Is catechol-O-methyltransferase gene associated with temporomandibular disorders? A systematic review and meta-analysis

Associations Between Temporomandibular Disorders and Brain Imaging-Derived Phenotypes

OBJECTIVE

Temporomandibular disorders (TMD) affect the temporomandibular joint and associated structures. Despite its prevalence and impact on quality of life, the underlying mechanisms of TMD remain unclear. Magnetic resonance imaging studies suggest brain abnormalities in patients with TMD. However, these lines of evidence are essentially observational and cannot infer a causal relationship. This study employs Mendelian randomisation (MR) to probe causal relationships between TMD and brain changes.

METHODS

Genome-wide association study (GWAS) summary statistics for TMD were collected, along with brain imaging-derived phenotypes (IDPs). Instrumental variables were selected from the GWAS summary statistics and used in bidirectional 2-sample MR analyses. The inverse-variance weighted analysis was chosen as the primary method. In addition, false discovery rate (FDR) correction of P value was used.

RESULTS

Eleven IDPs related to brain imaging alterations showed significant causal associations with TMD (P-FDR < .05), validated through sensitivity analysis. In forward MR, the mean thickness of left caudal middle frontal gyrus (OR, 0.76; 95% CI, 0.67-0.87; P-FDR = 1.15  ×  10-2) and the volume of right superior frontal gyrus (OR, 1.24; 95% CI, 1.10-1.39; P-FDR = 2.26  ×  10-2) exerted significant causal effects on TMD. In the reverse MR analysis, TMD exerted a significant causal effect on 9 IDPs, including the mean thickness of the left medial orbitofrontal cortex (β = -0.10; 95% CI, -0.13 to -0.08; P-FDR = 2.06 × 10-11), the volume of the left magnocellular nucleus (β = -0.15; 95% CI, -0.22 to -0.09; P-FDR = 3.26 × 10-4), the mean intensity of the right inferior-lateral ventricle (β = -0.09; 95% CI, -0.14 to -0.04; P-FDR = 2.23 × 10-2), the volume of grey matter in the anterior division of the left superior temporal gyrus (β = 0.09; 95% CI,  0.04-0.14; P-FDR = 1.69 × 10-2), and so forth.

CONCLUSIONS

This study provides genetic evidence supporting the bidirectional causal associations between TMD and brain IDPs, shedding light on potential neurobiological mechanisms underlying TMD development and its relationship with brain structure.

The polymorphism Val158Met in the COMT gene: disrupted dopamine system in fibromyalgia patients?

ABSTRACT

The single-nucleotide polymorphism (SNP) rs4680 in the catechol-O-methyltransferase gene ( COMT ) is a missense variant (Val158Met) associated with altered activity of the COMT enzyme and suggested as a predictive feature for developing some chronic pain conditions. However, there are controversial results on its role in fibromyalgia (FM). Here, the SNP Val158Met was analyzed in 294 FM patients (without comorbidities) and 209 healthy controls (without chronic pain). The concurrent impact of Val158Met genotypes and FM comorbid disorders (depression and sleep impairment) on FM risk were tested. In addition, the genotypic distribution of FM patients in relation to pain intensity was evaluated. The G allele (Val) resulted in being more represented in the FM group (57.8%) compared with the control group (48.8%; P = 0.037). Logistic regression highlighted that having the G/G (Val/Val) homozygous genotype was associated with 2 times higher risk of having FM compared with the A/A (Met/Met) carriers ( P = 0.038), whereas depression and sleep impairment increased FM risk by 12 and 8 times, respectively ( P < 0.001). However, considering only the FM patient group, the A/A homozygous genotype was significantly associated with severe pain intensity ( P = 0.007). This study highlighted associations between the SNP Val158Met and both FM and pain intensity, suggesting a link between dopaminergic dysfunction and vulnerability to chronic pain. Further studies should explore this SNP in FM patients in conjunction with COMT enzymatic activity and other symptoms connected with the dopaminergic system such as depression or sleep impairment.

Artificial Intelligence in Orthodontics: Critical Review

With increasing digitalization in orthodontics, certain orthodontic manufacturing processes such as the fabrication of indirect bonding trays, aligner production, or wire bending can be automated. However, orthodontic treatment planning and evaluation remains a specialist's task and responsibility. As the prediction of growth in orthodontic patients and response to orthodontic treatment is inherently complex and individual, orthodontists make use of features gathered from longitudinal, multimodal, and standardized orthodontic data sets. Currently, these data sets are used by the orthodontist to make informed, rule-based treatment decisions. In research, artificial intelligence (AI) has been successfully applied to assist orthodontists with the extraction of relevant data from such data sets. Here, AI has been applied for the analysis of clinical imagery, such as automated landmark detection in lateral cephalograms but also for evaluation of intraoral scans or photographic data. Furthermore, AI is applied to help orthodontists with decision support for treatment decisions such as the need for orthognathic surgery or for orthodontic tooth extractions. One major challenge in current AI research in orthodontics is the limited generalizability, as most studies use unicentric data with high risks of bias. Moreover, comparing AI across different studies and tasks is virtually impossible as both outcomes and outcome metrics vary widely, and underlying data sets are not standardized. Notably, only few AI applications in orthodontics have reached full clinical maturity and regulatory approval, and researchers in the field are tasked with tackling real-world evaluation and implementation of AI into the orthodontic workflow.

