Application of female uterine cavity flora as a marker in the diagnosis of endometriosis

Abstract

The present application relates to the technical field of molecular diagnosis, and specifically relates to application of female uterine cavity flora as a marker in endometriosis diagnosis. The present application collects uterine cavity flora of patients, extracts genomic DNA, performs bacterial 16s-rRNA sequencing, uses KEGG as a reference database for function prediction, determines that abnormal abundance of uterine cavity flora dominant bacteria has significant correlation with dysmenorrhea and high CA125 value of endometriosis patients, clarifies the correlation between abnormal uterine cavity flora and endometriosis, and provides a new method for evaluating the risk of endometriosis by detecting uterine cavity flora atlas.

Description

[0001] Technical Field: This invention relates to the field of molecular diagnostic technology, specifically to the application of uterine flora as a biomarker in the diagnosis and assessment of endometriosis.

[0002] Background: Endometriosis is a complex disease of the female reproductive system, characterized by the growth of endometrial-like tissue on tissues and organs outside the uterine cavity. Patients often experience infertility and progressively worsening dysmenorrhea, severely impacting women's physical and mental health. The incidence rate is increasing year by year, placing a heavy burden on families and society. Early diagnosis is difficult, it is hard to cure, and recurrence is a major challenge in its treatment. There is a lack of diagnostic and treatment methods targeting the underlying causes of endometriosis. Current imaging techniques have low detection rates for small lesions, and may even lead to missed diagnoses and misdiagnoses. Significant breakthroughs in the diagnosis and treatment of endometriosis have not yet been achieved. Therefore, there is an urgent clinical need to find a biomarker for early diagnosis of endometriosis through real-time detection, capable of dynamically monitoring disease progression and providing prognostic assessment. In recent years, significant progress has been made in the application of microbiota in the medical field. Domestic and international research on microbiota has focused on gut microbiota, while research on intrauterine microbiota is scarce. In fact, intrauterine microbiota is directly located in the endometrium and uterine cavity, and is more closely related to the spatial environment of the female reproductive tract. Recent studies have found that the female reproductive tract harbors a colonizing microbiota in a non-disease-prone state, and abnormal changes in this microbiota are closely related to gynecological diseases such as endometritis and embryo implantation failure. The intrauterine microbiota may directly affect the endometrium through metabolism, inflammatory environment, and immune responses, altering endometrial proliferation and migration phenotypes, thereby inducing endometrial dysfunction and leading to disease. Therefore, abnormal intrauterine microbiota may play a significant role in the occurrence, development, diagnosis, and treatment of endometriosis.

[0003] Since the Second Human Genome Project was proposed in 2001, numerous studies have confirmed the correlation between the composition of the human microbiome and a large number of chronic diseases, including digestive, metabolic, reproductive, and nervous system diseases. The project's inclusion of research on intrauterine bacterialomics and the application of high-throughput DNA sequencing technology and big data bioinformatics functional prediction has provided favorable conditions for studying the impact of intrauterine flora on diseases. In 2020, some studies collected vaginal fluid, situ endometrium, and endometriotic lesions, extracted DNA, and analyzed the samples, identifying the microbiome through high-throughput DNA sequencing of 16S rRNA marker genes. In 2021, sequencing of the V4 region of the 16S rRNA gene in the endometrial microbiome of endometriosis patients on the Miseq platform concluded that it exhibits high bacterial diversity. Therefore, developing highly sensitive and specific biological diagnostic biomarkers suitable for endometriosis, using intrauterine flora as a starting point, is crucial to meeting the needs of clinical diagnosis and development of endometriosis.

[0004] Summary of the Invention: The purpose of this invention is to overcome the shortcomings of the prior art and provide an application of uterine flora as a biomarker in the diagnosis and assessment of endometriosis. By clarifying the association between abnormal uterine flora and endometriosis, this invention provides a biomarker that can be used to assess the risk of endometriosis.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The present invention provides the application of a reagent for detecting the expression level of endometrial bacteria in biological samples in the preparation of endometriosis diagnostic and assessment products.

[0006] This invention collects uterine flora from patients, extracts genomic DNA, and performs bacterial 16S-rRNA sequencing. After raw data splicing and filtering, visualization operations are performed, and bacterialomics-related data are mined. KEGG is used as a reference database for functional prediction, and the diversity and abundance of uterine flora are analyzed. Compared with the uterine flora of non-endometriosis patients, it is found that abnormal abundance of dominant bacteria in the uterine flora is significantly correlated with dysmenorrhea and high CA125 values ​​in patients with endometriosis. This provides a new method for assessing the risk of endometriosis by detecting uterine flora profiles. Therefore, uterine flora can serve as a biomarker for assessing the diagnosis and prognosis of patients with endometriosis. In a specific embodiment, the uterine flora genes are derived from uterine swabs.

