Peripheral blood RNA modification marker m 7 Use of G in a diagnostic PCOS kit

Abstract

This invention belongs to the field of biomedical technology, specifically relating to peripheral blood RNA modification markers m 7 Application of G in the preparation of diagnostic kits for PCOS. This invention establishes a high-throughput quantitative detection and analysis platform for RNA modifications based on triple tandem liquid chromatography-mass spectrometry (LC-MS / MS), discovering differential RNA modifications between PCOS patients and controls. These differential RNA modifications were further analyzed by constructing a Bayesian generalized linear model, revealing the presence of m in the peripheral blood of PCOS patients. 7 G can serve as a specific molecular marker for the diagnosis of PCOS. This molecular marker has high sensitivity and is easy to detect in the diagnosis of PCOS.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to peripheral blood RNA modification markers m 7 Application of G in diagnostic PCOS kits. Background Technology

[0002] The information disclosed in this background section is intended only to enhance understanding of the overall background of the invention and is not necessarily to be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art.

[0003] Polycystic ovary syndrome (PCOS) is a complex and common reproductive endocrine disorder affecting up to 7.8% of women of reproductive age and is one of the leading causes of anovulatory infertility. Common clinical features of PCOS include insulin resistance, irregular menstrual cycles, hyperandrogenemia, and endocrine metabolic abnormalities. Its etiology is complex and diverse, and its clinical manifestations are heterogeneous, making it difficult to standardize the diagnostic criteria for PCOS.

[0004] PCOS is the result of the combined effects of genetic susceptibility and environmental factors. Epigenetics plays a crucial role in its pathogenesis, including DNA methylation, histone modification, and RNA modification. Studies have shown that RNA modification is involved in important processes such as granulosa cell proliferation and apoptosis. PCOS patients exhibit altered RNA modification levels of Foxo3 and Flot2 mRNA in their granulosa cells, affecting gene expression and contributing to the development of PCOS.

[0005] The commonly used diagnostic criteria for PCOS is the 2003 Rotterdam diagnostic criteria, which state that PCOS can be diagnosed if two of the following three criteria are present: 1) infrequent ovulation or anovulation; 2) hyperandrogenemia or clinical manifestations of hyperandrogenemia (such as hirsutism, acne, etc.); 3) ultrasound examination on days 3-5 of the menstrual cycle showing an ovarian volume ≥10ml or the presence of ≥12 follicles with a diameter of 2-9mm on either side. In addition, other causes of hyperandrogenemia must be excluded (hyperprolactinemia, thyroid disease, congenital adrenal hyperplasia, Cushing's syndrome, androgen-secreting tumors, 21-hydroxylase deficiency atypical adrenal hyperplasia, etc.). Based on current diagnostic criteria, multiple blood tests are required for several examinations, including: estrogen, testosterone, follicle-stimulating hormone, luteinizing hormone, prolactin, progesterone, anti-Miller hormone, dehydroepiandrosterone, sex hormone-binding globulin, fasting blood glucose, fasting insulin, and oral glucose tolerance test. Ultrasound examination includes two methods: transabdominal ultrasound and transvaginal (rectal) ultrasound. Abdominal ultrasound is often affected by intestinal gas and upper abdominal fat, making it difficult to clearly show the corticomedullary and medullary blood flow. Although transvaginal (rectal) ultrasound can avoid the disadvantages of transabdominal ultrasound, it is often affected by the operator's operation method and subjectivity, making it impossible to accurately estimate the volume of the ovary and follicles, affecting the accuracy of subsequent diagnosis.

[0006] With the development of biotechnology, molecular biomarkers have provided new insights into the diagnosis of PCOS. Currently, molecular diagnostic markers for PCOS include metabolites, follicle count, and SNP markers. However, traditional diagnostic methods still require a combination of medical history, ultrasound, and various immunochemical reagent kits, which presents drawbacks such as complexity, high cost, and strong subjectivity. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a peripheral blood RNA modification marker m 7 Application of G in the preparation of diagnostic kits for PCOS. This invention establishes a high-throughput quantitative detection and analysis platform for RNA modifications based on triple tandem liquid chromatography-mass spectrometry (LC-MS / MS), discovering differential RNA modifications between PCOS patients and controls. These differential RNA modifications were further analyzed by constructing a Bayesian generalized linear model, revealing the presence of m in the peripheral blood of PCOS patients. 7 G can serve as a specific molecular marker for the diagnosis of PCOS. This molecular marker has high sensitivity and is easy to detect in the diagnosis of PCOS.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0009] In a first aspect, the present invention provides peripheral blood RNA modification marker m 7Application of G in the preparation of diagnostic PCOS kits.

