Oral microbiome diversity and mortality in metabolic syndrome: a cohort study

Metabolic syndrome (MetS) is associated with a higher risk of mortality. Oral microbiome diversity is related to health outcomes, but its role in forecasting MetS prognosis and the relevant pathogenic mechanisms is still largely unexplored.

Data from 1,769 MetS patients were extracted from the National Health and Nutrition Examination Survey (NHANES) 2009-2012 cycle. To evaluate alpha diversity, the Shannon index, Faith's phylogenetic diversity (PD), observed operational taxonomic units (OTUs), and the Inverse Simpson index were determined. ALDEx2 was employed for differential abundance analysis in the high-diversity subgroup. Co-occurrence network analysis was subsequently conducted, followed by partitioning around medoids (PAM) clustering for community typing. Prognostic associations were validated through Cox regression.

Both the Shannon index (hazard ratio [HR] = 0.78, 95% confidence interval [CI]: 0.63-0.96) and the Inverse Simpson index (HR = 0.84, 95% CI: 0.74-0.96) were inversely associated with mortality. In the high-diversity subgroup, differential abundance analysis did not identify any OTU whose relative abundance differed significantly by survival status. According to network analysis, the deceased group exhibited a higher density of positive co-occurrences (283 vs. 224 edges) alongside a notable expansion of negative interactions (71 vs. 15 edges), which was a hallmark of declining community stability. Two clusters were identified through community typing, yet this classification was not significantly related to survival outcomes (CType_2 vs. CType_1: HR = 1.05, 95% CI: 0.73-1.49).

Oral microbiome diversity exhibits a negative association with mortality among MetS patients. However, in the high-diversity subgroup, ecological network disruption, rather than alpha diversity or differential taxonomic richness, differentiates the deceased patients from the alive counterparts. This suggests that community structure is a promising risk marker with a higher sensitivity than diversity alone.