Vaginal Microbiome and Pregnancy Complications: A Review.
Angeliki GeredeKonstantinos NikolettosEleftherios VavoulidisChrysoula Margioula-SiarkouStamatios PetousisMaria GiourgaPanagiotis FotinopoulosMaria SalagianniSofoklis StavrosKonstantinos DinasNikolaos NikolettosAikaterini DomaliPublished in: Journal of clinical medicine (2024)
Background/Objectives: There are indications that the microbial composition of the maternal mucosal surfaces is associated with adverse events during pregnancy. The aim of this review is to investigate the link between vaginal microbiome alterations and gestational complication risk. Methods: This comprehensive literature review was performed using Medline and Scopus databases. The following search algorithm was used, "Pregnancy Complications" [Mesh] AND (Vagin*), and after the literature screening, 44 studies were included in the final review. Results: The studies that were included investigated the association between vaginal microbial composition and preterm birth, miscarriage, preeclampsia, ectopic pregnancy, gestational diabetes mellitus, chorioamnionitis, and preterm premature rupture of membranes. In most of the studies, it was well established that increased microbial diversity is associated with these conditions. Also, the depletion of Lactobacillus species is linked to most of the gestational complications, while the increased relative abundance and especially Lactobacillus crispatus may exert a protective effect in favor of the pregnant woman. Several pathogenic taxa including Gardnerella , Prevotella , Sneathia , Bacterial Vaginosis-Associated Bacteria-2 , Atopobium , and Megasphera seem to be correlated to higher maternal morbidity. Conclusions: Vaginal microbiome aberrations seem to have an association with pregnancy-related adverse events, but more high-quality homogenous studies are necessary to reliably verify this link.
Keyphrases
- preterm birth
- pregnancy outcomes
- pregnant women
- gestational age
- birth weight
- low birth weight
- case control
- microbial community
- weight gain
- risk factors
- case report
- deep learning
- machine learning
- early onset
- staphylococcus aureus
- physical activity
- wastewater treatment
- preterm infants
- pseudomonas aeruginosa
- neural network
- single molecule