Vagina biomarker for premature delivery of elderly puerpera as well as screening and application of vagina biomarker

Abstract

The invention discloses a vagina biomarker for premature delivery of an elderly puerpera as well as screening and application of the vagina biomarker. The biomarker comprises two vagina bacterium biomarkers and two vagina metabolite biomarkers. The method comprises the following steps: performing 16SrDNA amplicon sequencing and metagenome sequencing on vaginal secretion sample DNA, performing non-targeted metabonomics detection on vaginal secretion, and analyzing the relevance between vaginal flora structure, functional information and metabolites and premature delivery of elderly pregnant women. Through multi-omics correlation analysis, the screened vaginal bacterium category with the premature delivery reduction rate of the elderly pregnant woman, two vaginal secretion metabolites and the screened vaginal bacterium category with the premature delivery reduction rate of the elderly pregnant woman are classified. The biomarker provided by the invention can be used as a detection target for preparing a kit for premature delivery occurrence risk of the elderly pregnant woman, or can be used as a target for preparing a medicine for treating and / or preventing premature delivery of the elderly pregnant woman.

Description

Technical Field

[0001] The present invention belongs to the field of research on vaginal flora and human health, and specifically relates to vaginal biomarkers for the occurrence of preterm birth in elderly pregnant women, as well as screening and application thereof. Background Art

[0002] Appropriate childbearing age remains a global concern. The trend of delaying marriage and childbearing has increased globally. This may be attributed to changes in social norms, increased opportunities for female education and career development, and advancements in assisted reproductive technology. According to a report, between 2006 and 2015, women giving birth at the age of 15 - 17 accounted for 2.5%, those at the age of 30 - 34 accounted for 24.9%, and those over the age of 35 accounted for 14.9%. Globally, the number of pregnant women aged 35 and above is on the rise. Some research reports state that maternal age is associated with adverse pregnancy outcomes, including preeclampsia, postpartum hemorrhage, gestational diabetes mellitus, fetal miscarriage and death. The occurrence of adverse pregnancy outcomes, such as fetal growth restriction and low - birth - weight infants, may be attributed to multiple maternal factors, including obesity, parity, gravidity, use of in vitro fertilization - embryo transfer (IVF - ET), cervical ectropion and scarred uterus. These factors may act alone or in combination. Some research reports state that advanced age is associated with preterm birth. This may be due to the general increase in overweight and obesity, the growth of elderly pregnant women, and the growth of high - risk populations. However, the pathophysiology of preterm birth remains mostly unknown. Therefore, it is important to identify additional risk factors. In addition, there is an urgent need to identify multidimensional biomarkers to assist in the early diagnosis and treatment intervention of preterm birth in elderly mothers. Along with the rapid economic development and social transformation in China, maternal and child health will face new problems. Risk factors such as high - nutrient diet, low physical activity, obesity, and elderly pregnant women will affect maternal health and pregnancy outcomes. Among them, gestational diabetes mellitus (GDM), as one of the main complications during pregnancy, seriously endangers maternal and child health. Studying the pathogenesis of GDM and finding risk factors that can be used to predict GDM early play a crucial role in preventing and controlling GDM, reducing adverse pregnancy outcomes, and reducing the risk of long - term diabetes in mothers.

[0003] Several studies have shown that the vaginal microbiota changes with age, and the age - related microbiota may lead to increased intestinal permeability and systemic inflammation, resulting in the loss of health - related vaginal microbiota characteristics. In addition, some studies have emphasized the correlation between serum physiological and biochemical indicators and vaginal microbiota during pregnancy. However, no studies have explored the relationship between reproductive age, biochemical indicators, and vaginal microbiota. Therefore, it is crucial to use clinical, biochemical, and microbiological indicators to determine the impact of reproductive age on maternal health.

[0004] Vaginal microbiota can serve as biomarkers reflecting maternal health status during pregnancy. For example, bacterial vaginosis is characterized by the depletion of lactobacilli and an increase in microbial diversity. A high-diversity vaginal microbiota, such as Gardnerella and Atopobium, is also associated with bacterial vaginosis. Si et al. (2022) showed that Atopobium may play an important role in the pathogenesis of spontaneous abortion. The composition of the maternal vaginal microbiota is associated with preterm birth. In particular, Lactobacillus is usually associated with a lower risk of preterm birth. Disturbance of the vaginal microbiota is associated with adverse pregnancy outcomes. However, previous research findings on the relationship between the vaginal microbiota and preterm birth have been conflicting. Sherrianne et al. reported that the composition of the vaginal microbiota was not associated with the risk of preterm birth in African American women during pregnancy. This may explain the observed low preterm birth rate, as well as biogeographical and ethnic differences. Our investigation revealed that although clinical indicators such as fetal fibronectin and cervical length have been identified as potential biomarkers for preterm birth, few stable and reliable biomarkers for preterm birth have been found. This is due to low specificity or insufficient evidence. Therefore, it is necessary to clarify the relationship between preterm birth and the vaginal microbiota in the Chinese population, including its influencing factors, especially in older mothers. In addition, our understanding of the specific mechanisms of potential host-microbiota interactions in preterm birth is limited.

