Gingival crevicular fluid and serum levels of resistin in obese and non-obese subjects with and without periodontitis and association with single nucleotide polymorphism at -420.

OBJECTIVE: Resistin is an adipocytokine, which have been studied for its role in insulin resistance and recently in inflammation. The present study was designed to study the gingival crevicular fluid (GCF) and serum levels of resistin in obese and non-obese subjects with and without periodontitis and to further study the association of single-nucleotide polymorphism (SNP) -420 with these levels.
MATERIALS AND METHODS: A total of 90 subjects were divided based on gingival index (GI), probing pocket depth (PPD), clinical attachment level (CAL), body mass index (BMI) and waist circumference (WC) into: Non-obese healthy (Group 1, n = 30, BMI ≤ 22.9 and WC < 90 for male subjects and < 80 for female subjects, PPD ≤ 3 mm, CAL = 0, GI = 0), non-obese periodontitis (Group 2, n = 30, BMI ≤ 22.9 and WC < 90 for male subjects and < 80 for female subjects, PPD ≥ 5 mm, CAL ≥ 3, GI ≥ 1) and obese periodontitis (Group 3, n = 30, BMI ≥ 25.0 and WC ≥ 90 for male subjects and ≥ 80 for female subjects, PPD ≥ 5 mm, CAL ≥ 3, GI ≥ 1). The GCF and serum levels of resistin were quantified using enzyme-linked immunosorbent assay and compared amongst the study groups. Further, the association of the resistin levels with periodontal inflammation and SNP at -420 was studied.
RESULTS: The mean resistin levels were highest in Group 3 (14.66 ± 5.93 ng/ml and 9.99 ± 7.22 μg/ml), followed by Group 2 (12.34 ± 4.31 ng/ml and 7.47 ± 3.94 μg/ml) and least in Group 1 (7.09 ± 3.34 ng/ml and 6.05 ± 3.61 μg/ml) in serum and GCF respectively. The levels positively correlated with GI, PPD, CAL, BMI, WC and waist-hip ratio (r < 0.6). The SNP at -420 showed that GG genotype was associated with Group 2 and 3 i.e. periodontitis, while CC genotype was associated with periodontal health. The GG genotype was also associated with high serum resistin levels as compared to CC and CG genotypes.
CONCLUSION: Resistin levels increased with periodontal inflammation indicating its possible inflammatory role in periodontitis. GG genotype at -420 is associated with increased serum resistin and with periodontal disease. Thus, further research is needed to study GG genotype and increased serum and GCF resistin levels as putative risk factors for periodontal diseases.

INTRODUCTION

Periodontal diseases are caused by bacterially derived factors and antigens that stimulate a local inflammatory reaction and activation of the innate immune system leading to loss of the connective tissue attachment and alveolar bone.[123] There has been growing interest in the association of periodontal inflammation with numerous systemic diseases notably heart diseases,[4] diabetes[5] and preterm low birth weight delivery.[6] The World Health Organization has recognized obesity as a predisposing factor for major chronic diseases ranging from cardiovascular disease to cancer.[7] In addition, a consistent positive association has been reported between obesity and periodontal inflammation.[8]

It has been demonstrated in previous research that adipose tissue contributes to sustained inflammatory response and cytokine dysregulation, playing an important role in inflammatory diseases.[9] Furthermore, while adipose tissue in lean individual secretes anti-inflammatory adipokines such as adiponectin, interleukin (IL)-10, IL-4, IL-13 and apelin, in obesity proinflammatory adipocytokines such as leptin, resistin tumor necrosis factor-alpha (TNF-α), IL-6, as well as other cytokines are released.[10] It is now clear that the adipose tissue is complex and metabolically active and secretes numerous immunomodulatory molecules, known collectively as adipokines. A recent addition to the list of these chemical inflammatory mediators is the adipocyte-derived hormone called resistin.[11]

Resistin is a member of a secretory protein family, known as resistin-like molecules (RELMs). The family is characterized by a highly conserved, cysteine-rich C terminus in which the spacing of the cysteines is invariant. There are four members in the mouse RELMs family: Resistin, RELMα, RELMβ and RELMg. Only two counterparts were found in human: Resistin and RELMβ.

