Identification of Potential Biomarkers in the Cervicovaginal Fluid by Metabolic Profiling for Preterm Birth

Dysbiotic Vaginal Microbiota Induces Preterm Birth Cascade via Pathogenic Molecules in the Vagina

Dysbiotic vaginal microbiota (DVM) disturb the vaginal environment, including pH, metabolite, protein, and cytokine profiles. This study investigated the impact of DVM on the vaginal environment in 40 Korean pregnant women and identified predictable biomarkers of birth outcomes. Cervicovaginal fluid (CVF) samples were collected in the third trimester using vaginal swabs, examined for pH, and stored at -80 °C for further analysis. The samples were grouped as full-term (FTB, n = 20) and preterm (PTB, n = 20) births. The microbiota was profiled in the V1-V9 regions. The levels of targeted metabolites, TLR-4, and cytokines were determined. The pH of CVF from PTB (>4.5) was significantly higher than that of the CVF from FTB (>3.5) (p < 0.05). Neonatal gestational age at delivery, birth weight, and Apgar score differed significantly between groups. The relative abundances of beneficial Lactobacillus spp., such as Lactobacillus gasseri, Lactobacillus jensenii, and Bifidobacterium, were higher in FTB, whereas those of pathogenic Enterococcus faecalis, Staphylococcus, Prevotella, Ureaplasma parvum, and Corynebacterium spp. were higher in PTB. Acetate, methanol, TLR-4, and TNF-α levels were negatively correlated with gestational age at delivery and birth weight. Moreover, ethanol, methanol, TLR-4, IL-6, IL-1β, and TNF-α levels were positively correlated with succinate, acetate, acetoacetate, formate, and ammonia. Overall, DVM induces preterm birth via pathogenic molecules in the vagina.

Lipidomic Analysis of Cervicovaginal Fluid for Elucidating Prognostic Biomarkers and Relevant Phospholipid and Sphingolipid Pathways in Preterm Birth

Cervicovaginal fluid (CVF) is an excellent specimen for monitoring preterm birth (PTB) as it characterizes cervical metabolites, the vaginal environment, and specific host immune responses. However, extensive lipid analysis of CVF to explain PTB has not been studied. In this study, we performed a systematic analysis combining high-throughput lipid analysis and omics to discover the unique metabolic properties of the cervix. Liquid chromatography-high resolution mass spectrometry successfully detected a total of 190 lipids in the CVF of 30 PTB and 30 term birth (TB) pregnant women. The whole lipidomics dataset analyzed by combining multivariate and univariate statistical analysis revealed 35 lipid biomarkers, including phospholipids and sphingolipids. Remarkably, sphingomyelin, which plays a physiologically essential role in sphingolipids, was significantly downregulated in PTB. Metabolic pathway study provides a close relationship between vaginal microbial organization and cell membrane formation, further supporting the robustness of our findings. Sphingolipids and phospholipids, which were determined to be important lipids for predicting PTB in our study, showed a high value of receiver operating characteristic (ROC) curve >0.7, indicating that a lipid diagnostic test and understanding the mechanism of lipids is highly related to the vaginal microbiome. Therefore, our result has high potential as a predictor of PTB.

Second trimester short cervix is associated with decreased abundance of cervicovaginal lipid metabolites

BACKGROUND

A short cervix is a risk factor for preterm birth. The molecular drivers of a short cervix remain elusive. Metabolites may function as mediators of pathologic processes.

OBJECTIVE

We sought to determine if a distinct cervicovaginal metabolomic profile is associated with a short cervix (<25 mm) to unveil the potential mechanisms by which premature cervical remodeling leads to a short cervix.

STUDY DESIGN

This was a secondary analysis of a completed prospective pregnancy cohort. Cervicovaginal fluid was obtained between 20 and 24 weeks' gestation. The participants selected for metabolomic profiling were frequency-matched by birth outcome and cervicovaginal microbiota profile. This analysis included 222 participants with cervical length measured. A short cervix was defined as one having length <25 mm, as measured by transvaginal ultrasound. Unpaired t-tests were performed with a Bonferroni correction for multiple comparisons.

RESULTS

There were 27 participants with a short cervix, and 195 with normal cervical length. Of the 637 metabolites detected, 26 differed between those with a short cervix and those with normal cervical lengths; 22 were decreased, of which 21 belonged to the lipid metabolism pathway (all P<.000079). Diethanolamine, erythritol, progesterone, and mannitol or sorbitol were increased in the cases of short cervix. Among participants with Lactobacillus-deficient microbiota, only diethanolamine and mannitol or sorbitol differed between short cervix (n=17) and normal cervical length (n=75), both increased.

