CN112458164A - High androgen polycystic ovarian syndrome endometrial receptivity biomarker, kit and judgment method - Google Patents

Abstract

The invention relates to a group of high androgen polycystic ovary syndrome endometrial receptivity biomarkers, a kit and a judgment method. The biomarker can provide a high-efficiency, rapid, strong-specificity and high-sensitivity detection and evaluation means for early detection and diagnosis, targeted intervention and embryo transplantation guidance of a high androgen polycystic ovarian syndrome infertility patient; the kit for detecting the endometrial receptivity of the hyperandrogenic polycystic ovarian syndrome contains the endometrial receptivity marker, and can provide an efficient, quick, high-specificity and high-sensitivity detection and evaluation means for early detection and diagnosis of patients suffering from infertility caused by the hyperandrogenic polycystic ovarian syndrome.

Description

High androgen polycystic ovarian syndrome endometrial receptivity biomarker, kit and judgment method

Technical Field

The invention relates to the technical field of biology, and particularly relates to a group of high androgen polycystic ovary syndrome endometrial receptivity biomarkers, a kit and a judgment method.

Background

Polycystic ovary syndrome (PCOS) is an endocrine disturbance syndrome with the coexistence of reproductive dysfunction and abnormal carbohydrate metabolism common to women in the reproductive age, and is a main cause of anovulatory infertility, while the abnormality of the endometrial state is another important factor causing the infertility and is one of the main causes of difficulty in the treatment of the PCOS infertility.

PCOS is acted by related factors such as environment and heredity, and excessive androgen is one of important characteristics; previous studies show that free testosterone in PCOS patients is increased, hyperandrogenism and obesity PCOS patients are emphasized in clinical presentation, and androgen has double regulation and control effects on follicular development, so that the growth of early follicles is promoted, and follicular development can be hindered by inducing atresia and apoptosis. Excessive androgen stimulation activates intracellular inflammatory factor signaling pathways, ultimately inducing chronic inflammation in PCOS patients. A few studies have also shown that androgens can exert an antioxidant effect and regulate the decidua of endometrial stromal cells. There is currently no clear understanding of how circulating androgens exert their inflammatory or anti-inflammatory effects and their effects on the endometrium. That is, although high androgen levels are an important feature of PCOS, the cause of the disease in PCOS patients with high androgen levels is not necessarily caused by high androgen levels, and needs to be further determined by other criteria.

The endometrium is the target organ for the action of the estrogen and the progestogen. Patients with PCOS have a defect in corpus luteum function due to prolonged anovulation or poor follicular development, resulting in the long-term abnormal stimulation of the endometrium by estrogen, lack of progestogen regulation, and the endometrium thus exhibiting different degrees of proliferative changes, even progression to endometrial cancer. Endometrial Receptivity (ER) refers to the receptivity of the endometrium to the embryo, i.e. the ability to allow the embryo to adhere to it until a specific stage of implantation is completed, with strict temporal and spatial constraints, typically only 6-10 days after ovulation, lasting less than 48 hours. The complicated endocrine and metabolic abnormality of the PCOS patient body can cause the decline of the endometrial receptivity, and the ovulation induction treatment further aggravates the abnormal development of the endometrium and the abnormal expression of the receptivity marker molecules, so that the embryo planting rate is reduced. At present, the key problem to be solved urgently for improving the success rate of pregnancy of patients with PCOS is to improve the tolerance of endometrium of patients with PCOS. Therefore, the search for the etiology of the uterus and endometrium has important clinical significance for the prevention and diagnosis and treatment of diseases.

While detection of regulatory factors affecting intimal tolerance is one of the major means for assessing the status of endometrium in PCOS patients, currently discovered regulatory factors affecting intimal tolerance mainly include sex hormones and their receptors, integrins, leukemia inhibitory factor, and homeobox gene HOXA10 and other genes and factors. Wherein, the integrin plays an important role in cell adhesion, the expression level of the integrin is periodically changed, and the peak value occurrence time is consistent with the planting window; leukemia inhibitory factor is a cell factor with multiple effects, can induce cell proliferation, differentiation, maintain cell survival and the like, plays an important role in embryo development and transplantation, and researches show that the expression of the leukemia inhibitory factor in uterine cavity flushing fluid of the infertile women is higher than that of pregnant women; homeobox genes participate in regulating the expression of genes and controlling organogenesis and cell differentiation; in addition, factors or proteins such as insulin-like growth factor binding protein, epidermal growth factor, matrix metalloproteinase and the like are all involved in regulating and controlling the tolerance of the inner membrane. Although some relevant markers affecting intimal tolerance were successively found and even applied to clinical exploration, detection with a single tolerance marker has limited accuracy and low specificity. Some simple combinations of related factors of endometrial receptivity are also studied to solve the clinical problems of patients with partial damaged endometrial implantation states to a certain extent, but due to individualized differences in disease development, particularly PCOS patients have high heterogeneity, the specificity and sensitivity of single index detection are limited, and many unknown functional molecules are still needed to be further mined and developed.