Although resistin was firstly postulated to contribute to insulin resistance, more and more evidence indicated that it may also be involved in the inflammatory process. Resistin levels have been reported to be upregulated by pro-inflammatory agents.[12] Although, addition of recombinant human resistin protein to macrophages from both mouse and human resulted in the enhanced secretion of pro-inflammatory cytokines, TNF-α and IL-12.[13]

Plasma resistin levels were found associated with many inflammatory markers in some pathophysiological conditions.[14] Increased serum resistin levels are also reported in middle-aged Japanese women with periodontitis when compared with the healthy controls.[15] Presence of resistin in gingival crevicular fluid (GCF) was reported in a recent study which was correlated with gingival index (GI) scores.[16]

An abundance of evidence has emerged linking resistin to insulin resistance.[11] Blood resistin concentration was positively correlated to obesity in patients with acute myocardial infarction.[17] Also recent studies indicate that resistin may promote the initiation or perpetuation of the atherosclerotic state by activating vascular endothelial cells.[18] Thus resistin may be a missing link between inflammatory diseases, including periodontitis and systemic conditions such as diabetes atherosclerosis etc.

In addition, several single-nucleotide polymorphisms (SNPs) have been identified in the human resistin gene (RETN), one of these (a C to G substitution at position −420 in the 5’ flanking region of the gene) alters the transcriptional activity and is associated with increased resistin messenger ribonucleic acid levels in abdominal fat[19] and elevated serum resistin levels.[1920]

In the light of the above facts, the present study is designed to further probe into the role of resistin in the pathogenesis of periodontal diseases. The aim of this study is to assess the levels of resistin in serum and GCF in subjects with periodontal disease and to correlate them with disease severity and obesity. Further, this research aimed to study the SNP in resistin gene in the promoter region −420 and its correlation with periodontal disease.

MATERIALS AND METHODS

Study population

The study group consisted of 90 age and sex balanced participants (45 males and 45 females; age range: 23-54 years). Inclusion criteria included individuals who were within 23-54 years of age with clinical signs of disease in their respective group and ≥ 20 natural teeth. Patients with aggressive periodontitis, using tobacco in any form and with gross oral pathology or tumors, or any other systemic diseases that can alter the course of periodontal disease were excluded. Patients, who were on any medication that affected their periodontal status or who received periodontal therapy in the preceding 6 months, were also excluded. The ethical clearance was approved by the Institutional Ethical Committee and review board. The protocol was clearly explained to all patients, and written informed consent was obtained from all recruits. The study was conducted from November 2009 to April 2010. Each participant underwent a full-mouth periodontal probing and charting and peri-apical radiographs were taken using the long-cone technique. Radiographic bone loss was recorded dichotomously (as present or absent) to differentiate patients with chronic periodontitis. No delineation was attempted within the chronic periodontitis group based on the extent of alveolar bone loss.

Data collection and patient grouping

Participants were asked to wear light indoor clothing when they were measured for weight, height and circumferences of the waist and hips. Measurements were taken uniformly according to a standard protocol. Weight was measured to the nearest 0.1 kg, using a digital weight scale. Waist circumference (WC) was measured at 2.5 cm above the umbilicus and hip circumference at the level of maximum width of the buttocks with the subject in a standing position. Circumferences and height were measured to the nearest 0.1 cm. All measurements were taken twice. A tolerance limit of 1 kg was set for weight measurement and 1 cm for height and circumference measurements. A third measurement was taken if the difference of the first two measurements was greater than the tolerance limit. Using the average of the two closest measurements, body mass index (BMI) (weight in kilograms divided by the square of height in meters) and waist-hip ratio (WHR) (WC divided by the hip circumference) were then calculated for the analysis.

