Abstract
Objectives
Salivary proton Nuclear Magnetic Resonance Spectroscopy ( 1 H NMR) has been widely used in metabonomic studies. A research gap still exists in analysing the metabolic profile in obese children suffering from severe dental caries. The aim of this study was to analyse the most identified metabolites in 10–12 years old obese children with severe dental caries and compare them with normal healthy age-matched children.
Materials and methods
Obese children with Body Mass Index Z-score > +2 ( n = 20) and normal weight children (control) ( n = 20) with severe caries underwent 1.5 mL saliva collection followed by 1 H NMR imaging. Spectra were analysed using TopSpin 3.5 and metabolite assignments were made using Chenomx NMR suite and human metabolite database.
Results
A total of 38 common metabolites were identified out of which eight were significantly increased in obese children (p < 0.05). Succinylacetone and glutamine among eight other metabolites significantly increased in the saliva of obese children suffering from severe dental caries. They were also the top contributors in the VIP score plot.
Conclusions
Thirteen (3 amino acids, 4 carboxylic acids, 2 ketoacids, 1 alcohol and 3 miscellaneous metabolites) out of the 38 metabolites identified in normal and obese children with severe dental caries, had high VIP score. Glutamine and succinylacetone showed the highest VIP score with eight metabolites significantly increased in the saliva of obese children.
Clinical relevance
This study could pave way in advancing our understanding of the relationship between caries and obesity and the potential role the metabolites can play in comparison with the normal individuals.
1
Introduction
Pediatric obesity is a known precursor to obesity and other non-communicable diseases (NCDs) in adulthood. NCD Risk Factor Collaboration (NCD-RisC) holds the largest global database on obesity in children and adolescents aged 5–19 years [ ]. Based on the World Health Organisation (WHO) growth reference curve, body mass index (BMI) values for both boys and girls at +1 SD (25.4 kg/m 2 for boys and 25.0 kg/m 2 for girls) are equivalent to the overweight while the +2 SD value (29.7 kg/m 2 for both sexes) are for obesity [ ]. In Saudi Arabia, reported obesity prevalence of 4.1–20.9% [ ] in school children is increasing due to significant changes in dietary habits and lifestyle practices. Furthermore, dental caries levels in Saudi Arabia have a prevalence of 86 % in primary teeth and 65 % in permanent teeth [ ]. A positive association was found between obesity and dental caries in various regions of Saudi Arabia [ , ].
Lipid metabolism, tyrosine, alanine, the urea cycle [ ], and inflammation markers [ ] appear to be implicated in obesity and its related disorders. Metabonomics is defined as the quantitative measurement of the multiparametric time-related metabolic responses of a complex (multicellular) system to a pathophysiological intervention or genetic modification [ ]. Nuclear magnetic resonance (NMR) is well suited for mixture studies and has been applied with success in studies involving metabolites with biofluids requiring little or no sample preparation steps [ ]. Salivary metabonomics is gaining recognition as a valuable source of biological information for severe dental caries risk and an increased BMI. The most commonly found metabolites in dental caries can be summed up as acetate, propionate, butyrate, monosaccharides, organic acids, and acetone [ , ], whereas obese pediatric patients showed high amounts of palmitic acid, myristic acid, urea, butanediol and N-acetyl galactosamine [ ]. Although most metabolites that are detectable in saliva by 1 H NMR (proton-NMR) have been identified in obesity or dental caries independently, yet, identifying and interpreting the levels of specific metabolites in obese children suffering from severe dental caries is still lacking.
Saliva, an easily accessible body fluid, holds tremendous potential in diagnostic dentistry, and its value is unquestionable. Salivary 1 H NMR has been used extensively in dentistry (salivary metabonomics) to help diagnose various conditions. 1 H NMR technology has been employed in these children to compare the metabolite profile with that of systemically healthy children. However, there is still lack of information on obese and healthy children with severe dental caries status and it would be interesting to explore their differences using salivary metabonomics. In this study, we targeted only smaller range of age group (10–12 years) of patients to reduce the variability of results involved with large effect size/SD values. For ease of access and to reduce potential errors during sample collection from a young population below 10 years, it was decided to include only older age group children (10–12 years). The aim of this study was to determine and compare the salivary metabolite profile between obese pediatric patients and normal healthy children in severe dental caries.
