Identifying Predictive Bacterial Markers from Cervical Swab Microbiota on Pregnancy Outcome in Woman Undergoing Assisted Reproductive Technologies

从宫颈拭子微生物群中识别可预测接受辅助生殖技术治疗的女性妊娠结局的细菌标记物

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作者:Annacandida Villani, Andrea Fontana, Stefano Barone, Silvia de Stefani, Mariangela Primiterra, Massimiliano Copetti, Concetta Panebianco, Cristiana Parri, Natale Sciannamè, Pasqua Anna Quitadamo, Alessandra Tiezzi, Liliana Santana, Annamaria Maglione, Federica D'Amato, Francesco Perri, Simone Palini

Aims

Failure of the embryo to implant causes about three-fourths of lost pregnancies. Female genital tract microbiota has been associated to Assisted Reproductive Technologies (ART) outcomes. The objective of this study was to analyze the microbiota of human cervical swab and to correlate these findings with the ART outcomes. Materials and

Background and aims

Failure of the embryo to implant causes about three-fourths of lost pregnancies. Female genital tract microbiota has been associated to Assisted Reproductive Technologies (ART) outcomes. The objective of this study was to analyze the microbiota of human cervical swab and to correlate these findings with the ART outcomes. Materials and

Discussion

Cervix is colonized by microorganisms which can play a role in ART outcomes as seen by an overall decrease in embryo attachment rates and pregnancy rates in both fertile and infertile women. If confirmed in a larger cohort, the abundance of these bacteria can be useful not only as a marker of unfavorable pregnancy outcome but also they may open the way to new interventional strategies based on genital tract microbiota manipulation in order to increase the pregnancy rates in woman undergoing assisted reproductive technologies.

Methods

In this study, 88 cervical swabs were collected from women undergoing ART cycles, with various causes of infertility, at the beginning of the ART protocols. After microbial DNA extraction, V3-V4 variable regions of the 16S rRNA gene were amplified and sequenced on the Illumina MiSeq platform. PEnalized LOgistic Regression Analysis (PELORA) was performed to identify clusters of bacterial populations with differential abundances between patients with unfavorable and favorable pregnancy outcome groups, respectively.

Results

We identified a core of microorganisms at lower taxonomic levels that were predictive of women's pregnancy outcomes. Statistically significant differences were identified at species levels with Lactobacillus salivarius, Lactobacillus rhamnosus among others. Moreover the abundance of Lactobacillus crispatus and iners, respectively increased and decreased in favorable group as compared to unfavorable group, resulted within the core of microorganisms associated to positive ART outcome. Although the predominance of lactobacilli is generally considered to be advantageous for ART outcome, we found that also the presence of Bifidobacterium (together with the other lactobacilli) was more abundant in the favorable group.

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