Dental Diseases

Primary analysis was performed using Generalized Summary Mendelian Randomisation^{40 (link)} (GSMR), implemented in GCTA (v1.92.0). Compared with other summary-statistic based estimators, GSMR is reported to have greater statistical power because GSMR uses genome-wide data to account for sampling variance in SNP-exposure and SNP-outcome estimates^{40 (link)}.
Genome-wide summary statistics for seven metabolic traits and two cardiovascular outcomes were selected as follows: BMI; meta-analysis of GIANT with UK Biobank^{65 (link)}; for waist-to-hip ratio adjusted for BMI; GIANT consortium^{66 (link)}, for coronary artery disease CARDIOGRAM plus C4D meta-analysis^{67 (link)}; for stroke the MEGASTROKE consortium^{68 (link)}; for type 2 diabetes, the DIAGRAM consortium^{69 (link)}; for fasting glucose the ENGAGE consortium^{70 (link)}; for HDL cholesterol, LDL cholesterol and triglycerides, the GLGC data sets were used^{71 (link)}.
To achieve adequate variance explained and therefore statistical power, multiple SNPs were included as instrumental variables for all traits. All variants associated with dental disease or metabolic traits (P < 5 × 10⁻⁸) after LD clumping using reference data from the cohorts arm of the UK10K project (https://www.uk10k.org/data.html) to produce index SNPs (r² threshold, 0.01) were included as potential instrumental variables. No attempt was made to manually screen variants for possible undesirable pleiotropic effects, with filtering instead performed as part of the HEIDI-outlier procedure.
HEIDI-outlier filtering, is an extension of the heterogeneity in dependent instruments method^{72 (link)}. This analysis projects a plausible distribution of causal effect (βxy) estimated from a non-outlying genetic instrumental variable, and tests whether other single nucleotide polymorphisms (SNPs) have values of βxy compatible with this estimate, on the assumption that pleiotropic variants will have outlying values^{40 (link)}. Following default criteria, potentially outlying variants with (P < 0.01 for pleiotropy) were removed and βxy was estimated from the remaining instruments.
In the primary analysis, variants in the HLA region (chr6: 25–35 Mb) were removed for estimation of casual effects of DMFS/dentures, except for a single-lead variant. For estimation of causal effects of other traits on DMFS/dentures, full genome-wide data were used.
Methods used for sensitivity analysis are described in Supplementary Note 4.

A conditional YC3.60 expression construct was generated by inserting a loxP-flanked thymidine kinase promoter and neomycin phosphotransferase gene cassette as well as the YC3.60 gene downstream of the CAG promoter of the pCXN2 vector. The resulting plasmid vector was designated as pCAG-LoxPneoLoxP/Came-2. After BamHI digestion, the linearized plasmid vector DNA was microinjected into the pronuclei of C57BL/6 fertilized mouse eggs and transferred to pseudopregnant females. The floxed YC3.60 reporter (YC3.60^flox) mouse line was crossed with a CD19-Cre mouse line, which resulted in CD19⁺ cell-specific YC3.60 expression in YC3.60^flox/CD19-Cre mice because of the loss of the loxP flanked neomycin cassette. The YC3.60^flox mouse line was crossed with CD4-Cre, Nestin-Cre, and CAG-Cre mouse lines. YC3.60^flox/CD19-Cre mice were crossed with CD22^−/− and lpr mice to obtain YC3.60^flox/CD19-Cre/CD22^−/− and YC3.60^flox/CD19-Cre/lpr/lpr mice, respectively. All mice were maintained in our animal facility under SPF conditions in accordance with guidelines of the Institutional Animal Care and Use Committee of Tokyo Medical and Dental University. All experimental procedures on animals were approved by the Institutional Animal Care and Use Committee of Tokyo Medical and Dental University, and all experiments were carried out in accordance with approved guidelines.

We considered a scoping review, articles mentioning in the title, abstract, introduction or methodology that a scoping review/search/study/exercise was conducted or studies conducting mapping reviews or literature mapping. Studies were included regardless of the year of publication and methodology or reporting quality.
We considered “Dental Public Health” as the science and art of preventing and controlling dental diseases and promoting dental health through organized community efforts [13 ]. Articles reporting narrative reviews, systematic reviews, assessing study quality, overviews, commentaries, and scoping review protocols were excluded.

All participants underwent physical examinations, oral examinations, and anthropometric measurements, together with fasting blood sample collection for biochemical tests. The anthropometric parameters included body weight, height, body mass index (BMI), waist and hip circumferences, waist-hip ratio (WHR), blood pressure, and heart rate. The blood biochemical indicators included total cholesterol (TC), total triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma glutamyl transpeptidase (GGT), fasting plasma glucose (FPG), fasting serum insulin (FSI), glycosylated hemoglobin (HbA1c) and C-reactive protein (CRP). In addition, the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) was used to ascertain IR. The formula is as follow: HOMA-IR = FPG (mmol/L) × FSI (mU/L)/22.5(Matthews et al., 1985 (link)). A thorough dental exam was conducted to assess dental caries, periodontal status, and other dental conditions listed above by the same dentist. Interdental clinical attachment loss presents at ≥ 2 non-adjacent teeth, or buccal or oral clinical attachment loss ≥ 3 mm with pocketing >3 mm presents at ≥ 2 teeth are diagnosed as periodontitis(Tonetti et al., 2018 (link)). The number of decayed, missing, and filled teeth (DMFT) for each subject were recorded. The unpaired Student’s t-test was carried out to analyze anthropometric and biochemical indicators, except for sex and periodontitis, for which the chi-square test was used.