[0005] Some studies have reported that changes in the vaginal microbiota and metabolites are related to the occurrence and regulation of pregnancy-related diseases. Ziklo et al. (2018) reported that dysregulation of the vaginal microbiota and a higher vaginal kynurenine / tryptophan ratio were associated with genital Chlamydia trachomatis infection. William et al. (2021) reported multiple associations between vaginal metabolites such as diethanolamine and ethyl glucoside and subsequent preterm birth. Flavia et al. (2021) identified a group of metabolites (leucine, tyrosine, aspartic acid, lactic acid, betaine, acetic acid, and Ca 2+ ) associated with the risk of preterm birth. These studies suggest the potential of vaginal metabolites as early biomarkers for adverse pregnancy outcomes. Further research is needed to understand the interactions between the vaginal microbiota and its metabolite characteristics in older mothers, as well as the impact of the vaginal ecosystem on preterm birth and other adverse pregnancy outcomes in older mothers. Summary of the Invention

[0006] The object of the present invention is to provide vaginal biomarkers for preterm birth in elderly pregnant women, screening and applications thereof. Based on the vaginal secretions of elderly pregnant women as samples, metagenomic sequencing and metabolomics detection methods are used to process and analyze the microorganisms and metabolites in the samples respectively. Finally, four biomarkers including Gardnerella vaginalis, Lactobacillus crispatus, lactose, and D-galactose are screened out, providing guidance for the early diagnosis, prevention, prediction, intervention treatment, and precise medication of preterm birth in elderly pregnant women, and further helping to understand the pathogenesis and targeted medication of preterm birth in elderly pregnant women and other aspects of research.

[0007] According to the first aspect of the present invention, there is provided a vaginal bacterial biomarker for preterm birth in elderly pregnant women, including at least one of the following 2 types of bacteria: Gardnerella vaginalis and Lactobacillus crispatus; wherein, the relative abundance of Gardnerella vaginalis is significantly increased in the vaginal flora of elderly preterm pregnant women, and the relative abundance of Lactobacillus crispatus decreases in the vaginal flora of elderly preterm pregnant women. Preferably, Gardnerella vaginalis is associated with an increased risk of preterm birth in elderly pregnant women, and Lactobacillus crispatus is associated with a decreased risk of preterm birth in elderly pregnant women.

[0008] According to another aspect of the present invention, there is provided a vaginal secretion biomarker for preterm birth in elderly pregnant women, including at least one of the following 2 vaginal secretion metabolites: lactose and D-galactose.

[0009] According to another aspect of the present invention, there is provided the application of the vaginal flora biomarker for preterm birth in elderly pregnant women as a detection target in the preparation of a kit for the risk of preterm birth in elderly pregnant women.

[0010] According to another aspect of the present invention, there is provided the application of the vaginal flora biomarker for preterm birth in elderly pregnant women as a target in the preparation of a drug for the treatment and / or prevention of preterm birth in elderly pregnant women; preferably, the drug is a probiotic, prebiotic, or synbiotic.

[0011] According to another aspect of the present invention, there is provided the application of the vaginal secretion metabolite biomarker for preterm birth in elderly pregnant women as a detection target in the preparation of a kit for the risk of preterm birth in elderly pregnant women during the early pregnancy.

[0012] Meanwhile, the above-mentioned biomarkers can also be used as intervention targets to continuously monitor the health status of individuals, so as to perform early intervention when abnormal characteristics related to the occurrence of preterm birth in certain elderly pregnant women are found.

[0013] The present invention also provides the use of the above-mentioned biomarker in the preparation of a drug for treating preterm birth in elderly pregnant women. Preferably, the present invention provides a pharmaceutical composition, which contains a drug that reduces the risk of preterm birth in elderly pregnant women by regulating the relative content of the biomarker for evaluating the risk of preterm birth in elderly pregnant women. The pharmaceutical composition can regulate the microbial biomarker to balance the relative content between various genera of bacteria, reduce the risk of preterm birth in elderly pregnant women. At the same time, the pharmaceutical composition can regulate the content of metabolites in vaginal secretions, reduce adverse metabolites, and improve the internal environment of the individual.

[0014] Generally speaking, compared with the prior art by the above technical solution conceived by the present invention, the following technical advantages are mainly possessed:

[0015] (1) Based on a pregnant women cohort, the present invention performs metagenomic deep sequencing on vaginal bacteria of pregnant women of different ages and performs liquid chromatography-tandem mass spectrometry detection on vaginal secretions to respectively obtain the abundance contents of bacteria of differential genera and differential metabolites. The present invention efficiently screens out 4 predictive biomarkers including Gardnerella vaginalis, Lactobacillus crispatus, lactose, and D-galactose, etc., which can be used as detection targets in the application of preparing a detection kit for the risk of preterm birth in elderly pregnant women, or as targets in the application of preparing drugs for treating and / or preventing preterm birth in elderly pregnant women.

