Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.
Journal:
Journal of the European Academy of Dermatology and Venereology : JEADV
PMID:
38284174
Abstract
BACKGROUND: Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or require skilled expertise, warranting alternate tests. Application of machine-learning tools to heterogeneous and high-dimensional multi-omics datasets finds promising potential in data integration and may aid biomarker discovery.