Use of HSF2 gene as diagnostic marker in preparation of product for diagnosing polycystic ovary syndrome

Abstract

The present invention relates to the technical field of molecular diagnosis, and in particular to a use of an HSF2 gene as a diagnostic marker in the preparation of a product for diagnosing polycystic ovary syndrome (PCOS). It is found that the HSF2 gene or an HSF2 protein can be used as a diagnostic marker for PCOS. Compared with a healthy control group, the transcription of HSF2 in the peripheral blood of a PCOS patient and an offspring thereof is significantly elevated, thereby showing a statistical difference. On the basis of sequencing data of the HSF2 gene, an ROC curve for diagnosing PCOS offspring inheritance on the basis of the HSF2 gene is established, and an AUC value is 0.8384. Results show that the HSF2 gene as a diagnostic marker can implement diagnosis or prediction of PCOS, especially diagnosis or prediction of PCOS in an offspring, and has high accuracy, thereby providing a new basis for effective diagnosis of PCOS.

Description

Application of HSF2 gene as a diagnostic marker in the preparation of products for diagnosing polycystic ovary syndrome

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This disclosure claims priority to Chinese patent application number 202410259851.1, filed with the Chinese Patent Office on March 7, 2024, entitled “Application of HSF2 gene as a diagnostic marker in the preparation of products for diagnosing polycystic ovary syndrome,” the entire contents of which are incorporated by reference into this disclosure. Technical Field

[0003] The present disclosure relates to the field of molecular diagnosis technology, and in particular to the use of the HSF2 gene as a diagnostic marker in the preparation of products for diagnosing polycystic ovary syndrome. Background Art

[0004] Polycystic ovary syndrome (PCOS) is a public health issue that significantly affects women's reproductive, metabolic, and psychological health. Over the past few decades, clinical research on PCOS patients has primarily focused on infertility and subfertility.

[0005] Studies have shown that compared with normal women, mothers with PCOS have a negative impact on the growth, cardiac health, reproductive health and neurological development of their offspring and children. Currently, there is a lack of effective diagnostic markers for PCOS and its offspring.

[0006] Summary of the Invention

[0007] To address the above-mentioned issues, the present disclosure aims to, for example, provide the use of the HSF2 (heat shock transcription factor 2) gene as a diagnostic marker in the preparation of products for diagnosing offspring with polycystic ovary syndrome. The present disclosure discovered that the HSF2 gene is highly expressed in the peripheral blood of patients with polycystic ovary syndrome and their offspring, relative to healthy controls and their offspring. This gene can be used as a diagnostic marker for the offspring of polycystic ovary syndrome, providing new evidence for the genetic diagnosis of polycystic ovary syndrome.

[0008] In order to achieve the above objectives, the present disclosure provides the following technical solutions:

[0009] The embodiments of the present disclosure provide the use of the HSF2 gene or HSF2 protein as a diagnostic marker in the preparation of a reagent or kit for diagnosing polycystic ovary syndrome.

[0010] The embodiments of the present disclosure provide the use of a reagent for detecting the expression level of the HSF2 gene or the expression level of the HSF2 protein in preparing a kit for diagnosing polycystic ovary syndrome.

[0011] The embodiments of the present disclosure also provide the use of the HSF2 gene and / or HSF2 protein as a marker in the preparation of a product for predicting polycystic ovary syndrome.

[0012] The embodiments of the present disclosure provide use of a reagent for detecting HSF2 gene expression and / or a reagent for detecting HSF2 protein expression in preparing a product for predicting polycystic ovary syndrome.

[0013] The present disclosure also provides a method for diagnosing or predicting polycystic ovary syndrome in a subject, comprising the following steps:

[0014] Obtaining a test result of a marker expression level of the subject; wherein the marker includes: HSF2 gene and / or HSF2 protein;

[0015] The test results of the subject's marker expression level are input into a trained prediction model to obtain a prediction result for the sample; the prediction model is trained to predict the risk score of polycystic ovary syndrome in the sample based on the marker expression level.

[0016] An embodiment of the present disclosure also provides a system for diagnosing or predicting polycystic ovary syndrome in a subject, which includes: a processor and a memory, wherein the memory is used to store a program, and when the program is executed by the processor, the processor performs the method for diagnosing or predicting polycystic ovary syndrome in a subject as described in the aforementioned embodiment.