[0010] The beneficial effects achieved by one or more technical solutions of the present invention are as follows:

[0011] This invention utilizes LC-MS / MS to identify and quantify 15 RNA modification types in the peripheral blood of a training cohort: m 2 ,2,7 G,m 1 A,m 7 G,m 5 C,m 5 U,m 1 G,m 2 G,m 2,2 G,Gm,I,Am,Im,m 6 A, Cm, Um, among which Cm is expressed the highest, m 2,2,7 G expression was lowest. Compared to healthy control patients, guanine and m were present in the peripheral blood of PCOS patients. 7 The level of G modification increased significantly.

[0012] The results of fitting analysis using a Bayesian generalized linear model show that, in the discovery cohort, incorporating 15 RNA modification markers and their quantitative information into Model 1 achieves an accuracy AUC of 1.00; 7 G is the modification with the most significant difference, which will change m 7 Quantitative information of G was incorporated into the construction of Model 2, which achieved an accuracy AUC of 0.954. Validation was performed in the validation queue, and the results showed that Model 1 achieved an AUC of 0.923 and Model 2 achieved an AUC of 0.889.

[0013] This invention, based on a high-throughput RNA modification detection platform using LC-MS / MS and machine learning methods, discovers a specific biomarker for RNA modification in PCOS—m. 7 G, its high sensitivity and sensitivity indicate m 7 G can serve as a specific molecular marker for the diagnosis of PCOS and can be used in the development of PCOS diagnostic kits. Attached Figure Description

[0014] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0015] Figure 1 This is a schematic diagram of the detection, screening, and model validation process for peripheral blood RNA modification biomarkers in this invention;

[0016] Figure 2This is a comparison of the expression of different RNA modification types in peripheral blood in Example 1;

[0017] Figure 3 The m values ​​represent the control group and the PCOS patient group in Example 1. 7 G-modified horizontal comparison chart;

[0018] Figure 4 This is a graph showing the principal component analysis results of the types and quantities of RNA modification markers in Example 2;

[0019] Figure 5 This is a graph showing the fitting analysis results of the Bayesian generalized linear model constructed in Example 2. Figure a shows the fitting analysis results of 15 RNA modification markers and their quantitative information incorporated into Model 1, and figure b shows the fitting analysis results of m... 7 Quantitative information about G is incorporated into the fitting analysis results of Model 2;

[0020] Figure 6 The images show the results of the Bayesian generalized linear model being validated in the validation queue in Example 3. Image a shows the validation results of Model 1, and image b shows the validation results of Model 2. Detailed Implementation

[0021] As mentioned earlier, traditional diagnostic methods still require a combination of medical history taking, ultrasound, and multiple immunochemical reagent kits, which is complex, costly, and subjective. With the development of biotechnology, molecular biomarkers have provided new insights into the diagnosis of PCOS. Currently, molecular diagnostic markers for PCOS include metabolites, follicle count, and SNP markers. RNA modification is a novel, non-invasive, highly sensitive diagnostic substance that plays an important role in the pathogenesis of PCOS; however, there are no reports on the application of RNA modification biomarkers in the diagnosis of PCOS.

[0022] In a first typical embodiment of the present invention, peripheral blood RNA modification marker m 7 Application of G in the preparation of diagnostic PCOS kits.

[0023] In one or more embodiments of this implementation, the kit includes a detector for m. 7 Reagent for detecting G modification level.

[0024] In one or more embodiments of this implementation, the test sample of the kit is peripheral blood.

[0025] The detection, screening, and model validation process of peripheral blood RNA modification biomarkers in this invention is as follows: Figure 1 As shown, it includes the following steps:

[0026] Step 1: Using an LS-MS / MS triple tandem liquid chromatography-mass spectrometry system, quantitative detection of multiple types of RNA modifications was performed on blood samples from PCOS patients and healthy volunteers.

[0027] Step 2 involves using machine learning to analyze the types and levels of RNA modifications obtained in Step 1 to construct an integrated model for PCOS diagnosis.

[0028] Step 3: Apply the integrated model built in Step 2 to the verification queue for verification.

[0029] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below with reference to specific embodiments and comparative examples.

[0030] Example 1

[0031] Types and quantitative detection of RNA modifications

[0032] 1.1 RNA extraction

[0033] Peripheral blood was collected from patients, and total RNA was extracted according to the Trizol LS reagent instructions. RNA concentration was then measured.

[0034] 1.2 RNA hydrolysis

[0035] RNA was digested into single nucleotides according to the system shown in Table 1, wherein the 10X reaction buffer contained Tirs-HCl (2.5M, pH 8.0), MgCl2 (50mM), and BSA (5mg / mL).

[0036] Table 1 Composition of the RNA hydrolysis system

[0037]

[0038] The above system was reacted in a PCR instrument at 37°C for 3 hours. After the reaction was completed, 50 μL of the reaction mixture was transferred to an ultrafiltration concentration tube (Nanosep 3K). Then, it was centrifuged at 14,000 rpm and 4°C for 20 minutes. The filtrate in the collection tube was transferred to a chromatographic sample vial with an inner tube. Note that no air bubbles should be generated in the inner tube for subsequent mass spectrometry detection.