[0016] (2) As an excretory product of the body, vaginal secretions are relatively stable and accurate samples for studying the vaginal flora. Studying vaginal samples to identify the differential flora between preterm patients and healthy pregnant women at an early stage when preterm birth has not occurred and predicting the risk of preterm birth in pregnant women is helpful for early prevention and diagnosis.

[0017] (3) The biomarkers related to preterm birth in elderly pregnant women proposed by the present invention have high value for the early prevention and early diagnosis of preterm birth. First, the availability, operability, safety, and affordability of vaginal secretion samples ensure the compliance of patients. Second, the representativeness and relative stability of vaginal secretion samples for the vaginal flora ensure the reliability of research results. Third, the vaginal sample flora information is achieved based on high-throughput sequencing technology, and the obtained biomarkers have high sensitivity and specificity. Fourth, the biomarkers described in the present invention can also be used to monitor the effects and responses of preterm pregnant women to intervention treatments throughout the pregnancy. Description of the Drawings

[0018] Figure 1 are the clinical characteristics and biochemical indexes of parturients of different reproductive ages in Examples 1-2.

[0019] Figure 2 are the α-diversity, β-diversity, and composition of the vaginal microbial communities of parturients of different reproductive ages in Example 3.

[0020] Figure 3 It is the correlation analysis between the vaginal microbiota of parturients of different reproductive ages in Example 3 and clinical indicators, biochemical indicators, and the occurrence of delivery complications.

[0021] Figure 4 It is the alpha diversity, beta diversity, and composition of the vaginal microbiota of elderly mothers with cervical ectropion (CE) and non-cervical ectropion (N_CE) in Example 3.

[0022] Figure 5 It is the bacterial community function of elderly mothers with cervical ectropion (CE) and non-cervical ectropion (N_CE) in Example 3.

[0023] Figure 6 It is the CAZyme annotation profile of elderly mothers with CE and N_CE in Example 3.

[0024] Figure 7 It is the differential analysis of vaginal metabolites and metabolic pathway enrichment analysis between the N_CE and CE groups in Example 4.

[0025] Figure 8 It is the correlation analysis of the relationship between clinical indicators, biochemical indicators, vaginal microbiota, and metabolites. Detailed implementation manners

[0026] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0027] Example 1 Subject recruitment and sample collection

[0028] In this study, pregnant women of different ages were recruited. All participants were local residents in southern China and had no history of smoking or drinking. Vaginal swab samples were collected and stored at -80°C until further analysis. The participants did not receive any medications, antibiotics, probiotics, or prebiotics within one month before sampling. Clinical information of all pregnant women was recorded, including age, height, weight, BMI, gestational age, parity, gravidity, systolic blood pressure (SBP) and diastolic blood pressure (DBP), as well as any adverse pregnancy outcomes, such as fetal growth restriction, low birth weight infants, and preterm birth. The following information of pregnant women was also recorded: in vitro fertilization-embryo transfer (IVF-ET) and pregnancy complications, including cervical ectropion, scarred uterus, uterine fibroids, adenomyosis, amniotic fluid, oligohydramnios, polyhydramnios, pelvic infection, polycystic ovary syndrome (PCOS), intrahepatic cholestasis of pregnancy (ICP), gestational diabetes mellitus (GDM), obesity, preeclampsia, anemia, group B streptococcus (GBS) infection, cardiovascular (CV) infection, and Escherichia coli infection. And various factors that may lead to delivery complications were recorded, including Escherichia coli infection, premature rupture of membranes (PROM), fetal distress, perineal laceration, leakage of amniotic fluid from the buttocks, uterine cervical notch (UCAN), placental adhesion, and mode of delivery (cesarean section, vaginal delivery, and miscarriage) (Table 1).