Transcriptomics is a subject for studying gene transcription conditions and transcription regulation and control rules in cells on the whole level, and is an important means for studying cell phenotype and function. Unlike the genome, temporal and spatial limitations are included in the definition of transcriptomes. Thus, transcriptome profiling can provide information on the expression of certain genes under specific conditions and, based thereon, infer the function of the corresponding unknown gene, reveal the mechanism of action of the particular regulatory gene. By using the molecular label based on the gene expression profile, the phenotype attribution of the cell can be distinguished, and the molecular label can be used for diagnosing diseases. The transcriptomics research technology can be applied to typing and diagnosis of clinical diseases, particularly primary malignant tumors, and can describe the survival time of a patient, the response to a medicament and the like in detail through establishing a transcriptome differential expression profile; meanwhile, transcriptomics technology is often used for screening differentially expressed genes among different samples, and the differences among the samples are revealed by combining bioinformatics analysis means such as differential gene GO functional analysis and KEGG Pathway analysis, so as to analyze the molecular mechanisms causing the differences among the samples. Although the research on molecules influencing the membrane tolerance of PCOS is reported previously, the molecules belong to a single marker, the detection flux is low, and the accuracy is limited. And the PCOS intimal tolerance is judged by adopting a plurality of biomarkers, the state of the endometrium in the planting window can be comprehensively evaluated from a plurality of aspects such as cell adhesion, energy metabolism, inflammatory reaction and the like, and the endometrial tolerance is judged according to the state. If abnormal expression of the cell adhesion-related biomarkers in the multiple biomarkers of the patient is detected, the abnormal expression indicates that the cell adhesion function of the endometrium of the patient is possibly abnormal, and the endometrial receptivity of the patient is further influenced. Thus, multiple biomarkers are used to assess endometrial receptivity with greater accuracy and precision.

Disclosure of Invention

The invention aims to provide a group of high androgen PCOS endometrial receptivity biomarkers, a kit and a method for judging endometrial receptivity.

The invention provides a group of high androgen PCOS endometrium receptivity biomarkers, and the biomarkers have significant difference in the expression level of endometrium of PCOS infertile people with different androgen levels.

Further, the biomarker has an absolute value of mean expression of the endometrium at an androgen level of 0.481ng/mL or less in a human with PCOS infertility population that is at least twice as great as the absolute value of mean expression of the endometrium at an androgen level of 0.481 ng/mL.

Further, at least 4 up-regulated genes and/or down-regulated genes are included; the average expression level of the up-regulated gene in the endometrium of the human body with the androgen level less than or equal to 0.481ng/mL in the PCOS infertile population is larger than the average expression level of the endometrium of the human body with the androgen level more than 0.481 ng/mL.

The average expression level of the down-regulated gene in the endometrium of a human body with the androgen level less than or equal to 0.481ng/mL in the PCOS infertile population is less than the average expression level of the endometrium with the androgen level more than 0.481 ng/mL;

the up-regulated genes include:

u1, MAGED, gene ID ENSG00000179222, Gene Note MAGE family member D1, Chinese name MAGE family member D1;

u2, ITGA4, gene ID ENSG00000115232, gene annotation for integrin subbunit alpha 4, Chinese name integrin subunit α 4;

u3, MUC7, gene ID ENSG00000171195, gene note mucin 7, chinese name mucin 7;

u4, KRT12, gene ID ENSG00000187242, gene annotation as keratin 12, chinese name keratin 12;

u5, KRT37, gene ID ENSG00000108417, gene annotation keratin 37, chinese name keratin 37;

u6, FGL1, gene ID ENSG00000104760, gene annotation fibrinogen like 1, chinese name fibrinogen-like 1;

u7, FSBP, gene ID ENSG00000265817, gene annotation for fibrinogen silencer binding protein, Chinese name fibrinogen silencer binding protein;

u8, AK4P3, gene ID ENSG00000233381, gene annotation 4 adenylate kinase 3 pseudogene, Chinese name adenylate kinase 4pseudogene 3;

u9, ANXA2P3, gene ID ENSG00000216740, gene annotation annexin A2pseudogene 3, Chinese name annexin A2pseudogene 3.

