DEMONSTRATION OF MICROBIAL SUBGROUPS AMONG NORMAL VAGINAL MICROBIOTA DATA

In this study we identified subgroups of observations relating to the healthy vaginal microbiota. This microbiota resides in a dynamic envir onment that undergoes cyclic change during the menstrual cycle. Cluste r analysis procedures were applied to divide a set of 226 normal micro biota observations into groups. Three subgroups containing 100, 65, an d 61 observations were identified. Plots of principal components deter mined by canonical analysis were obtained to demonstrate graphically t he clustering of normal vaginal microbiota observations into subgroups . Results from the cluster analyses were verified using a predictive l egit regression model. Analysis of mean legit values for the three clu sters demonstrated that they differed from each other. Further verific ation was obtained using data from women with abnormal vaginal microbi ota, either due to a yeast infection or the use of an iodine-based med icated douche product, and applying them to the clustering results dev eloped using the normal microbiota observations. Observations from bot h abnormal groups clustered outside the boundaries of the three normal microbiota subgroups. These results indicate that it may be possible to identify normal microbiota subgroups that are prone to the developm ent of an abnormal microbiota.