Genetic Polymorphisms in TGFΒ1 and TGFΒ3 as a Potential Biomarker for Oral Health-Related Quality of Life in Children with Dental CariesABSTRACT
Objective: To determine whether polymorphisms in the TGF-β1 (rs1800469) and TGF-β3 (rs2268626) genes are potential biomarkers for oral health-related quality of life (OHRQoL) in children with dental caries, by evaluating the effect of caries severity on OHRQoL and examining its association with these genetic polymorphisms.
Material and Methods: This was a cross-sectional study in which the presence and severity of dental caries were determined through clinical examination and classified into low or high severity. Oral health-related quality of life was assessed using the Early Childhood Oral Health Impact Scale (ECOHIS), while genetic polymorphisms were analyzed using DNA extracted from oral mucosa cells and genotyped through real-time PCR. The association between candidate genes and ECOHIS scores and domains was evaluated using the Mann-Whitney non-parametric test, with a significance level set at p < 0.05.
Results: A total of 130 parents/caregivers of children aged 2-5 years completed the ECOHIS questionnaire. No significant association was observed between genetic polymorphisms and OHRQoL in any domain (p > 0.05).
Conclusion: TGFβ1(rs1800469) and TGFβ3(rs2268626) may not confer an increased risk for poor OHRQoL in children with caries experience.
Keywords:
Dental Caries; Genetics; Polymorphism; Genetic; Quality of Life.
Introduction
Quality of life (QoL) is defined as a person's assessment of their social well-being within the society in which they live. Thus, QoL encompasses multiple domains, including socioeconomic, mental, and physical health. Because it is subjective and personal, QoL is a broad concept that goes beyond the mere absence of disease [1]. The multifaceted concept of oral health-related quality of life (OHRQoL) in dentistry refers to the impact that oral disorders can have on an individual’s daily life and well-being [2].
With the advances of molecular medicine, it is possible to identify genes that may be related to diseases or general health conditions [3]. There is convincing evidence that genetic factors may influence quality of life. Many genes have been identified as potential indicators of QoL due to advances in genetic medicine, and researchers are encouraged to replicate these studies to confirm which candidate genes can be considered true biomarkers [4].
Epidemiological studies in dentistry have begun to employ these technologies to associate genetic polymorphisms with oral health outcomes. The main technique used for this purpose is real-time polymerase chain reaction (PCR) [3]. Several genes have been linked to OHRQoL, with associations reported for oral diseases and conditions, including dental caries [5-9], malocclusion [10-12], and temporomandibular disorders [13].
Genetic variations can influence OHRQoL, yet many candidate genes and pathways remain unreplicated. Transforming Growth Factor β1 (TGFβ1) and β3 (TGFβ3), immunosuppressive genes suggested as potential biomarkers for quality of life [4] and later associated with depression [14], have not yet been validated as biomarkers for OHRQoL. In contrast, the link between dental caries and impaired OHRQoL is well established [15-17].
TGFβ is a pleiotropic cytokine that regulates and differentiates cells involved in the inflammatory process, being considered predominantly pro-inflammatory [18]. In addition to its role in inflammation, TGFβ has been shown to act as a neuroprotective factor, promoting memory and protecting against cognitive decline [19]. The TGFβ gene family, which includes TGFβ1, TGFβ2, and TGFβ3, is located on chromosome 19q13.1-13.3 [20].
Polymorphisms in TGFβ1 and TGFβ3 may influence oral health-related quality of life by modulating inflammatory responses and tissue repair mechanisms in the oral cavity. Variations in these genes could alter cytokine expression or function, potentially affecting the host response to cariogenic biofilms, the severity of dental lesions, and associated symptoms such as pain, functional limitations, and discomfort. These biological effects may, in turn, translate into measurable differences in OHRQoL, as children with more severe or symptomatic caries experience greater impacts on daily activities, psychosocial well-being, and overall oral function [15-17].
Based on this rationale, the purpose of the present study is to determine whether polymorphisms in TGFβ1 and TGFβ3 are potential biomarkers of OHRQoL in children with dental caries by evaluating the effect of caries severity on OHRQoL and examining their association with these polymorphisms.