[0007] As a preferred embodiment of the application described in this invention, the product includes a reagent kit or a chip, but is not limited to these and also includes products commonly found in the art.

[0008] As a preferred embodiment of the application described in this invention, abnormal abundance of dominant bacteria in the uterine cavity is significantly correlated with dysmenorrhea and high values ​​of CA125 and CA199 in patients with endometriosis.

[0009] In a preferred embodiment of the application described in this invention, the reagents include those for collecting intrauterine bacteria, extracting total DNA using the CTAB method, quantitative PCR detection, and high-throughput sequencing for intrauterine bacteria detection. In a preferred embodiment of the application described in this application, the biological sample includes intrauterine bacterial swabs, specifically derived from the uterine cavity.

[0010] The present invention also provides a method for screening reagents for the diagnosis and assessment of endometriosis in vitro. The method uses candidate reagents to detect the expression level of uterine bacteria in biological samples. If the detection can be achieved, the candidate reagents can be used as diagnostic and assessment reagents for endometriosis.

[0011] The present invention also provides a diagnostic assessment kit for endometriosis, the kit comprising reagents for detecting the expression level of endometrial bacteria in biological samples.

[0012] Experimental results and analysis showed that: 1. In both the endometriosis EM group and the non-endometriosis control HE group, Lactobacillus and Firmicutes were the dominant bacteria, with a higher relative abundance of these genera / phyla in the EM group. Endometriosis patients exhibited decreased intrauterine flora richness and diversity, with significant differences in abundance between species and higher species richness within each group. Random forest analysis identified the most important marker species for inter-group differences, with the top 5 genera being Streptococcus, Lactobacillus, Gardnerella, Klebsiella, and Haemophilus.

[0013] 2. In patients with endometriosis, CA125 levels, CA199 levels, dysmenorrhea symptoms, and gut microbiota were significantly correlated.

[0014] As a preferred embodiment of the endometriosis diagnostic and assessment kit of the present invention, the reagents include reagents for collecting uterine bacteria, extracting total DNA by CTAB method, quantitative PCR detection, and high-throughput sequencing for detecting uterine bacteria.

[0015] In a preferred embodiment of the endometriosis diagnostic and assessment kit of the present invention, the biological sample includes uterine cavity bacteria, specifically derived from uterine cavity bacterial swabs.

[0016] In some implementations, the methods used in this application for detecting gene expression are known in the art and are not intended to limit this application. For those skilled in the art, there may be various modifications and variations to the methods used in this application for detecting gene expression.

[0017] Compared with existing technologies, this application provides the application of intrauterine flora as a biomarker in the diagnosis and assessment of endometriosis. Intrauterine flora may affect the occurrence and development of endometriosis and is expected to be used as a biomarker to assess the risk of endometriosis in patients. Attached Figure Description

[0018] Figure 1 A bar chart showing the abundance of representative uterine cavity samples at the major genus level (top 10).

[0019] Figure 2 A bar chart showing the relative abundance of intrauterine bacteria in the EM and HE groups (top 10 by genus).

[0020] Figure 3 The top 5 are the abundance bars at the main hilum level for representative uterine cavity samples.

[0021] Figure 4 The bar chart shows the relative abundance of intrauterine bacteria in the EM and HE groups (top 5 by phylum).

[0022] Figure 5 A hierarchical tree diagram of the uterine flora, categorized by phylum, class, order, family, genus, and species.

[0023] Figure 6 The diversity of ALPHA in the intrauterine flora of the EM and HE groups.

[0024] Figure 7 Dilution curve for evaluating the richness of intrauterine flora.

[0025] Figure 8 This is a curve showing the abundance of intrauterine flora.

[0026] Figure 9 A random forest analysis diagram of representative samples (classified by phylum).

[0027] Detailed Description of Embodiments: To better illustrate the purpose, technical solution, and advantages of this application, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0028] In the following embodiments, unless otherwise specified, the experimental methods used are conventional methods, and the materials and reagents used are commercially available unless otherwise specified, and the raw materials used in each parallel experiment are the same.

