Vaginal microbiome diversity and preterm birth: results of a nested case-control study in Peru

Premature rupture of membranes and changes in the vaginal microbiome - Probiotics

Preterm birth affects approximately 15 million women worldwide, of which 30 % is due to preterm premature rupture of membranes (PPROM). The reasons for shortening the duration of pregnancy are seen in genetic, hormonal, immunological and socio-economic conditions. Recent years have provided a lot of evidence on the impact of the microbiota and whole microbiome on pregnant women, suggesting that the microorganisms inhabiting the vagina significantly affect the risk of preterm delivery. The aim of the study was to review studies evaluating the composition of the vaginal microflora and its role in the occurrence of preterm labor caused by PPROM, and to evaluate the potential beneficial effect of probiotics on preventing the development of preterm labor. Vaginal microbial dysbiosis is observed in PPROM, which, due to its association with a high risk of prematurity and infection, increases neonatal morbidity and mortality. Further research on biomarkers for screening, early prognosis and diagnosis of PPROM seems advisable. Probiotics as a potential intervention can prevent the development of pathological vaginal flora, reducing the risk of infection in women planning pregnancy and pregnant women.

Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process

The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

Analysis of Vaginal Microbiota Variations in the Third Trimester of Pregnancy and Their Correlation with Preterm Birth: A Case-Control Study

This study conducted a detailed analysis of the vaginal microbiota in pregnant women to explore its correlation with preterm birth (PTB) outcomes. The primary objective was to identify microbial variations associated with increased PTB risk. Secondary objectives included investigating how changes in microbial composition relate to the local immune environment and PTB. Utilizing a retrospective case-control design, the study involved pregnant women with liveborn infants between 2019 and 2023. In total, 89 women who delivered preterm and 106 term deliveries were included. Data collection focused on third-trimester vaginal cultures. Statistically significant differences were observed between the preterm and full-term groups in several areas. The median white blood cell count (10.2 × 103/mm3 vs. 7.6 × 103/mm3, p = 0.009) and neutrophil count (7.2 × 103/mm3 vs. 5.1 × 103/mm3, p < 0.001) were higher in the preterm group. Vaginal pH was also elevated in preterm births (5.6 vs. 4.4, p < 0.001), with a higher prevalence of bacterial vaginosis (29.2% vs. 12.3%, p = 0.001) as indicated by the Nugent Score. The study noted a significant association of PTB with the presence of Candida spp. (OR = 1.84, p = 0.018), Gardnerella vaginalis (OR = 2.29, p = 0.003), Mycoplasma hominis (OR = 1.97, p = 0.007), and Ureaplasma urealyticum (OR = 2.43, p = 0.001). Conversely, a reduction in Lactobacillus spp. correlated with a decreased PTB risk (OR = 0.46, p = 0.001). The study provides compelling evidence that specific vaginal microbiota components, particularly certain pathogenic bacteria and an altered Lactobacillus profile, are significantly associated with PTB risk. These findings highlight the potential of targeting microbial factors in strategies aimed at reducing PTB rates. Further research is necessary to fully understand the complex interplay between microbial dynamics, host immunity, and PTB outcomes.

Relationship of Lactobacillus Vaginal Microbiota Changes and the Risk of Preterm Birth: A Systematic Review and Meta-Analysis

