Oral diseases · 2026
The Role of the Oral Microbiome in Circulating Metabolic Biomarkers and the Influence of Air Pollution.
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Luo Jiajun, Wu Yuqing, Ahsan Habibul, Olopade Christopher O, Pinto Jayant M, Aschebrook-Kilfoy Briseis
Аннотация
AIMS: The oral microbiome is at the frontline for environmental exposure and plays an important role in human metabolism. This study explores the relationship between PM2.5 exposure, the oral microbiome, and metabolic biomarkers including ghrelin, resistin, and insulin.
METHODS: Data from 473 adult participants (97.7% Black; median age: 53.6) were analyzed. PM2.5 exposure was retrospectively assigned based on residential addresses, metabolic biomarkers were measured from blood samples, and oral microbiome profiles were obtained from saliva samples. Multivariate linear regression, weighted quantile sum regression, and high-dimensional mediation analysis were employed to estimate microbiome-biomarker associations, the association of the oral microbiome mixture, and mediation effects for PM2.5 exposure.
RESULTS: A total of 20 oral microbiome taxa were significantly associated with at least one biomarker, with genus Atopobium linked to all three. Insulin demonstrated the strongest sensitivity to the oral microbiome influence. Genera in phyla Actinomycetota and Bacillota played key roles in the relationship between the oral microbiome and metabolic biomarkers. Mediation analysis revealed that the oral microbiome mediated 16.5% and 11.1% of PM2.5's associations with resistin and insulin, respectively.
CONCLUSION: This study suggests potential mechanisms regarding how the oral microbiome influences metabolic biomarkers and mediates the metabolic effects of PM2.5 exposure.
METHODS: Data from 473 adult participants (97.7% Black; median age: 53.6) were analyzed. PM2.5 exposure was retrospectively assigned based on residential addresses, metabolic biomarkers were measured from blood samples, and oral microbiome profiles were obtained from saliva samples. Multivariate linear regression, weighted quantile sum regression, and high-dimensional mediation analysis were employed to estimate microbiome-biomarker associations, the association of the oral microbiome mixture, and mediation effects for PM2.5 exposure.
RESULTS: A total of 20 oral microbiome taxa were significantly associated with at least one biomarker, with genus Atopobium linked to all three. Insulin demonstrated the strongest sensitivity to the oral microbiome influence. Genera in phyla Actinomycetota and Bacillota played key roles in the relationship between the oral microbiome and metabolic biomarkers. Mediation analysis revealed that the oral microbiome mediated 16.5% and 11.1% of PM2.5's associations with resistin and insulin, respectively.
CONCLUSION: This study suggests potential mechanisms regarding how the oral microbiome influences metabolic biomarkers and mediates the metabolic effects of PM2.5 exposure.