[0029] The criteria for recruiting patients with endometriosis in this application include:

[0030] Inclusion criteria:

[0031] (1) Patients aged ≥18 years and ≤50 years, and who are premenopausal women;

[0032] (2) The menstrual cycle is normal (28±7 days), and the sampling was not taken during menstruation, pregnancy, or lactation.

[0033] (3) No oral contraceptives, contraceptive injections, subdermal implants or intrauterine devices have been used within at least 3 months prior to sampling;

[0034] (4) No sexual activity for at least 3 days prior to sampling;

[0035] (5) No antibiotics or probiotics, hormone replacement therapy, or GnRH-a drugs have been used within at least 8 weeks prior to sampling;

[0036] (6) No vaginal irrigation, medication application, or cervical treatment was performed within 7 days prior to sampling;

[0037] Exclusion criteria

[0038] (1) Patients aged <18 years or >50 years;

[0039] (2) The patient is menstruating, pregnant, or breastfeeding;

[0040] (3) Postmenopausal status;

[0041] (4) The control group should exclude those with clinical manifestations of endometriosis, such as dysmenorrhea, pelvic pain, dyspareunia and / or infertility (having 12 months of regular unprotected intercourse but failing to conceive).

[0042] (5) Had taken antibiotics or probiotics within 8 weeks prior to sampling;

[0043] (6) Patients with a history of inflammatory bowel disease, functional bowel disease, gastrointestinal tumors or surgery, acute or severe gastrointestinal symptoms requiring drug treatment, gastrointestinal infection, bacterial vaginosis, cervicitis, pelvic inflammatory disease, urinary tract infection, thyroid disease, diabetes, any acute inflammation, any malignant tumor, fever of any cause, infectious disease, or autoimmune disease.

[0044] (7) Abnormal TCT and / or HPV results in the past three years;

[0045] (8) Body Mass Index (BMI) ≥ 30 kg / m2

[0046] Experimental group: Endometriosis patients in stages I-IV who are scheduled for surgical treatment;

[0047] Control group: Patients who do not have endometriosis but have other benign diseases such as uterine fibroids or ovarian tumors and require surgical treatment, and outpatients (without a history of endometriosis).

[0048] Example 1: Collection of intrauterine bacterial samples

[0049] All specimens were collected prior to treatment. Disposable nasal swabs (Bikman) were used to collect uterine cavity samples, avoiding contact with the vagina and cervix. If there was discharge at the external cervical os, it was first wiped with a dry cotton ball. The swab was inserted deep into the uterine cavity, rotated 5-10 times, and held for approximately 10 seconds. Two swabs were collected from each patient. After collection, the samples were placed in sterile cryovials and quickly frozen in liquid nitrogen for at least 15 minutes. They were then transferred to a -80°C freezer for storage as soon as possible. The patient's name, age, menstrual history, reproductive history, smoking and alcohol history, clinical symptoms, size of endometriosis lesions, family history of endometriosis, and chronic comorbidities (such as hypertension, heart disease, etc.) were recorded.

[0050] Example 2: Sample Extraction and Detection

[0051] (1) Total DNA extraction by CTAB method: Kit: omega M5635-02

[0052] 1. Place the swab in the lysis buffer and add 500 μL of 2% CTAB (hexadecyltrimethylammonium bromide);

[0053] 1. Add a small amount of glass beads and homogenize at 40 Hz / 270 s; 2. Add 50 μL of lysozyme (50 mg / mL) and 5 μL of RNase A, incubate at 37°C for 30 min with 225 cycles; 3. Add 20 μL of proteinase K (20 mg / mL) and 25 μL of 10% SDS, vortex to mix, and incubate at 56°C for 20 min; 4. Add an equal volume of phenol:chloroform (300 μL), invert to mix, and centrifuge at 12000 rpm for 5 min to ensure complete denaturation and precipitation of the protein; 5. Take 450 μL of the supernatant and add 1 μL of carrier protein. 6. Mix RNA (1ug / ul) thoroughly; 7. Alternatively: Mix with an equal volume of chloroform, invert and mix, centrifuge at 12000 rpm for 5 min, and collect the supernatant; 8. Add 250ul of binding buffer, vortex and mix, and incubate at -20℃ for 5 min; 9. Repeat adsorption and rinsing, and discard the waste liquid; 10. Open the cap and let stand for 1 min, then add 50ul of DNase-free water preheated at 65℃; 11. Let stand at room temperature for 2 min, centrifuge at 12000 rpm for 2 min, and collect the DNA solution; 12. Measure the absorbance of the DNA solution.