Objective: With a global incidence of more than 10%, preterm birth (PTB) remains a significant concern. The vaginal microbiome strongly influences the well-being of the female reproductive tract. This study examines the correlation between changes in Lactobacillus vaginal microbiota and the PTB risk. Materials and Methods: A thorough search of PubMed, Web of Science, Cochrane Library, and EMBASE was conducted to locate studies that examined the association between changes in Lactobacillus vaginal microbiota and the risk of PTB from January 1, 2010, to January 30, 2023. The risk of PTB was determined by calculating odds ratios (ORs) with 95% confidence intervals (CIs). Results: In our analysis, there were 11 studies with 1577 pregnant women. The findings revealed a significant negative correlation between higher Lactobacillus abundance and the PTB risk (OR = 0.49, 95% CI: 0.29-0.84, p = 0.009 < 0.05). Similarly, the four individual dominant species, Lactobacillus crispatus (OR = 0.3, 95% CI: 0.14-0.67, p = 0.003 < 0.05), Lactobacillus gasseri (OR = 0.34, 95% CI: 0.17-0.69, p = 0.003 < 0.05), Lactobacillus iners (OR = 0.68, 95% CI: 0.49-0.93, p = 0.016 < 0.05), and Lactobacillus jensenii (OR = 0.43, 95% CI: 0.21-0.89, p = 0.024 < 0.05), were also negatively associated with the PTB risk. The risk of Lactobacillus for PTB was significant in both America (OR = 0.67; 95% CI: 0.50-0.92) and Asia (OR = 0.20; 95% CI: 0.09-0.47), whereas no significant risk was found in Europe (OR = 0.49; 95% CI: 0.11-2.15). Conclusions: Our study demonstrated that the abundance of Lactobacillus and the four dominant individual species (L. crispatus, L. jensenii, L. iners, and L. gasseri) were significantly and negatively associated with the PTB risk.

Comparison of databases useful for the analysis of vaginal microbiota in Japanese women using next-generation sequencing data (QIIME 2 software)

AIMS

Approximately 10% of children are born prematurely, and bacterial vaginosis during pregnancy is associated with preterm delivery. Highly accurate species-level vaginal microflora analysis helps control bacteria-induced preterm birth. Therefore, we aimed to conduct a bioinformatic analysis of gene sequences using 16S databases and compare their efficacy in comprehensively identifying potentially pathogenic vaginal microbiota in Japanese women.

METHODS AND RESULTS

The 16 s rRNA databases, Silva, Greengenes, and the basic local alignment search tool (BLAST) were compared to determine whether the classification quality could be improved using the V3-V4 region next-generation sequencing (NGS) sequences. It was found that NGS data were aligned using the BLAST database with the QIIME 2 platform, whose classification quality was higher than that of Silva, and the combined Silva and Greengenes databases based on the mutual complementarity of the two databases.

CONCLUSIONS

The reference database selected during the bioinformatic processing influenced the recognized sequence percentage, taxonomic rankings, and accuracy. This study showed that the BLAST database was the best choice for NGS data analysis of Japanese women's vaginal microbiota.

Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth

BACKGROUND

High-throughput sequencing measurements of the vaginal microbiome have yielded intriguing potential relationships between the vaginal microbiome and preterm birth (PTB; live birth prior to 37 weeks of gestation). However, results across studies have been inconsistent.

RESULTS

Here, we perform an integrated analysis of previously published datasets from 12 cohorts of pregnant women whose vaginal microbiomes were measured by 16S rRNA gene sequencing. Of 2039 women included in our analysis, 586 went on to deliver prematurely. Substantial variation between these datasets existed in their definition of preterm birth, characteristics of the study populations, and sequencing methodology. Nevertheless, a small group of taxa comprised a vast majority of the measured microbiome in all cohorts. We trained machine learning (ML) models to predict PTB from the composition of the vaginal microbiome, finding low to modest predictive accuracy (0.28-0.79). Predictive accuracy was typically lower when ML models trained in one dataset predicted PTB in another dataset. Earlier preterm birth (< 32 weeks, < 34 weeks) was more predictable from the vaginal microbiome than late preterm birth (34-37 weeks), both within and across datasets. Integrated differential abundance analysis revealed a highly significant negative association between L. crispatus and PTB that was consistent across almost all studies. The presence of the majority (18 out of 25) of genera was associated with a higher risk of PTB, with L. iners, Prevotella, and Gardnerella showing particularly consistent and significant associations. Some example discrepancies between studies could be attributed to specific methodological differences but not most study-to-study variations in the relationship between the vaginal microbiome and preterm birth.