Material and Methods
Ethical Aspects
This cross-sectional study was approved by the local Human Ethics Committee of the University Federal Fluminense (Protocol no. 3.939.452). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and its subsequent amendments, or comparable ethical principles [21]. All children were given permission to participate in the study after their parents or guardians signed a written informed consent form. The study protocol was prepared according to the principles for reporting the results of genetic association studies defined by the STrengthening the REporting of Genetic Association Studies (STREGA) Declaration [22].
Sample Selection
The study included children of both sexes, aged two to five years, as the clinical sample. Their parents or legal guardians participated solely as respondents in the ECOHIS questionnaire, having completed and returned it along with the informed consent form. For convenience, the sample was drawn from the city of Nova Friburgo, State of Rio de Janeiro, Brazil, over a period of 18 months. Children without dental caries were not included. Parents and caregivers who were unable to write or speak Brazilian Portuguese fluently, who failed to sign and return the informed permission form, or who failed to complete the questions correctly were excluded. Children with mixed dentition, who did not allow the exams to be completed or with other potential confounding factors affecting the OHRQoL (i.e., malocclusion such as increased overjet, anterior open bite, posterior crossbite, and anterior crossbite; dental trauma such as fractures, avulsion, and tooth discoloration; children undergoing orthodontic or prosthetic treatment; syndromic; or with special needs) were also excluded.
Data Collection
This study was performed in three steps: 1) Non-clinical data assessment: Self-application of an OHRQoL questionnaire; 2) Oral examination to determine caries experience; 3) Genetic analysis: Collection of biological material, selection of genes/genetic polymorphisms, DNA extraction and genotype analysis.
1) Non-Clinical Data Assessment: Self-Application of an OHRQoL Questionnaire
Parents/caregivers completed a survey about their children's age, sex, and ethnicity. The Early Childhood Oral Health Impact Scale (ECOHIS), which has been validated in Brazilian Portuguese, was the sociodental indicator used [23]. Every parent was asked to fill out the survey. They completed the surveys at home and sent them back to the school with their signed informed consent.
This questionnaire comprises 13 items distributed across two sections: child impact and family impact. The child impact section has four sub-scales: symptoms, function, psychology, and self-image/social interaction. The family impact section has two sub-scales: parental distress and family function. Response categories of ECOHIS were coded on a five-point scale: 0 = never; 1 = hardly ever; 2 = occasionally; 3 = often; and 4 = very often. The score for each domain is calculated through a simple sum of the scores of each item. The total score ranges from 0 to 52, with higher scores denoting greater oral health impact and poorer OHRQoL. A higher ECOHIS score indicates a larger impact and/or more problems - that is, a poorer oral health-related quality of life [23].
However, since the research aims to relate the child’s genetics with OHRQoL, only the child subscale was considered, excluding the family subscale. Thus, the evaluated domains were oral symptoms, child function, child’s psychological and social interactions. Question 1 was assigned to the symptom domain; 2,3,4 and 5 to the function domain; 6 and 7 to the psychological domain; 8 and 9 to the social interaction domain. Questions 10, 11, 12, and 13 were excluded because they pertained to the parental and family subscales. This division enabled the analysis to assess whether the gene's impact was in one or more domains of the OHRQoL.
2) Oral Examination to Determine the Phenotype (Caries Experience)
Clinical examinations were performed by experienced pediatric dentists and have been previously described [24]. Interand intra-examiner calibration for caries diagnosis had been conducted in prior studies [5,7,8], following standardized procedures and demonstrating high reliability and reproducibility of the clinical measurements.
The World Health Organization protocol [25] for oral health surveys was used to diagnose caries in primary teeth, using the dmft index (decayed, missing, filled teeth). White spot lesions were also evaluated according to ‘the first sign of caries lesion on enamel that can be detected with the naked eye’ and used alongside the terms ‘initial’ or ‘incipient’ lesions [26]. The determination of phenotypes was established considering caries severity [27]: low caries group, dmft = 1-5 or presence of white lesion in enamel; and high caries experience group, dmft = 6.
