (ROC) curves of interleukin-17 (IL-17) and IL-10,
(A) stage I nonsmoker versus control, (B) stage I smoker versus control, (C) stage II nonsmoker versus control, (D) stage II smoker versus control, (E) stage III nonsmoker versus control, and (F) stage III smoker versus control. AUC, area under curve.
Table 12
ROC of each group from control
|
Test result variable(s)
|
AUC
|
p-Value
|
Optimal cut off point
|
%Sensitivity
|
%Specificity
|
|
Stage I nonsmokers
|
IL-17
|
0.989
|
Excellent
|
0.000
|
144.82
|
92
|
96
|
|
IL-10
|
0.947
|
Excellent
|
0.000
|
106.345
|
92
|
96
|
|
Stage I smokers
|
IL-17
|
0.986
|
Excellent
|
0.000
|
134.101
|
92
|
96
|
|
IL-10
|
0.984
|
Excellent
|
0.000
|
94.372
|
92
|
96
|
|
Stage II nonsmokers
|
IL-17
|
0.973
|
Excellent
|
0.000
|
134.715
|
92
|
92
|
|
IL-10
|
0.960
|
Excellent
|
0.000
|
91.502
|
88
|
92
|
|
Stage II smokers
|
IL-17
|
0.925
|
Excellent
|
0.000
|
129.84
|
88
|
88
|
|
IL-10
|
0.899
|
Very good
|
0.000
|
89.158
|
76
|
88
|
|
Stage III nonsmokers
|
IL-17
|
0.749
|
Good
|
0.003
|
66.67
|
68
|
80
|
|
IL-10
|
0.544
|
Bad
|
0.594
|
50.613
|
56
|
64
|
|
Stage III smokers
|
IL-17
|
0.762
|
Good
|
0.002
|
63.995
|
60
|
84
|
|
IL-10
|
0.486
|
Not useful
|
0.869
|
67.835
|
68
|
44
|
Abbreviations: AUC, area under curve; IL-17, interleukin-17; ROC, receiver operating
characteristic.
Discussion
This study was designed to determine the potential of IL-17 and IL-10 to diagnose
patients with periodontitis by measuring their concentrations in saliva and also individuals
with healthy gingiva along with the presence of smoking as a risk factor.
Increased level of PLI among all periodontitis stages was noted, which comes in accordance
with Asif et al[15] who reported increasing plaque scores from mild, moderate-to-severe periodontitis;
this is justifiable by the dose–response relationship between oral hygiene (OH) and
periodontitis, as poorer OH results in higher plaque levels and thus, more periodontal
destruction.[16]
Also, smoking could exacerbate the condition as heat and accumulated product of combustion
result in tobacco stain and calculus, which favor plaque accumulation.[17]
With regard to BOP, it was highest in all periodontitis stages compared with controls
reflecting the inflammatory state of tissues; this coincides with Hormdee et al[18] who reported similar findings.
The smokers presented a significant reduction in BOP% in each stage compared with
nonsmokers; this coincides with Ali and Ali in 2012,[19] and this is probably due to tobacco smoking causing vasoconstriction of peripheral
vessels.[20]
Highest PPD belonged to stage III smokers with higher PPD values in the smoker's group
of each stage, and this agrees with Velidandla et al,[21] who reported that cigarette smoking is associated with increased pocket severity,
which is related to the local effect of smoke, altering the local temperature, and
favoring plaque formation and, thus, more severe pocketing.
CAL was also shown to be higher in all smokers' periodontitis stages; this could be
due to the change in the subgingival plaque composition, the virulence of subgingival
bacteria, and alteration of the host response, which increase the destruction of periodontium
and bone resorption, in addition to the damaging effects of nicotine in increasing
the production of collagenase, suppressing the growth of gingival fibroblast, and
the production of collagen and fibronectin.[22] These results were in corroboration with an overwhelming body of data from multiple
studies that have demonstrated CAL is more prevalent and severe in patients who were
tobacco users compared with nontobacco users.[23]
Various reports show considerable variation in how IL-17 is expressed in periodontitis.