CONCLUSIONS

We believe future studies of the vaginal microbiome and PTB will benefit from a focus on earlier preterm births and improved reporting of specific patient metadata shown to influence the vaginal microbiome and/or birth outcomes.

The Vaginal Microbiota of Pregnant Women Varies with Gestational Age, Maternal Age, and Parity

The composition of the vaginal microbiota is heavily influenced by pregnancy and may factor into pregnancy complications, including spontaneous preterm birth. However, results among studies have been inconsistent due, in part, to variation in sample sizes and ethnicity. Thus, an association between the vaginal microbiota and preterm labor continues to be debated. Yet, before assessing associations between the composition of the vaginal microbiota and preterm labor, a robust and in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required. Here, we report a large longitudinal study (n = 474 women, 1,862 vaginal samples) of a predominantly African-American cohort-a population that experiences a relatively high rate of pregnancy complications-evaluating associations between individual identity, gestational age, and other maternal characteristics with the composition of the vaginal microbiota throughout gestation resulting in term delivery. The principal factors influencing the composition of the vaginal microbiota in pregnancy are individual identity and gestational age at sampling. Other factors are maternal age, parity, obesity, and self-reported Cannabis use. The general pattern across gestation is for the vaginal microbiota to remain or transition to a state of Lactobacillus dominance. This pattern can be modified by maternal parity and obesity. Regardless, network analyses reveal dynamic associations among specific bacterial taxa within the vaginal ecosystem, which shift throughout the course of pregnancy. This study provides a robust foundational understanding of the vaginal microbiota in pregnancy and sets the stage for further investigation of this microbiota in obstetrical disease. IMPORTANCE There is debate regarding links between the vaginal microbiota and pregnancy complications, especially spontaneous preterm birth. Inconsistencies in results among studies are likely due to differences in sample sizes and cohort ethnicity. Ethnicity is a complicating factor because, although all bacterial taxa commonly inhabiting the vagina are present among all ethnicities, the frequencies of these taxa vary among ethnicities. Therefore, an in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required prior to evaluating associations between the vaginal microbiota and obstetrical disease. This initial investigation is a large longitudinal study of the vaginal microbiota throughout gestation resulting in a term delivery in a predominantly African-American cohort, a population that experiences disproportionally negative maternal-fetal health outcomes. It establishes the magnitude of associations between maternal characteristics, such as age, parity, body mass index, and self-reported Cannabis use, on the vaginal microbiota in pregnancy.

Vaginal flora during pregnancy and subsequent risk of preterm birth or prelabor rupture of membranes: a nested case-control study from China

BACKGROUND

The findings of the association of vaginal flora with preterm birth (PTB) or prelabor rupture of membranes (PROM) were conflicts. Moreover, vaginal flora was different by ethnicity and the evidence from China was limited.

METHODS

This study was a nested case control study, based on Yiwu birth cohort. We assessed vaginal microbiota in the second or third trimester, using 16S rDNA Amplicon Sequencing and explored the association between the diversity and composition of vaginal flora and PTB or PROM.

RESULTS

We finally included 144 pregnant women. In present study, the alpha diversity of TPROM (Term prelabor rupture of membranes) samples was lower than that of full term samples (Chao1 index: P < 0.05). When we further categorized PTB (Preterm birth) into SPB (PTB without PROM) and PPROM (Preterm prelabor rupture of membranes), there was no difference between SPB and full term. In addition, we found that the proportion of PCoA2 in TPROM group was different from that in full term group and preterm group. The difference between groups was significant according to anosim analysis (R = 0.059, P < 0.001). With LEfSe (Linear discriminant analysis Effect Size) analysis, we found that the abundance of Lactobacillus in the vaginal flora of pregnant women with preterm birth was the highest (P = 0.003).

CONCLUSION

In Chinese pregnant women, the alpha diversity in TPROM group was significantly lower than that in both PTB and full term group. However, there was no difference between PTB and full term. Lactobacillus was the most abundant in preterm birth group. More studies should be conducted to confirm our findings.