[0029] A total of 195 participants were recruited in this study. According to maternal age, the study population was divided into four groups to explore the associations among maternal factors, vaginal microbiota, and pregnancy outcomes in women of different ages. It has been reported that the optimal childbearing age range for women is 23 - 30 years old. Therefore, this study included a group of women younger than 23 years old, a group of women aged 23 - 30 years old, a group of women aged 30 - 35 years old, and a group of women older than 35 years old. The average gestational weeks of these groups were 23 weeks ( Figure 1 a). Table 1 shows the maternal factors of the four age groups, including height, weight, BMI, gestational age, parity, gravidity, systolic blood pressure, and diastolic blood pressure. The parity of the group of women older than 35 years old (Y35 group) was significantly higher than that of the group of women younger than 23 years old (Y23 group) (p < 0.05)( Figure 1b). However, there were no significant differences in other clinical characteristics among the four groups (p > 0.05). Table 1 shows that maternal age is an important factor in pregnancy outcomes. Compared with mothers aged 23 - 35 years, adolescent mothers aged 17 - 22 years and advanced maternal age mothers aged 36 - 41 years had a higher risk of adverse pregnancy outcomes, including fetal growth restriction, low birth weight infants, and preterm birth. This study recorded the use of assisted reproductive technologies, including cervical and in vitro fertilization - embryo transfer (IVF - ET), as well as adverse pregnancy history. Among the study groups, the Y35 group had the highest IVF - ET utilization rate (25.8%) (Table 1). Table 1 shows the occurrence of pregnancy complications, such as cervical ectopy, scarred uterus, uterine fibroids, adenomyosis, amniotic fluid, oligohydramnios, polyhydramnios, pelvic infection, polycystic ovary syndrome, intrahepatic cholestasis of pregnancy, gestational diabetes, obesity, preeclampsia, anemia, group B streptococcus infection, cardiovascular disease, Escherichia coli infection, and premature rupture of membranes. With increasing age, the incidence of cervical ectopy in pregnant women increased significantly, especially in the Y30 - 35 and Y35 groups, reaching 23.8% and 22.6% respectively. However, the incidence of group B streptococcus infection in the Y23 - 30 group (14.7%) was significantly higher than that in the other three groups (p < 0.05), which requires further study. Table 1 shows the statistical analysis of delivery complications in pregnant women, including fetal distress, perineal laceration, breech leakage, cervical notch, placental adhesion, and mode of delivery (cesarean section, vaginal delivery, or abortion). Compared with mothers aged 23 - 30 years, adolescent mothers aged 17 - 22 years and advanced maternal age mothers aged 36 - 41 years had significantly higher cesarean section rates, reaching 50.0% and 71.0% respectively. Pregnant women aged 23 - 30 years and 30 - 35 years showed a trend towards vaginal delivery. In addition, the incidence of abortion was higher in advanced maternal age mothers.

[0030] Table 1. Detailed clinical characteristics of pregnant women among the recruited subjects

[0031]

[0032]

[0033]

[0034] FGR: Fetal growth restriction; LBWI: Low birth weight infants; CC: Cervical cerclage; IVF-ET: In vitro fertilization-embryo transfer; APPH: Adverse pregnant production history; PCOS: Polycystic ovary syndrome; ICP: Intrahepatic cholestasis of pregnancy; GDM: Gestational diabetes mellitus; GBS: Streptococcus agalactiae; CV: Candida vulvovaginal; E.coli: Escherichia coli; PROM: Premature rupture of membranes; UCAN: Umbilical cord around neck.

[0035] Example 2 Detection of Clinically Relevant Basic Indicators

[0036] Biochemical indicators in the vaginal secretions of pregnant women were measured using an enzyme-linked immunosorbent assay (ELISA) kit (Beijing Dongsong Boye Biotechnology Co., Ltd., Beijing, China). The measured indicators included interleukin (IL-1β), IL-6, IL-8, IL-10, human chorionic gonadotropin (HCG), progesterone (PROG), estrogen (E), hydroxybutyrate dehydrogenase (HBD-2), G protein-coupled receptor 30 (GPR30), and C-reactive protein (CPR), and the measurements were performed according to the manufacturer's instructions.

[0037] Compared with mothers aged 23 - 30 years, adolescent mothers aged 17 - 22 years and older mothers aged 36 - 41 years showed higher levels of IL-1β (p < 0.05)( Figure 1 c). In addition, the level of IL-6 in the Y35 group was higher than that in the Y23 - 30 and Y30 - 35 groups (p < 0.05)( Figure 1 d). The levels of IL-8 and HCG increased significantly with age (p < 0.05)( Figure 1 e, f). The results showed that the PROG levels in the Y35 and Y23 - 30 groups were higher than those in adolescent mothers aged 17 - 22 years (p < 0.05)( Figure 1 g). In addition, the level of GPR30 showed a trend of increasing first and then decreasing, and the level of GPR30 in the Y30 - 35 group was higher than that in the Y35 group (p < 0.05)( Figure 1h). However, there were no significant differences in serum IL-10, E, HBD-2, or CRP levels among the four groups.

[0038] To investigate the correlations between maternal age and clinical laboratory tests, biochemical indices, and other maternal factors, heatmaps were created using Spearman correlation analysis. Maternal age was positively correlated with parity ( Figure 1 i) and IL-8 levels ( Figure 1 j), as well as with mode of delivery, preterm birth, IVF-ET, APPH, and columnar epithelial ectopy ( Figure 1 k). These findings suggest that maternal age has a significant impact on these indices, including adverse outcomes.

[0039] Example 3 Metagenomic sequencing analysis of vaginal secretions

[0040] 3.1 DNA extraction, PCR amplification, and sequencing

[0041] DNA was extracted as described previously. Using the E.Z.N.A. Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA), DNA was extracted from vaginal secretion samples according to the manufacturer's protocol. Paired-end sequencing was performed using Illumina NovaSeq / HiseqXten (Illumina Inc., San Diego, CA, USA) with the NovaSeq kit / HiSeqX kit (www.illumina.com).

