In this study, we evaluate the association between vaginal and cervical human papillomavirus infections high-risk types (HPV+H), negative controls (HPV−), the bacterial biota, and urinary metabolites via integration of metagenomics, metabolomics, and bioinformatics analysis. We recently proposed that testing urine as a biofluid could be a non-invasive method for the detection of cervical HPV+H infections by evaluating the association between cervical HPV types and a total of 24 urinary metabolites identified in the samples.
Department of Microbiology and Medical Zoology
School of Medicine