3) Genetic Analysis: Collection of biological material, selection of genes/genetic polymorphisms, DNA extraction and genotype analysis
Oral cells were collected from the saliva of all patients through a CytoSoftTM CP-5B brush (Medical Packaging Corp., Camarillo, USA) and stored at -20°C until processing [5]. Genomic DNA was extracted from the cells for genotyping, as previously described by Küchler et al. [3]. This material was collected in a sterile container, identified, and frozen to maintain the sample's characteristics and enable genotyping for the laboratory of the Health Institute of Nova Friburgo, RJ, Brazil.
The amount and purity of DNA were determined using a spectrophotometer (Nanodrop 1000, Thermo Scientific, Wilmington, NC, USA). Only DNA samples with an A260 nm/A280 nm ratio of 1.8 or higher were used. All the examiners were blinded to the assignment of the sample groups. Analysis of gene polymorphisms was performed by real-time polymerase chain reaction using the TaqMan assay (Stratagene Mx3005P; Agilent Technologies, Santa Clara, CA, USA) [3,28].
Candidate genes were chosen according to the Consortium for Genetics and Quality of Life Research guidelines [29]. To find previously identified single-nucleotide polymorphisms for each candidate gene based on its potential function regulation, we used the UCSC Genome Browser website. Two missense genetic polymorphisms were selected and investigated in the TGFβ1 (rs1800469) and TGFβ3 (rs2268626) genes, because they were previously identified as affecting OHRQoL, with people with depressive disorder showing higher levels of TGFβ [30]. In addition, polymorphisms in these genes have been reported in the literature to be immunosuppressive and may be associated with depression [14]. The characteristics of the studied genetic polymorphisms are summarized in Table 1.
Genetic polymorphisms in TGFβ1 and TGFβ3 as potential biomarkers for oral health-related quality of life in children with dental caries.
Statistical Analysis
IBM Statistical Package for Social Science, version 23.0 (IBM Corp., Armonk, NY, USA) was used to analyze the data, and a significance level of p < 0.05 was used. A normal distribution test was performed on the variables. The deviation of the Hardy-Weinberg balance was examined using the conventional chi-square test. Parametric tests were used to check if the variables had a normal distribution. Using the OHRQoL scale and domain, potential genes were analyzed using the Mann-Whitney non-parametric test. The OHRQoL of the highand low-caries groups was compared. The child's genotype and OHRQoL were evaluated, and the results were categorized by caries severity (low or high)
Results
Initially, 622 children/caregivers were invited to participate in the study. One hundred and forty-one patients were lost. They did not agree to complete the OHRQoL questionnaire. One hundred and seventy-four returned the incomplete questionnaire and one hundred and seventy-seven were excluded because they were free of caries. Thus, after applying the eligibility criteria, 130 pairs of parents/caregivers and children were included for evaluation of OHRQoL. Of the 130 children included, 38 had high caries experience, while 92 had low caries experience. Of the 105 samples amplified for TGFβ1, 31 were from children with high caries experience and 73 from children with low caries experience. Of the thirty-one samples that were amplified for TGFβ3, ten belonged to children with high caries experience and forty-one to children with low experience (Figure 1).
Caries experience severity was associated with the OHRQoL (Table 2). The result of the ECOHIS scale was 3.90 (SD, 3.79) and 4.55 (SD, 3.15), while the median was (1-6) and 4.00 (2-7) (p < 0.129) in the low and high-risk groups of caries experience, respectively. Children with severe caries experience showed a negative impact on OHRQoL in the function domain (p = 0.017). However, no significant differences were observed between genetic polymorphisms and OHRQoL in any domain (p > 0.05).
Table 3 shows the association between TGFβ1 and TGFβ3 gene polymorphisms and OHRQoL in children with low and high severity of caries. For each gene, both dominant and recessive inheritance models were analyzed. In the dominant model, carriers of at least one variant allele (e.g., AA + AG for TGFβ1) are compared with homozygous carriers of the reference allele (e.g., GG). In the recessive model, only homozygous carriers of the variant allele (e.g., AA) are compared with individuals carrying at least one reference allele (e.g., AG + GG). No significant differences were observed in any OHRQoL domain for either gene or inheritance model (p > 0.05), indicating that these polymorphisms do not appear to influence oral health-related quality of life in this sample.
Association between TGFβ1 and TGFβ3 and OHRQoL in the group of children with low-severity caries and high-severity caries.