COMT and SCN9A gene variants do not contribute to chronic low back pain in Mexican-Mestizo patients

BACKGROUND

Chronic low back pain (CLBP) is a complex condition in which genetic factors play a role in its susceptibility. Catechol-O-methyltransferase (COMT) and sodium channel NaV1.7 (SCN9A) genes are implicated in pain perception. The aim is to analyze the association of COMT and SCN9A with CLBP and their interaction, in a Mexican-Mestizo population.

METHODS

A case-control study was conducted. Cases corresponded to adults of both sexes with CLBP. Controls were adults with no CLBP. Variants of SCN9A and COMT were genotyped. Allelic and genotypic frequencies and Hardy-Weinberg equilibrium (HWE) were calculated. Association was tested under codominant, dominant, and recessive models. Multifactor dimensionality reduction was developed to detect epistasis.

RESULTS

Gene variants were in HWE, and there was no association under different inheritance models in the whole sample. In women, in codominant and dominant models, a trend to a high risk was observed for AA of rs4680 of COMT (OR = 1.7 [0.5-5.3] and 1.6 [0.7-3.4]) and for TT of rs4633 (OR = 1.6 [0.7-3.7] and 1.6 [0.7-3.4]). In men, a trend to low risk was observed for AG genotype of rs4680 in the same models (OR = 0.6 [0.2-1.7] and 0.7 [0.3-1.7]), and for TC genotype of rs4633 in the codominant model (OR = 0.6 [0.2-1.7]). In the interaction analysis, a model of the SCN9A and COMT variants showed a CVC of 10/10; however, the TA was 0.4141.

CONCLUSION

COMT and SCN9A variants are not associated with CLBP in the analyzed Mexican-Mestizo population.

The association of gene polymorphisms in catechol-O'methyltransferase (COMT) and β2-adrenergic receptor (ADRB2) with temporomandibular joint disorders

OBJECTIVE

Temporomandibular disorder (TMD) has a multifactorial etiology that includes environmental, psychological, and genetic factors. This study aimed to evaluate the possible relationship between polymorphisms in Catechol-O-methyltransferase (COMT) and β2-adrenergic receptor (ADRB2) genes with TMD.

DESIGN

This observational case-control study included 80 patients and 70 healthy controls. The diagnosis of TMD was made using the diagnostic criteria for TMD and the following TMD categories were used for the case group: muscular TMD and articular TMD (disc displacement and arthralgia). A genotyping study of gene polymorphisms in COMT (rs 9332377) and ADRB2 (rs20530449) was performed from genomic DNA isolated from blood. The chi-square test was used to analyze the relationships. P < 0.05 was accepted as a significant difference.

RESULTS

The polymorphic TT and CT genotype for COMT (rs rs9332377) was significantly higher in the articular TMD group while the non-polymorphic CC genotype was significantly lower in the articular TMD group (P < 0.05). Regarding ADRB2 (rs20530449), the polymorphic GG genotype was similarly considerably more common in the articular TMD group (p < 0.05). In addition, the T allele in the COMT (rs rs9332377) gene was found to be significantly higher in the articular TMD group (p < 0.05).

CONCLUSIONS

In the Turkish population, gene polymorphisms in COMT (rs9332377) and ADRB2 (rs2053044) were associated with articular TMD. This study supports the hypothesis that changes in COMT and ADRB2 genes may play a role in temporomandibular joint pain and predisposition to TMD.

