Inferred functional microbiome features are associated with clinical trajectories of low-grade cervical lesions

Abstract

The cervicovaginal microbiome has been associated with human papillomavirus (HPV)-related cervical disease, but its role in determining the clinical trajectory of low-grade squamous intraepithelial lesions (LSIL) remains unclear. We investigated whether microbial taxonomic, ecological, and inferred functional features could distinguish LSIL regression from progression and improve risk stratification. The cervicovaginal microbiome of 90 women with LSIL and known clinical outcomes was profiled using 16S rRNA gene sequencing. Overall microbiome diversity and composition did not differ significantly between regression and progression groups. Instead, microbial profiles clustered primarily by community state type (CST), with CST I-B nominally more frequent among regression cases. Within Lactobacillus-dominated communities, CST I-B exhibited distinct inferred functional profiles characterized by enrichment of carbohydrate metabolism and fermentation pathways and relative depletion of nucleotide biosynthesis pathways compared with CST I-A. Exploratory logistic regression models based on age, or microbiome taxa alone, showed limited discriminatory performance, whereas an integrated model incorporating age, microbiome, and inferred functional pathway features improved apparent discrimination between regression and progression in this cohort (AUC = 0.76, 95% CI 0.66–0.86). Differences in microbial community organization and inferred functional profiles were observed to be associated with LSIL clinical trajectories, whereas taxonomic composition alone showed limited discriminatory value. Integrating microbial taxonomic, ecological, and functional features modestly improved the apparent discrimination of LSIL outcomes, suggesting that inferred functional features may provide complementary information that warrants future research.