2
Materials and methods
2.1
Study design
This is a non-randomized case control study on children in the age group of 10–12 years. The sample size was calculated using the software PS: Power and Sample Size Calculation version 3.1.2 with the level of significance (α) of 0.05 and power (β) of 80% [ ]. Based on the mean and SD values of earlier published research [ ], the calculated sample size was 16. Considering a drop-out rate of 20%, the final sample size was increased to 20. A total of 40 children were recruited for the study. Ethical approval to conduct the study was obtained from the Institutional Review Board, King Khalid University, Saudi Arabia (Ethical Clearance No: IRB/KKUCOD/ETH/2021-22/050) and from Jawatankuasa Etika Penyelidikan Manusia Universiti Sains Malaysia (JEPeM-USM), Malaysia (USM/JEPeM/22060343). This study was conducted on obese pediatric patients and normal healthy children in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki). A written informed consent was obtained from the parents/guardians of the obese pediatric patients and normal healthy children. Obese children attending dental clinics of King Khalid University, Abha, Saudi Arabia for routine dental treatment were randomly selected for the study as experimental group ( n = 20), whereas healthy non-obese children from the same population were recruited as control ( n = 20). Inclusion criteria was only children between the age group of 10–12 years with DMFS/dmfs score more than 5 approximal surfaces. For experimental group, their BMI with Z-score >+2 for their respective age having more than 95th percentile without any systemic illness whereas for control group BMI with Z-score ≤+1 [ ]. Only the children who agreed for the Rapid Antigen Test and tested negative for Covid-19 were included in the study. Intraoral examination was conducted and a DMFS/dmfs score was given based on WHO criteria. All subjects with high DMFS/dmfs score of more than 5 were selected. These subjects then underwent 1.5 ml of whole saliva collection in a sterile manner in a calibrated test tube. All samples were taken in the morning between 9:00 a.m. and 10:00 a.m. These samples were stored at −80 ° C in cryogenic tubes which were then subjected to 1 H NMR analysis. Potential confounders include other causes of dental caries and patients’ genetic predisposition to develop obesity. Possible effect modifiers include patients’ recent food intake history and time dependant loss of salivary metabolites. This manuscript is prepared according to the STROBE guidelines.
2.2
Assessment of DMFS/dmfs status
Community Periodontal Index (CPI) probe that conformed to WHO specifications and single use mouth mirror and tweezers were used for oral diagnosis. Following the examination, World Health Organisation, Oral Health Assessment form for children (by tooth surface) 2013, was filled. More than 5 approximal surfaces involvement was considered as fulfilment of inclusion criteria. All the subjects were from the same geographical location of Abha city. Two experienced observers (a pediatric dentist and oral diagnosis specialist) carried out the examination (BMI and DMFS/dmfs) to address the potential source of bias.
2.3
Collection of saliva samples
Those who tested negative for Covid 19 were subjected to saliva collection 24 h after dental treatment to avoid blood contamination, and 12 h after the use of caffeine. Morning collections (9 a.m.–10.00 a.m.) were done to minimise the effect of the circadian rhythm. Patients were refrained upon awaking from eating, drinking, and oral hygiene. General guidelines were followed for saliva collection i.e., not to eat, brush or chew gum for 2 h before the test. A calm environment was maintained to avoid external stimulation. Unstimulated whole saliva with passive expectoration in a sterile container was used with head slightly tilted. The patient’s head was placed slightly inclined forward, dropping the 1.5 ml of saliva into a funnel that was connected to a graduated tube. All the patients were instructed to have the total saliva that was produced to be dropped without swallowing.
2.4
1 H NMR spectroscopy
Amount of saliva needed for NMR analysis was approximately 0.5 ml. Bruker Ascend 500 MHz Spectrometer (Bruker©, Biospin, Ettlingen, Germany) was used for the estimation of salivary metabolites. For high-resolution 1 H NMR analysis of aqueous liquids (food liquids, urine, blood plasma, bacterial spent medium), the samples were prepared by adding a deuterated buffer solution. The protocol for storage and transport of saliva samples was according to that given by Bertram et al. [ ]. The samples were transferred immediately to the laboratory, and centrifuged at 2000× g for 10 min and then the supernatant was stored at −80 °C.
