It is of great importance to uncover causal biomarkers to gain insight into the pathogenesis of oral diseases and identify novel treatment targets for prevention and treatment thereof. This study aimed to systematically evaluate the causal effects of hundreds of metabolites on 10 dental traits using a 2-sample Mendelian randomization (MR) approach. Genetic variants from genome-wide association studies of 309 known metabolites were used as instrumental variables. We selected 10 dental traits, including clinical measures of dental diseases, from the Gene-Lifestyle Interactions in Dental Endpoints Consortium and self-reported oral health data from the UK Biobank. The causal relationships between metabolites and dental traits were inferred using the inverse variance-weighted approach and further controlled for horizontal pleiotropy using 5 additional MR methods. After correcting for multiple tests, 5 metabolites were identified as causal biomarkers. Genetically predicted increased levels of mannose were associated with lower risk of bleeding gums (odds ratio [OR] = 0.72; 95% confidence interval [CI], 0.61-0.85; P = 9.9 × 10-5). MR also indicated 4 metabolites on the causal pathway to dentures, with fructose (OR = 0.50; 95% CI, 0.36-0.70; P = 5.2 × 10-5) and 1-palmitoleoyl-glycerophosphocholine (OR = 0.67; 95% CI, 0.56-0.81; P = 4.8 × 10-5) as potential protective factors and glycine (OR = 1.22; 95% CI, 1.11-1.35; P = 5.6×10-5) and 1,5-anhydroglucitol (OR = 1.32; 95% CI, 1.14-1.52; P = 1.5 × 10-4) as risk factors. The causal associations were robust in various sensitivity analyses. We further observed some shared metabolites among different dental traits, implying similar biological mechanisms underlying the pathogenic processes. Finally, the pathway analysis revealed several significant metabolic pathways that may be involved in the development of dental disorders. Our study provides novel insights into the combination of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for dental disorders. It highlighted 5 metabolites and several pathways as causal candidates, warranting further investigation.

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循环代谢物和牙齿特征：孟德尔随机研究。

发现因果生物标志物对于深入了解口腔疾病的发病机制并确定预防和治疗口腔疾病的新治疗靶点具有重要意义。本研究旨在使用 2 样本孟德尔随机化 (MR) 方法系统评估数百种代谢物对 10 种牙齿特征的因果影响。来自 309 种已知代谢物的全基因组关联研究的遗传变异被用作工具变量。我们从牙科终点联盟的基因-生活方式相互作用和英国生物银行的自我报告口腔健康数据中选择了 10 个牙齿特征，包括牙科疾病的临床测量。使用逆方差加权方法推断代谢物和牙齿性状之间的因果关系，并使用另外 5 种 MR 方法进一步控制水平多效性。经过多次测试校正后，5 种代谢物被确定为因果生物标志物。基因预测甘露糖水平增加与牙龈出血风险降低相关（比值比 [OR] = 0.72；95% 置信区间 [CI]，0.61-0.85；P = 9.9 × 10-5）。MR 还表明 4 种代谢物与假牙的因果途径相关，其中包括果糖（OR = 0.50；95% CI，0.36-0.70；P = 5.2 × 10-5）和 1-棕榈油酰甘油磷酸胆碱（OR = 0.67；95% CI， 0.56-0.81；P = 4.8 × 10-5）和甘氨酸（OR = 1.22；95% CI，1.11-1.35；P = 5.6×10-5）和1,5-脱水葡萄糖醇（OR = 1.32；P = 5.6×10-5）作为潜在的保护因子。 95% CI, 1.14-1.52; P = 1.5 × 10-4) 作为危险因素。在各种敏感性分析中，因果关系是稳健的。我们进一步观察到不同牙齿特征之间存在一些共同的代谢物，这意味着致病过程背后存在相似的生物学机制。最后，通路分析揭示了可能与牙齿疾病发生有关的几个重要代谢通路。我们的研究为代谢组学和基因组学的结合提供了新的见解，以揭示牙科疾病的发病机制和治疗策略。它强调了 5 种代谢物和几种途径作为候选因果关系，值得进一步研究。