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ORIGINAL ARTICLE  
Year : 2022  |  Volume : 33  |  Issue : 1  |  Page : 18-23
Salivary tumor necrosis factor–Alpha and malondialdehyde levels in children with class II malocclusion and sleep disorders: An evaluative study


Department of Pediatric and Preventive Dentistry, AB Shetty Memorial Institute of Dental Sciences, Nitte (Deemed to be University), Mangalore, Karnataka, India

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Date of Submission23-Nov-2021
Date of Decision15-Apr-2022
Date of Acceptance19-Apr-2022
Date of Web Publication09-Aug-2022
 

   Abstract 


Context: Recently biomarkers for sleep disorders have provided an alternative and convenient means of diagnosis for children at risk. Aim: To evaluate salivary TNF-α and Malondialdehyde (MDA) levels in children with skeletal class II malocclusion and with a positive history of sleep disorders. Settings and Design: This prospective evaluative study was carried out from October 2020 to March 2021, in the Department of Pediatric and Preventive Dentistry. Material and Methods: 21 children aged 8-12 years with skeletal class II malocclusion and at least one sleep disorder participated in the study (Group 1). 21 age and gender matched children with no skeletal malocclusion and no reported history of sleep disorders served as a comparison group (Group 2). All children were evaluated regarding their sleep history and clinically examined to determine craniofacial morphology. Unstimulated saliva was collected from all children. Salivary TNF-α was measured with a solid-phase sandwich ELISA. Salivary MDA was measured by using TBA reagent. Statistical Analysis: Intergroup comparison for age and normally distributed data was done using t-test. Comparison of frequencies of categories of variables was done using Chi-square test. Inter group comparison for TNF-α was done using Mann–Whitney U test. Results: There were significantly higher levels of salivary TNF-α and MDA, in children of Group 1 when compared to that of Group 2 children (p < 0.01). Conclusion: Salivary TNF-α and MDA may be a simple and non-invasive tool in the identification and screening of children at high risk for sleep disorders.

Keywords: Biomarker, children, malondialdehyde, sleep disorders, tumor necrosis factor-alpha

How to cite this article:
Prabhu N, Shetty V. Salivary tumor necrosis factor–Alpha and malondialdehyde levels in children with class II malocclusion and sleep disorders: An evaluative study. Indian J Dent Res 2022;33:18-23

How to cite this URL:
Prabhu N, Shetty V. Salivary tumor necrosis factor–Alpha and malondialdehyde levels in children with class II malocclusion and sleep disorders: An evaluative study. Indian J Dent Res [serial online] 2022 [cited 2022 Sep 29];33:18-23. Available from: https://www.ijdr.in/text.asp?2022/33/1/18/353525



   Introduction Top


Sleep disturbances can affect the physical growth of the child as it is reported that the peaks of growth hormone secretion are most commonly observed during deep sleep.[1] Other negative consequences of sleep disorders in children include behavioral and learning issues, leading to poor academic performances.[2] Unfortunately, sleep problems are largely underdiagnosed and underreported in the majority of children. Although overnight polysomnography (PSG) is the gold standard for the diagnosis of sleep disorders, its relative complexity and costs have led to the search for alternative diagnostic methods, especially in children. Among several other diagnostic methods, discovery of biomarker has recently received enormous attention.[3]

A biomarker is a “biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process or of a condition or disease”.[3] In recent decades, the advent of biomarkers for obstructive sleep apnea (OSA) and sleep disorders have provided an alternative and more convenient means of diagnosing individuals at high risk for these conditions. The serum biomarkers associated with OSA include inflammatory biomarkers oxidative stress markers and metabolic markers.[4] Very few studies have however evaluated Tumor necrosis factor-alpha (TNF-α) and Malondialdehyde (MDA) in children with sleep problems.

Interferences in normal sleep and pattern of breathing results in diminished levels of oxygen which could trigger a cascade of events resulting in oxidative stress, alterations in metabolism, endothelial damage and resultant inflammation.[5],[6] TNF-α is one of the most important cytokines involved in sleep regulation and is also a key modulator of systemic inflammation.[7] Repetitive hypoxia and reoxygenation seen in sleep disordered breathing leads to the generation of reactive oxygen species (ROS), which may play an important role in activating multiple proinflammatory cytokines including TNF- α,IL-6 and IL-8.[8],[9]

Oxidative stress is defined as an imbalance between oxidant and antioxidant mechanisms. Intermittent hypoxia induces oxidative stress in obstructive sleep apnea syndrome (OSAS) patients which plays a significant pathophysiological role.[4] The most important mechanism of tissue damage is peroxidation of lipids in cell membranes formed by free oxygen radicals. One of the products of destruction in lipid peroxidation is MDA. Hence MDA is used as a marker of oxidative stress in the biological systems.[10]

Serum based biomarkers require blood sampling and hence may not be suitable for children. Saliva samples can be obtained noninvasively and are more likely to be accepted by children. We hypothesise that a combination of biomarkers which could simultaneously evaluate multiple pathogenic pathways is more predictive than individual ones, hence in our study, we have selected salivary TNF-α and MDA.

