Author:
Lyu Xinyi,Xu Xueyuan,Shen Sihong,Qin Feng
Abstract
IntroductionThe dysbiosis of the oral microbiome is associated with the progression of various systemic diseases, including diabetes. However, the precise causal relationships remain elusive. This study aims to investigate the potential causal associations between oral microbiome and type 2 diabetes (T2D) using Mendelian randomization (MR) analyses.MethodsWe conducted bidirectional two-sample MR analyses to investigate the impact of oral microbiome from saliva and the tongue T2D. This analysis was based on metagenome-genome-wide association studies (mgGWAS) summary statistics of the oral microbiome and a large meta-analysis of GWAS of T2D in East Asian populations. Additionally, we utilized the T2D GWAS summary statistics from the Biobank Japan (BBJ) project for replication. The MR methods employed included Wald ratio, inverse variance weighting (IVW), weighted median, MR-Egger, contamination mixture (ConMix), and robust adjusted profile score (RAPS).ResultsOur MR analyses revealed genetic associations between specific bacterial species in the oral microbiome of saliva and tongue with T2D in East Asian populations. The MR results indicated that nine genera were shared by both saliva and tongue. Among these, the genera Aggregatibacter, Pauljensenia, and Prevotella were identified as risk factors for T2D. Conversely, the genera Granulicatella and Haemophilus D were found to be protective elements against T2D. However, different species within the genera Catonella, Lachnoanaerobaculum, Streptococcus, and Saccharimonadaceae TM7x exhibited multifaceted influences; some species were positively correlated with the risk of developing T2D, while others were negatively correlated.DiscussionThis study utilized genetic variation tools to confirm the causal effect of specific oral microbiomes on T2D in East Asian populations. These findings provide valuable insights for the treatment and early screening of T2D, potentially informing more targeted and effective therapeutic strategies.
Funder
Sichuan Province Science and Technology Support Program