Participants were categorized into three groups based on the GI, pocket probing depths (PPD), clinical attachment levels (CALs), BMI,[21] WC and radiographic evidence of bone loss.

Group 1 (healthy) consisted of 30 Non-Obese individuals (BMI ≤ 22.9 and WC < 90 for male subjects and < 80 for female subjects) with clinically healthy periodontium, a GI = 0 (absence of clinical inflammation), PPD ≤ 3 mm and CALs = 0 with no evidence of bone loss on radiographs

Group 2 (Non Obese chronic periodontitis) consisted of 30 Non-obese individuals (BMI ≤ 22.9 and WC < 90 for male subjects and < 80 for female subjects) who showed clinical signs of gingival inflammation, a GI > 1, PPD ≥ 5 mm and CAL ≥ 3 mm and radiographic evidence of bone loss

Group 3 (Obese chronic periodontitis) consisted of 30 Obese (BMI ≥ 25.0 and WC ≥ 90 for male subjects and ≥ 80 for female subjects) individuals who had signs of clinical inflammation, a GI > 1, PPD ≥ 5 mm and CALs ≥ 3 mm with radiographic evidence of bone loss.

GCF and serum sample collection and storage

All clinical assessments using a periodontal probe, radiographs, group allocations and sampling-site selections were performed by one examiner to ensure adequate intra-examiner reproducibility. Calibration trials were performed prior to study to ensure adequate intra-examiner reproducibility. The examiner was considered calibrated once statistically significant correlation and no statistically significant difference between duplicate measurements were obtained (r = 0.87 for PPD and r = 0.90 for CAL). The difference between the examinations was within 1 mm in 86% of PPD measurements and 92% of CAL measurements. Samples were collected on the subsequent day by a second examiner. Only one site per patient was selected on day-1 as a sampling site in the periodontitis groups (Groups 2 and 3), whereas in the healthy group, multiple sites (three to five sites per patient) with an absence of inflammation were sampled to ensure the collection of an adequate amount of GCF. In patients with chronic periodontitis, sites with CAL ≥ 3 mm were identified using a periodontal probe and the site showing the greatest CAL and signs of inflammation, along with radiographic confirmation of bone loss, were selected for sampling. On the subsequent day, after gently drying the area, supragingival plaque was removed without touching the marginal gingiva and the area was isolated with cotton rolls to avoid saliva contamination. GCF was collected by placing the micro-capillary pipette at the entrance of the gingival sulcus and gently touching the gingival margin. A standardized volume of 1 μL was collected using the calibration on white color-coded 1-to 5-μL calibrated volumetric micro-capillary pipettes (Sigma Aldrich, USA). Each sample collection was allotted a maximum of 10 min and sites that did not express any GCF within the allotted time were excluded. This was carried out to ensure a traumatism and micropipettes that were suspected to be contaminated with blood and saliva were excluded from the study. Collected GCF samples were immediately transferred to airtight plastic vials and stored at −70°C until assayed.

A volume of 4 ml of blood was collected from the antecubital fossa by venipuncture using a 20-gauge needle. Blood was immediately transferred to the laboratory. Blood sample (2 ml) was allowed to clot at room temperature and after 1 h, serum was separated from the blood by centrifuging at 3,000 g for 5 min the extracted serum was immediately transferred to a plastic vial and stored at − 70°C until the time of assay and the remaining 2 ml whole blood was used for isolation of deoxyribonucleic acid (DNA) for genetic polymorphism.