The down-regulated genes include, but are not limited to,

d1, ITGB3, gene ID ENSG00000259207, gene annotation for integrin subbentbeta 3, chinese name integrin subunit beta 3;

d2, ITGA2, gene ID ENSG00000164171, gene annotation for integrin subbunit alpha 2, Chinese name integrin subunit alpha 2;

d3, MEGF6, gene ID ENSG00000162591, gene annotation as multiple EGF like domains 6, chinese name multiple EGF-like domain 6;

d4, MUC16, gene ID ENSG00000181143, gene note mucin 16, chinese name mucin 16;

d5, PCDH17, gene ID ENSG00000118946, Gene Note protocadherin 17, Chinese name tropocadherin 17;

d6, PCDHA10, gene ID ENSG00000250120, gene annotation protocadherin alpha 10, Chinese name procalcitonin alpha 10;

d7, DCHS2, gene ID ENSG00000197410, Gene annotation dachsous cadherin-related 2, Chinese name tropocadherin 23;

d8, KRT17, gene ID ENSG00000128422, gene note keratin 17, chinese name keratin 17;

d9, KRT85, gene ID ENSG00000135443, gene annotation as keratin 85, chinese name keratin 85;

d10, ANXA10, gene ID ENSG00000109511, gene annotation annexin a10, chinese name annexin a 10;

d11, IL22RA1, gene ID ENSG00000142677, gene annotation of interleukin 22receptor subunit alpha 1, Chinese name interleukin 22receptor subunit alpha 1;

d12, IL6ST, gene ID ENSG00000134352, Gene annotation Interleukin 6signal transducer, Chinese name interleukin 6signal transducer.

Furthermore, the biomarker screening method comprises the steps of measuring and analyzing the average expression level of all biomarker genes in the endometrium of the PCOS infertile people with different androgen levels by an RNA-Seq method, screening the biomarkers with large absolute difference of the average expression level in the endometrium of the PCOS infertile people with different androgen levels according to the analysis result, and screening the biomarkers related to the endometrial receptivity from the biomarkers with large absolute difference of the average expression level.

Further, the screening method comprises the following steps:

s1, collecting a sample, wherein the sample is endometrial tissue of a PCOS sterile patient.

S2, grouping the samples, wherein the samples collected by the human body with the androgen level less than or equal to 0.481ng/mL are classified into normal group, and the samples collected by the human body with the androgen level more than 0.481ng/mL are classified into hyper group.

S3, respectively carrying out RNA-Seq determination and analysis on the genes of all the biomarkers in the samples of the normal group and the hyper group, wherein the expression amount of each biomarker is different in a multiple of two groups of samples.

S4, screening a group of biomarkers related to endometrial receptivity from the biomarkers with the mean expression level absolute value difference multiple more than or equal to 2 times according to the characteristics of each biomarker.

Further, the kit contains the group of high androgen PCOS endometrial receptivity biomarkers.

Further, the kit contains 4-5 representative biomarkers, and the representative biomarkers are screened in a manner that each biomarker in the group of PCOS endometrial markers is weighted according to the mean fold difference absolute value of the expression of the biomarker in people with different androgen levels and the specific biological function of the biomarker, wherein the biomarker is represented by the biomarker with high weight.

The invention provides a method for judging endometrial receptivity of people suffering from infertility caused by high androgen PCOS, which is characterized in that the method is used for judging the endometrial receptivity of the high androgen PCOS by using the kit for detecting the endometrial receptivity caused by the high androgen PCOS, and comprises the following steps:

1) detecting the average expression level of the biomarker in the kit of the endometrium of a normal pregnant female with a certain sample amount of high androgen level, and calculating to obtain the reference value range of the normal average expression level of the biomarker in the kit in the endometrium of the androgen level range;

2) detecting the expression level of the corresponding biomarker in the endometrium of the patient with high androgen PCOS by using the kit;

3) comparing the expression level of the biomarker obtained in the step 2) with the corresponding reference value range in the step 1), wherein the comparison mode is that the expression level of the biomarker measured by a patient with high androgen level is compared with the reference value range of normal expression level;

when the expression level of the biomarker is within the reference value range, judging that the expression level of the tolerance-related gene regulated by androgen is normal in the endometrium of the patient;

and when the expression level of the biomarker is out of the reference value range, judging that the expression level of the tolerance related gene regulated by androgen is abnormal in the endometrium of the patient.

Drawings

FIG. 1 is a technical roadmap for the present invention;

FIG. 2 is a heat map of the PCOS endometrium differential expression genes of the normal and hyper groups of the present invention;

FIG. 3 is a heat map of differentially expressed genes for a panel of PCOS endometrial receptivity biomarkers of the present invention.

Detailed Description

The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.

One group of endometrial receptivity biomarkers of the invention had significant differences in the mean endometrial expression levels of PCOS-infertile populations at different androgen levels. The different androgen levels refer to grouping patients according to their serum androgen levels (T), and the difference in expression level of a set of PCOS endometrial receptivity biomarkers refers to the difference between the different groupings; meanwhile, judgment of significant difference specifically requires judgment by statistics, and significant difference is generally considered when the difference in average expression amount is 1-fold or more.

