CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
Beijing Laboratory of Biomedical Materials, Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
J Dent Res. 2023 Dec;102(13):1460-1467. doi: 10.1177/00220345231196536. Epub 2023 Oct 21.
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; = 9.9 × 10). MR also indicated 4 metabolites on the causal pathway to dentures, with fructose (OR = 0.50; 95% CI, 0.36-0.70; = 5.2 × 10) and 1-palmitoleoyl-glycerophosphocholine (OR = 0.67; 95% CI, 0.56-0.81; = 4.8 × 10) as potential protective factors and glycine (OR = 1.22; 95% CI, 1.11-1.35; = 5.6×10) and 1,5-anhydroglucitol (OR = 1.32; 95% CI, 1.14-1.52; = 1.5 × 10) 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.
揭示因果生物标志物对于深入了解口腔疾病的发病机制以及确定预防和治疗这些疾病的新靶点非常重要。本研究旨在使用两样本 Mendelian 随机化 (MR) 方法系统评估数百种代谢物对 10 种牙科特征的因果影响。使用来自 309 种已知代谢物的全基因组关联研究的遗传变异作为工具变量。我们从基因-生活方式相互作用在牙科终点联盟中选择了 10 种牙科特征,包括牙科疾病的临床测量,以及来自英国生物库的自我报告的口腔健康数据。使用逆方差加权方法推断代谢物与牙科特征之间的因果关系,并使用另外 5 种 MR 方法进一步控制水平多效性。在进行多重检验校正后,鉴定出 5 种代谢物作为因果生物标志物。遗传预测的甘露糖水平升高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; = 9.9×10)。MR 还表明,在通向义齿的因果途径上有 4 种代谢物,其中果糖(OR = 0.50;95%CI,0.36-0.70; = 5.2×10)和 1-棕榈酰基甘油磷酸胆碱(OR = 0.67;95%CI,0.56-0.81; = 4.8×10)是潜在的保护因素,而甘氨酸(OR = 1.22;95%CI,1.11-1.35; = 5.6×10)和 1,5-脱水葡萄糖醇(OR = 1.32;95%CI,1.14-1.52; = 1.5×10)是风险因素。在各种敏感性分析中,因果关联都是稳健的。我们还观察到不同牙科特征之间存在一些共同的代谢物,这表明致病过程中存在相似的生物学机制。最后,途径分析揭示了几个可能参与牙齿疾病发展的重要代谢途径。本研究为代谢组学和基因组学的结合提供了新的见解,揭示了口腔疾病的发病机制和治疗策略。它突出了 5 种代谢物和几个途径作为因果候选物,值得进一步研究。