[0042] 3.2 16S rRNA gene data processing

[0043] Then, high-quality sequences were processed using the DADA2 plugin in the QIIME2 (version 2020.2) pipeline, which obtains single-nucleotide resolution based on the error profile within the sample. DADA2-denoised sequences are commonly referred to as amplicon sequence variants (ASVs). To minimize the impact of sequencing depth on alpha and beta diversity measurements, the number of sequences per sample was diluted to 4000, which still yielded an average Good's coverage of 97.90%. Taxonomic assignment of ASVs was performed using the Vsearch consensus classifier implemented in QIIME2 and the SILVA 16S rRNA database (v138). Analysis of 16S rRNA microbiome sequencing data was performed using a free online platform on the Majorbio Cloud Platform (www.majorbio.com).

[0044] 3.3 Metagenomic data processing

[0045] The data was analyzed on the free online platform of Majorbio CloudPlatform (www.majorbio.com). Briefly, paired Illumina reads were trimmed for adapters and low-quality reads (length < 50bp or quality value < 20 or containing N bases) were removed by fastp. The reads were aligned to the human genome using BWA, and any hits related to the reads and their paired reads were removed. Metagenomic data assembly was performed using MEGAHIT, which utilizes a succinct de Bruijn graph. Contigs with length ≥ 300bp were selected as the final assembly results, and these contigs were then used for further gene prediction and annotation. The representative sequences of the non-redundant gene catalog were aligned to the NR database for taxonomic annotation using Diamond with an e-value of 1e-5. KEGG annotation was performed using Diamond against the Kyoto Encyclopedia of Genes and Genomes database with an e-value of 1e-5. Carbohydrate-active enzyme annotation was performed in the CAZy database using hmmScan.

[0046] A total of 16,960,487 high-quality reads with an average length of 424.98bp were obtained from 195 vaginal secretion samples. The Sobs curve reached a stable plateau ( Figure 2 a), indicating that the sequencing depth for analyzing most bacterial communities was sufficient. Meanwhile, the Chao index, representing the richness and diversity of the community, decreased in the other three groups, especially in the Y35 group when compared with the Y23-30 group. This indicates a difference in bacterial biodiversity between the Y23-30 and Y35 groups. However, no significant difference was observed between the two groups ( Figure 2 b). To investigate whether there were differences in the vaginal microbiota composition between mothers aged 36 - 41 and mothers of other age groups, we performed hierarchical clustering (unweighted FastUnifrac) and NMDS analysis ( Figure 2 c). Based on the composition of bacterial communities in all samples, the bacterial communities were classified into four types, indicating obvious differences in vaginal microbiota between different maternal ages.

[0047] Figure 2 The relative abundances of vaginal bacterial communities at the phylum, family, and genus levels are shown. Firmicutes was the most detected phylum in the samples, followed by Actinobacteria, which contradicts the previous survey results of bacterial biodiversity in the United States. This difference may be due to regional and ethnic differences. In adolescent mothers aged 17 - 22, Fusobacteria was the dominant phylum, while Proteobacteria was more abundant in the Y23-30, Y30-35, and Y35 groups. In addition, with the increase in age, the relative abundance of Bacteroidetes decreased, and the Y35 group showed the lowest abundance of Bacteroidetes. Figure 2d). At the family level, Lactobacillaceae and Bifidobacteriaceae were enriched in most samples, which was consistent with previous reports. Compared with the other three groups, the Y23-30 group had the highest number of Alcaligenaceae. The Y23 group had unique Leptotrichiaceae and Veillonellaceae families. Enterococcaceae was enriched in the Y30-35 group, while Streptococcaceae and Atopobiaceae were dominant in the Y30-35 and Y35 groups ( Figure 2 e). At the genus level, Lactobacillus and Gardnerella were enriched in all four groups ( Figure 2 f - h). The Y23-30 group had the highest number of unique genera, reaching 319 ( Figure 2 i). LDA Effect Size (LEfSe) was used to identify key vaginal microbes that affect maternal age. As Figure 2 shown in j, k, the relative abundance of Gardnerella was lower in the other three groups. In addition, the Y23 group showed higher levels of Aerococcus, Sneathia, and Megasphaera, while the abundance of Alloscardovia in the Y30-35 and Y35 groups was higher than that in the Y23-30 group. In contrast, the potential probiotics Akkermansia and Bacteroides were reduced in the Y30-35 and Y35 groups. These findings suggest a potential association between age-related physiological function changes and the abundance of vaginal microbes.