Lactobacillus iners and genital health: molecular clues to an enigmatic vaginal species

Purpose of review

Vaginal lactobacilli are recognized as important drivers of genital health including protection against bacterial vaginosis and sexually transmitted infections. Lactobacillus iners is distinct from L. crispatus, L. gasseri, and L. jensenii by its high global prevalence in vaginal microbiomes, relatively small genome, production of only L-lactic acid, and inconsistent associations with genital health outcomes. In this review, we summarize our current understanding of the role of L. iners in the vaginal microbiome, highlight the importance of strain-level consideration for this species, and explain that while marker gene-based characterization of the composition of the vaginal microbiota does not capture strain-level resolution, whole metagenome sequencing can aid in expanding our understanding of this species in genital health.

Recent findings

L. iners exists in the vaginal microbiome as a unique combination of strains. The functional repertoires of these strain combinations are likely wide and contribute to the survival of this species in a variety of vaginal microenvironments. In published studies to date, strain-specific effects are aggregated and may yield imprecise estimates of risk associated with this species.

Summary

The worldwide high prevalence of Lactobacillus iners warrants more research into its functional roles in the vaginal microbiome and how it may directly impact susceptibility to infections. By incorporating strain-level resolution into future research endeavors, we may begin to appreciate L. iners more thoroughly and identify novel therapeutic targets for a variety of genital health challenges.

Vaginal microbiota in women with spontaneous preterm labor versus those with term labor in Kenya: a case control study

Background

Preterm birth is a global problem with about 12% of births in sub-Saharan Africa occurring before 37 weeks of gestation. Several studies have explored a potential association between vaginal microbiota and preterm birth, and some have found an association while others have not. We performed a study designed to determine whether there is an association with vaginal microbiota and/or placental microbiota and preterm birth in an African setting.

Methods

Women presenting to the study hospital in labor with a gestational age of 26 to 36 weeks plus six days were prospectively enrolled in a study of the microbiota in preterm labor along with controls matched for age and parity. A vaginal sample was collected at the time of presentation to the hospital in active labor. In addition, a placental sample was collected when available. Libraries were constructed using PCR primers to amplify the V6/V7/V8 variable regions of the 16S rRNA gene, followed by sequencing with an Illumina MiSeq machine and analysis using QIIME2 2022.2.

Results

Forty-nine women presenting with preterm labor and their controls were enrolled in the study of which 23 matched case–control pairs had sufficient sequence data for comparison. Lactobacillus was identified in all subjects, ranging in abundance from < 1% to > 99%, with Lactobacillus iners and Lactobacillus crispatus the most common species. Over half of the vaginal samples contained Gardnerella and/or Prevotella; both species were associated with preterm birth in previous studies. However, we found no significant difference in composition between mothers with preterm and those with full-term deliveries, with both groups showing roughly equal representation of different Lactobacillus species and dysbiosis-associated genera. Placental samples generally had poor DNA recovery, with a mix of probable sequencing artifacts, contamination, and bacteria acquired during passage through the birth canal. However, several placental samples showed strong evidence for the presence of Streptococcus species, which are known to infect the placenta.

Conclusions

The current study showed no association of preterm birth with composition of the vaginal community. It does provide important information on the range of sequence types in African women and supports other data suggesting that women of African ancestry have an increased frequency of non-Lactobacillus types, but without evidence of associated adverse outcomes.

Longitudinal study of the vaginal microbiome in pregnancies involving preterm labor

Objectives

Alterations in the vaginal bacterial flora reflect the status of various obstetric conditions and are associated with mechanisms that underlie certain pregnancy-associated complications. These changes are also a predictive biomarker for clinical outcomes of these adverse events.

Methods

We examined the vaginal microbiome in samples from pregnant Japanese women with preterm labor.