CONCLUSION

A short cervix is associated with decreased cervicovaginal lipid metabolites, particularly sphingolipids. This class of lipids stabilizes cell membranes and protects against environmental exposures. Increased diethanolamine-an immunostimulatory xenobiotic-is associated with a short cervix. These observations begin to identify the potential mechanisms by which modifiable environmental factors may invoke cell damage in the setting of biological vulnerability, thus promoting premature cervical remodeling in spontaneous preterm birth.

A Deep Look at the Vaginal Environment During Pregnancy and Puerperium

A deep comprehension of the vaginal ecosystem may hold promise for unraveling the pathophysiology of pregnancy and may provide novel biomarkers to identify subjects at risk of maternal-fetal complications. In this prospective study, we assessed the characteristics of the vaginal environment in a cohort of pregnant women throughout their different gestational ages and puerperium. Both the vaginal bacterial composition and the vaginal metabolic profiles were analyzed. A total of 63 Caucasian women with a successful pregnancy and 9 subjects who had a first trimester miscarriage were enrolled. For the study, obstetric examinations were scheduled along the three trimester phases (9-13, 20-24, 32-34 gestation weeks) and puerperium (40-55 days after delivery). Two vaginal swabs were collected at each time point, to assess the vaginal microbiome profiling (by Nugent score and 16S rRNA gene sequencing) and the vaginal metabolic composition (1H-NMR spectroscopy). During pregnancy, the vaginal microbiome underwent marked changes, with a significant decrease in overall diversity, and increased stability. Over time, we found a significant increase of Lactobacillus and a decrease of several genera related to bacterial vaginosis (BV), such as Prevotella, Atopobium and Sneathia. It is worth noting that the levels of Bifidobacterium spp. tended to decrease at the end of pregnancy. At the puerperium, a significantly lower content of Lactobacillus and higher levels of Gardnerella, Prevotella, Atopobium, and Streptococcus were observed. Women receiving an intrapartum antibiotic prophylaxis for Group B Streptococcus (GBS) were characterized by a vaginal abundance of Prevotella compared to untreated women. Analysis of bacterial relative abundances highlighted an increased abundance of Fusobacterium in women suffering a first trimester abortion, at all taxonomic levels. Lactobacillus abundance was strongly correlated with higher levels of lactate, sarcosine, and many amino acids (i.e., isoleucine, leucine, phenylalanine, valine, threonine, tryptophan). Conversely, BV-associated genera, such as Gardnerella, Atopobium, and Sneathia, were related to amines (e.g., putrescine, methylamine), formate, acetate, alcohols, and short-chain fatty-acids (i.e., butyrate, propionate).

Multivariate analysis of NMR-based metabolomic data

Nuclear magnetic resonance (NMR) spectroscopy allows for simultaneous detection of a wide range of metabolites and lipids. As metabolites act together in complex metabolic networks, they are often highly correlated, and optimal biological insight is achieved when using methods that take the correlation into account. For this reason, latent-variable-based methods, such as principal component analysis and partial least-squares discriminant analysis, are widely used in metabolomic studies. However, with increasing availability of larger population cohorts, and a shift from analysis of spectral data to using quantified metabolite levels, both more traditional statistical approaches and alternative machine learning methods have become more widely used. This review aims at providing an overview of the current state-of-the-art multivariate methods for the analysis of NMR-based metabolomic data as well as alternative methods, highlighting their strengths and limitations.

Significance of analysis of lipid extracts in cervical canal secretion for diagnosing of placenta-associated complications of pregnancy

Omics technologies hold great potential as the basis for development of the new diagnostic approaches in obstetrics. Cervicovaginal fluid (CVF) as part of the mother-placenta-fetus system can be used to diagnose obstetric complications. This study aimed to identify the features of lipid composition of the cervical canal secretion peculiar to Intrauterine Growth Restriction (IUGR) and preeclampsia (PE). We took CVF samples from 57 pregnant women and subjected them to an in-depth clinical-anamnestic and mass-spectrometric analysis. Lipid extracts of CVF were analyzed with a liquid chromatography system coupled with a mass analyzer. As a result, we identified 239 lipid compounds. In case of 17 lipids, mathematical analysis revealed significant differences between samples from women with normal pregnancy indicator values (normal group) and patients from the IUGR group (p < 0.05). As for the normal group and PE group patients, there were significant differences identified for 3 lipids (p < 0.05). Comparison of samples from the PE and IUGR groups yielded statistically significant differences in levels of two lipids (p < 0.05). Mainly, the lipids were oxylipins, sphingomyelins, triglycerides, and cardiolipins. The developed diagnostic model had the sensitivity of 0.81 and specificity of 0.91 (cut-off level — 0.50; AUC — 0.85). The data obtained are valuable in the context of development of the new methods of diagnosing placentaassociated complications of pregnancy and for understanding new mechanisms of pathogenesis of these complications.