[0017] An embodiment of the present disclosure further provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the method for diagnosing or predicting polycystic ovary syndrome in a subject as described in the aforementioned embodiment. Beneficial effects:

[0018] The present disclosure discovered that the HSF2 gene or HSF2 protein can be used as a diagnostic marker for polycystic ovary syndrome (PCOS). Compared to a healthy control group, HSF2 transcription in the peripheral blood of PCOS patients and their offspring was significantly elevated, with statistically significant differences. Based on the sequencing data of the HSF2 gene, the present disclosure established a receiver operating characteristic (ROC) curve for the diagnosis of PCOS offspring inheritance based on the HSF2 gene, with an AUC value of 0.8384. The results demonstrate that the HSF2 gene can be used as a diagnostic marker to diagnose or predict PCOS, particularly in PCOS offspring, with high accuracy, providing new evidence for the effective diagnosis of PCOS. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without any creative work.

[0020] FIG1 is a comparison of the percentage of embryo development in the PCOS mouse model and the control mouse model before implantation of F0 oocytes into normal ICR mice after in vitro fertilization in the embodiment;

[0021] Figures 2 and 3 show the results of differentially expressed genes analysis at different oocyte GV stages;

[0022] Figure 4 shows the expression results of the HSF2 gene at different oocyte GV stages;

[0023] FIG5 shows the effect of HSF2 protein on oocyte maturation at the GV stage;

[0024] Figure 6 shows the time of oocyte PBE discharge;

[0025] Figure 7 shows the HSF2 transcriptional expression results in PCOS patients, healthy controls, and the offspring of the two groups;

[0026] Figure 8 shows the results of HSF2 transcriptional expression in oocytes of PCOS patients and healthy controls at different stages;

[0027] FIG9 is a ROC curve for diagnosing PCOS offspring inheritance based on the HSF2 gene. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments.

[0029] Therefore, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the present disclosure as claimed, but merely represents selected embodiments of the present disclosure. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present disclosure without creative effort shall fall within the scope of protection of the present disclosure.

[0030] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings. However, the present disclosure can be implemented in many different ways as defined and covered by the claims.

[0031] The present disclosure found that HSF2 transcription in the peripheral blood of PCOS patients was significantly elevated compared to that of the healthy control group. Similarly, HSF2 transcription levels were significantly elevated in the offspring of PCOS patients compared to the offspring of the healthy control group, with both differences being statistically significant. Based on HSF2 gene sequencing data, the present disclosure established a receiver operating characteristic (ROC) curve for HSF2 gene-based diagnosis of PCOS offspring, with an AUC value of 0.8384. These results demonstrate that the HSF2 gene and / or HSF2 protein can be used as markers for the diagnosis of PCOS, particularly in offspring of PCOS, with high accuracy, providing new evidence for the effective diagnosis of polycystic ovary syndrome.

[0032] The present disclosure provides the use of the HSF2 gene or HSF2 protein as a diagnostic marker in the preparation of a reagent or kit for diagnosing polycystic ovary syndrome.

[0033] In some embodiments, the diagnostic subjects of the reagent or kit preferably include offspring of patients with polycystic ovary syndrome.

[0034] The embodiments of the present disclosure also provide the use of a reagent for detecting the expression level of the HSF2 gene or the expression level of the HSF2 protein in preparing a kit for diagnosing polycystic ovary syndrome.

[0035] In some embodiments, the diagnostic subjects of the reagent or kit preferably include offspring of patients with polycystic ovary syndrome.

[0036] The embodiments of the present disclosure also provide the use of the HSF2 gene and / or HSF2 protein as a marker in the preparation of a product for predicting polycystic ovary syndrome.

[0037] The embodiments of the present disclosure also provide the use of a reagent for detecting the expression level of the HSF2 gene and / or a reagent for detecting the expression level of the HSF2 protein in the preparation of a product for predicting polycystic ovary syndrome.

[0038] In some embodiments, the product comprises: a reagent, a kit, or a chip.

[0039] In some embodiments, the diagnostic or prognostic subjects of the product include offspring of patients with polycystic ovary syndrome.