Qualitative analysis was achieved using unbuffered samples that were prepared by adding 50 μl of D 2 O to 500 μl supernatant. Spectra were acquired on Bruker 500 MHz magnet equipped with Avance Neo Console by Bruker Corporation©, Ettlingen, Germany, with a Carr-Purcell-Meiboom-Gill (CPMG) spin-echo pulse sequence with water suppression using excitation sculpting with gradients to filter out broad macromolecule resonances, a total echo time of 64 ms, relaxation delay of 4 s, acquisition time of 1 s, and 256 transients collected with 16 k data points following four dummy scans, with a spectral width of 16 ppm (−3 to 12 ppm). Spectra were analysed in TopSpin 3.5 (Bruker Corporation©, Massachusetts, USA). A 0.3 Hz exponential line broadening function was applied before Fourier transformation and automatic phase correction. Baselines were inspected and polynomial baseline correction applied. Metabolite assignments were made using Chenomx NMR suite (v9.0 , Chenomx Inc.©, Edmonton, Canada), human metabolite database ( http://www.hmdb.ca ) and literature values [ ]. The concentration of these metabolites were profiled with respect to formate as an internal reference standard and concentration set at 30 μM as per previous studies [ ]. The use of formate as an internal reference standard in dental caries before has not been documented before and hence, this is the first study where formate has been used for this purpose.
Metabolite peaks were manually fitted using chemical shift with line width patterns of 500 MHz NMR database library inbuilt in NMR suite of Chenomx software and quantified relative to the TSP peak in each spectrum. Univariate and multivariate statistical analysis on the concentration profiling data of multiple salivary metabolites was conducted utilising Metaboanalyst ( https://www.metaboanalyst.ca/ ), a free web-based server built on the R programming language [ ]. Quantitative data was analysed using independent samples T-test.
3
Results
Healthy children had a mean BMI of 20.225 (SD = 0.97272) and DMFS/dmfs score of 11.4 (SD = 2.011) whereas those for obese children were 28.175 (SD = 1.772) and 11.6 (SD = 2.542) respectively. During the assessment of BMI and DMFS/dmfs score, two independent observers had moderate to substantial strength of agreement based on Cohen’s Kappa statistic {Cohens Kappa statistic: For BMI = 0.668, p < 0.001; For DMFS/dmfs scoring = 0.57 (p < 0.001)}.
3.1
Metabolites in the saliva samples of normal and obese children with severe dental caries
Fig. 1 shows the stacking of representative one-dimensional (1D) CPMG 1 H NMR spectra recorded on normal and obese children saliva samples. NMR enables both identification and quantification of metabolites by analysing peak characteristics in 1D 1 H NMR spectra such as chemical shift, coupling constant, and line-width. The salivary metabolites were identified making use of 500 MHz NMR database library of metabolites in the Chenomx NMR suite in combination with public databases and literature. A total 38 salivary metabolites were identified as shown in Table 1 .
