Back

Assessing causal relationships between oral microbiota and Periodontitis: evidence from Mendelian randomization analysis

Wei, Z.-f.; Wuzhang, J.-p.; Huang, Y.-t.

2026-02-03 dentistry and oral medicine
10.64898/2026.02.01.26345317 medRxiv
Show abstract

ObjectiveThis study utilizes small-sample periodontitis data to exploratively investigate causal relationships between the oral microbiome and periodontitis in East Asian populations. We aimed to identify specific oral microbial taxa that may drive disease pathogenesis. Given the exploratory nature of the dataset, findings should be interpreted as hypothesis-generating. MethodsWe performed a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary statistics for tongue dorsum and salivary microbiomes alongside periodontitis data in East Asian populations. Primary causal estimates were derived using the inverse-variance weighted (IVW) method, supplemented by MR-Egger, weighted median, weighted mode, and simple mode methods. To ensure robustness, we assessed heterogeneity using Cochrans Q test, evaluated horizontal pleiotropy via the MR-Egger intercept and MR-PRESSO tests, and applied Steiger filtering to rule out reverse causality. ResultsWe identified 60 species-level microbial taxa causally associated with periodontitis, comprising 29 negative and 31 positive associations. These taxa were predominantly enriched within the genera Campylobacter, Pauljensenia, Solobacterium, and Streptococcus. ConclusionThis study provides tentative evidence for causal links between specific species-level oral microbial taxa and periodontitis, highlighting potential targets for prevention and therapeutic intervention.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.