[0040] The present invention has no particular limitation on the type of reagents for detecting HSF2 gene expression and / or HSF2 protein expression, and these reagents can be obtained according to common knowledge, existing methods, or commercially available reagents.

[0041] In some embodiments, the reagents for detecting the expression level of the HSF2 gene are configured to be related reagents for detecting the expression level of the HSF2 gene by at least one of Southern blotting, Northern blotting, PCR, reverse transcriptase PCR, real-time quantitative PCR, nanoarray, macroarray, autoradiography, and in situ hybridization.

[0042] In some embodiments, the reagents for detecting HSF2 protein expression are configured as: BCA method, Bradford method, Western blotting, immunohistochemistry, ELISA detection, flow cytometry, protein chip and two-dimensional electrophoresis to detect HSF2 protein expression.

[0043] The present disclosure also provides a method for diagnosing or predicting polycystic ovary syndrome in a subject, comprising the following steps:

[0044] Obtaining a test result of the expression level of a marker of the subject; wherein the marker includes: HSF2 gene and / or HSF2 protein;

[0045] The detection results of the expression levels of the subject's markers are input into a trained prediction model to obtain a prediction result for the sample; the prediction model is trained to predict the risk score of polycystic ovary syndrome of the sample based on the expression levels of the markers.

[0046] In some embodiments, the subject comprises an offspring of polycystic ovary syndrome.

[0047] In some embodiments, the training method of the trained prediction model includes:

[0048] Obtaining the detection results of the marker expression levels in the training samples and the corresponding annotation results; the annotation results include the risk score of the sample suffering from polycystic ovary syndrome;

[0049] Input the detection results of the training samples into the prediction model to obtain the prediction results of the training samples;

[0050] According to the labeling results and prediction results of the training samples, the parameters of the prediction model are updated to obtain the trained prediction model.

[0051] In some embodiments, the annotation result includes: a label representing a risk score of the sample suffering from polycystic ovary syndrome. The label can be a character or a string.

[0052] In some embodiments, the categories and number of training samples can be routinely selected by those skilled in the art, and the total number of training samples and the number of training samples of various categories (e.g., healthy people and patients) can be independently ≥ any value among 10, 50, 100, 200, 300, 400 and 500, or a range between any two of them. The training samples can include a positive group (e.g., high risk or diseased) and a negative group (e.g., low risk or healthy).

[0053] In some embodiments, the present invention does not specifically limit the type of prediction model, and the prediction model can be selected from conventional algorithmic models in the art for predicting or diagnosing diseases based on gene or protein expression. Optionally, the prediction model includes any one of a decision tree, a logistic regression model, a support vector machine, a KNN, a naive Bayesian, and a random forest.

[0054] An embodiment of the present disclosure also provides a system for diagnosing or predicting polycystic ovary syndrome in a subject, comprising: a processor and a memory, wherein the memory is used to store a program, and when the program is executed by the processor, the processor performs the method for diagnosing or predicting polycystic ovary syndrome in a subject as described in any of the aforementioned embodiments.

[0055] The memory may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0056] The processor can be an integrated circuit chip with signal processing capabilities. The processor 120 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0057] The diagnostic or predictive system can be a server, a cloud platform, a mobile phone, a tablet computer, a laptop computer, an ultra-mobile personal computer (UMPC), a handheld computer, a netbook, a personal digital assistant (PDA), a wearable electronic device, a virtual reality device, or other devices. Therefore, the embodiments of the present disclosure do not limit the type of diagnostic or predictive system.

[0058] In addition, an embodiment of the present disclosure further provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the method for diagnosing or predicting polycystic ovary syndrome in a subject as described in any of the aforementioned embodiments.

[0059] The computer-readable medium may be a general storage medium, such as a mobile disk, a hard disk, and the like.

[0060] To further illustrate the present disclosure, the application of the HSF2 gene provided by the present disclosure as a diagnostic marker in the preparation of products for diagnosing polycystic ovary syndrome is described in detail below in conjunction with the accompanying drawings and examples, but they should not be construed as limiting the scope of protection of the present disclosure.

