Loading...
Population-scale characterization of the oral microbiome and associations with metabolic health
Xue, Haochen Godneva, Anastasia Tang, Feilong Li, Huifa Li, Yulong Hu, Ming Li, Ruobing Su, Jionglong Segal, Eran Razzak, Imran
Xue, Haochen
Godneva, Anastasia
Tang, Feilong
Li, Huifa
Li, Yulong
Hu, Ming
Li, Ruobing
Su, Jionglong
Segal, Eran
Razzak, Imran
Files
Supervisor
Department
Computational Biology
Embargo End Date
Type
Journal article
Date
License
http://creativecommons.org/licenses/by/4.0/
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
The oral microbiome may capture system-specific information about host metabolic health, yet large-scale, multi-system evidence remains scarce. We analyzed 9,431 participants in the Human Phenotype Project (HPP), integrating buccal-swab oral whole metagenome profiles with 44 metabolic measures spanning liver ultrasound, continuous glucose monitoring (CGM), and dual energy X ray absorptiometry (DXA). Here we show that using a microbiome-wide association study (MWAS) framework, we constructed a multilayer map across strains, gene families and pathways, revealing widespread associations: 213 strains, 124,603 gene families and 299 pathways were significantly associated with metabolic measures. Prioritizing the strongest and cross-phenotype signals, we identified multiple oral features with most significant associations to metabolic health. For example, acyl carrier protein (ACP) was associated with lower liver inflammation and reduced adiposity, whereas polyamine biosynthesis and ceramide α oxidation tracked higher glucose variability and adverse liver and adiposity phenotypes. Leveraging these MWAS-derived signals, we trained disease classification models using phenotype-selected oral features, which outperformed full-feature oral models across six metabolic diseases. These association signals were also robust in oral-health sensitivity analyses in HPP, and key BMI and waist-circumference associations directionally replicated at the genus level in an independent cohort (n = 20, 293). Together, these findings provide a population-scale oral–metabolic association map and highlight the potential of oral microbial markers as non-invasive tools for metabolic risk stratification.
Citation
H. Xue, A. Godneva, F. Tang, H. Li, Y. Li, M. Hu , et al., "Population-scale characterization of the oral microbiome and associations with metabolic health," Nature Communications, 2026, https://doi.org/10.1038/s41467-026-72748-3.
Source
Nature Communications
Conference
Keywords
31 Biological Sciences, 32 Biomedical and Clinical Sciences, 42 Health Sciences, 4202 Epidemiology
Subjects
Source
Publisher
Springer Nature