The expression level of the endometrium of the patient with different biomarkers at different androgen levels is very different, so that the expression level of the endometrium of the patient with different androgen levels cannot be judged by simply detecting the absolute value of the expression level of one or some differential genes, namely, the expression level of the endometrium of the patient with different androgen levels PCOS as the biomarker is related to the serum androgen level value of the patient, the absolute value of the expression level of one or some differential genes in the endometrium of one patient is higher than that of the other patient, but the endometrial receptivity of the patient with high expression level cannot be directly judged to be good due to the difference of the androgen level values of the two patients, and the reason is that the clinical pregnancy outcome of some patients with high androgen level is worse.

A group of biomarkers related to the state of endometrium can be obtained through transcriptomic analysis (RNA-Seq) so as to solve the defects of the prior art.

Therefore, the application aims to detect the gene expression profile of endometrium of PCOS (prestressed concrete) infertile people with androgen level by RNA-Seq technology, screen differential genes among different comparison groups by using fold difference (FC) and P value (P-value), further verify and screen a group of corresponding markers for evaluating the endometrium tolerance of PCOS infertile people with different androgen level, and the biomarkers can be used for accurately judging the endometrium tolerance of different PCOS infertile people.

The invention has the advantages that a group of PCOS endometrium receptivity biomarkers is provided, and a detection and evaluation means with high efficiency, rapidness, strong specificity and high sensitivity can be provided for the early detection and diagnosis, the targeted intervention and the guidance of embryo transplantation of a PCOS infertility patient; the invention screens the endometrial receptivity genes differentially expressed in PCOS endometrium of androgen level normal group and hyper group by RNA-Seq transcriptomics technology for the first time, opens up a new way for screening the PCOS endometrial receptivity marker, and provides a high-efficiency, quick, strong-specificity and high-sensitivity detection and evaluation means for early discovery and diagnosis of patients suffering from PCOS infertility; the kit for detecting the endometrial receptivity of the PCOS, which contains the endometrial receptivity marker, can provide an efficient, quick, high-specificity and high-sensitivity detection and evaluation means for early detection and diagnosis of patients suffering from infertility of the PCOS.

Examples

This example is a screening method of a group of PCOS endometrial receptivity biomarkers of the present invention, comprising the following steps:

step 1: collecting samples

Intrauterine scratching is carried out on endometrium at the middle luteal stage of an infertility patient, and the intrauterine scratching specifically comprises the following steps:

on days 7-9 of the luteal phase (LH) of the patient, a disposable endometrial sampling tube was used for endometrial sampling, and the specific sampling procedure was:

washing and disinfecting: washing vulva with 0.1% Andofu for 2 times;

putting a speculum: putting the speculum into the vagina in a closed manner, then opening the speculum, exposing the cervix and fixing;

sampling: placing the sampling tube into the uterine cavity from the cervix, adjusting the angle according to the position of the uterus of a patient, pulling the needle core of the sampling tube outwards to the position of the cervical orifice after the sampling tube reaches the uterine fundus, pulling the sampling tube back and forth to suck tissues for about 6-8mm, and taking out the sampling tube; the removed intima tissue was placed in a dish with saline.

In this example, the patient is less than or equal to 40 years old.

Step 2: grouping endometrial samples

After collecting endometrial samples from infertile patients, grouping was performed according to the following:

1) screening an intima sample of the polycystic ovarian syndrome from the samples obtained in the step 1 according to a polycystic ovarian syndrome diagnosis standard (Rotterdam diagnosis standard in 2003);

2) dividing the intimal sample of polycystic ovarian syndrome into normal group and hyper group according to the serum androgen level of the patient; wherein, according to the specification of the androgen detection kit, the androgen group has androgen level less than or equal to 0.481 ng/mL; the hyper group had androgen levels > 0.481 ng/mL.

The androgen levels are classified according to the reference ranges described in the ROCHE DIAGNOSTICS GMBH-Elecsys Testosterone II kit.

Wherein the selection criteria of the inner membrane sample of the polycystic ovarian syndrome are as follows: PCOS can be judged according to any two of the following three items: clinical or biochemical changes in hyperandrogenism; thin hair, egg laying or no ovulation; the ovary is found to be changed in a polycystic way by ultrasound.

Exclusion criteria were: the patient suffers from chromosome abnormality, thalassemia, virus infection, intrauterine death, dead fetus, ectopic pregnancy and other adverse pregnancy fatalities and pelvic cavity adhesion diseases; androgen insufficiency; insulin resistance due to other causes.

The inclusion and exclusion criteria are intended to be met simultaneously, i.e., if either of the exclusion criteria is met, then inclusion is not performed.