[0039] 1.3 Preparation of LC-MS / MS Standards

[0040] The RNA-modified standard was prepared into a 1 mg / mL concentrate and stored at -20°C. It was then diluted in a ratio of 100:50:20:10:4:2:1 to obtain a series of standards with gradient concentrations, which were used as external standards. 100 μL of each standard was then placed into chromatographic vials.

[0041] 1.4 LC-MS / MS detection of samples

[0042] The mobile phase and pump washing solution are prepared as follows: Mobile phase A is a 0.1% aqueous solution of formic acid, mobile phase B is an acetonitrile solution containing 0.1% formic acid, and pump washing solution is 10% isopropanol.

[0043] Set the liquid chromatography parameters as follows: sample cell temperature is 4℃; column temperature is 36℃; injection method is automatic needle washing injection; mobile phase flow rate is set to 0.4mL / min; phase B is set with a gradient that changes over time, as shown in Table 2; the liquid is set to flow into the waste liquid cell from 0 to 1 min, and the liquid after 1 min enters the mass spectrometer for detection.

[0044] Table 2. Phase B parameters of liquid chromatography

[0045]

[0046] Setting the mass spectrometer ion source parameters: Based on the recommendations in the Thermo Fisher Vantage mass spectrometer user guide, and in conjunction with the liquid chromatography method described above, set the mass spectrometer ion source parameters.

[0047] Set compound parameters: Set the parent ion, daughter ion, retention time, ion collision energy (CE), and Tube Lens value for each compound to be tested.

[0048] Equilibration column: At a constant temperature of 36℃, use an A-phase equilibration column with a flow rate of 0.4 mL / min. Experiments can only be carried out after the column pressure has stabilized.

[0049] Create a new batch sequence file in the Setup Sequence module of Xcalibur software, edit the sample sequence information, including sample name, detection order, data save path, sample location, sample loading volume and detection method, and set the system to automatically stop running after the last sample is detected.

[0050] Start testing.

[0051] 1.5 Quantitative Analysis of Mass Spectrometry Data

[0052] Quantitative analysis of mass spectrometry results was performed using the Quan Browser module on the Xcalibur workstation.

[0053] Retrieve the sequence file from the mass spectrometry detection, select the pre-set data processing method, and analyze all samples; select Show All Sample Type to extract the quantified mass spectrometry data; export the data to obtain the mass concentration of the compounds, and then calculate their molar concentrations.

[0054] The relative content of the compounds was compared and analyzed, and the calculation formula is as follows (in m).5 Taking C as an example, m 5 C, Cm, ac 4 C and 5hmC are both modifications of C:

[0055] m 5 C%=mol(m 5 C) / [mol(m 5 C) + mol(Cm) + mol(ac) 4 C)+mol(5hmC)+mol(C)].

[0056] like Figure 2 As shown, 15 RNA modification types were identified and quantified in the peripheral blood of the training cohort: m 2,2,7 G,m 1 A,m 7 G,m 5 C,m 5 U,m 1 G,m 2 G,m 2,2 G,Gm,I,Am,Im,m 6 A, Cm, Um, among which Cm is expressed the highest, m 2,2,7 G expression is lowest. For example... Figure 3 As shown, compared to healthy control patients, the m value of guanine in the peripheral blood of PCOS patients is higher. 7 The level of G modification increased significantly.

[0057] Example 2

[0058] Building an integrated model for PCOS diagnostics

[0059] 2.1 Principal Component Analysis (PCA)

[0060] Principal component analysis (PCA) was performed on the types and quantities of RNA modification markers obtained in Example 1. Figure 4 As shown, principal component 1 (PC1) can explain 46.1% of the sample variability, and PC2 can explain 19.4% of the sample variability. The PCOS and control groups are highly distinguishable. Samples from the same group are clustered together, while samples from different groups are far apart and can be completely separated on PC2. There are significant differences between the control group and PCOS patients.

[0061] 2.2 Constructing a Bayesian generalized linear model for fitting analysis

[0062] In the discovery cohort (26 control group and 30 PCOS patients), 15 RNA modification markers and their quantitative information were incorporated into the construction of model 1, such as... Figure 5 The accuracy AUC shown in 'a' is 1.00; m 7G is the modification with the most significant difference, which will change m 7 Quantitative information about G is incorporated into the construction of Model 2, such as Figure 5 As shown in b, its accuracy AUC reaches 0.95.

[0063] Example 3

[0064] The two Bayesian generalized linear models constructed in Example 3 were validated in a validation cohort (20 controls and 22 PCOS patients). Figure 6 As shown, the AUC of Model 1 reached 0.923; the AUC of Model 2 reached 0.889.

[0065] The results indicate that peripheral blood RNA modification markers can accurately diagnose PCOS, among which m 7 G modification can serve as a specific molecular marker for the diagnosis of PCOS.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. Detection of RNA m in peripheral blood of subjects 7 Application of G-modified reagents in the preparation of diagnostic PCOS kits.

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