Although enlarged tonsils and adenoids contribute greatly to pediatric sleep disordered breathing, craniofacial/skeletal abnormalities should also be considered. Class II malocclusion is the most frequently encountered and treated malocclusion in clinical practice. A retrognathic mandible may cause the tongue to decrease the pharyngeal airway space and obstruct the airway during sleep.[11] Studies have shown that children with class II malocclusion with a positive history of sleep disorders are considered to be at a high risk for developing sleep disordered breathing.[11],[12]

Hence in this study, we sought to evaluate salivary TNF-α and MDA levels in a group of children with skeletal class II malocclusion and a history of sleep disorders with a control group of children with no skeletal malocclusion and no reported history of sleep disorders.


   Methods Top


Ethical procedures

The Research Ethics Committee of our institution approved the study (Cert. No. ABSM/EC58/2019), which was in accordance with the 1964 Helsinki declaration and its later amendments. Parents or guardians who agreed with the inclusion of their children in this research signed an informed consent form, authorising their children's participation.

Experimental design

An evaluative, cross-sectional study was conducted which included a saliva sample. All children were subjected to a detailed analysis of their sleep history, and clinical evaluation of facial morphology. Children were assigned into two groups: Group 1 (study group) and Group 2 (control group). The children of Group 1 also underwent radiographic assessment of craniofacial morphology including evaluation of airway space.

Eligibility criteria and sample size

Children aged 8-12 years of either gender, reporting to the OPD of the department of Pediatric and Preventive dentistry and who fulfilled the eligibility criteria were included for the study. The inclusion criteria for Group 1 (study group) consisted of children having at least one sleep problem as determined by a validated sleep questionnaire.[13] Children with a retrognathic mandible and a normal/prognathic maxilla as determined by a physical and radiographic examination, with a decreased upper/lower pharyngeal airway space were included in the study. Children in the Group 2 (control group) had a normal jaw relation, without any skeletal malocclusion. These children also had no history of sleep problems.

Children with obesity (BMI >95th percentile for age and gender), asthma and chronic upper respiratory disorder, diabetes or pre-diabetes, acute infections, any genetic abnormality or underlying systemic disease, cerebral palsy or neuromuscular diseases, prior history of sleep apnoea treatment with continuous positive airway pressure (CPAP) or oral appliances/orthodontic treatment and children on steroids, chronic anti-inflammatory drugs or opioid pain medication were excluded from the study.

Sample size estimation was calculated with a 5% level of significance, 80% statistical power and effect size of 0.9, hence the sample size required for 2 independent groups was 21 each, and therefore we have included 42 children in this study

Clinical examinations

A single, well-trained investigator evaluated and recorded the sleep habits and problems of the children using a validated sleep questionnaire.[13] The investigator evaluated craniofacial morphology of every child by a detailed clinical examination. Lateral cephalogram was used for skeletal and airway assessment for children of Group 1. The following parameters were assessed:[12]

  1. SNA (°)
  2. Maxillary length (mm)
  3. SNB (°)
  4. Mandibular length (mm)
  5. ANB (°).
  6. Wit's appraisal
  7. Y Axis (°).
  8. Upper pharyngeal airway space
  9. Lower pharyngeal airway space


Recording of BMI

Standing height and weight of the children were measured and recorded simultaneously. Height of the children was recorded in centimeters following the standardised procedure. Weight was recorded in kilograms using the electronic digital weighing machine. BMI for every child was calculated (body mass/height2). BMI z-scores for age and sex was determined based on WHO reference 2007.[14]

Saliva collection

1.5-2 ml of unstimulated salivary samples was collected from the children early in the morning between 8 am and 11 am in a sterile container.[15] The children were asked to refrain from eating and drinking for at least 30 min prior to saliva collection. Samples were transported to Central Research Laboratory of our institution for centrifugation at 4000 rpm for 15 min. The supernatants were stored at -80°C.