According to the above grouping criteria, 10 patients with polycystic ovarian syndrome were recruited in the present example, wherein 5 patients in normal group and 5 patients in hyper group, and the basic information of the patients is shown in table 1:

TABLE 1 basic information of patients

And step 3: RNA-Seq detection of intimal samples for polycystic ovarian syndrome

The method comprises the following specific steps:

1) RNA extraction and detection: total RNA (total RNA) extraction is carried out on an endometrial sample of polycystic ovarian syndrome, and RAN integrity and purity analysis including agarose gel electrophoresis analysis of RNA integrity and DNA pollution of the sample is carried out on the total RNA after extraction.

Wherein, a NanoPhotometer spectrophotometer is adopted to detect the purity of RNA; the RNA concentration is accurately quantified by adopting a Qubit2.0 Fluorometer; RNA integrity was accurately determined using an Agilent 2100 bioanalyzer.

2) Library construction and quality inspection: the initial RNA of the library is total RNA, and the total amount is more than or equal to 1 mu g. The library building kit used in library building is Illumina

UltraTM RNA Library Prep Kit. mRNA with a polyA tail was enriched by oligo (dT) magnetic beads, and the resulting mRNA was then randomly fragmented with divalent cations in NEB Fragmentation Buffer. Using fragmented mRNA as a template and random oligonucleotide as a primer, synthesizing a first strand of cDNA in an M-MuLV reverse transcriptase system, then degrading the RNA strand by RNaseH, and synthesizing a second strand of cDNA by using dNTPs as a raw material under a DNA polymerase I system. And (3) carrying out end repair on the purified double-stranded cDNA, carrying out end repair, adding an A tail, connecting with a sequencing joint, screening cDNA about 200bp by using AMPure XP beads, carrying out PCR amplification, purifying a PCR product by using the AMPure XP beads again, and finally obtaining the library. After the library is constructed, a Qubit2.0 Fluorometer is used for preliminary quantification, the library is diluted to 1.5 ng/mu l, then an insert size of the library is detected by using an Agilent 2100bioanalyzer, and after the insert size meets the expectation, the effective concentration of the library is accurately quantified by qRT-PCR (the effective concentration of the library is higher than 2nM) so as to ensure the quality of the library.

3) And (3) machine sequencing: after the library is qualified, Illumina sequencing is carried out on different libraries according to the effective concentration and the requirement of the target offline data volume, and 150bp paired end reading is generated. The basic principle of Sequencing is Sequencing by Synthesis (Sequencing by Synthesis). Adding four kinds of fluorescence-labeled dNTPs, DNA polymerase and a joint primer into a sequenced flow cell for amplification, releasing corresponding fluorescence every time one fluorescently-labeled dNTP is added when each sequencing cluster extends a complementary chain, and acquiring sequence information of a fragment to be detected by a sequencer through capturing a fluorescence signal and converting an optical signal into a sequencing peak through computer software.

4) And (3) data analysis: converting image data measured by a high-throughput sequencer, and then performing quality control analysis, sequence comparison, new transcript prediction, gene expression level quantification, differential expression analysis, differential gene enrichment analysis, differential gene protein network interaction analysis, variable shear analysis and SNP analysis, wherein the specific analysis steps are as follows:

a. and (3) data quality control: the image data of the sequencing fragment obtained by the high-throughput sequencer is converted into sequence data (reads) through CASAVA base recognition, and the file is in a fastq format and mainly comprises sequence information of the sequencing fragment and sequencing quality information corresponding to the sequence information. The raw data obtained by sequencing contains a small amount of reads with sequencing adapters or with lower sequencing quality. In order to ensure the quality and reliability of data analysis, the raw data needs to be filtered. Mainly comprises removing reads with a connector (adapter), removing reads containing N (N represents that base information cannot be determined), and removing low-quality reads (reads with the base number of Qphred less than or equal to 20 accounting for more than 50% of the length of the whole read). Meanwhile, Q20, Q30 and GC content calculations were made on clean data. All subsequent analyses were high quality analyses based on clean data.

b. Sequence alignment to reference genome

The reference genome and gene model annotation files are downloaded directly from the genome website. An index of the reference genome was constructed using HISAT2 v2.0.5 and paired-end clean reads were aligned to the reference genome using HISAT2 v 2.0.5. We chose his sat2 as the alignment tool because his sat2 could generate a database of splice junctions based on gene model annotation files and therefore had better alignment than other non-splice alignment tools.

c. Prediction of New transcripts New gene prediction was performed using StringTie (Mihalea Pertea. et al. 2015). StringTie applies a network streaming algorithm and optional de-heading assembly to splice transcripts.

d. Quantification of Gene expression levels FeatureNunts were used to calculate reads mapped to each gene. The FPKM for each gene is then calculated based on the length of the gene and the reads mapped to that gene are calculated. FPKM refers to the expected number of fragments per kilobase of a fragment of a transcript sequence sequenced per million base pairs.