[0061] Example

[0062] Establishment of PCOS mouse model and single-cell transcriptome sequencing

[0063] 1. F0: Four-week-old female C57BL / 6J mice were randomly divided into two groups. One group received daily subcutaneous injections of dehydroepiandrosterone (DHEA, final concentration 6 mg / 100 g) dissolved in 50 μL sesame oil for 20 days. A PCOS model was established if vaginal smears showed no obvious estrous cycles (denoted as PCOS). The other group received an equal amount of 50 μL sesame oil as the control group (Control).

[0064] F2: F0 oocytes are fertilized in vitro with embryos from unrelated adult male mice and transplanted into normal ICR mice to produce F1 female offspring. F1 oocytes are fertilized in vitro with embryos from unrelated adult male mice and transplanted into normal ICR mice to produce F2 female offspring.

[0065] 2. Collect GV stage oocytes from F0 and F2 female mice for single-cell transcriptional sequencing

[0066] (1) Oocyte collection: Each mouse was injected with 10 IU of pregnant mare serum gonadotropin (PMSG), and oocytes were collected after ovarian puncture with a 30-gauge needle. To collect GV-stage oocytes, 48 ​​hours after PMSG injection, each mouse was injected with 10 IU of human chorionic gonadotropin (hCG) for superovulation. 14 hours after hCG injection, cumulus-oocyte complexes (COCs) were isolated from the ampulla of the oviduct. The cumulus masses were removed in a culture medium containing 0.5 mg / mL hyaluronidase at 37°C, and denuded GV-stage oocytes were obtained.

[0067] (2) Single-cell transcriptome RNA sequencing (scRNA-seq) was performed on oocytes collected from PCOS mice and the control group as follows:

[0068] A. Cell sample preparation: Use a Pasteur pipette to aspirate single cells, resuspend them in 1× PBS, and place them at the bottom of an EP tube. Operate on ice.

[0069] B. First-Strand cDNA Synthesis: Prepare lysis buffer and add it to the EP tube containing the single cell. Add Oligo(dT)VN primer and dNTP Mix, mix gently, and then react in a PCR instrument. Reaction conditions: Extend at 72°C for 3 minutes, then immediately place on ice for 2 minutes. Prepare the reverse transcription reaction system and proceed at 42°C for 90 minutes, 70°C for 15 minutes, and then cool to 4°C.

[0070] C. Full-length cDNA Amplification and Purification: Prepare a PCR amplification system (single cell full-length mRNA-Amplication kit, N712, Vazyme) consisting of 10 μL of first-strand cDNA synthesis product, 2 μL of nuclease-free H₂O, 0.5 μL of PCR Primer, and 12.5 μL of 2× Amplification Mix, for a total of 25 μL. Mix well and react in a PCR instrument. Reaction conditions: denaturation at 98°C for 10 seconds, annealing at 65°C for 15 seconds, extension at 72°C for 6 minutes (16 cycles), extension at 72°C for 5 minutes, and cooling at 4°C. After magnetic bead separation and purification, product quality control and identification were performed using an Agilent 2100 Bioanalyzer.

[0071] D. Library construction and sequencing: The above product fragments were processed according to the DNA library preparation kit and then loaded onto the Illumina HiSeq platform for sequencing using the PE150 mode.

[0072] E. Perform gene expression analysis on the sequencing results and calculate the correlation between each sample pair. The method is described in the literature [Prenatal androgen exposure and transgenerational susceptibility to polycystic ovary syndrome Nat Med. 2019 Dec; 25(12): 1894-1904.].

[0073] The results are shown in Figures 1 to 4 and Table 1.

[0074] Table 1 cRNA-seq differential expression analysis results

[0075] As shown in Figure 1, there was no significant difference in the percentage of embryo development between the PCOS mouse model and the control group mice after F0 oocytes were fertilized in vitro and implanted into normal ICR mice.

[0076] As shown in Table 1, there are 2307 up-regulated genes in the GV of F0 mice and 264 up-regulated genes in the GV of F2 mice, of which 89 are up-regulated genes with overlapping transgenerational inheritance. Analysis confirmed that HSF2 is involved in the regulation.

[0077] As shown in Figures 2 and 3, Tram2 and Set are differentially expressed genes in the GV stage. The present disclosure also found that an open binding site for HSF2 appeared near Tram2 and Set genes (<300 kb), and this open region is specific to PCOS and stably inherited.