[0048] By evaluating the relationship between vaginal microbial species and clinical indicators related to maternal age. The results showed a significant association between maternal vaginal microbes and age-related maternal clinical and biochemical indicators ( Figure 3 ). The abundance of Lactobacillus was negatively correlated with gestational age and parity. The abundance of certain genera, including Aeromonas, Acinetobacter, Escherichia-Shigella, and Staphylococcus, increased in adolescent mothers aged 17 to 22 years and was positively correlated with gestational age and parity. In addition, Gardnerella was negatively correlated with age and parity. In contrast, the abundance of Atopobium and Alloscardovia increased in older mothers aged 36 - 41 years, and they were positively correlated with age ( Figure 3 a, b).

[0049] Among mothers aged 36 - 41, the increased IL-8 was negatively correlated with Lactobacillus and Fusobacterium, and positively correlated with Gardnerella and Ureaplasma. Achromobacter, Bacillus, Aeromonas, Romboutsia, Pseudomonas, Sphingomonas, and Fenollaria were enriched in adolescent mothers aged 17 - 22 and negatively correlated with IL-10. The level of IL-10 was positively correlated with Peptostreptococcus, while progesterone PROG was negatively correlated with Fenollaria. GPR30 was positively correlated with Klebsiella, and the estrogen level was negatively correlated with Achromobacter. However, Enterococcus was positively correlated with Peptostreptococcus spp. In contrast, HBD_2 was negatively correlated with Streptococcus ( Figure 3 c, d).

[0050] This study found that Lactobacillus was negatively correlated with cervical ectropion, while Gardnerella and Atopobium were positively correlated with cervical ectropion. In addition, Gardnerella was positively correlated with preterm birth. This study also found that Achromobacter, Streptococcus, and Anaerococcus were negatively correlated with the use of cesarean section, while Anaeroglobus was positively correlated with cesarean section. In older mothers aged 36 - 41, Alloscardovia increased and was positively correlated with uterine fibroids. Sneathia, Aeromonas, and Megasphaera were enriched in adolescent mothers aged 17 - 22 and positively correlated with placental adhesion, FGR, oligohydramnios, obesity, and preeclampsia. In addition, Pseudoramibacter was positively correlated with the use of assisted reproductive technology (IVF_ET). This study found that Lactobacillus was positively correlated with the mode of delivery, and bacteria including Achromobacter, Streptococcus, Prevotella, Bacillus, Aeromonas, Delftia, Romboutsia, Acinetobacter, Escherichia-Shigella, Staphylococcus, Pseudomonas, and Stenotrophomonas were negatively correlated with the mode of delivery ( Figure 3 e, f).

[0051] The above results indicate that there is a potential link between the vaginal microbiota, particularly Lactobacillus and Gardnerella, and adverse pregnancy outcomes, such as preterm birth in mothers aged 36 - 41 years. This link may be related to maternal factors such as parity, IVF_ET, mode of delivery, and cervical ectopy.

[0052] Increased Gardnerella and decreased Lactobacillus crispatus may induce cervical ectopy, which is a major maternal factor affecting preterm birth. Mothers aged 36 - 41 years were divided into two groups according to the presence or absence of cervical ectopy. Figure 4 showed that the Chao and Shannon indices in the cervical ectopy (CE) group were lower than those in the N_CE group, but the difference was not significant (p > 0.05) ( Figure 4 a - b). The beta - diversity results of the vaginal microbiome were significantly different between the two groups (p < 0.05) ( Figure 4 c). The abundances of Firmicutes, Actinobacteria, and Proteobacteria were higher in the N_CE group, while Actinobacteria was the most abundant phylum in the CE group ( Figure 4 d). At the genus level, there were no significant differences in the abundances of Lactobacillus, Streptococcus, Achromobacter, Atopobium, Prevotella, or Bifidobacterium between the two groups (p > 0.05), but the abundance of Gardnerella was significantly higher in the CE group than in the N_CE group (p < 0.05) ( Figure 4 e - g).

[0053] Through metagenomic sequencing, the study found that the abundances of Lactobacillus crispatus, Bifidobacterium dentium, and Lactobacillus inertus were significantly lower in the CE group than in the N_CE group. In contrast, the abundance of Gardnerella was significantly higher in the CE group than in the N_CE group ( Figure 4 h - j). These results suggest that Gardnerella may induce CE, which may be a major maternal factor leading to preterm birth in pregnant women. In addition, Lactobacilli are considered functional probiotics that can inhibit the growth of Gardnerella.

