EBioMedicine (Jul 2022)

Parity and gestational age are associated with vaginal microbiota composition in term and late term pregnancies

  • Kaisa Kervinen,
  • Tiina Holster,
  • Schahzad Saqib,
  • Seppo Virtanen,
  • Vedran Stefanovic,
  • Leena Rahkonen,
  • Pekka Nieminen,
  • Anne Salonen,
  • Ilkka Kalliala

Journal volume & issue
Vol. 81
p. 104107

Abstract

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Summary: Background: Vaginal microbiota and its potential contribution to preterm birth is under intense research. However, only few studies have investigated the vaginal microbiota in later stages of pregnancy or at the onset of labour. Methods: We used 16S rRNA gene amplicon sequencing to analyse cross-sectional vaginal swab samples from 324 Finnish women between 37–42 weeks of gestation, sampled before elective caesarean section, at the onset of spontaneous labour, and in pregnancies lasting ≥41 weeks of gestation. Microbiota data were combined with comprehensive clinical data to identify factors associated with microbiota variation. Findings: Vaginal microbiota composition associated strongly with advancing gestational age and parity, i.e. presence of previous deliveries. Absence of previous deliveries was a strong predictor of Lactobacillus crispatus dominated vaginal microbiota, and the relative abundance of L. crispatus was higher in late term pregnancies, especially among nulliparous women. Interpretation: This study identified late term pregnancy and reproductive history as factors underlying high abundance of gynaecological health-associated L. crispatus in pregnant women. Our results suggest that the vaginal microbiota affects or reflects the regulation of the duration of gestation and labour onset, with potentially vast clinical utilities. Further studies are needed to address the causality and the mechanisms on how previous labour, but not pregnancy, affects the vaginal microbiota. Parity and gestational age should be accounted for in future studies on vaginal microbiota and reproductive outcomes. Funding: This research was supported by EU H2020 programme Sweet Crosstalk ITN (814102), Academy of Finland, State Research Funding, and University of Helsinki.

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