Results

The microbiota composition in preterm delivery (PD) samples differed from those of control or threatened preterm delivery (TPD) samples in principal component analysis. An increase in Firmicutes and a decrease in Actinobacteria were significantly associated with PD only (both P<0.01). In the Firmicutes phylum, Lactobacillus tended to be abundant, and the abundance of L. iners and L. crispatus was especially high, whereas the L. gasseri population was low in PD samples. Longitudinal analysis showed that the abundance of L. iners decreased after commencing tocolytic treatment in TPD samples compared with before treatment, but it remained high in PD samples.

Conclusions

The vaginal microbiome may be a useful prognostic indicator of preterm labor and a monitoring tool for tocolytic treatment to prevent preterm birth.

The vaginal microbiome and the risk of preterm birth: a systematic review and network meta-analysis

Preterm birth is a major cause of neonatal morbidity and mortality worldwide. Increasing evidence links the vaginal microbiome to the risk of spontaneous preterm labour that leads to preterm birth. The aim of this systematic review and network meta-analysis was to investigate the association between the vaginal microbiome, defined as community state types (CSTs, i.e. dominance of specific lactobacilli spp, or not (low-lactobacilli)), and the risk of preterm birth. Systematic review using PubMed, Web of Science, Embase and Cochrane library was performed. Longitudinal studies using culture-independent methods categorizing the vaginal microbiome in at least three different CSTs to assess the risk of preterm birth were included. A (network) meta-analysis was conducted, presenting pooled odds ratios (OR) and 95% confidence intervals (CI); and weighted proportions and 95% CI. All 17 studies were published between 2014 and 2021 and included 38-539 pregnancies and 8-107 preterm births. Women presenting with "low-lactobacilli" vaginal microbiome were at increased risk (OR 1.69, 95% CI 1.15-2.49) for delivering preterm compared to Lactobacillus crispatus dominant women. Our network meta-analysis supports the microbiome being predictive of preterm birth, where low abundance of lactobacilli is associated with the highest risk, and L. crispatus dominance the lowest.

Contribution of Lactobacillus iners to Vaginal Health and Diseases: A Systematic Review

Lactobacillus iners, first described in 1999, is a prevalent bacterial species of the vaginal microbiome. As L. iners does not easily grow on de Man-Rogosa-Sharpe agar, but can grow anaerobically on blood agar, it has been initially overlooked by traditional culture methods. It was not until the wide application of molecular biology techniques that the function of L. iners in the vaginal microbiome was carefully explored. L. iners has the smallest genome among known Lactobacilli and it has many probiotic characteristics, but is partly different from other major vaginal Lactobacillus species, such as L. crispatus, in contributing to the maintenance of a healthy vaginal microbiome. It is not only commonly present in the healthy vagina but quite often recovered in high numbers in bacterial vaginosis (BV). Increasing evidence suggests that L. iners is a transitional species that colonizes after the vaginal environment is disturbed and offers overall less protection against vaginal dysbiosis and, subsequently, leads to BV, sexually transmitted infections, and adverse pregnancy outcomes. Accordingly, under certain conditions, L. iners is a genuine vaginal symbiont, but it also seems to be an opportunistic pathogen. Further studies are necessary to identify the exact role of this intriguing species in vaginal health and diseases.

An Insight into Vaginal Microbiome Techniques

There is a unique microbial community in the female lower genital tract known as the vaginal microbiota, which varies in composition and density and provides significant benefits during pregnancy, reproductive cyclicity, healthy newborn delivery, protection from preterm birth, infections such as UTIs, bacterial vaginosis, and so on, and improves the efficacy of treatments for vaginal cancers. Methods: It is necessary to know how the vaginal microbiome is composed in order to make an accurate diagnosis of the diseases listed above. A microbiome’s members are difficult to classify, and the way microbial communities function and influence host–pathogen interactions are difficult to understand. More and more metagenomic studies are able to unravel such complexities due to advances in high-throughput sequencing and bioinformatics. When it comes to vaginal microbiota research, we’ll be looking at the use of modern techniques and strategies that can be used to investigate variations in vaginal microbiota in order to detect diseases earlier, better treat vaginal disorders, and boost women’s health. Discussion: The discussed techniques and strategies may improve the treatment of vaginal disorders and may be beneficial for women’s overall health.

