A biomarker for evaluating ovarian reserve function, a detection kit and application thereof

Abstract

The present application relates to the technical field of biomarkers, and particularly relates to a biomarker combination for evaluating ovarian reserve function, a detection kit and application thereof. In the prior art, there is a lack of early prediction means for reduced ovarian reserve function, and clinical diagnosis relies on hormone levels and ultrasonic examination, which has the problems of low sensitivity and limited prediction capability. To solve the above problems, multiple serum protein marker combinations significantly related to reduced ovarian reserve function are screened and determined by proteomic sequencing and differential analysis on serum samples of patients. The combinations can be used for early prediction of reduced ovarian reserve function, and have high sensitivity and specificity. The marker combinations of the present application can be used for developing in vitro diagnostic products, and are suitable for female fertility evaluation and individualized assisted reproductive program selection, and can provide scientific basis for early screening and precise intervention of ovarian function related diseases.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of biomarkers, and in particular, the application relates to a biomarker for evaluating ovarian reserve function, a detection kit and application thereof. BACKGROUND

[0002] Reproductive aging, as one of the most critical pathogenic factors of infertility, not only includes physiological aging, but also aging caused by various environmental, lifestyle and pathological factors, which seriously threatens female reproductive health and fertility outcomes. Diminished ovarian reserve (DOR) is manifested as a decrease in the number and / or quality of oocytes, which further affects ovarian function and fertility. According to the "Expert Consensus on Clinical Diagnosis and Treatment of Diminished Ovarian Reserve" (Chinese Journal of Obstetrics and Gynecology, 2023), DOR has been clearly identified as an independent diagnosis and treatment object in clinical practice. Its common manifestations include reduced ovarian responsiveness, shortened cycle, infertility, etc. The incidence rate is showing an increasing trend year by year, and there is a trend of younger onset. The recommended diagnostic criteria proposed in the consensus are: anti-Mullerian hormone (AMH) <1.1 ng / mL, antral follicle count (AFC) <5-7, and basal follicle-stimulating hormone (FSH) ≥10 IU / L. The pathogenesis of DOR is complex, and there are usually no obvious clinical symptoms in the early stage, and it is often identified after assisted reproductive failure or reduced ovarian response.

[0003] Some studies have found, through joint analysis of transcriptome, methylation and metabolome, that multiple metabolic pathways in the granulosa cells of patients with premature ovarian insufficiency (POI) are restructured, among which lipid metabolism abnormalities are particularly significant. Given that DOR is widely considered to be a precursor stage of POI, related lipid metabolism disorders may have already occurred in the early stage of DOR. Sphingomyelin is a bioactive lipid widely distributed in cell membranes and involved in various signal transductions. Its metabolic abnormalities can lead to abnormal accumulation of key downstream molecules such as ceramide. Ceramide is a core intermediate and structural basis in the sphingolipid metabolic pathway and is considered to be one of the most lipid toxic lipids, widely involved in pathological processes such as apoptosis, aging and inflammatory response. Therefore, the present application focuses on the expression level of ceramide in follicular fluid and explores its feasibility as an early prediction marker for diminished ovarian reserve. It has a clear mechanism and good clinical application prospect.

[0004] Current clinical diagnosis of DOR mainly relies on hormone level detection (such as FSH, AMH) and evaluation of antral follicle count (AFC). However, these indicators are greatly affected by physiological cycle fluctuations, have obvious individual differences, and are abnormal only after significant decline of ovarian function, making it difficult to identify the early stage of ovarian hypofunction. The existing method is more suitable for reflecting the current state of ovarian reserve rather than the early signal of dynamic monitoring of functional changes, and is prone to miss the intervention opportunity. Therefore, it has important clinical value to develop a more sensitive, stable and early warning biomarker. At present, there is no rapid and standardized diagnostic kit for ovarian hypofunction, which limits the early identification and precise management of related diseases. The present application constructs a model based on the ceramide level in follicular fluid, avoids cycle dependence and directly reflects the lipid metabolism state in the local microenvironment of the ovary, is suitable for real-time judgment of ovarian status in assisted reproductive cycles, and can more sensitively capture early abnormal signals of ovarian function, and has application prospect. SUMMARY

[0005] In order to fill the gap in the early identification of ovarian reserve function decline in the prior art, the present application provides an application of ceramide for evaluating ovarian reserve function, in particular to ceramide as a biomarker in the preparation of a kit for evaluating ovarian reserve function and a use method. The specific technical solutions are as follows:

[0006] In one aspect of the present application, a group of biomarkers for diagnosing ovarian reserve function decline is provided, the biomarkers comprising a plurality of metabolites selected from ceramide components. The biomarkers can be used for evaluation and diagnosis of ovarian reserve function decline in a subject.