Vaginal health in women and the possibility of predicting preterm birth through microbiome analysis

Background: With the recent development of next-generation sequencing technology, the microbiome in the body is being revealed in detail. It is also possible to describe the normal vaginal microenvironment and, more specifically, any changes in pregnancy. Moreover, we present the hypothesis that the microbiome is a contributing factor to preterm birth (PTB).Current Concepts: High estrogen status stimulates the maturation and proliferation of vaginal epithelial cells and the accumulation of glycogen, which promotes lactic acid production and maintains the vaginal environment at an acidic pH. The vaginas of most premenopausal women are predominantly colonized by Lactobacillus which plays an important role in local defense. Recently, it has also been reported that there are several specific types of Lactobacillus species, while other anaerobes, including Gardnerella and Atopobium also coexist in the vagina. Vaginal dysbiosis is defined as various expressions of microorganisms, secretion of specific metabolites, and changes in pH. During pregnancy, a multitude of microbiome changes occur in the oral cavity, gut, vagina, and placenta. The risk of PTB increases if the microbiome changes to one of dysbiosis. It is possible to analyze the characteristic microbiome composition related to PTB and to develop biomarkers predicting PTB. It is necessary to educate patients based on these findings.Discussion and Conclusion: Microbiome analysis has contributed significantly to understanding the association between women’s vaginal health and PTB. Continued research will also contribute to public health by assisting in the prediction and prevention of PTB.

Can Lactobacillus spp. Be a Factor Reducing the Risk of Miscarriage?

Pregnancy loss is a common obstetric problem. Significant causes of miscarriage include genetic and epigenetic disorders of the embryo, immunological and endocrine factors, uterine malformations, improper embryo selection, and lifestyle. Perhaps a hitherto underappreciated cause of miscarriage may be an abnormal microbiota composition of the female reproductive system. Lactobacillus spp. is the most common bacteria within the reproductive tract. However, the protective role of Lactobacilli in the vagina has been well described in the literature, while it is still unknown what function Lactobacilli may have in the uterus. Moreover, new research shows that Lactobacillus spp. can have a role in miscarriage. However, both molecular and immunological mechanisms of host-Lactobacillus spp. interactions are not fully understood. Understanding these relationships will help address the importance and extent of the protective role of Lactobacillus spp. in miscarriage.

The Role of Innate Immune System in the Human Amniotic Membrane and Human Amniotic Fluid in Protection Against Intra-Amniotic Infections and Inflammation

Intra-amniotic infection and inflammation (IAI) affect fetal development and are highly associated with preterm labor and premature rupture of membranes, which often lead to adverse neonatal outcomes. Human amniotic membrane (hAM), the inner part of the amnio-chorionic membrane, protects the embryo/fetus from environmental dangers, including microbial infection. However, weakened amnio-chorionic membrane may be breached or pathogens may enter through a different route, leading to IAI. The hAM and human amniotic fluid (hAF) respond by activation of all components of the innate immune system. This includes changes in 1) hAM structure, 2) presence of immune cells, 3) pattern recognition receptors, 4) cytokines, 5) antimicrobial peptides, 6) lipid derivatives, and 7) complement system. Herein we provide a comprehensive and integrative review of the current understanding of the innate immune response in the hAM and hAF, which will aid in design of novel studies that may lead to breakthroughs in how we perceive the IAI.