Associations between Anxiety, Depression, Chronic Pain and Oral Health-Related Quality of Life, Happiness, and Polymorphisms in Adolescents' Genes

Adolescence is marked by changes and vulnerability to the emergence of psychological problems. This study aimed to investigate associations between anxiety/depression/chronic pain and oral health-related quality of life (OHRQoL)/happiness/polymorphisms in the COMT, HTR2A and FKBP5 genes in Brazilian adolescents. A cross-sectional study was conducted with ninety adolescents 13 to 18 years. Anxiety, depression and chronic pain were evaluated using the RDC/TMD. The Oral Health Impact Profile was used to assess oral OHRQoL. The Subjective Happiness Scale was used to assess happiness. Single-nucleotide polymorphisms in COMT (rs165656, rs174675), HTR2A (rs6313, rs4941573) and FKBP5 (rs1360780, rs3800373) were genotyped using the Taqman® method. Bivariate and multivariate logistic regression analyses were performed (p < 0.05). Chronic pain and depression were associated with feelings of happiness (p < 0.05). A significant inverse association was found between anxiety and OHRQoL (p = 0.004). The presence of minor allele C of COMT rs174675 was significantly associated with depression (p = 0.040). Brazilian adolescents with depression and chronic pain considers themselves to be less happy than others and those with anxiety are more likely to have a negative impact on OHRQoL. Moreover, the rs174675 variant allele in the COMT gene was associated with depressive symptoms in Brazilian adolescents.

Temporomandibular disorder in construction workers associated with ANKK1 and DRD2 genes

The study aimed to explore the influence of genetic polymorphisms in ANKK1 and DRD2 on the signs and symptoms of temporomandibular disorder (TMD) in construction workers. This cross-sectional study included only male subjects. All construction workers were healthy and over 18 years age. Illiterate workers and functionally illiterate workers were excluded. The diagnosis of TMD was established according to the Research Diagnostic Criteria for TMD (RDC/TMD). Genomic DNA was used to evaluate the genetic polymorphisms ANKK1 (rs1800497) and DRD2 (rs6275; rs6276) using Real-Time PCR. Chi-square or Fisher exact tests were used to evaluate genotypes and allele distribution among the studied phenotypes. The established alpha of this study was 5%. The sample included a total of 115 patients. The age of the patients ranged from 19 to 70 years (mean age 38.2; standard deviation 11.7). Chronic pain (87.7%), disc displacement (38.2%), and joint inflammation (26.9%) were the most frequently observed signs and symptoms. The genetic polymorphism rs6276 in DRD2 was associated with chronic pain (p=0.033). In conclusion, our study suggests that genetic polymorphisms in DRD2 and ANKK1 may influence TMD signs and symptoms in a group of male construction workers.

A Computational Data Mining Strategy to Identify the Common Genetic Markers of Temporomandibular Joint Disorders and Osteoarthritis

Statement of Problem  Prosthodontic planning in patients with temporomandibular joint disorders (TMDs) is a challenge for the clinicians.

Purpose  A differential biomarker identification could aid in developing methods for early detection and confirmation of TMD from other related conditions.

Materials and Methods  The present study identified candidate genes with possible association with TMDs. The observational study delineates genes from three datasets retrieved from DisGeNET database. The convergence of datasets identifies potential genes related to TMDs with associated complication such as osteoarthritis. Gene ontology analysis was also performed to identify the potential pathways associated with the genes belonging to each of the datasets.

Results  The preliminary analysis revealed vascular endothelial growth factor A ( VEGFA ), interleukin 1 β ( IL1B , and estrogen receptor 1 ( ESR1 ) as the common genes associated with all three phenotypes assessed. The gene ontology analysis revealed functional pathways in which the genes of each dataset were clustered. The chemokine and cytokine signaling pathway, gonadotropin-releasing hormone receptor pathway, cholecystokinin receptors (CCKR) signaling, and tumor growth factor (TGF)-β signaling pathway were the pathways most commonly associated with the phenotypes. The genes CCL2, IL6 , and IL1B were found to be the common genes across temporomandibular joint (TMJ) and TMJ + osteoarthritis (TMJ-OA) datasets.

Conclusion  Analysis through computational approach has revealed IL1B as the crucial candidate gene which could have a strong association with bone disorders. Nevertheless, several immunological pathways have also identified numerous genes showing putative association with TMJ and other related diseases. These genes have to be further validated using experimental approaches to acquire clarity on the mechanisms related to the pathogenesis.

Polymorphisms in the HTR2A and HTR3A Genes Contribute to Pain in TMD Myalgia

Background: The aim of this study was to investigate if single nucleotide polymorphisms (SNPs) related to monoaminergic neurotransmission, in particular the serotonergic pathway, contribute to pain perception in patients with temporomandibular disorder (TMD) myalgia and if there is a correlation to jaw function as well as psychosocial factors such as stress, anxiety and depression.

Materials and Methods: One hundred and seventeen individuals with TMD myalgia were included. A venous blood or saliva sample was taken for genetic analyses and genotyped regarding HTR2A (rs9316233) HTR3A (rs1062613), HTR3B (rs1176744), SERT (5-HTTLPR) and COMT (rs4680). A clinical examination according to Diagnostic Criteria for TMD (DC/TMD) was performed and axis II data (psychosocial factors) were compared between participants with different genotypes for each gene using Kruskall–Wallis test. The characteristic pain intensity (CPI) was tested for correlations to scores for the Perceived Stress Scale, Generalized Anxiety Disorder, and Patient Health Questionnaires using Spearman's rank correlation test with Bonferroni correction for multiple testing. To further explore data factor analysis was performed to identify latent factors associated to the outcome variables.