[0007] In one aspect of the present application, the application of ceramide as a biomarker in the evaluation of ovarian reserve function is provided, which is suitable for the auxiliary diagnosis of ovarian hypofunction, preferably for the early prediction of DOR.

[0008] In one embodiment, the biomarker refers to a metabolic product present in a biological sample of a subject, the subject can be a human or other mammal, and the biological sample includes but is not limited to follicular fluid, serum, urine or feces, preferably follicular fluid.

[0009] In a preferred embodiment, the metabolic product is one or more ceramides, including but not limited to 16:0 Ceramide, 18:0 Ceramide, 22:0 Ceramide, 24:1 Ceramide, etc.

[0010] In another embodiment, the present application also provides a kit for assisting in assessing the status of ovarian function, comprising ceramide standard, sample pretreatment solution, detection analysis instruction and reference standard value table, suitable for mass spectrometry platform detection. The kit is used for diagnosing ovarian reserve function. The kit further comprises an extraction solution, which is composed of chloroform and methanol, and the volume ratio is 2:1. Further, the kit further comprises a 700 μL 96-well plate, a 350 μL V-shaped 96-well plate, a sealing plate silica gel, and a 96-well sealing aluminum film.

[0011] In another aspect of the present application, a method for using the above-mentioned kit for diagnosing reduced ovarian reserve function is provided, specifically, by determining the levels of metabolites in the follicular fluid of the subject, and inputting these determination values into a random forest model to obtain a score cutoff value for judgment.

[0012] In an embodiment, the kit is used for diagnosing the method for using the kit for diagnosing the decline of ovarian reserve function, comprising the following steps: a) preparing different concentrations of metabolite standard solution: preparing different concentrations of standard solution of 6 ceramide substances, including 16:0 Ceramide, 18:0 Ceramide, 18:1 Ceramide, 24:0 Ceramide, 24:0 Ceramide, and 24:1 Ceramide, respectively. Prepare different concentrations of ceramide standard solution: use 6 ceramide substances, including Cer(d18:1 / 16:0), Cer(d18:1 / 18:0), Cer(d18:1 / 18:1), Cer(d18:1 / 20:0), Cer(d18:1 / 24:0), and Cer(d18:1 / 24:1(15Z)) as raw materials, accurately weigh an appropriate amount of standard, and add a mixed solution of chloroform / ethanol / DMSO (v / v / v) in a volume ratio of 5:4:1, and ultrasonic dissolution. After uniform dispersion in an ice bath, it is ready for use; b) internal standard solution preparation: take 10 μL of 25 mmol / L Cer 19:0 (ceramide) stock solution in methanol to 10 mL, and mix thoroughly to obtain a 25 μmol / L internal standard working solution. Add the internal standard solution to the 96-well microplate; c) follicular fluid sample preparation and sample addition: prepare the 700 μL microplate provided by the kit, and add 5 μL of concentration gradient standard or blank control to A1-A8 wells, and add 2 μL of test follicular fluid sample or 2 μL of low, medium, and high concentration quality control to the other wells, while adding 2 μL of internal standard working solution. Cover with a silicone cover, shake at 1000 rpm for 10 min. Centrifuge at 2000g for 2 min, gently remove the silicone cover to avoid spilling of the liquid in the micro-well, and cover the cover to prevent contamination. d) Add 350 μL of loading buffer to each well, cover and shake vigorously; -20°C for 20 min, then centrifuge at 2000g for 20 min. Take 150 μL of supernatant and move it to a clean V-shaped microplate, cover with aluminum foil, and place it in the automatic sampler for testing. e) Quantitative analysis and result judgment: detect the peak area of each ceramide in the sample by LC-MS / MS, calculate the concentration according to the standard curve, input the random forest model for analysis, and obtain the biomarker concentration score. According to the threshold value, judge whether the ovarian reserve function is reduced.

[0013] In an embodiment, the random forest model applied by the present application can be a software available on the market, which can also be optionally part of the above-mentioned kit. As a preferred solution, the software package is part of the kit.

[0014] In a preferred embodiment, the extraction step of ceramides is as follows: take 50 μL of follicular fluid sample, add 50 μL of pre-cooled triple distilled water, mix well, add 400 μL of chloroform / methanol (2:1, v / v) mixed extraction solution and 10 μL of internal standard solution (such as Ceramide 19:0, 25 μM), vortex mix, and centrifuge at 4°C, 13000 rpm for 10 minutes, collect the lower organic phase, vacuum concentrate or nitrogen blow dry, add methanol / isopropanol (4:1) for redissolution, and use for subsequent mass spectrometry detection.

