Oral microbiome signatures predict biological age and host health.

Jia-Jun Zhao, Ming Hu, Siyan Li, Qianqian Wang, Qiufen Mo, Huilin Yu

State Key Laboratory for Development and Utilization of Forest Food Resources, College of Food and Health, Zhejiang A&F University, Hangzhou, Zhejiang, China.State Key Laboratory for Development and Utilization of Forest Food Resources, College of Food and Health, Zhejiang A&F University, Hangzhou, Zhejiang, China. · pubmed

Paper

Abstract

Identifying robust, non-invasive biomarkers of biological age is key to preventive medicine. While gut aging clocks exist, the oral microbiome remains underexplored as a quantitative biomarker. Using oral microbiome data from two NHANES cohorts (N = 4,675), we identified 64 age-dependent bacterial genera and developed a machine learning model predicting chronological age, with generalizability in an independent external cohort (N = 1,293). We derived an Oral Microbiome Aging Acceleration (OMAA) Score as the residual of predicted age against chronological age. The OMAA Score independently predicted all-cause mortality (HR = 1.05, P = 0.024) and frailty (OR = 1.05, P = 0.008), correlated with impaired kidney function (lower eGFR: β = -0.066, P = 5.22×10

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Research summary

The paper claims that oral microbiome signatures can predict biological age and host health outcomes. This research is relevant as it explores the oral microbiome as a potential biomarker for biological aging, which could contribute to understanding and addressing the root causes of aging and age-related health issues.

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