e. Differential expression analysis between two comparative combinations (two biological replicates per group) was performed using the DESeq 2R software (1.16.1). DESeq2 provides a statistical program for determining differential expression in digital gene expression data using a model based on negative binomial distribution. The resulting P values were adjusted using the methods of Benjamini and Hochberg to control the false discovery rate. Genes with adjusted P-value <0.05 were found to be assigned as differentially expressed by DESeq 2. (for the use of edgeR without biological replicates) prior to performing differential gene expression analysis, read counts were adjusted by the edgeR package by a scale normalization factor for each sequencing library. Differential expression analysis of the two conditions was performed using the edgeR software package (3.18.1). The P value was adjusted using the Benjamini & Hochberg method. The corrected P value and | log2foldchange | serve as thresholds for significant differential expression.

f. Differential gene enrichment analysis, namely realizing GO enrichment analysis of differential expression genes through clusterProfiler R software, wherein the length deviation of the genes is corrected. GO term with corrected P value less than 0.05 was considered to be significantly enriched by differentially expressed genes.

g. Differential Gene protein network interaction analysis PPI analysis of differentially expressed genes is based on the STRING database of known and predicted protein-protein interactions. For species present in the database, we construct the network by extracting a list of target genes from the database; otherwise, the target gene sequence is aligned to the selected reference protein sequence using diamond (0.9.13), and then a network is established based on the known interactions of the selected reference species.

h. Alternative splicing assay alternative splicing is an important mechanism for regulating gene expression and protein variables. AS events were analyzed using rMATS (3.2.5) software, mainly including the five alternative splicing events SE, RI, MXE, A5SS, A3 SS.

And (i) SNP analysis, namely performing mutation site analysis on the sample data by using GATK software, and annotating the mutation site by using SnpEff software.

The results obtained by RNA-Seq detection and data analysis are as follows:

740 inner membrane difference genes whose absolute difference in expression amounts was 2.0-fold or more were identified in the normal group, among which 377 up-regulated genes and 363 down-regulated genes, as compared with the hyper group, and FIG. 2 is a heat map of the above-mentioned difference genes.

And 4, step 4: screening the differential genes obtained in the step 3, and screening a group of biomarkers capable of reflecting the difference characteristics of the intimal states of the normal group and the hyper group, wherein the group of biomarkers comprises 21 differential genes, 9 up-regulated genes (U1-U9) and 12 down-regulated genes (D1-D12), specific gene and average expression ratio values are shown in Table 2, and FIG. 3 is a differential gene expression heat map of the group of endometrial receptivity biomarkers.

Wherein, the up-regulated gene refers to that the average expression level in a human body with the androgen level less than or equal to 0.481ng/mL is larger than the average expression level in a human body with the androgen level more than 0.481ng/mL, and the down-regulated gene refers to that the average expression level in a human body with the androgen level less than or equal to 0.481ng/mL is smaller than the average expression level in a human body with the androgen level more than 0.481 ng/mL.

TABLE 2 logarithmic values of the ratio of the absolute values of the mean expression levels of a group of endometrial receptivity biomarkers and the absolute values of the mean expression levels thereof in the normal and hyper groups

Because the current technical means can not directly detect and extract the biomarkers related to the endometrial receptivity, all the differential genes of the endometrium are detected by the screening method of the invention, and then the biomarkers related to the endometrial receptivity in the differential genes are screened out by the known characteristics of all the biomarkers.

The kit for detecting endometrial receptivity provided by the invention contains the group of endometrial receptivity biomarkers.

Weighting each biomarker in the group of PCOS endometrial markers according to the expression multiple difference and specific biological functions of the biomarker in people with different androgen levels, wherein the biomarker is represented by the high weight, and combining 4-5 of the biomarkers to obtain the kit which can be used for detecting endometrial receptivity of PCOS infertility patients.

The specific biological function means that the further detection has larger influence on the symptoms of the infertility patients in practical application; the specific weighting patterns are to be further analyzed for each specific biomarker.

The kit description and the use method comprise the following steps:

1) detecting the average expression level of the biomarkers in the kit of the endometrium of normal pregnant women in different androgen level ranges of a certain sample amount, and calculating to obtain the normal expression level reference value range of the biomarkers in the kit in the androgen level range;

2) detecting androgen level abnormality, namely expression quantity of the corresponding biomarker in endometrium of PCOS patient with testosterone value larger than 0.481mg/mL by using the kit;

3) comparing the expression level of the biomarker obtained in the step 2) with the corresponding reference value range in the step 1), wherein the comparison mode is that the expression level of the biomarker measured by patients with the same androgen level range is compared with the reference value range of the expression level of the corresponding biomarker in normal pregnant women;

when the expression level of the biomarker is within the reference value range, judging that the endometrial receptivity of the PCOS patient with high androgen level is good; when the expression level of the biomarker is out of the reference value range, the endometrial receptivity of the PCOS patient with high androgen level is judged to be poor.

