Functional microbiome features distinguish clinical trajectories in low-grade cervical lesions

Background . 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. Results . 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 more frequently observed among regression cases. Within Lactobacillus -dominated communities, CST I-B exhibited distinct predicted functional profiles characterized by enrichment of carbohydrate metabolism and fermentation pathways and relative depletion of nucleotide biosynthesis pathways compared with CST I-A. Logistic regression models based on age, or microbiome taxa alone, showed limited discriminatory performance, whereas an integrated model incorporating age, microbiome, and predicted microbial functional pathway features significantly improved discrimination between regression and progression (AUC = 0.76, 95% CI 0.66–0.86). Conclusions . Differences in microbial community organization and inferred functional profiles were associated with LSIL clinical trajectories, whereas taxonomic composition alone showed limited discriminatory value. Integrating microbial taxonomic, ecological, and functional features modestly improved the prediction of lesion progression and supports the potential of microbiome-derived functional features for future risk stratification.