Cross-platform, multi-cohort identification of a caries microbial signature

Abstract

Abstract Objective To identify a robust salivary microbial signature associated with caries using a cross-platform, multi-cohort design. Design Full-length 16S rRNA gene sequencing (ONT) and shotgun metagenomics (MET) were performed in a derivation cohort with matched data (n = 463). Associations between the oral microbiome and caries were evaluated using confounder-adjusted linear models with nested cross-validation. Identified species were incorporated into microbial risk scores and tested in two independent ONT-based cohorts (n = 3,457 and n = 215). Results ONT and MET shared community structure despite differences in sequencing depth and detection sensitivity. Inter-individual ecological distances were moderately correlated (Spearman ρ = 0.48), with significant Procrustes alignment (r = 0.60), and mean relative abundances of shared species were strongly correlated (ρ = 0.75), but agreement at the individual species level was more variable. Ten species were consistently associated with caries across platforms and analytical approaches. Risk scores based on these species were strongly associated with caries burden in the derivation cohort (R2 = 0.46 for MET; R2 = 0.42 for ONT) and replicated in independent cohorts (mean R2 = 0.27 and 0.10). Detection- and abundance-based scores performed similarly and combining them provided minimal additional predictive value. Detection-based scores showed a slightly greater incremental contribution to model fit. Leave-one-out analyses confirmed that associations were not strongly driven by individual species. Conclusions Key ecological features of the oral microbiome are reproducible across sequencing platforms. The microbial signature of caries can be summarised using a detection-based risk score which may have potential uses in caries risk assessment.