The good endometrial receptivity mainly refers to normal expression level of receptivity related genes regulated by androgen, and the poor endometrial receptivity refers to abnormal expression level of the receptivity related genes regulated by androgen.

In addition, due to the more characterization of PCOS, the technical scheme of the invention is only to establish the relationship between high androgen and endometrial receptivity of PCOS patients. In another version of the protocol of patent No. 202011264955.X, the body index is used as a further characteristic to establish its relationship to endometrial receptivity of PCOS patients.

Since androgen levels and body indices are two different characterizations, the populations targeted by the two characterizations are not the same.

The target population of the application is high androgen PCOS infertile patients, and when the PCOS patients are combined with high androgen, the kit disclosed by the application is used for detecting to judge the endometrial receptivity of the PCOS patients. For patients with PCOS infertility, if their androgen levels are normal, other characterizations and methods can be selected to determine endometrial receptivity.

If the PCOS sterile patient has more than two characteristics at the same time, the different characteristics can be detected and judged respectively. If the same PCOS infertility patient is tested by the two kits to determine the result of inconsistency when the endometrial receptivity of the same PCOS infertility patient is determined, for example, the method for determining endometrial receptivity of the same PCOS infertility patient (202011264955.X) is used to determine that the endometrial receptivity of the same PCOS infertility patient is good by using a group of endometrial receptivity biomarkers, the kit and the method for determining endometrial receptivity (202011264955.X), but the method for determining endometrial receptivity of the same PCOS infertility patient is used to determine that the endometrial receptivity of the same PCOS infertility patient is poor by using the method for determining endometrial receptivity of the same PCOS infertility patient, which is caused by the fact that the genes contained in the two detection kits for determining endometrial receptivity are inconsistent, both are related markers reflecting endometrial receptivity, but the specific biological functions are different, and the indicated endometrial receptivity is also directed to different functional aspects.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (8)

1. A group of high androgen polycystic ovary syndrome endometrium receptivity biomarkers, which are characterized in that the mean expression quantity of the biomarkers in endometrium of the people who are not pregnant with polycystic ovary syndrome at different androgen levels has significant difference.

2. The panel of high androgen polycystic ovary syndrome endometrial receptivity biomarkers of claim 1, wherein said biomarkers have an absolute value of mean expression of endometrium of 0.481ng/mL or less for androgen levels in a population with polycystic ovary syndrome infertility that is at least twice as high as the absolute value of mean expression of endometrium of 0.481ng/mL human androgen levels.

3. The panel of high androgen polycystic ovary syndrome endometrial receptivity biomarkers of claim 1, comprising a total of at least 4 up-regulated genes and/or down-regulated genes;

the average expression level of the up-regulated gene in the endometrium of a human body with the androgen level less than or equal to 0.481ng/mL in the infertility population with polycystic ovary syndrome is larger than the average expression level of the endometrium of a human body with the androgen level more than 0.481 ng/mL;

the average expression level of the down-regulated gene in the endometrium of a human body with the androgen level less than or equal to 0.481ng/mL in the infertility population with polycystic ovary syndrome is less than the average expression level of the androgen level in the endometrium of a human body with the androgen level more than 0.481 ng/mL;

the up-regulated genes include:

u1, MAGED, gene ID ENSG00000179222, Gene Note MAGE family member D1, Chinese name MAGE family member D1;

u2, ITGA4, gene ID ENSG00000115232, gene annotation for integrin subbunit alpha 4, Chinese name integrin subunit α 4;

u3, MUC7, gene ID ENSG00000171195, gene note mucin 7, chinese name mucin 7;

u4, KRT12, gene ID ENSG00000187242, gene annotation as keratin 12, chinese name keratin 12;

u5, KRT37, gene ID ENSG00000108417, gene annotation keratin 37, chinese name keratin 37;

u6, FGL1, gene ID ENSG00000104760, gene annotation fibrinogen like 1, chinese name fibrinogen-like 1;

u7, FSBP, gene ID ENSG00000265817, gene annotation for fibrinogen silencer binding protein, Chinese name fibrinogen silencer binding protein;

u8, AK4P3, gene ID ENSG00000233381, gene annotation 4 adenylate kinase 3 pseudogene, Chinese name adenylate kinase 4pseudogene 3;

u9, ANXA2P3, gene ID ENSG00000216740, gene annotation annexin A2pseudogene 3, Chinese name annexin A2pseudogene 3;

the down-regulated genes include, but are not limited to,

d1, ITGB3, gene ID ENSG00000259207, gene annotation for integrin subbentbeta 3, chinese name integrin subunit beta 3;