| Class | # | Salivary Metabolite | ID | Normal saliva | Obese saliva | p value |
|---|---|---|---|---|---|---|
| Mean ± SD | Mean ± SD | |||||
| Amino acids | 1 | Alanine | HMDB0000161 | 8.81 ± 5.48 | 198.88 ± 365.84 | 0.16 |
| 2 | Creatine phosphate | HMDB0001511 | 2.76 ± 1.97 | 23.67 ± 30.63 | 0.07 | |
| 3 | Creatinine | HMDB0000562 | 1.09 ± 1.64 | 5.84 ± 5.69 | 0.04∗ | |
| 4 | Glutamate | HMDB0000148 | 13.74 ± 11.02 | 270.92 ± 581.27 | 0.23 | |
| 5 | Glutamine | HMDB0000641 | 8.08 ± 6.37 | 26.42 ± 21.8 | 0.03∗ | |
| 6 | Glycine | HMDB0000123 | 47.25 ± 53.5 | 412.86 ± 621.91 | 0.12 | |
| 7 | Histidine | HMDB0000177 | 2.63 ± 4.28 | 20.09 ± 21.04 | 0.04∗ | |
| 8 | Phenylalanine | HMDB0000159 | 5.65 ± 5.12 | 63.71 ± 141.32 | 0.26 | |
| 9 | Taurine | HMDB0000251 | 7.49 ± 5.36 | 67.6 ± 135.71 | 0.23 | |
| 10 | Tyrosine | HMDB0000158 | 8.55 ± 8.89 | 66.03 ± 141.34 | 0.27 | |
| Alcohols | 11 | Ethanol | HMDB0000108 | 13 ± 5.97 | 86.34 ± 97.72 | 0.05 |
| 12 | Ethylene glycol | HMDB0037790 | 1.48 ± 0.86 | 80.98 ± 177.41 | 0.22 | |
| 13 | Isopropanol | HMDB0000863 | 4.41 ± 2.32 | 30.42 ± 59.57 | 0.24 | |
| 14 | Methanol | HMDB0001875 | 29.73 ± 46.63 | 73.66 ± 81.67 | 0.20 | |
| Amine | 15 | Dimethylamine | HMDB0000087 | 0.31 ± 0.21 | 3.82 ± 4.11 | 0.03∗ |
| 16 | Methylamine | HMDB0000164 | 0.35 ± 0.19 | 17.87 ± 30.08 | 0.12 | |
| Carboxylic acids | 17 | 5-Aminopentanoate | HMDB0003355 | 4.84 ± 3.84 | 21.1 ± 22.4 | 0.06 |
| 18 | Acetate | HMDB0000042 | 637.74 ± 368.7 | 2154.09 ± 2199.73 | 0.07 | |
| 19 | Citrate | HMDB0000094 | 0.7 ± 0.33 | 8.06 ± 9.02 | 0.03∗ | |
| 20 | Glycolate | CHEBI:29805 | 2.65 ± 1.14 | 68.12 ± 103.85 | 0.09 | |
| 21 | Maleate | HMDB0000176 | 0.41 ± 0.39 | 7.3 ± 13.65 | 0.18 | |
| 22 | Malonate | HMDB0000691 | 2.73 ± 1.66 | 61.04 ± 79 | 0.06 | |
| 23 | Methylmalonate | HMDB0000202 | 7.18 ± 5.75 | 37.4 ± 57.07 | 0.16 | |
| 24 | Propionate | HMDB0000237 | 112.14 ± 72.36 | 199.51 ± 176.29 | 0.21 | |
| 25 | Succinate | HMDB0000254 | 2.20 ± 2.75 | 46.67 ± 60.65 | 0.06 | |
| 26 | Trans-aconitate | HMDB0000958 | 0.8 ± 0.55 | 8.41 ± 11.02 | 0.07 | |
| Ketoacids | 27 | Acetoacetate | HMDB0000060 | 4.05 ± 3.55 | 17.54 ± 14.5 | 0.02∗ |
| 28 | Pyruvate | HMDB0000243 | 7.54 ± 5.95 | 119.23 ± 180.42 | 0.10 | |
| 29 | Succinylacetone | HMDB0000635 | 0.76 ± 0.18 | 8.59 ± 8.44 | 0.02∗ | |
| Miscellaneous | 30 | 2-Phenylpropionate | HMDB0011743 | 2.34 ± 1.94 | 15.66 ± 27.67 | 0.19 |
| 31 | 5,6-Dihydrothymine | HMDB0000079 | 3.36 ± 2.81 | 22.34 ± 25.26 | 0.05 | |
| 32 | Acetoin | HMDB0003243 | 2.46 ± 1.36 | 15.61 ± 17.75 | 0.06 | |
| 33 | Acetone | HMDB0001659 | 12.08 ± 18.22 | 69.13 ± 101.34 | 0.14 | |
| 34 | Choline | HMDB0000097 | 1.04 ± 0.84 | 13.52 ± 16.33 | 0.04∗ | |
| 35 | Glucose | HMDB0000122 | 3.59 ± 4.39 | 16.57 ± 17.58 | 0.06 | |
| 36 | Isocaproate | HMDB0000689 | 1.3 ± 1 | 4.73 ± 4.96 | 0.07 | |
| 37 | Lactate | HMDB0000190 | 61.98 ± 96.8 | 74.22 ± 125.05 | 0.83 | |
| 38 | Pantothenate | HMDB0000210 | 1.55 ± 1.27 | 26.01 ± 60.36 | 0.27 |
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