Assessment of resistin levels using enzyme-linked immunosorbent assay (ELISA)

Samples were assayed for resistin levels using a commercially available ELISA kit (Quantikine human Resistin Immunoassay, RandD Systems, Inc., USA), with a minimum detection level of 0.026 ng/ml. Samples were analyzed at the Department of Microbiology, Kempegowda Institute of Medical Sciences, Bangalore, India. All reagents were allowed to warm to room temperature (18-25°C) before use. All the samples and standards were run in duplication. 100 μL of assay diluent was added to each well. 100 μL Standard, control, or appropriately diluted samples were added to the wells. Incubate for 2 h at room temperature. After 2 h the wells were aspirated and washed using the wash buffer. 200 μL of the resistin conjugate (monoclonal antibody against resistin conjugated to horseradish peroxidase with preservatives) was added to each well and incubated for 2 h at room temperature. After 2 h, the washing process was repeated. Following this, 200 μL of Substrate Solution (stabilized hydrogen peroxide + stabilized chromogen [tetramethylbenzidine]) was added to each well and incubated for 30 min at room temperature protecting from light. After 30 min. 50 μL of stop solution to each well. Determine the optical density of each well within 30 min, using a microplate reader set to 450 nm.

The SNP is using TaqMan analysis

DNA extraction

A volume of 500 μL of a blood sample was centrifuged at 10,000 rpm for 3-4 min and super supernatant discarded. In the next step, 500 μL of Tris-ethylenediaminetetraacetic acid buffer was added and centrifuged for 3-4 min at 10,000 rpm and supernatant discarded. This step for repeated 3-4 times. 500 μL of lysis buffer-1 was added and centrifuged for 3-4 min. The process was followed by the addition of lysis buffer-2 and 50 μL of proteinase-K. The sample was then kept in a water bath at 75°C for 2 h and in boiling water for 10 min and stored at − 20°C.

SNP-Typing

SNP −420 was typed by TaqMan analysis (Chromous biotech). Typing was done in (Polymerase chain reaction) PCR thermal cycler machine (Corbett research). The probes used were VIC 5’-CATGAAGACGGAGGC C-3’ for −420C and FAM 5’- ATGAAGAGGGAGGCC-3’ for −420G. Forward and reverse primers were 5’-CCACCTCCTGACCAGTCTCT-3’ and 5’- AGCCTTCCCACTTCCAACAG-3’, respectively.

Statistical analysis

ANOVA and post-doc analysis using least square difference (LSD) method were carried out for a comparison of resistin levels among groups. With the use of the Spearman rank correlation co-efficient, the relationship between the resistin concentration and clinical parameters were analyzed with a software program (SPSS version 17.1, IBM, Chicago, IL). P <0.05 was considered to be statistically significant. The sample size was estimated at 30 subjects in each group to achieve an 80% power to detect a difference of 0.5 between the null hypothesis and the alternative mean.

RESULTS

All samples in each group tested positive for resistin levels. The highest mean resistin concentrations in GCF and serum were obtained in Group 3 and the least mean resistin concentrations in Group 1. The analysis of variance showed that differences in levels of resistin concentrations among all groups for GCF and serum samples were statistically significant at P < 0.05. When Groups 1 and 2, 1 and 3 were compared (LSD method), differences in their means were statistically significant [Table 1].

Table 1

Descriptive statistics, ANOVA and post-hoc (LSD method) to compare the study groups

A significant positive correlation between GCF and serum resistin concentrations was observed in the all the study groups. GCF and serum resistin levels were positively correlated with PPD and CAL, this correlation was significantly in Group 2 and 3 for PPD. Further, the correlations between GCF and serum resistin levels and clinical parameters in the whole study population irrespective of the groups were positive with GI, PPD CAL, BMI, WC and WHR [Table 2].

Table 2

Spearman rank correlation test among the level of resistin in serum and GCF and clinical parameters

The genotype distribution showed that the GG genotype was more frequent in Group 2 and 3, while CC genotype was more frequent in Group 1. Table 3 shows the comparison of serum and GCF resistin levels, clinical parameters and Obesity measures among the genotypes. GG genotype showed significantly higher PPD.

Table 3

Polymorphism in resistin promoter region at −420 amongst the groups and study population

Further when the, GCF and serum resistin levels, clinical parameters and obesity measures were compared amongst the genotypes, GG genotype showed significant higher PPD, CAL, GI and serum resistin levels as compared to CC and CG genotype. Similarly, CG genotype showed higher PPD and CAL as compared to CC genotype and the difference was statistically significant [Table 4].