[0054] (2) Initial PCR amplification of the target fragment:

[0055] Primer sequences for the V3-V4 variable region of the 16S rRNA gene:

[0056] 338F: ACTCCTACGGGAGGCAGCA

[0057] 806R: GGACTACHVGGGTWTCTAAT

[0058] Amplification system 25ul:

[0059] 5x buffer 5μL

[0060] dNTP (2.5mM) 2μL

[0061] Forwardprimer (10 μM) 1 μL

[0062] Reverseprimer (10µM) 1μL

[0063] DNA Template 1μL ddH2O 14.75μL

[0064] Fast pfu DNA Polymerase 0.25μL

[0065] Amplification conditions: 25 cycles

[0066] (3) Second round of expansion:

[0067] The PCR reaction, using the amplification product from the initial PCR as a template, aims to further extend the target fragment and obtain a complete adapter-ligated fragment. The number of cycles is set to 8-10. After PCR, the PCR products are subjected to agarose gel electrophoresis, and the DNA is purified.

[0068] (4) DNA purification and recovery:

[0069] 1. First, add sterile water to bring the system to 50 μl; 2. Add 30 μl of 0.6 times magnetic bead washing buffer, shake well to suspend, place on a magnetic rack and incubate at room temperature for magnetic bead adsorption. When the solution becomes clear, aspirate the supernatant; 3. Add 200 μl of 80% ethanol, which must be added while suspended in the air, ensuring the pipette tip does not touch the magnetic beads. Wait 30 seconds and discard the supernatant; 4. Add another 200 μl of 80% ethanol, wait 30 seconds, discard the supernatant, and remove as much alcohol as possible during the alcohol removal process; 5. Let stand at room temperature for 5 minutes to evaporate the alcohol; 6. Add 25 μl of Elution Buffer to elute, shake to mix, and incubate at room temperature for 5 minutes; 7. Store the supernatant from the PCR tube in a centrifuge tube after standing.

[0070] Example 3: High-throughput sequencing performed on the instrument

[0071] 1. After recovery, the library is subjected to quality control. Based on the specificity of the polymorphic region of the bacterial 16S rRNA sequence, it is used as a marker for comparison and analysis with the database for species identification. Among them, V3-V4 has the most moderate number of bases compared with other polymorphic regions, and is the best choice at present.

[0072] 2. DADA2 Sequence Denoising: Using the Illumina MiSeq sequencer, the DADA2 method (Callahan et al., 2016) was primarily employed to generate ASV (amplicon sequence variant) sequences. ASVs provide higher resolution microbial resolution information compared to traditional OTUs.

[0073] 3. Vsearch Clustering: Set the absolute abundance to 10, discard sequences with unmatched primers, cluster high-quality sequences at a 97% similarity level, and output representative sequences and OTUs tables respectively.

[0074] Example 4: Data Analysis

[0075] 1. Cluster analysis of raw data: The process of species taxonomy annotation essentially involves comparison with a reference sequence database to improve the resolution of species annotation. Annotation is typically performed at seven levels: kingdom, phylum, class, order, family, genus, and species, to mark the differences between species and their ancestral, related, and dissimilar species. However, in actual analysis, not all characteristic sequences can obtain species and genus-level annotation information. This experiment uses the Greengenes and Silva databases by default.

[0076] 2. Constructing a phylogenetic tree: Here, the FastTree method from the maximum likelihood approach is used by default to construct the tree to obtain the genetic distance or phylogenetic relationship between sequences. Based on the statistical data after clustering the taxonomic units, statistical analysis of the number of taxonomic units and taxonomic composition analysis are performed.

[0077] 3. Diversity analysis: including Alpha diversity and Beta diversity. This experiment was divided into an experimental group and a control group: Alpha diversity represents habitat diversity; Beta diversity refers to habitat diversity analysis.

[0078] 4. Differential analysis: P-value analysis was used to determine whether there were significant differences in the intrauterine microbial community (P < 0.05) and to identify species with differences between groups.

[0079] Results: 1. Relative abundance of intrauterine microbiota in the two groups classified by genus / phylum: In both the endometriosis group (EM group) and the non-endometriosis control group (HE group), Lactobacillus and Firmicutes were predominant, with a higher relative abundance of these genera / phyla in the EM group. Microbial diversity was lower in the EM group than in the HE group, indicating a certain difference between the two groups. Figure 1-4 (Tables 1 and 2)

[0080] Table 1. Relative abundance of intrauterine microbiota in the two groups of cases classified by genus.