IL-17 is a proinflammatory cytokine that serves the dual roles of protection and tissue
destruction. On the protective side, IL-17 confers protective immunity against microbial
pathogens by preserving barrier integrity and producing antimicrobial factors and
granulocytes such as neutrophils and macrophages.[24] It can also promote the activation of osteoclasts and potentiate neutrophilic inflammation.[24]
[25] The above-stated properties can explain the upregulation of this cytokine observed
in this study of periodontitis in stages I and II when compared with the healthy controls,
similar to the reports by some authors regarding saliva,[11]
[26] GCF,[27] and serum,[28] which all stated an increase in IL-17 levels in periodontitis regardless of the
differences in study settings.
It can be assumed that as the disease gets more advanced, higher proinflammatory interleukins
concentration in saliva would be detected, but this is not the case in this study;
the downregulation of IL-17 levels in saliva as periodontitis progressed to stage
III was quite an exciting finding. A study conducted by Liukkonen et al demonstrated
higher levels of IL-17 in localized periodontitis; meanwhile, these levels were significantly
lower in healthy and in generalized periodontitis; he stated that in saliva, IL-17
concentrations increase at an early phase of periodontitis but then reduce when the
disease progresses.[29] Sadeghi et al also reported lower IL-17 levels in GCF of periodontitis compared
with those who were healthy and attributed it to the link that IL-17 has to bone resorption
in periodontitis, so basically, its lower concentration in periodontally affected
sites might be due to its consumption.[30]
A recent study by Rodríguez-Montaño et al has reported a significant decrease in IL-17
levels in plasma of periodontitis,[31] and suggested the possibility that IL-17 is inversely proportional to the chronicity
of the disease, a pattern that perhaps coincides with the results of the present study.
As far as smoking is concerned, it did not own a significant impact on IL-17 levels
in each of the three stages of periodontitis; these results were in accordance with
Sulistio et al, who reported no significant differences in total IL-17 levels in GCF
between smokers and non-smokers with periodontitis[32] these results, however, fail to meet with results from Javed et al, who reported
higher salivary IL-17 among cigarette smokers than nonsmokers with periodontitis.[33]
Multiple possible explanations might justify these differences; one is that nonsmoker
patients may have been passive smokers through exposure from individuals who actively
smoke; this may affect the results since there is a piece of evidence that passive
smoking can activate proinflammatory cytokines.[34] Additionally, in this study, heavy cigarette smokers were exclusively included based
on CDC definition criteria, which might be different from the criteria used by other
studies. Additionally, tobacco smoking was self-reported in this study. However, an
accurate determination of a person being a smoker or a passive/nonsmoker can be done
using an assessment of whole salivary cotinine levels.[35]
Published literature on using salivary IL-17 as a diagnostic biomarker according to
the 2017 classification for different stages of periodontitis is limited, and most
of the available studies are comparative, only determined levels of IL-17 in health
and disease.
This study, however, assessed the ability of this biomarker to diagnose periodontitis
with different severities, and the results showed a potential of IL-17 to discriminate
periodontal health and periodontitis with the highest AUC (0.987) between stage I
and controls with 92% sensitivity and 96% specificity; also IL-17 was able to differentiate
among the different stages of periodontitis; this coincides with Inönü et al who reported
the potential of IL-17 to differentiate periodontal health from periodontitis with
an AUC value of 0.807.[11] However, these findings were not consistent with a study by Ozçaka et al[36] who attributed the reduction of IL-17 levels in saliva to the possibility that saliva
cannot reveal significant effects on IL-17 content, suggesting that it is useless
for detecting disease presence and/or its severity. After all, the complex role of
Th17 cells and its signature cytokine IL-17 in periodontitis, shown to be essential
but is still controversial; many conflicting factors could have caused these variations.