Table 4

Comparison of study parameters amongst different genotype groups: LSD method

DISCUSSION

Resistin is an adipokine and is an important potential factor linking obesity to type 2 diabetes. Although resistin was firstly postulated to contribute to insulin resistance, more evidence is linking it to inflammation.[1322] Studies have also highlighted the association of SNP −420 with the levels of resistin.[23]

In the light of current information, the present study was designed to estimate the GCF and serum resistin levels in non-obese individuals with healthy gingiva, non-obese periodontitis patients and obese periodontitis patients. The aim was to evaluate the correlation between the serum and GCF resistin levels among the study groups and to study their correlation with obesity measures, i.e. BMI, WC and WHR. Further, the genetic polymorphism of resistin at −420 was studied and correlated with clinical parameters and obesity measures.

In the present study design, the influence of age and sex on resistin concentrations is minimized by including an equal number of males and females in the study and selecting the patients within the specified age group (23-53 years). In the present study, the extra-crevicular (un-stimulated) method of GCF collection using micro-capillary pipettes is used to ensure atraumatism, to obtain an undiluted sample of native GCF, the volume of which could be accurately assessed and to avoid non-specific attachment of the analyte to filter-paper fibers.[24]

The GCF and serum resistin levels were higher in Group 2 and 3 as compared to Group 1 (healthy periodontium). This finding is in accordance with previously reported increased resistin levels in periodontitis in the Japanese populations.[1516] The increase in GCF resistin levels in positive correlation with serum levels can be attributed to seepage of resistin from serum or to the local production by inflammatory cells, such as neutrophils.[16] Further, the GCF and serum resistin levels correlated positively with signs of inflammation and periodontal disease, i.e. GI, PPD and CAL. This association of resistin with inflammation further adds to the previous evidences that were suggestive of the role of resistin in inflammatory diseases such as arthritis[22] and inflammatory bowel diseases.[25] However, in order to have a clinically significant relationship/association the correlation coefficients higher than 0.60 are required that reveals the complex nature and other contributory factors to periodontal health.[26]

GCF and serum resistin levels were correlated with obesity measures such as BMI, WC and WHR when all groups were considered (study population), but this correlation was not significant in Group 3 and Group 1. Further, no significant difference was noted in GCF and serum resistin levels between Group 2 and Group 3. Thus GCF and serum resistin levels increased with periodontal inflammation, but obesity did not affect the levels significantly when compared amongst the study groups.

Further our results of the assessment of the genotype at −420 revealed that the GG genotype was more prevalent in periodontitis groups (Groups 2 and 3) and genotype CC was associated with periodontal health. When study parameters were compared amongst the different genotype groups, serum resistin levels were higher in subjects with the GG genotype followed in order by those with CG and those with CC. This finding was in accordance with previous results where GG genotype has been associated with increased levels of resistin.[23] The difference in GCF resistin levels was not statistically different amongst the genotype groups. The GG genotype of resistin SNP at −420 has been previously associated with increased type-2 diabetes susceptibility.[21] Further increased serum resistin has been positively correlated with systolic blood pressure, low high-density lipoprotein cholesterol and C-reactive protein in Japanese population.[23] Our results along with the previous findings, highlight the possible role of resistin serum levels and GG genetic polymorphism at −420 in explaining the association of periodontal diseases and type-2 diabetes mellitus.

In summary, periodontal inflammation was associated with high resistin levels and GG genotype of resistin SNP at −420. This highlights the inflammatory role of resistin in periodontal disease. But it is not clear which other factors other than obesity parameters affect the levels of resistin in chronic periodontitis subjects. Thus further studies are needed to clarify the role of other parameters such as diabetes status on resistin levels in periodontitis cases. Due to its limitations, our study fails to highlight the temporal nature of this association, which needs further investigation using longitudinal studies. The inflammatory role of resistin and its association with other adipocytokines in chronic and aggressive periodontitis also needs further probing.