[0078] As shown in Figure 4 , the transcription level of HSF2 gene in GV stage oocytes derived from POCS offspring was significantly increased compared with that in the control group.

[0079] Example

[0080] Effects of HSF2 on the maturation function of GV-stage oocytes in the control group F0 mice in the aforementioned example

[0081] HSF2 antibody (TAB807407, TrueMAB) and mRec-HSF2 (PM45894M5, Origene) were added to IVF culture medium (G-IVF TMPLUS, Vitrolife), HSF2 antibody was diluted 1:100, and the final concentration of mRec-HSF2 was 200 ng / mL. At the same time, control groups without HSF2 antibody and mRec-HSF2 were set up. In the control group of the HSF2 antibody group, IgG (12-370, Millipore) diluted in equal proportions was added to the control IVF culture medium. Each oocyte was cultured in a 25 μL culture medium covered with mineral oil. The oocytes were incubated and imaged in a separate chamber in an embryo slide culture dish designed for living cells (Vitrolife). Each oocyte was incubated at the same starting point in a humidified atmosphere of 6% CO2 at 37°C with an embryoscope time-lapse system (Vitrolife). Images were collected every 5 minutes for 72 hours. Some of the results are shown in Figures 5 and 6, where GVBD is nuclear membrane rupture and PBE is polar body expulsion.

[0082] As shown in Figures 5 and 6, incubation of GV-stage oocytes with HSF2 antibodies significantly promoted oocyte maturation, with statistical significance; incubation of GV-stage oocytes with recombinant HSF2 protein (mRec-HSF2) significantly inhibited oocyte maturation, with statistical significance. This indicates that HSF2 protein inhibits oocyte maturation.

[0083] Example

[0084] Clinical specimens were collected and transcriptome sequencing was performed

[0085] 1. Rotterdam Standards:

[0086] (1) Oligomenorrhea, amenorrhea, or irregular uterine bleeding include: A. Menarche > 1 or < 3 years: menstrual cycle < 21 or > 45 days; B. Menarche > 3 years: menstrual cycle < 21 or > 35 days, or < 8 menstrual cycles per year; C. Menarche > 1 year: menstrual cycle > 90 days;

[0087] (2) Primary amenorrhea after the age of 15 or 3 years after breast development.

[0088] (3) clinical manifestations of hyperandrogenism or hyperandrogenism;

[0089] (4) Ultrasound manifestation of PCOM. PCOM is defined as 12 or more follicles with a diameter of 2 to 9 mm on one ovary and / or increased ovarian volume (>10 mL; calculated by the formula: 0.5 × length × width × thickness).

[0090] 2. Data Source

[0091] The Department of Gynecology and Reproductive Medicine at Peking Union Medical College Hospital recruited patients with polycystic ovary syndrome (PCOS) and healthy volunteers, including mothers and daughters. Forty-three PCOS patients were included in the experimental group and 48 in the control group. Detailed information is provided in Tables 2–4. PCOS daughters were included if they had reached menarche for at least one year, were between 15 and 30 years old, and met the three Rotterdam PCOS patient inclusion criteria (menstrual irregularities, kaohsiung, and PCOM). PCOS mothers were included if they were premenopausal and met the two Rotterdam PCOS patient inclusion criteria (menstrual irregularities, kaohsiung), with menstrual irregularities not occurring in the past 1–2 years. Healthy control daughters were included if they had reached menarche for at least one year, were between 15 and 30 years old, and had no menstrual irregularities or kaohsiung symptoms. Healthy control mothers were included if they had no menstrual irregularities or kaohsiung symptoms.

[0092] Table 2 Clinical information of PCOS group and control group Note: BMI, body mass index; D2, day 2; FSH, follicle-stimulating hormone; LH, luteinizing hormone; 2hPG, 2h postprandial blood glucose; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglycerides; T-CHO, total cholesterol; P<0.05 indicates statistically significant difference, the same applies to the following tables.

[0093] Table 3 Clinical information of daughters in the PCOS group and the control group

[0094] Table 4 provides the anthropometric and biochemical characteristics of PCOS patients and controls with GV oocytes Note: E2, estradiol; TSH, thyroid-stimulating hormone; T3, triiodothyronine; T4, tetraiodothyronine; IVF, in vitro fertilization; P, progesterone.