d2, ITGA2, gene ID ENSG00000164171, gene annotation for integrin subbunit alpha 2, Chinese name integrin subunit alpha 2;

d3, MEGF6, gene ID ENSG00000162591, gene annotation as multiple EGF like domains 6, chinese name multiple EGF-like domain 6;

d4, MUC16, gene ID ENSG00000181143, gene note mucin 16, chinese name mucin 16;

d5, PCDH17, gene ID ENSG00000118946, Gene Note protocadherin 17, Chinese name tropocadherin 17;

d6, PCDHA10, gene ID ENSG00000250120, gene annotation protocadherin alpha 10, Chinese name procalcitonin alpha 10;

d7, DCHS2, gene ID ENSG00000197410, Gene annotation dachsous cadherin-related 2, Chinese name tropocadherin 23;

d8, KRT17, gene ID ENSG00000128422, gene note keratin 17, chinese name keratin 17;

d9, KRT85, gene ID ENSG00000135443, gene annotation as keratin 85, chinese name keratin 85;

d10, ANXA10, gene ID ENSG00000109511, gene annotation annexin a10, chinese name annexin a 10;

d11, IL22RA1, gene ID ENSG00000142677, gene annotation of interleukin 22receptor subunit alpha 1, Chinese name interleukin 22receptor subunit alpha 1;

d12, IL6ST, geneID ENSG00000134352, Gene annotation Interleukin 6signal transducer, Chinese name interleukin 6signal transducer.

4. The panel of biomarkers of high androgen polycystic ovary syndrome endometrial receptivity as claimed in claim 1, wherein said biomarkers are selected by measuring and analyzing the expression level of all biomarker genes in endometrium of polycystic ovary syndrome infertile population with different androgen level by RNA-Seq method, and selecting the biomarkers with large difference of mean expression level absolute value in endometrium of polycystic ovary syndrome infertile population with different androgen level according to the analysis result, and then selecting the biomarkers related to endometrial receptivity from the biomarkers with large difference of mean expression level absolute value.

5. The group of high androgen polycystic ovary syndrome endometrial receptivity biomarkers according to claim 2, wherein the method for screening the biomarkers comprises the following steps:

s1, collecting a sample, wherein the sample is endometrial tissue of a patient suffering from polycystic ovarian syndrome infertility;

s2, grouping the samples, wherein the samples collected by the human body with the androgen level less than or equal to 0.481ng/mL are classified into normal group, and the samples collected by the human body with the androgen level more than 0.481ng/mL are classified into hyper group;

s3, respectively carrying out gene expression quantity determination on the samples of the normal group and the hyper group by adopting RNA-Seq, and simultaneously comparing and analyzing the difference multiple of the average expression quantity of each biomarker in the two groups of samples;

s4, screening a group of biomarkers related to endometrial receptivity from the biomarkers with the expression quantity absolute value difference multiple more than or equal to 2 times according to the characteristics of each biomarker.

6. A kit for detecting endometrial receptivity of hyperandrogenism polycystic ovarian syndrome, wherein the kit comprises a group of endometrial receptivity biomarkers according to any one of claims 1-5.

7. The kit for detecting endometrial receptivity for hyperandrogenism polycystic ovarian syndrome according to claim 6, wherein said kit comprises 4-5 representative biomarkers selected by,

weighting each biomarker in the group of polycystic ovarian syndrome endometrial markers according to the absolute value of the fold difference of the expression of each biomarker in different androgen level polycystic ovarian syndrome populations and the specific biological function of each biomarker, wherein the biomarker is represented by the high weight.

8. A method for judging endometrial receptivity of high androgen polycystic ovarian syndrome, which is characterized in that a kit for detecting endometrial receptivity according to any one of claims 6 to 7 is used for judging a polycystic ovarian syndrome infertility patient, and the method comprises the following steps:

1) detecting the average expression level of the biomarker in the kit of the endometrium of a normal pregnant female with a certain sample amount of high androgen level, and calculating to obtain the reference value range of the normal average expression level of the biomarker in the kit in the endometrium of the androgen level range;

2) detecting the expression level of the corresponding biomarker in the endometrium of the patient with the high androgen polycystic ovary syndrome by adopting the kit;

3) comparing the expression level of the biomarker obtained in the step 2) with the corresponding reference value range in the step 1), wherein the comparison mode is that the expression level of the biomarker measured by a patient with high androgen level is compared with the reference value range of normal expression level;

when the expression level of the biomarker is within the reference value range, judging that the expression level of the tolerance-related gene regulated by androgen is normal in the endometrium of the patient;

and when the expression level of the biomarker is out of the reference value range, judging that the expression level of the tolerance related gene regulated by androgen is abnormal in the endometrium of the patient.

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