[0054] KEGG analysis was used to identify the biological functions of each bacterial species. Figure 5a, e), analysis revealed differences between metabolisms, genetic information processing, environmental information processing, cellular processes, human diseases, and biological systems in elderly mothers with and without CE (N_CE). Enrichment of metabolism-related genes in all samples indicated that metabolism plays a key role in the vaginal microbiome. KEGG pathways related to "metabolic pathways", "biosynthesis of secondary metabolites", and "microbial metabolism in diverse environments" were more prevalent in both groups. Additionally, "galactose metabolism", which is involved in carbohydrate metabolism, was more enriched in the vaginal microbiome of elderly mothers in the N_CE group than in the CE group ( Figure 5 b, f). Enzymes related to the galactose metabolism (ko00052) pathway, including 2.7.1.11, 2.7.1.144, 2.7.1.2, 2.7.1.200, 2.7.1.207, 2.7.1.6, 2.7.7.12, 2.7.7.9, 3.2.1.10, 3.2.1.20, 3.2.1.22, 3.2.1.23, 3.2.1.26, 3.2.1.85, 4.1.2.40, 4.2.1.6, 5.1.3.2, 5.1.3.3, and 5.3.1.26. Among them, key enzymes (2.7.1.200, 3.2.1.20, 3.2.1.23, and 5.1.33) involved in the classical Leloir pathway of galactose metabolism and gluconeogenesis pathway were significantly enriched in the vaginal microbiome of N_CE individuals compared to CE samples ( Figure 5 c, d, g, h).

[0055] This study aimed to evaluate the effect of CE on the enzymes in the vaginal microbiome of elderly mothers involved in carbohydrate metabolism. Search for gene families in the CAZy database ( Figure 6 ). As shown in Figure 6 a, at the CAZY classification level, the related gene counts of GHs (378) and GTs (205) were enriched in all samples, followed by carbohydrate esterases CEs (105), auxiliary activities (AAs; 24), and carbohydrate-binding modules (CBMs; 18). Figure 6b and c show the family level. The abundances of GT8, CE7, AA3, GT101, GH2, GT32, CE3, AA4, and GH13_29 were higher in the N_CE samples than in the CE samples (p < 0.05). In contrast, the abundances of GT2_Glycos_transf_2, GH13_20, GT28, GH13_32, and GH20 were significantly lower in the N_CE samples than in the CE samples (p < 0.05). To investigate the effect of glycoside hydrolases on the galactose metabolic pathway, we analyzed the levels of GH109, GH2, GH42, and GH13_29. The results showed that these enzymes were significantly more abundant in the N_CE samples than in the CE samples (p < 0.05). The GH2 gene is involved in the galactose metabolic pathway and was significantly upregulated in the N_CE vaginal microbiome compared with the CE samples (p < 0.05)( Figure 6 d-f).

[0056] Example 4 Metabolome sequencing analysis of vaginal secretions

[0057] 4.1 Sequencing of vaginal metabolome on the machine

[0058] To extract metabolites, vaginal swabs were immersed in physiological saline and mixed evenly using a vortex mixer. Then the mixture was centrifuged, and the supernatant was collected. The supernatant (100 μL) was suspended in a solvent composed of methanol and acetonitrile in a 2:1 ratio (v:v). The mixture was vortexed for 1 minute and stored at -20 °C for 2 hours. Finally, the mixture was centrifuged at 10,000 rpm for 20 minutes at 4 °C. The remaining liquid after centrifugation was collected, concentrated in a freeze vacuum, and 150 μL of a composite solution (methanol:H2O = 1:1, v:v) was added for analysis. The mixture was vortexed for 1 minute and centrifuged at 10,000 rpm for 30 minutes at 4 °C. The obtained supernatant was collected and placed in a sample vial for liquid chromatography-mass spectrometry (LC-MS / MS) analysis. The samples were analyzed and processed in both positive and negative ion modes. The chromatographic column used was a Thermo scientific TMAccucore TM C18 Column (100×2.1 mm, 2.6 μm), with the column temperature set at 40 °C; the injection volume was 2 μL; gradient elution: time: 0, 2, 10, 15, 18, 20, 25 min; mobile phase A (%) : 95, 95, 60, 40, 10, 95, 95; mobile phase B (%) : 5, 5, 40, 60, 90, 5, 5; the flow rate was 0.3 mL / min. The mobile phase composition was as follows: positive ion mode: 0.1% formic acid aqueous solution and acetonitrile; negative ion mode: 5 mmol / L ammonium acetate aqueous solution and acetonitrile. Mass spectrometry conditions: electrospray ionization (ESI) parameters: capillary temperature (Capillary Temp): 300 °C. Auxiliary gas heater temperature (Aux Gas Heater Temp): 350 °C. Sheath gas flow rate (Sheath Gas Flow Rate): 45 Arb. Auxiliary gas flow rate (Aux Gas Flow Rate): 10 Arb. Spray voltage (Spray Voltage): 3 kV. Scanning mode: full scan range (Full MS Scan Range): 100 - 800 m / z. Resolution: 120,000. Data-dependent secondary scan (DD-MS 2) resolution: 30,000. Collision energy (Collision Energy): 40. 10 μL of the supernatant of each sample was mixed with the QC sample to evaluate the repeatability and stability of the LC-MS analysis process.

[0059] 4.2 Metabolome data processing and analysis

[0060] The raw data collected by LC-MS / MS was processed using CompoundDiscoverer 3.1 (Thermo Fisher Scientific, USA). The processing included peak extraction, retention time correction within and between groups, adjacent ion merging, missing value filling, background peak marking, and metabolite identification. The molecular weight, retention time, peak area, and identification results of the compounds were determined. Metabolites were identified by combining several databases, including the BGI library, mzCloud, and ChemSpider (HMDB, KEGG, and LipidMaps).