It could be the sampling technique, the different biological fluids, and tissues from
which the samples were obtained, and also, what is worth mentioning is the state of
periodontal disease activity (stability), namely periodontal tissue breakdown possibly
being in the quiescent period when samples were collected.
IL-10 is the other diagnostic candidate of this study; this cytokine restricts and
inhibits the action of multiple proinflammatory cytokines.
Significantly higher concentration of IL-10 in periodontitis stage I and II comparing
it to health was noted; this comes in agreement with Fenol et al who found that IL-10
levels were higher in periodontitis than in health, attributing the results to the
severity of the inflammatory process going on providing sufficient stimulus for a
positive IL-10 response,[37] likewise, in a study by Varma et al, there was higher IL-10 levels in periodontitis
stage I and II compared with health.[38] On the contrary, Tâlvan et al in 2017[39] reported higher levels of this cytokine in health despite differences in study design,
samples, and settings, explained by its well-known role in maintaining the health
and stability of periodontal tissues.
The result of this study also revealed decreasing levels of this biomarker along with
the stages of periodontitis, and this is in solidity with Tâlvan et al in 2017,[39] where IL-10 levels decreased from early to generalized, being the lowest in aggressive
periodontitis; thus, it is tempting to speculate that the higher expression of IL-10
accounts for the less severe form of the disease when compared with the progressed
state of periodontitis.
Unlike IL-17, there is a downward trend of IL-10 levels with the potential to differentiate
smokers from nonsmokers; similar findings were reported by He et al.[40] This might be explained by the tendency of smoking to exhibit suppressive action
against anti-inflammatory molecules, including IL-10, which could be caused partly
by the changes in vascular formations and microcirculatory functions in periodontal
tissue due to smoking that can influence immune function and the subsequent inflammatory
reaction in the gingiva.[41]
From another perspective, some authors reported an IL-10 rise in smoker's periodontitis
than nonsmokers,[42] and attributed it to the ability of smoking to disturb the balance between helper
T cells toward a Th2 predominance and thus more of Th2 cytokines as IL-10.
As for the diagnostic potential of these biomarkers, currently, there is a limited
number of published studies assessing the diagnostic potential of IL-10 for the staging
of periodontitis to compare with.
In a study by Varma et al 2019, IL-10 has shown a significant difference between the
health, gingivitis, and periodontitis group, but the difference between health and
gingivitis was higher than that between health and periodontitis.[38]
When correlating both biomarkers to each other, the correlation turned out to be negative,
and this correlation seems logical as IL-17 is negatively regulated by several cytokines,
one of which is IL-10.[43]
Published literature has reported the antagonistic roles of these two cytokines with
each other as Moretti et al and Sun et al[44]
[45] have described a dampening effect of IL-10 on the expression of IL-17 and indicating
the protective role of IL-10 in suppressing an IL-17 periodontitis trait and the upregulation
of IL-17 inflammatory responses in the condition of IL-10 deficiency.
When looking from a clinical point of view, the term “clinically significant” findings
are those who make the patient improve the quality of life and makes him/her feel,
function well and those which improve medical care.[46]
This definition could be translated on findings of this study, meaning, if periodontitis
could be diagnosed by a POC device using IL-17 or IL-10 levels in saliva, patients
could easily diagnose their periodontitis at home and visit dental clinics at a suitable
time; current disease activity and responses to treatment can be easily monitored
at a chair-side providing a comfortable dental experience to the patient.
However, the clinical value further relies on the discovery of new information, any
alternative therapies, cost-effectiveness, and the safety profile of the recently
designed test protocol; consequently, although this POC testing is technically feasible,
actual clinical application is still a challenge, and thus, with respect to findings
of this study, much further research and investigation are important to validate the
biomarkers (IL-17, IL-10) with large populations that suitably account for diversity
such as those related to race, region, gender, and age since careful analysis is mandatory
before adopting a newly emerged diagnostic test in the current clinical protocol.