Discussion
An individual’s genetic predisposition can influence the perception of quality of life (QoL). Numerous studies have demonstrated associations between genetic variations and QoL [4,29-32]. Understanding these genetic factors may allow the identification of patients susceptible to deficits in OHRQoL and guide targeted healthcare interventions [28]. Recent research in dentistry has suggested that an individual’s genetic background can affect the perception of OHRQoL across different oral conditions [6-13].
Polymorphisms in TGFβ1 and TGFβ3 may influence OHRQoL by modulating the host immune and inflammatory response in the oral cavity. TGFβ is a pleiotropic cytokine involved in the regulation of immune cells and tissue repair [18], and variations in these genes could alter cytokine expression or function. Such alterations may affect the host’s response to cariogenic biofilms, potentially influencing the severity of dental lesions, associated pain, and functional limitations in chewing, speaking, or other oral activities. Consequently, these biological effects could translate into measurable differences in OHRQoL. Although our study did not observe a significant association between TGFβ1 and TGFβ3 polymorphisms and OHRQoL in the analyzed sample, understanding these pathways remains important for identifying children who may be genetically predisposed to more severe clinical outcomes and greater impacts on daily oral functioning.
Although many genes have been implicated in OHRQoL, most candidate genes have not yet been replicated. In this study, TGFβ1 and TGFβ3 were evaluated as potential biomarkers for OHRQoL in children with caries experience. However, no significant relationship between these genes and OHRQoL was observed in the studied sample.
Other genes, such as TNF-α [7] and IL1A [6], have also been investigated as potential biomarkers with negative effects on OHRQoL in children with caries experience. Yet, several studies have not established a clear correlation between caries-related genetic polymorphisms and OHRQoL [15-17]. Previous work has linked TGFβ genes to QoL in systemic conditions, such as major depressive disorder in individuals with childhood abuse [14], or to oral conditions like malocclusion [11], but evidence supporting these genes as biomarkers in oral health remains limited. Our findings align with this, suggesting that, at least in the studied population, TGFβ1 and TGFβ3 polymorphisms do not directly predict OHRQoL outcomes.
The impact of caries on children’s QoL is already widely studied in the literature and is considered more harmful for OHRQoL than other oral conditions, such as dental trauma or malocclusion [15,16]. Caries can influence several domains of life and may impair school performance during childhood [33]. This scenario reinforces the results of this research, as children with higher caries severity experienced greater negative impacts on OHRQoL, particularly in the functional domain, according to ECOHIS.
It is important to note that this study focused on the child impact section of the ECOHIS and excluded the family impact subscale. This choice was based on the fact that the genetic analysis was performed in the children themselves; therefore, only the child-reported domains could plausibly be influenced by their own TGFβ1 and TGFβ3 polymorphisms. While excluding the family subscale may underestimate broader social and emotional consequences for caregivers, it allows for a more direct assessment of the potential impact of the child’s genetic background on their functional and psychosocial experiences. Consequently, comparisons with previous studies using the full ECOHIS should be interpreted with caution, as total OHRQoL scores may differ when family-related impacts are included.
Finally, the low number of studies replicating the genetic relationship with OHRQoL is a limitation of this study. Our research focused on a single population - children attending municipal schools in Nova Friburgo - limiting external validity. Nevertheless, the QoL instrument used was validated and translated into multiple languages, supporting the possibility of replication in other settings. Additionally, convenience sampling without a formal sample size calculation introduces potential bias. Future research is needed to evaluate the pathways mediating immune responses in children with high caries experience and to further explore TGFβ1 and TGFβ3 as potential biomarkers across diverse populations.
Conclusion
The genetic polymorphisms in TGFβ1 and TGFβ3 cannot be considered as biomarkers for OHRQoL in children with caries experience.
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Financial Support
The authors were supported by grants by individual scholarships (FAPERJ-Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro [#E-26/202.712/2018 / # E-26/201.337/2022 (LAA);#E-26/ 204.724/2022 (JMB)] and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 (TOF and LMNN).
Acknowledgments
We are indebted to the study participants.
Data Availability
The data used to support the findings of this study can be made available upon request to the corresponding author.
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Academic Editor:
Alessandro Leite Cavalcanti
