Circulating Metabolites and Dental Traits: A Mendelian Randomization Study

孟德尔随机化 优势比 置信区间 医学 多效性 混淆 内科学 生命银行 全基因组关联研究 遗传学 单核苷酸多态性 生物信息学 生物 基因 遗传变异 基因型 表型
作者
Qiwen Zheng,Wenxin Li,Ying Zhang,Xi Liu,Yi Fu,Sha Luo,Xuliang Deng,Changqing Zeng
出处
期刊:Journal of Dental Research [SAGE]
卷期号:102 (13): 1460-1467 被引量:9
标识
DOI:10.1177/00220345231196536
摘要

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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