[0095] 3. Peripheral blood mononuclear cells (PBMCs) were extracted from PCOS patients and healthy subjects for transcriptome sequencing.

[0096] (1) Collect whole blood using an anticoagulant tube (EDTA, citrate). After blood collection, gently invert the tube to mix. After anticoagulation, transfer to a 15 mL centrifuge tube, add an equal volume of PBS, and invert to mix.

[0097] (2) Add an equal volume of Ficoll separation solution equilibrated to room temperature to a new 15 mL centrifuge tube as that of the diluted blood.

[0098] (3) Spread the diluted blood evenly on the surface of the separation solution, making sure to keep the interface between the two liquid surfaces clear.

[0099] (4) Centrifuge at room temperature in a swing-out rotor at 600 g for 30 min with the break point set to 0.

[0100] (5) Carefully aspirate and discard most of the plasma layer, then aspirate the buffy coat cells into a new 15 mL centrifuge tube, add 10 mL PBS-BSA, and centrifuge at 250 g for 10 min.

[0101] (6) Carefully discard the supernatant and add 5 mL of PBS to resuspend the cells.

[0102] (7) Centrifuge in a swing-out rotor at 250g for 10 minutes. Carefully discard the supernatant. Add 1 mL of TRIzol lysis buffer to the cell pellet and lyse at room temperature for 2–3 minutes, repeatedly pipetting until the visible cell layer is completely dissolved.

[0103] Shanghai Tianhao Biotechnology Co., Ltd. was commissioned to perform transcriptome sequencing. The specific steps include:

[0104] 1) Pass quality control samples and provide Illumina 2×150bp sequencing data, with a data volume of ≥6G raw data / sample, Q30>80%; and the rRNA ratio is less than 3% of the raw data. "Raw data" refers to the data after filtering out the adapter sequences from the raw data.

[0105] 2) Raw data quality control: filter the raw data, remove the sequencing primers and terminal low values, and retain the remaining sequences greater than 35 bp; count the data volume before and after filtering;

[0106] 3) Reference sequence alignment analysis (default alignment database: human hg38);

[0107] A. Use STAR software to align the filtered reads with the reference database and perform statistical analysis of the comparison results;

[0108] B. Reads distribution statistics on the reference genome;

[0109] C. Transcriptome data quality assessment (sequencing saturation analysis, redundant sequence analysis, RNA degradation analysis, etc.);

[0110] 4) Quantitative analysis of mRNA expression (default gene annotation database: UCSC refGene, please note if other databases are used);

[0111] A. Calculation of FPKM and Read count values;

[0112] B. Sample expression analysis (FPKM density distribution comparison chart of each sample, FPKM distribution chart of each sample);

[0113] C. Principal component analysis of samples;

[0114] D. Sample correlation heatmap;

[0115] 5) mRNA differential expression analysis;

[0116] A. Deseq2 software was used to analyze the differentially expressed genes between the case group and the control group;

[0117] B. For comparison of multiple groups, ANOVA analysis of variance was used for testing.

[0118] 4. The oocytes (MII stage, 2 cell and GV stage) obtained from PCOS patients and the control group were subjected to single-cell transcriptome RNA sequencing (scRNA-seq) using the method of the previous embodiment.

[0119] The results were analyzed using Graphpad Prism 9.5.1. Data are presented as mean ± standard deviation, and comparisons between groups were made using two-sample independent sample t-tests. The results are shown in Figures 7 to 9.

[0120] As shown in Figure 7, HSF2 transcription in the peripheral blood of mothers with PCOS was significantly higher than that in the healthy control group. Similarly, HSF2 transcription in the daughters of PCOS patients was significantly higher than that in the daughters of the healthy control group, both with statistically significant differences. This indicates that HSF2 is significantly increased in both PCOS patients and their daughters compared to the healthy control group.

[0121] As shown in Figure 8 , the differential expression of HSF2 only appeared in the GV stage of PCOS patients, with statistical significance, but was not expressed in the MII and 2cell stages, with no statistical significance.

[0122] Based on the transcriptome sequencing data of the HSF2 gene, Graphpad Prism 9.5.1 software was used to construct a receiver operating characteristic (ROC) curve for the diagnosis of PCOS in offspring based on the HSF2 gene (Figure 9), using the samples in Tables 2 and 3. The AUC value was 0.8384. These results demonstrate that the HSF2 gene can be used as a diagnostic marker to diagnose PCOS in offspring with high accuracy.

