Abstract
Nearly one third of all subfertility causes remain unexplained. In addition, assisted-reproductive technologies (ARTs) such as IVF-ICSI are invasive and only 25% to 35% of women become pregnant after the first embryo transfer (ET). Recently, research has revealed that the success of ART may be affected by the microorganisms of
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the urogenital tract. Specifically, studies have shown the presence of Lactobacillus species during ART may increase the likelihood of conception. Two prospective studies were performed to explore the predictive value of the vaginal microbiome on ART outcome. The first trial, The ReceptIVFity study, included a cohort of subfertile women between the ages 20 and 44 years from 8 IVF centers to build a prediction model for IVF and IVF-ICSI outcome of fresh ET at day 3. Participant's vaginal microbiota is analyzed using the interspace profiling technique, detecting and identifying all bacteria present. Vaginal microbiome profiles were then stratified into 1 or 5 community state types (CSTs), based on dominantmicrobial species previously described in the literature. Pregnancy outcomes based on each CSTwere used to develop a prediction model focusing on a small number of vaginal bacterial species detected by interspace profiling. The second study intended to validate this model by including samples from consenting women presenting for IVF or IVF-ICSI treatment between March 2018 and May 2018 at a center in Germany. The final study cohort included 192 participants. Commonly used predictors for pregnancy outcome including body mass index and duration of infertility were not statistically different between the pregnant women and nonpregnant women. A predictive algorithm for failure to become pregnant was defined using CST profiles to have the following parameters: Relative Lactobacillus load <20%, relative load of L. jensenii >35%, presence of Gardnerella vaginalis IST I, or Proteobacteria >28% of total bacterial load. This profile was referred to as an "unfavorable microbiome profile." A total of 34 participants were found to have an unfavorable profile, with only a 5.9% pregnancy rate, resulting in a predictive accuracy to not become pregnant of 94% (sensitivity, 26%; specificity, 97%). Relative abundance of Lactobacillus crispatus (≥60%) was associated with a 24% chance of pregnancy following ET (15/63), whereas women with <60% L. crispatus had a 53% pregnancy rate. The 82% of women with a favorable microbiome profile were stratified into high and average pregnancy chance based on the abundance of L. crispatus, and the difference in these groups was highly significant (P = 0.0003). The validation of the predictive model included a study cohort of 50 women (14 unfavorable microbiota, 13 high L. crispatus, 23 lowL. crispatus profile). None of the unfavorable profile participants became pregnant, 31%of the women with a high L. crispatus profile became pregnant, and 52% of the women with a low L. crispatus profile became pregnant. These results show that a low abundance of Lactobacillus show an increase in IVF and IVF-ICSI outcome; however, a high abundance (>60%) of L. crispatus is not advantageous.Women presentingwith an unfavorable microbiota profile had a 7-fold lower chance of becoming pregnant compared with women with favorable profiles after IVF or IVF-ICSI.
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