Recording of salivary TNF-α

Salivary TNF-α levels was measured with a solid-phase sandwich enzyme linked-immunosorbent assay (ELISA) (Sincere Biotech). Reagents, Samples and Standards were prepared. Sample and Standards were added and incubated for 30 min at 37°C, it was then washed 5 times and Horseradish peroxidase (HRP)-Conjugate reagent was added and incubated for 30 min at 37°C. After washing 5 times, Chromogen was added and incubated for 15 min at 37°C. 50 μl Stop Solution was added, to stop the reaction (the blue color changed to yellow colour immediately). Absorbance was read at 450 nm within 15 min.

Recording of salivary MDA

250 μL of the saliva was diluted to 500 μL with distilled water. To the diluted sample 1 mL of trichloroacetic acid-thiobarbituric acid-hydrochloric acid (TCA-TBA-HCl) reagent was then added. The samples were kept in boiling water bath for 15 min. The reaction mixture was then cooled and centrifuged. The supernatant was then taken and the optical density of the pink color formed was read at 535 nm. The concentration of MDA in the sample was noted by plotting the obtained absorbance against the standard graph. The optical density of the pink color formed is directly proportional to the concentration of MDA in the given sample.[16]

Statistical analysis

Data was subjected to statistical analysis using Statistical Package for Social Sciences (SPSS v 26.0, IBM). Descriptive statistics like frequencies and percentage for categorical data, mean and standard deviation (SD) for numerical data has been depicted.

Normality of numerical data was checked using Shapiro-Wilk test and was found that the most data followed a normal curve; hence parametric tests have been used for comparisons. Inter group comparison (2 groups) for age and normally distributed data was done using t-test. Comparison of frequencies of categories of variables with groups was done using Chi-square test. The data for TNF-α did not follow a normal curve, hence non-parametric tests have been used for comparisons. Inter group comparison (2 groups) was done using Mann Whitney U test.

Bivariate correlations between 2 numerical variables were done using Pearson's correlation (r value). For all the statistical tests, P < 0.05 was considered to be statistically significant, keeping α error at 5% and β error at 20%, thus giving a power to the study as 80%.


   Results Top


The mean age (±SD) of the children of Group 1 and Group 2 was 10.19 (±1.470) and 9.71 (±1.454) respectively. The gender ratio (M:F) was 0.52:0.48 and 0.48:0.52 for Group 1 and Group 2 respectively. Inter group comparison of age and gender revealed that there were statistically no significant differences between the two groups.

Analysis of sleep problems revealed that 14 (67%) children reported with snoring, 8 (38%) children sleeping with mouth open, 2 (10%) children with sleep talking, 2 (10%) children with frequent awakening, 2 (10%) children with restless sleep and 1 (5%) child with daytime napping.

We observed that mean upper airway space in this group was 12.14 mm which was considerably lesser than the normal upper airway measurement (15-20 mm). Meanwhile, we recorded a mean lower airway space of 8.10 mm which was definitely lesser than the normal lower airway value (11-14 mm).

Mean Salivary TNF-α levels in Group 1 and Group 2 were 37.77 (± 15.017) pg./ml and 11.54 (±2.886) pg./ml, respectively [Table 1]. Mean Salivary MDA levels in Group 1 and Group 2 were 0.94 (±0.437) μM/L and 0.19 (±0.085) μM/L, respectively [Table 1]. We observed that there was a statistically highly significant difference in salivary TNF-α levels seen between the groups (P < 0.01) with higher values in Group 1 [Table 2]. There was a statistically highly significant difference in salivary MDA levels seen between the groups (P < 0.01) with higher values observed in Group 1 [Table 3]. There was a moderately strong negative correlation between salivary TNF-α and salivary MDA with the lower airway space in Group 1 (P < 0.05; [Graph 1] and [Graph 2], respectively). However, we found a statistically non-significant correlation between salivary TNF-α and salivary MDA with the upper airway space in Group 1 (P > 0.05).
Table 1: Mean values of Salivary TNF-α and MDA levels in both the groups

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Table 2: Intergroup comparison of Salivary TNF-α levels

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Table 3: Intergroup comparison of Salivary MDA levels

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   Discussion Top


When sleep problems were analysed in children of Group 1 we observed that snoring was the most prevalent problem (67%), followed by sleeping with mouth open (38%). Almost half the children (38%) reported more than 1 sleep problem. Analysis of cephalometric variables among the Group 1 children revealed that mean ANB angle was 5.1° which indicated that there was considerable anteroposterior skeletal discrepancy in these children. We observed a considerably reduced upper and lower airway space in this group. All children belonging to Group 1 were considered for myofunctional therapy at the end of the study.