Insights into epidemiologic assessments of the microbiome and challenges in identifying microbiome relationships with adverse pregnancy outcomes

Purpose of review

We describe different methods for microbiome assessment and analysis and highlight some of the challenges of using omics data in epidemiologic studies of adverse pregnancy outcomes.

Recent findings

Human microbiomes are dynamic and vary by ancestry and geography. The composition and dynamics of the vaginal microbiome has been associated with risk of preterm birth.

Summary

There are several different methods for characterizing the microbiome. Choice of method depends on the research question and resources available. Added to known challenges of conducting and analyzing epidemiologic studies are the unique challenges associated with microbiome detection and analysis. The resulting omics assessments of human microbial communities have great potential to identify prognostics, diagnostics and potentially therapeutics for adverse pregnancy outcomes.

Limitations of 16S rRNA Gene Sequencing to Characterize Lactobacillus Species in the Upper Genital Tract

The endometrial cavity is an upper genital tract site previously thought as sterile, however, advances in culture-independent, next-generation sequencing technology have revealed that this low-biomass site harbors a rich microbial community which includes multiple Lactobacillus species. These bacteria are considered to be the most abundant non-pathogenic genital tract commensals. Next-generation sequencing of the female lower genital tract has revealed significant variation amongst microbial community composition with respect to Lactobacillus sp. in samples collected from healthy women and women with urogenital conditions. The aim of this study was to evaluate our ability to characterize members of the genital tract microbial community to species-level taxonomy using variable regions of the 16S rRNA gene. Samples were interrogated for the presence of microbial DNA using next-generation sequencing technology that targets the V5-V8 regions of the 16S rRNA gene and compared to speciation using qPCR. We also performed re-analysis of published data using alternate variable regions of the 16S rRNA gene. In this analysis, we explore next-generation sequencing of clinical genital tract isolates as a method for high throughput identification to species-level of key Lactobacillus sp. Data revealed that characterization of genital tract taxa is hindered by a lack of a consensus protocol and 16S rRNA gene region target allowing comparison between studies.

Non-Lactobacillus-Dominated Vaginal Microbiota Is Associated With a Tubal Pregnancy in Symptomatic Chinese Women in the Early Stage of Pregnancy: A Nested Case-Control Study

The features of the vaginal microbiota (VM) community can reflect health status, and they could become new biomarkers for disease diagnosis. During pregnancy, domination of bacteria of the genus Lactobacillus in the VM community is regarded as a keystone because they stabilize the VM by producing antimicrobial compounds and competing adhesion. An altered VM composition provides a marker for adverse pregnancy outcomes. This nested case–control study aimed to characterize the VM in women with a tubal pregnancy (TP) presenting with pain and/or uterine bleeding in early pregnancy. Chinese women with a symptomatic early pregnancy of unknown location were the study cohort. 16S rDNA gene-sequencing of V3–V4 variable regions was done to assess the diversity, structures, taxonomic biomarkers, and classification of the VM community. The primary outcome was the location of the early pregnancy. The VM community in women with a TP showed higher diversity (PD-whole-tree, median: 8.26 vs. 7.08, P = 0.047; Shannon Diversity Index, median: 1.43 vs 0.99, P = 0.03) and showed different structures to those in women with an intrauterine pregnancy (IUP) (R = 0.23, P < 0.01). Bacteria of the genus Lactobacillus were significantly enriched in the IUP group, whereas bacteria of the genera Gardnerella and Prevotella were significantly enriched in the TP group. Lactobacillus abundance could be used to classify the pregnancy location (AUC = 0.81). Non-Lactobacillus-dominated microbiota (≤ 0.85% Lactobacillus) was significantly associated with a TP (adjusted odds ratio: 4.42, 95% confidence interval: 1.33 to 14.71, P = 0.02). In conclusion, among women with a symptomatic early pregnancy, a higher diversity and lower abundance of Lactobacillus in the VM is associated with a TP.