Cervicovaginal microbiota and metabolome predict preterm birth risk in an ethnically diverse cohort

The syndrome of spontaneous preterm birth (sPTB) presents a challenge to mechanistic understanding, effective risk stratification, and clinical management. Individual associations between sPTB, self-reported ethnic ancestry, vaginal microbiota, metabolome, and innate immune response are known but not fully understood, and knowledge has yet to impact clinical practice. Here, we used multi–data type integration and composite statistical models to gain insight into sPTB risk by exploring the cervicovaginal environment of an ethnically heterogenous pregnant population (n = 346 women; n = 60 sPTB < 37 weeks’ gestation, including n = 27 sPTB < 34 weeks). Analysis of cervicovaginal samples (10–15⁺⁶ weeks) identified potentially novel interactions between risk of sPTB and microbiota, metabolite, and maternal host defense molecules. Statistical modeling identified a composite of metabolites (leucine, tyrosine, aspartate, lactate, betaine, acetate, and Ca²⁺) associated with risk of sPTB < 37 weeks (AUC 0.752). A combination of glucose, aspartate, Ca²⁺, Lactobacillus crispatus, and L. acidophilus relative abundance identified risk of early sPTB < 34 weeks (AUC 0.758), improved by stratification by ethnicity (AUC 0.835). Increased relative abundance of L. acidophilus appeared protective against sPTB < 34 weeks. By using cervicovaginal fluid samples, we demonstrate the potential of multi–data type integration for developing composite models toward understanding the contribution of the vaginal environment to risk of sPTB.

Molecular Mechanism of Microbiota Metabolites in Preterm Birth: Pathological and Therapeutic Insights

Preterm birth (PTB) refers to the birth of infants before 37 weeks of gestation and is a challenging issue worldwide. Evidence reveals that PTB is a multifactorial dysregulation mediated by a complex molecular mechanism. Thus, a better understanding of the complex molecular mechanisms underlying PTB is a prerequisite to explore effective therapeutic approaches. During early pregnancy, various physiological and metabolic changes occur as a result of endocrine and immune metabolism. The microbiota controls the physiological and metabolic mechanism of the host homeostasis, and dysbiosis of maternal microbial homeostasis dysregulates the mechanistic of fetal developmental processes and directly affects the birth outcome. Accumulating evidence indicates that metabolic dysregulation in the maternal or fetal membranes stimulates the inflammatory cytokines, which may positively progress the PTB. Although labour is regarded as an inflammatory process, it is still unclear how microbial dysbiosis could regulate the molecular mechanism of PTB. In this review based on recent research, we focused on both the pathological and therapeutic contribution of microbiota-generated metabolites to PTB and the possible molecular mechanisms.

Identification of Indicators for Preterm Birth Using Retinoid Metabolites

Metabolites reflect the biochemical dynamics for the maintenance of pregnancy and parturition. UPLC-Q/TOF-MS and LC-MS/MS metabolomics were performed to identify and validate the plasma metabolomic signatures of preterm birth (PTB). We recruited pregnant women between 16 and 40 weeks 5 days gestational age at Ewha Womans Mokdong Hospital for a nested case-control study. In untargeted UPLC-Q/TOF-MS, score plots of partial least-squares discriminant analysis clearly separated the PTB group from the term birth (TB, n = 10; PTB, n = 11). Fifteen metabolites were significantly different between the two groups, as indicated by a variable importance in projection >1 and p < 0.05. Metabolic pathways involving retinol, linoleic acid, d-arginine, and d-ornithine were associated with PTB. Verification by LC-MS/MS focused on retinol metabolism (TB, n = 39; PTB, n = 20). Retinol levels were significantly reduced in PTB compared to TB, while retinal palmitate, all-trans-retinal, and 13-cis-retinoic acid (¹³cis-RA) significantly increased (p < 0.05). Retinol-binding protein levels were also elevated in PTB. Additionally, all-trans-retinal (AUC 0.808, 95% CI: 0.683–0.933) and ¹³cis-RA (AUC 0.826, 95% CI: 0.723–0.930) showed improved predictions for PTB-related retinol metabolites. This study suggests that retinoid metabolism improves the accuracy of PTB predictions and plays an important role in maintaining pregnancy and inducing early parturition.