We found significantly higher levels of salivary TNF-α in Group 1 children, with a mean value of 37.77 (± 15.07) pg./ml and a median of 30.21 pg./ml (P < 0.01). Our results are consistent with that of Gozal et al.,[17] who found elevated levels of morning plasma TNF-α levels in children with OSA, which correlated with apnea/hypopnea indices. Li Q and Zheng X in a meta-analysis concluded that circulating TNF-α was significantly higher in OSAS patients than in controls.[18] Tauman et al.[19] however observed that the shorter duration of disease in children compared with adults may explain the relatively weaker association between pediatric OAS and circulating pro-inflammatory cytokine concentration.

In our study, inter group comparison of salivary MDA levels revealed a significantly higher level in Group 1 children, with a mean value of 0.94 ± 0.437 μM/L (P < 0.01). Our results were in agreement with the findings of Asker et al.,[5] who found remarkably higher levels of serum MDA in OSAS group. Pau et al.[20] in a recent systematic review and meta-analysis concluded that MDA levels were significantly higher in OSAS when compared to non OSA patients They also suggested that MDA, which is a marker of lipid peroxidation is involved in the pathogenesis of OSA. Another meta-analysis by Chen et al.[21] also documented that circulating MDA was reduced by treatment of OSA by Continuous positive airway pressure therapy.

There is substantial evidence to support the concept that, obesity increases the risk for higher expression of inflammatory mediators, many of which have demonstrated roles in the pathophysiology of cardiovascular and endothelial dysfunction.[22] We have therefore excluded obese children from our study as obesity could have been a primary confounding factor effecting the levels of the biomarkers.

Hypopneas and bouts of breathing cessation during sleep results in elevated levels of pro-inflammatory serum cytokines.[23] Airway inflammation has been evidenced to be closely related to airway collapsibility and anatomic constriction, which are two critical mechanisms involved in the pathophysiology of OSA.[19] In the present study, we examined correlations between the studied biomarkers and upper and lower airways in the children of Group 1. We found a moderately strong negative correlation between Salivary TNF-α and Salivary MDA with lower airway space which was statistically significant (r = -0.605 and r = -0.638 respectively; P < 0.01). However correlations with upper airway space were statistically non-significant (r = 0.177 and r = 0.139 respectively; P > 0.05). From these results, we assume that local oropharyngeal inflammation in children with skeletal Class II malocclusion and sleep disorders could have contributed to narrowing of the lower airways.

To summarise our findings, we found highly significant differences in the levels of salivary biomarkers TNF-α and MDA between children having skeletal class II malocclusion with sleep disorders when compared to their healthy counterparts. We also found significant moderate and negative correlation between salivary TNF-α and MDA levels with lower airway in the children with malocclusion and sleep disorders. There appeared to be a highly significant high and positive correlation between salivary TNF-α and MDA levels in all children. All children belonging to Group 1 were considered for myofunctional therapy at the end of the study.

There are however some limitations to our study. We have examined a relatively small number of children and our study design was cross-sectional, which does not allow to explore the causal relationships involved. In our study, we have not considered the dental caries status of the children, which could have contributed to the inflammatory and oxidative processes in these children.

The area of sleep biomarkers in sleep research is comparatively new and there is scarcity of published reviews. Very few studies regarding salivary biomarkers in children have been carried out. In our study, we have simultaneously evaluated two biomarkers involved in the pathophysiological processes of sleep dysregulation, namely, inflammation and oxidative stress which could be used to better predict and diagnose children with sleep disorders.


   Conclusion Top


Our study has clearly demonstrated that salivary TNF-α and MDA levels are significantly elevated in children with skeletal class II malocclusion with sleep disorders. The measurement of salivary biomarkers is non-invasive, thus is especially useful in children. They could be used as a screening procedure to identify children at a greater risk for development of OSA and other sleep-related disorders. These children could be subsequently referred for a sleep study (PSG) if indicated. More research needs to be done to explore the application of other salivary biomarkers which can be used to identify children with sleep problems for both clinical as well as at home use. The relationship between biomarkers and other parameters such as sleep quality, sleep duration, OSA severity and response to treatment procedures should also be investigated.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

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Correspondence Address:
Dr. Vabitha Shetty
Professor, Department of Pediatric and Preventive Dentistry, AB Shetty Memorial Institute of Dental Sciences, Nitte (Deemed to be University) Mangalore, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijdr.ijdr_1103_21

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