Oral microbiome signatures predict biological age and host health

), and enhanced risk prediction for cancer (AUC 0.70 vs. 0.67, P = 0.009) and heart attack (AUC 0.79 vs. 0.76, P = 0.016) beyond conventional risk factors. Diet and medication had minimal association. The OMAA Score offers a scalable, non-invasive tool to identify high-risk individuals for age-related morbidity and mortality.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-04-17
DOI
https://doi.org/10.1038/s41467-026-72096-2
Primary Topic
Oral microbiology and periodontitis research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Oral microbiome signatures predict biological age and host health

Qianqian Wang, Ming Hu, Qiufen Mo, Siyan Li et al.
Nature Communications
Oral microbiology and periodontitis research
article

Oral microbiome signatures predict biological age and host health

Qianqian Wang, Ming Hu, Qiufen Mo, Siyan Li, Jia-Jun Zhao
article en

Abstract

), and enhanced risk prediction for cancer (AUC 0.70 vs. 0.67, P = 0.009) and heart attack (AUC 0.79 vs. 0.76, P = 0.016) beyond conventional risk factors. Diet and medication had minimal association. The OMAA Score offers a scalable, non-invasive tool to identify high-risk individuals for age-related morbidity and mortality.

Nature Communications
Zhejiang A & F University (CN), Donghua University (CN), Fudan University (CN), Huadong Hospital (CN)
Good health and well-being
Openalex Percentile: Top 13%
Oral microbiology and periodontitis research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.