New Insights into Vaginal Environment During Pregnancy

During pregnancy, the vaginal ecosystem undergoes marked changes, including a significant enrichment with Lactobacillus spp. and profound alterations in metabolic profiles. A deep comprehension of the vaginal environment may shed light on the physiology of pregnancy and may provide novel biomarkers to identify subjects at risk of complications (e.g., miscarriage, preterm birth). In this study, we characterized the vaginal ecosystem in Caucasian women with a normal pregnancy (n = 64) at three different gestational ages (i.e., first, second and third trimester) and in subjects (n = 10) suffering a spontaneous first trimester miscarriage. We assessed the vaginal bacterial composition (Nugent score), the vaginal metabolic profiles (¹H-NMR spectroscopy) and the vaginal levels of two cytokines (IL-6 and IL-8). Throughout pregnancy, the vaginal microbiota became less diverse, being mainly dominated by lactobacilli. This shift was clearly associated with marked changes in the vaginal metabolome: over the weeks, a progressive reduction in the levels of dysbiosis-associated metabolites (e.g., biogenic amines, alcohols, propionate, acetate) was observed. At the same time, several metabolites, typically found in healthy vaginal conditions, reached the highest concentrations at the end of pregnancy (e.g., lactate, glycine, phenylalanine, leucine, isoleucine). Lower levels of glucose were an additional fingerprint of a normal vaginal environment. The vaginal levels of IL-6 and IL-8 were significantly associated with the number of vaginal leukocytes, as well as with the presence of vaginal symptoms, but not with a condition of dysbiosis. Moreover, IL-8 concentration seemed to be a good predictor of the presence of vaginal Candida spp. Cytokine concentrations were negatively correlated to lactate, serine, and glycine concentrations, whereas the levels of 4-hydroxyphenyllactate, glucose, O-acetylcholine, and choline were positively correlated with Candida vaginal loads. Finally, we found that most cases of spontaneous abortion were associated with an abnormal vaginal microbiome, with higher levels of selected metabolites in the vaginal environment (e.g., inosine, fumarate, xanthine, benzoate, ascorbate). No association with higher pro-inflammatory cytokines was found. In conclusion, our analysis provides new insights into the pathophysiology of pregnancy and highlights potential biomarkers to enable the diagnosis of early pregnancy loss.

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.

Vaginal metabolic profiles during pregnancy: Changes between first and second trimester

During pregnancy, the vaginal microbiome plays an important role in both maternal and neonatal health outcomes. Throughout pregnancy, the vaginal microbial composition undergoes significant changes, including a decrease in overall diversity and enrichment with Lactobacillus spp. In turn, the modifications in the microbial profiles are associated with shifts in the composition of vaginal metabolites. In this study, we characterized the vaginal metabolic profiles throughout pregnancy at two different gestational ages, correlating them with a microscopic evaluation of the vaginal bacterial composition. A total of 67 Caucasian pregnant women presenting to the Family Advisory Health Centres of Ravenna (Italy) were enrolled and a vaginal swab was collected at gestational ages 9–13 weeks (first trimester) and 20–24 weeks (second trimester). The composition of the vaginal microbiome was assessed by Nugent score and women were divided in ‘H’ (normal lactobacilli-dominated microbiota), ‘I’ (intermediate microbiota), and ‘BV’ (bacterial vaginosis) groups. Starting from the cell-free supernatants of the vaginal swabs, a metabolomic analysis was performed by means of a ¹H-NMR spectroscopy. From the first to the second trimester, a greater number of women showed a normal lactobacilli-dominated microbiota, with a reduction of cases of dysbiosis. These microbial shifts were associated with profound changes in the vaginal metabolic profiles. Over the weeks, a significant reduction in the levels of BV-associated metabolites (e.g. acetate, propionate, tyramine, methylamine, putrescine) was observed. At the same time, the vaginal metabolome was characterized by higher concentrations of lactate and of several amino acids (e.g. tryptophan, threonine, isoleucine, leucine), typically found in healthy vaginal conditions. Over time, the vaginal metabolome became less diverse and more homogeneous: in the second trimester, women with BV showed metabolic profiles more similar to the healthy/intermediate groups, compared to the first trimester. Our data could help unravel the role of vaginal metabolites in the pathophysiology of pregnancy.

The Universal Soldier: Enzymatic and Non-Enzymatic Antioxidant Functions of Serum Albumin

As a carrier of many biologically active compounds, blood is exposed to oxidants to a greater extent than the intracellular environment. Serum albumin plays a key role in antioxidant defence under both normal and oxidative stress conditions. This review evaluates data published in the literature and from our own research on the mechanisms of the enzymatic and non-enzymatic activities of albumin that determine its participation in redox modulation of plasma and intercellular fluid. For the first time, the results of numerous clinical, biochemical, spectroscopic and computational experiments devoted to the study of allosteric modulation of the functional properties of the protein associated with its participation in antioxidant defence are analysed. It has been concluded that it is fundamentally possible to regulate the antioxidant properties of albumin with various ligands, and the binding and/or enzymatic features of the protein by changing its redox status. The perspectives for using the antioxidant properties of albumin in practice are discussed.