[0061] To investigate the association between the altered vaginal microbiome in CE patients and metabolites in older mothers, we performed untargeted metabolomic analysis on vaginal secretion samples from the CE group and the N_CE group. The OPLS-DA plot showed significant differences in vaginal metabolites between the CE group and the N_CE group ( Figure 7 a, b), indicating that there were significant differences in the vaginal microbiome metabolites between CE patients and the N_CE group. In this study, a volcano plot was used to identify 75 potential biomarkers for differentiating the CE group and the N_CE group. The selection criteria were an adjusted p-value less than 0.05 and |log2(FC)| > 1. Compared with the N_CE group, 37 metabolites were upregulated and 38 metabolites were downregulated in the CE group ( Figure 7 c-f). There were significant differences in the concentrations of lactose and D-galactose in vaginal secretions between CE and N_CE ( Figure 7 g-h).

[0062] Metabolites were classified according to their functional metabolic pathways, and enrichment analysis was performed using metabolic pathways. It was found that the main pathways affected in the CE group in the anion mode included histidine, ether lipid, galactose, arachidonic acid, and purine metabolism ( Figure 7 i). Several pathways affected in the CE group were revealed in the cation mode, including arginine biosynthesis, primary bile acid biosynthesis, galactose metabolism, and arginine and proline metabolism ( Figure 7 j).

[0063] To investigate whether the changing metabolite abundances were correlated with the abundances of the altered vaginal microbiota, Spearman correlation analysis was used to determine the relationship between the abundance differences of 23 microorganisms and 29 metabolites between the CE and N_CE groups ( Figure 8a). There is a positive correlation between CE-enriched D-galactose and Gardnerella species such as G. vaginalis and G. piotii. In contrast, D-galactose is negatively correlated with Lactobacillus species such as L. crispatus, L. jensenii, L. psittaci, L. acidophilus, L. kefiranofaciens, and L. helveticus. In addition, certain organic acids, including citric acid, succinic acid, propionic acid, and L-glutamic acid, and certain amino acids, such as DL-tryptophan, L-valine, and phenylalanine, are positively correlated with Gardnerella species, including G. vaginalis, G. piotii, G. leopoldii, and G. swidsinskii. The levels of xylitol and benzoic acid are negatively correlated with Gardnerella species.

[0064] In addition, this study also evaluated the relationships among clinical indicators, biochemical indicators, vaginal microbiota, and metabolites. The results showed a positive correlation between G. vaginalis, D-galactose concentration, and parity ( Figure 8 b, e). In addition, L. crispatus enriched in N_CE samples was negatively correlated with the IL-8 level ( Figure 8 c), while CE-enriched D-galactose was negatively correlated with the levels of IL-10 and GPR30 ( Figure 8 f). In addition, we observed a co-occurrence network between vaginal microbiota and pregnancy-related complications. Specifically, we found a negative correlation between L. crispatus and G. vaginalis, while G. vaginalis and D-galactose were positively correlated with the proportion of columnar epithelial ectopia ( Figure 8 d, g).

[0065] Collectively, these results suggest that the altered vaginal microbiota, especially the decreased abundance of Lactobacillus species and the increased abundance of Gardnerella species in CE patients, may be associated with the increased D-galactose concentration and the induction of adverse pregnancy outcomes in older mothers.

[0066] It is easy for those skilled in the art to understand that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A biomarker for preterm birth in elderly pregnant women, characterized in that, The biomarker is Gardnerella vaginalis, Lactobacillus crispatus, lactose, and / or D-galactose.

2. Use of the biomarker according to claim 1 in the preparation of a screening and / or diagnostic product for preterm birth in elderly primiparas.

3. Use of a reagent for detecting the biomarker according to claim 1 in the preparation of a screening and / or diagnostic product for preterm birth in elderly primiparas.

4. The application according to claim 3, characterized in that The product is a reagent or a kit.

5. According to the use described in claim 4, the reagent is a reagent for metagenomic sequencing and a reagent for metabolomics analysis.

6. The application according to claim 3, characterized in that The use is to evaluate the risk of preterm birth in elderly primiparas by detecting the abundance or concentration of Gardnerella vaginalis, Lactobacillus crispatus, lactose, and D-galactose in samples of elderly primiparas.

7. The application according to claim 6, characterized in that, The relative abundance of Gardnerella vaginalis increases in samples of elderly preterm primiparas, and the relative abundance of Lactobacillus crispatus decreases in samples of elderly preterm primiparas.

8. The application according to claim 6, characterized in that The concentrations of lactose and D-galactose increase in samples of elderly preterm primiparas.

9. The application according to claim 7 or 8, characterized in that The primipara is a primipara with cervical ectropion.

10. The application according to claim 6, characterized in that The sample is vaginal secretion.

Images