Causal effects of educational attainment on temporomandibular disorders and the mediating pathways: A Mendelian randomization study.

BACKGROUND: As one of the most important indicators of socioeconomic status, educational attainment (EA) exhibits a strong association with temporomandibular disorders (TMDs). Despite this link, there is a lack of evidence regarding the causal role of EA in either facilitating or preventing TMDs. OBJECTIVE: This study aimed to investigate the causal effect of education on TMDs and explore potential mediating pathways. METHODS: Utilizing summary statistics from genome-wide association studies on years of schooling (N = 766 345) and TMDs (N = 211 023), we conducted Mendelian randomization (MR) to assess the overall effect of education. Additionally, a two-step MR approach was employed to evaluate 30 potential mediators and calculate the mediation proportions in the association. Comprehensive sensitivity analyses were used to verify the robustness, heterogeneity, and pleiotropy. RESULTS: Univariable MR analyses revealed a causal effect of lower EA on an increased risk of TMDs (OR: 0.53, 95% CI: 0.43-0.66, p < .001). Five out of 30 modifiable factors were identified as causal mediators in the associations of EA with TMDs, including feeling nervous (mediation proportion: 11.6%), feeling tense (10.2%), depression (9.6%), feeling worry (7.6%) and daily smoking (8.9%). Meanwhile, no pleiotropy was detected in the analyses (p > .05). CONCLUSION: Our findings supported that higher EA has a protective effect on the onset of TMDs, with partial mediation by psychological disorders and daily smoking. Interventions on these factors thus have the potential of substantially reducing the burden of TMDs attributed to low education.

Analysis of the potential relationship between COVID-19 and Behcet's disease using transcriptome data.

To investigate the potential role of COVID-19 in relation to Behcet's disease (BD) and to search for relevant biomarkers. We used a bioinformatics approach to download transcriptomic data from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients and PBMCs of BD patients, screened the common differential genes between COVID-19 and BD, performed gene ontology (GO) and pathway analysis, and constructed the protein-protein interaction (PPI) network, screened the hub genes and performed co-expression analysis. In addition, we constructed the genes-transcription factors (TFs)-miRNAs network, the genes-diseases network and the genes-drugs network to gain insight into the interactions between the 2 diseases. We used the RNA-seq dataset from the GEO database (GSE152418, GSE198533). We used cross-analysis to obtain 461 up-regulated common differential genes and 509 down-regulated common differential genes, mapped the PPI network, and used Cytohubba to identify the 15 most strongly associated genes as hub genes (ACTB, BRCA1, RHOA, CCNB1, ASPM, CCNA2, TOP2A, PCNA, AURKA, KIF20A, MAD2L1, MCM4, BUB1, RFC4, and CENPE). We screened for statistically significant hub genes and found that ACTB was in low expression of both BD and COVID-19, and ASPM, CCNA2, CCNB1, and CENPE were in low expression of BD and high expression of COVID-19. GO analysis and pathway analysis was then performed to obtain common pathways and biological response processes, which suggested a common association between BD and COVID-19. The genes-TFs-miRNAs network, genes-diseases network and genes-drugs network also play important roles in the interaction between the 2 diseases. Interaction between COVID-19 and BD exists. ACTB, ASPM, CCNA2, CCNB1, and CENPE as potential biomarkers for 2 diseases.

Systematic Review and Meta-Analysis of Oxidative Stress and Antioxidant Markers in Oral Lichen Planus.

BACKGROUND: Oral lichen planus (OLP) is a relatively common chronic inflammatory disease of unknown etiology, which might be caused by oxidative stress and impaired antioxidant defense. OBJECTIVE: To systematically investigate the markers of oxidative stress and antioxidant systems in the saliva and blood from OLP patients and healthy controls. METHODS: The PubMed, Cochrane Library, and Embase were systematically queried to collect data from studies in which oxidative stress/antioxidant markers from OLP and healthy subjects had been evaluated until March 10, 2021. RESULTS: A total of 28 studies fulfilled inclusion criteria, and 25 of them, having 849 OLP patients and 1,052 control subjects and analyzing 12 oxidative stress and antioxidant state marker levels, were subjected to meta-analysis. We found a significant decrease in total antioxidant capacity (TAC) and uric acid (UA) and a significant increase in malondialdehyde (MDA) and nitric oxide (NO) levels in the saliva and serum/plasma of OLP patients. Moreover, a significant elevation of 8-hydroxy-deoxyguanosine (8-OHdG) and advanced oxidation protein product (AOOP) level and a decrease in vitamin C were also observed in the saliva of the OLP group. In contrast, salivary vitamin A, zinc, glutathione peroxidase (GPx), vitamin E, and nitrite were not significantly different between the two groups. In single studies, markers of oxidative stresses such as superoxide dismutase (SOD) and 8-isoprostanelevels were elevated in OLP, and antioxidant parameters such as glutathione (GSH) and total protein (TP) levels were dysregulated. CONCLUSION: This meta-analysis helps to clarify the profile of oxidative stress and antioxidant state markers in OLP patients although existing evidence is rather heterogeneous and many studies are affected by several limitations. Larger and more standardized studies are warranted to ascertain whether these markers are potential causes or effects of OLP and whether antioxidant therapy improving oxidative stress will be useful.

Assessment of the cancerization risk for oral potentially malignant disorders by clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry.

PURPOSE: To explore the feasibility of assessing the cancerization risk of oral potentially malignant disorders (OPMD) through a clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry. METHODS: We collected the baseline clinical data of 269 patients; then, performed autofluorescence, brush biopsy with DNA-image cytometry and histopathological examination. Then, we obtained the significant factors by univariate logistic analysis, constructed the clinical risk model by multiple logistic regression and selected the optimal cutoff value according to the maximum Youden index. Finally, we calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the clinical risk score ≥ cutoff value, autofluorescence and brush biopsy with DNA-image cytometry, and plotted the receiver-operating characteristic (ROC) curves and decision curve analysis (DCA). RESULTS: The clinical risk model is represented by the formula: 1 × gender + 1.6 × age group + 1 × lesion site + 1.4 × local stimulus + 1.5 × drink. The area under the curve (AUC) was 0.83, and the optimal cutoff score was 3. The AUC indicated that the clinical risk score ≥ 3 (0.74) and autofluorescence (0.77) had a certain diagnostic values, while brush biopsy with DNA-image cytometry (0.92) displayed a good value. Besides, the DCA showed that all three tests had clinical significance. CONCLUSIONS: The cancerization risk of patients can be assessed by the clinical risk model combined with sequence application of autofluorescence and brush biopsy with DNA-image cytometry, to decide whether histopathological examination or other intervention measures should be selected.