[0081]

[0082]

[0083] Table 2 Abundance of uterine cavity samples at the major hilum level (top 5)

[0084]

[0085] 2. In both the EM and HE groups, the intrauterine flora were relatively concentrated in bacilli and gamma-proteobacteria, with the abundance of these two flora being higher in the EM group compared to the HE group. Figure 5 )

[0086] 3. The Chao1 and Observed Specie indices (EM) were both lower in the Chao1 group than in the HE group, indicating that the richness of the uterine flora in patients with endometriosis may be reduced. The Faith's PD, Shannon, and Simpson indices (EM) were also lower in the Chao1 group than in the HE group, indicating that the diversity of the uterine flora in patients with endometriosis may be reduced. The Pielou's evenness index...

[0087] The lower abundance in the EM group indicates significant differences in species abundance among different species within the EM group. Figure 6 )

[0088] 4. Evaluation of intrauterine flora richness - Dilution curve: Under the condition of extracting the same sequence, the number of ASVs in the HE group was higher than that in the EM group, indicating that the species richness in the HE group was higher. (e.g.) Figure 7 )

[0089] 5. Evaluation of intrauterine flora diversity – Rank-abundance curve: The curve width of the HE group was greater than that of the EM group, and the curve decline was also relatively smoother, indicating that the HE group had higher intrauterine flora richness and uniformity than the EM group, while the EM group had a significantly higher proportion of dominant flora. (e.g.) Figure 8 )

[0090] 6. Random forest analysis suggests that these top-ranked species are marker species for inter-group differences. For example, the top 5 species by phylum are: Proteobacteria, Firmicutes, Actinobacteria, Bacteroides, and Fusobacteria. Figure 9 )

[0091] 7. Analysis showed that in patients with endometriosis, age, height, weight, BMI, ovarian cyst size, and obstetric history had no significant effect on gut microbiota (P>0.05), while CA125 levels, CA199 levels, and dysmenorrhea symptoms were significantly correlated with gut microbiota (P<0.05). (Table 3)

[0092] Table 3. Univariate analysis of the relationship between relevant factors and lactobacillus

[0093]

[0094]

[0095] *P<0.05

[0096] Based on the research findings, this application suggests that abnormal intrauterine flora is one of the mechanisms underlying the development of endometriosis, and it holds promise as a biomarker for assessing the risk of endometriosis in patients. Application methods include, but are not limited to, developing active ingredients that regulate intrauterine flora for the treatment of endometriosis, or using its abundance to assist in assessing the risk status of endometriosis patients. Furthermore, based on the research findings, this application suggests that abnormal intrauterine flora may be associated with dysmenorrhea symptoms, high levels of CA125 and CSA199 in endometriosis patients, and it holds promise as a biomarker for the diagnosis of endometriosis. Such applications include, but are not limited to, providing an endometriosis diagnostic kit, which includes reagents for detecting the abundance of intrauterine flora in the sample.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit the scope of protection of this application. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the substance and scope of the technical solutions of this application.

Claims

1. Application of uterine flora detection reagents in the preparation of products for the diagnosis and prognosis assessment of endometriosis.

2. The application as described in claim 1, characterized in that, The products include reagent kits or chips.

3. The application as described in claim 1, characterized in that, The dominant bacteria in the uterine cavity are significantly correlated with dysmenorrhea symptoms and high levels of blood CA125 and CA199 in patients with endometriosis.

4. The application as described in claim 1, characterized in that, The reagents include those for collecting intrauterine bacteria, extracting total DNA using the CTAB method, quantitative PCR detection, and high-throughput sequencing for intrauterine bacteria detection.

5. The application as described in claim 1, characterized in that, The biological sample includes the uterine cavity flora.

6. The application as described in claim 1, characterized in that, The method includes the following steps: a) Collect and test uterine cavity bacterial samples using a disposable nasal swab; b) Based on the bacterial 16S rRNA sequence as a marker, species identification was performed by comparison with the database and high-throughput sequencing was conducted. Subjects with high abundance of dominant lactic acid bacteria in the uterine cavity were considered high-risk, while subjects with low abundance of dominant lactic acid bacteria in the uterine cavity were considered low-risk. The risk of disease in low-risk subjects was lower than that in high-risk subjects.

7. The application as described in claim 6, characterized in that, The expression threshold of the uterine flora is set according to the range of the uterine flora in the endometrium of normal individuals.

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