[0123] Although the above embodiment provides a detailed description of the present disclosure, it is only a part of the embodiments of the present disclosure, not all of the embodiments. People can also obtain other embodiments based on this embodiment without creativity, and these embodiments all fall within the scope of protection of the present disclosure. Industrial Applicability

[0124] In summary, the present disclosure provides the use of the HSF2 gene as a diagnostic marker in the preparation of products for diagnosing polycystic ovary syndrome, which can achieve effective diagnosis or prediction of PCOS and its offspring with high accuracy.

Claims

1. Use of the HSF2 gene or HSF2 protein as a diagnostic marker in the preparation of a reagent or kit for diagnosing polycystic ovary syndrome.

2. The use according to claim 1, characterized in that The diagnostic subjects of the reagent or kit include offspring of patients with polycystic ovary syndrome.

3. Use of a reagent for detecting HSF2 gene expression or HSF2 protein expression in the preparation of a kit for diagnosing polycystic ovary syndrome.

4. The use according to claim 3, characterized in that The diagnostic subjects of the kit include offspring of patients with polycystic ovary syndrome.

5. The use according to claim 3 or 4, characterized in that The reagents for detecting the expression level of the HSF2 gene are configured as: relevant reagents for detecting the expression level of the HSF2 gene by at least one method selected from Southern blotting, Northern blotting, PCR, reverse transcriptase PCR, real-time quantitative PCR, nanoarray, macroarray, autoradiography and in situ hybridization.

6. The use according to any one of claims 3 to 5, characterized in that: The reagents for detecting the expression of HSF2 protein are configured as: relevant reagents for detecting the expression of HSF2 protein by at least one method selected from BCA method, Bradford method, Western blotting, immunohistochemistry, ELISA, flow cytometry, protein chip and two-dimensional electrophoresis.

7. Use of the HSF2 gene and / or HSF2 protein as a marker in the preparation of a product for predicting polycystic ovary syndrome.

8. Use of a reagent for detecting HSF2 gene expression and / or a reagent for detecting HSF2 protein expression in the preparation of a product for predicting polycystic ovary syndrome.

9. The use according to claim 7 or 8, characterized in that The subjects of the product include: offspring of patients with polycystic ovary syndrome.

10. A method for diagnosing or predicting polycystic ovary syndrome in a subject, characterized in that: It includes the following steps: Obtaining a test result of a marker expression level of the subject; wherein the marker includes: HSF2 gene and / or HSF2 protein; The detection results of the expression levels of the subject's markers are input into a trained prediction model to obtain a prediction result for the sample; the prediction model is trained to predict the risk score of polycystic ovary syndrome of the sample based on the expression levels of the markers.

11. The method according to claim 10, characterized in that The subjects include offspring of polycystic ovary syndrome.

12. The method according to claim 10 or 11, characterized in that The training method of the trained prediction model includes: Obtaining the detection results of the marker expression levels in the training samples and the corresponding annotation results; the annotation results include the risk score of the sample suffering from polycystic ovary syndrome; Input the detection results of the training samples into the prediction model to obtain the prediction results of the training samples; According to the labeling results and prediction results of the training samples, the parameters of the prediction model are updated to obtain the trained prediction model.

13. The method according to any one of claims 10 to 12, characterized in that: The prediction model includes any one of a decision tree, a logistic regression model, a support vector machine, a KNN, a naive Bayes and a random forest.

14. A system for diagnosing or predicting polycystic ovary syndrome in a subject, characterized in that: It includes: A processor and a memory, wherein the memory is used to store a program. When the program is executed by the processor, the processor performs the method for diagnosing or predicting polycystic ovary syndrome in a subject according to any one of claims 10 to 13.

15. The diagnostic or prognostic system according to claim 14, characterized in that The subjects include offspring of patients with polycystic ovary syndrome.

16. A computer-readable medium, characterized in that The computer-readable medium stores a computer program, and when the computer program is executed by a processor, the method for diagnosing or predicting polycystic ovary syndrome in a subject according to any one of claims 10 to 13 is implemented.

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