Vaginal bacterial load in the second trimester is associated with early preterm birth recurrence: a nested case-control study

OBJECTIVE

To assess the association between vaginal microbiome (VMB) composition and recurrent early spontaneous preterm birth (sPTB)/preterm prelabour rupture of membranes (PPROM).

DESIGN

Nested case-control study.

SETTING

UK tertiary referral hospital.

SAMPLE

High-risk women with previous sPTB/PPROM <34⁺⁰  weeks' gestation who had a recurrence (n = 22) or delivered at ≥37⁺⁰  weeks without PPROM (n = 87).

METHODS

Vaginal swabs collected between 15 and 22 weeks' gestation were analysed by 16S rRNA gene sequencing and 16S quantitative PCR.

MAIN OUTCOME MEASURE

Recurrent early sPTB/PPROM.

RESULTS

Of the 109 high-risk women, 28 had anaerobic vaginal dysbiosis, with the remainder dominated by lactobacilli (Lactobacillus iners 36/109, Lactobacillus crispatus 23/109, or other 22/109). VMB type and diversity were not associated with recurrence. Women with a recurrence, compared to those without, had a higher median vaginal bacterial load (8.64 versus 7.89 log₁₀ cells/mcl, adjusted odds ratio [aOR] 1.90, 95% CI 1.01-3.56, P = 0.047) and estimated Lactobacillus concentration (8.59 versus 7.48 log₁₀ cells/mcl, aOR 2.35, (95% CI 1.20-4.61, P = 0.013). A higher recurrence risk was associated with higher median bacterial loads for each VMB type after stratification, although statistical significance was reached only for L. iners domination (aOR 3.44, 95% CI 1.06-11.15, P = 0.040). Women with anaerobic dysbiosis or L. iners domination had a higher median vaginal bacterial load than women with a VMB dominated by L. crispatus or other lactobacilli (8.54, 7.96, 7.63, and 7.53 log₁₀ cells/mcl, respectively).

CONCLUSIONS

Vaginal bacterial load is associated with early sPTB/PPROM recurrence. Domination by lactobacilli other than L. iners may protect women from developing high bacterial loads. Future PTB studies should quantify vaginal bacteria and yeasts.

TWEETABLE ABSTRACT

Increased vaginal bacterial load in the second trimester may be associated with recurrent early spontaneous preterm birth.

Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid

PROBLEM

Preterm birth (PTB) is a major cause of increased morbidity and mortality in newborns. The main cause of spontaneous PTB (sPTB) is the activation of an inflammatory response as a result of ascending genital tract infection. Despite various studies on the effects of the vaginal microbiome on PTB, a practical method for its clinical application has yet to be developed.

METHOD OF STUDY

In this case-control study, 94 Korean pregnant women with PTB (n = 38) and term birth (TB; n = 56) were enrolled. Their cervicovaginal fluid (CVF) was sampled, and a total of 10 bacteria were analyzed using multiplex quantitative real-time PCR (qPCR). The PTB and TB groups were compared, and a PTB prediction model was created using bacterial risk scores using machine learning techniques (decision tree and support vector machine). The predictive performance of the model was validated using random subsampling.

RESULTS

Bacterial risk scoring model showed significant differences (P < 0.001). The PTB risk was low when the Lactobacillus iners ratio was 0.812 or more. In groups with a ratio under 0.812, moderate and high risk was classified as a U. parvum ratio of 4.6 × 10^-3 . The sensitivity and specificity of the PTB prediction model using bacteria risk score were 71% and 59%, respectively, and 77% and 67%, respectively, when white blood cell (WBC) data were included.

CONCLUSION

Using machine learning, the bacterial risk score in CVF can be used to predict PTB.