Results: Participants carrying at least one copy of the rare allele of the HTR2A (rs9316233) and HTR3A (rs1062613) had higher CPI compared with the participants with the homozygous common genotype (P = 0.042 and P = 0.024, respectively). Correlation analyses showed several significant positive correlations between CPI on one hand, and self-reported psychosocial distress and jaw function on the other hand for several genotypes that mostly were weak to moderate. The factor analysis identified two latent variables. One was positively correlated to the HTR3B gene, jaw function and self-reported parafunctions, and the other was positively correlated to psychological distress and negatively correlated to SERT.

Conclusion: Taken together, the polymorphism rs1062613 in the HTR3A gene contributes to pain intensity in TMD myalgia. This together with positive interactions between pain variables and psychological factors in genotypes strengthens that pain and psychological distress are related. Further research is needed to explore this as well as the influence of gene-to-gene interactions on pain and psychological distress.

Is there an association of genetic polymorphisms of the catechol-O-methyltransferase gene (rs165656 and rs174675) and the 5-hydroxytryptamine receptor 2A gene (rs4941573 and rs6313) with sleep bruxism in individuals with obstructive sleep apnea?

OBJECTIVE

To evaluate the association of single-nucleotide polymorphisms within the catechol-O-methyltransferase and 5-hydroxytryptamine receptor 2A genes with sleep bruxism in individuals diagnosed with obstructive sleep apnea.

DESIGN

Sixty-nine individuals with suspected sleep-related problems were evaluated by polysomnography, following the recommendations of the American Academy of Sleep Medicine. Deoxyribonucleic acid (DNA) samples were collected only from 48 of the study participants because of missing polysomnographic data. DNA samples were collected and two single-nucleotide polymorphisms in the 5-hydroxytryptamine receptor 2A encoding HTR2A gene (rs4941573 and rs6313) and two in the catechol-O-methyltransferase gene (rs165656 and rs174675) were selected to be genotyped using real-time polymerase chain reaction. The association between sleep bruxism and genetic polymorphisms was investigated by recessive and dominant models. Association analyses were performed using a 95% confidence interval and the level of statistical significance was p < 0.05.

RESULTS

From the 69 study participants, 48 were included in the polymorphism analysis and sleep bruxism was present in 35.4%. No significant differences were observed in the dominant and recessive models (p > 0.05). Haplotype and diplotype analyses revealed the predicted four haplotypes and two diplotypes were not associated with sleep bruxism.

CONCLUSION

Polymorphisms rs174675 and rs165656 in the catechol-O-methyltransferase gene and rs4941573 and rs6313 in the 5-hydroxytryptamine receptor 2A gene were not significantly associated with sleep bruxism in individuals with obstructive sleep apnea.

Genetic variation in catechol-O-methyltransferase is associated with individual differences in conditioned pain modulation in healthy subjects

BACKGROUND

Genetic variation in the catechol-O-methyltransferase (COMT) gene is associated with sensitivity to both acute experimental pain and chronic pain conditions. Four single nucleotide polymorphisms (SNPs) have traditionally been used to infer three common haplotypes designated as low, average and high pain sensitivity and are reported to affect both COMT enzymatic activity and pain sensitivity. One mechanism that may partly explain individual differences in sensitivity to pain is conditioned pain modulation (CPM). We hypothesized that variation in CPM may have a genetic basis.

METHODS

We evaluated CPM in 77 healthy pain-free Caucasian subjects by applying repeated mechanical stimuli to the dominant forearm using 26-g von Frey filament as the test stimulus with immersion of the non-dominant hand in hot water as the conditioning stimulus. We assayed COMT SNP genotypes by the TaqMan method using DNA extracted from saliva.

RESULTS

SNP rs4680 (val¹⁵⁸ met) was not associated with individual differences in CPM. However, CPM was associated with COMT low pain sensitivity haplotypes under an additive model (p = 0.004) and the effect was independent of gender.

CONCLUSIONS

We show that, although four SNPs are used to infer COMT haplotypes, the low pain sensitivity haplotype is determined by SNP rs6269 (located in the 5' regulatory region of COMT), suggesting that inherited variation in gene expression may underlie individual differences in pain modulation. Analysis of 13 global populations revealed that the COMT low pain sensitivity haplotype varies in frequency from 13% to 44% and showed that two SNPs are sufficient to distinguish all COMT haplotypes in most populations.