[0015] In the detection aspect, it is recommended to use an LC-MS / MS platform, an UPLC system with a CSH C18 column (2.1x100mm, 1.7 μm), to separate by gradient elution, and to use positive ion mode and multiple reaction monitoring (MRM) mode for quantification. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings are included to provide a further understanding of the application, and are incorporated in and constitute a part of this specification, illustrate embodiments of the application, and together with the description serve to explain the principles of the application. In the drawings:

[0017] Figure 1 : ROC curve plot of diagnostic value of ceramide combination random forest model;

[0018] Figure 2 : ROC curve plot of ceramide combination random forest model in external validation set. DETAILED DESCRIPTION

[0019] The preferred embodiments of the present application will be described hereinafter with reference to the accompanying drawings, and it is to be understood that the preferred embodiments described herein are illustrative of and not limiting to the present application. Some non-essential improvements and adjustments made by those skilled in the art according to the above summary of the application are also considered to fall within the scope of protection of the present application.

[0020] The experimental methods in the examples not specified in the specific conditions are usually carried out according to the conventional conditions, such as the conditions described in textbooks and experimental guidelines, or the conditions recommended by the manufacturers.

[0021] Example 1 Screening of differential biomarkers

[0022] The test samples in the present application are approved by the local ethics committee and obtain the informed consent of all subjects. A total of 100 subjects are enrolled according to the inclusion criteria, and the basic characteristics are shown in Table 1. The contents of various ceramides in the follicular fluid samples of 50 patients with normal ovarian reserve function (NOR) and 50 patients with confirmed decreased ovarian reserve function (DOR) are detected by liquid chromatography-mass spectrometry (LC-MS), and the detection results are shown in Table 2.

[0023] 1. Collection of follicular fluid

[0024] On the day of oocyte retrieval in patients receiving assisted reproductive technology treatment, follicular fluid containing dominant follicles containing oocytes (diameter >1.4 cm) was collected from DOR patients and healthy control population, and was separated and stored at -80°C until use. The inclusion and exclusion criteria of the clinical cohort population are as follows:

[0025] (1) Inclusion criteria:

[0026] The inclusion criteria for DOR patients are: (1) women of childbearing age between 20 and 40 years old; (2) AMH <1.1 ng / ml, bilateral ovarian AFC <5-7, basal FSH ≥10 IU / L, at least 2 of the 3 criteria are met; (3) patients with complete clinical and IVF cycle information.

[0027] The inclusion criteria for healthy controls are: women aged 20 to 40 years old who have oviduct factors or male factors for oocyte retrieval; regular menstrual cycle; normal ovarian reserve function.

[0028] (2) Exclusion criteria: women in pregnancy, lactation or menopause; women with uterine, ovarian, tubal related diseases or surgical treatment history; women with endocrine and metabolic abnormalities such as hypertension, diabetes, hyperlipidemia, thyroid function abnormalities; cancer patients or those who have received radiotherapy and chemotherapy within five years.

[0029] Table 1 Basic characteristics of the enrolled population

[0030]

[0031] 2. Detection of ceramides in follicular fluid samples

[0032] Sample preparation: The follicular fluid sample was slowly thawed at 4°C, 50 μL follicular fluid was taken in a 1.5 mL centrifuge tube, 50 μL triple distilled water was added, and mixed well. Then 400 μL chloroform / methanol (2:1, v / v) mixture and 10 μL internal standard solution (internal standard concentration was 25 μM, Cer 19:0) were added to each sample, vortexed for 15 min and then stood for 15 min. Then centrifuged at 13000 rpm for 10 min at 4°C, and the lower organic phase (containing ceramide) was transferred to a new EP tube. The dried sample was stored at -80°C for later use.

[0033] When the sample was redissolved, 100 μL pre-cooled methanol / isopropanol (4:1, v / v) mixture was added, vortexed for 10 min, and centrifuged at 18000 rpm for 10 min at 4°C. 60-70 μL supernatant was taken and transferred to a sample injection bottle containing an internal standard for LC-MS analysis. Finally, 2 μL sample was injected.

[0034] Chromatographic conditions: Waters UPLC CSH C18 column (1.7 μm, 2.1 x 100 mm, Waters, USA) was used, the flow rate was 0.2 mL / min, the column temperature was 40°C, the autosampler temperature was 4°C, and the injection volume was 2 μL. The mobile phase A was water:methanol (7:3) + 0.4% formic acid, and the mobile phase B was methanol:isopropanol (7:3) + 0.4% formic acid. The gradient elution program is shown in Table 2:

[0035] Table 2 Gradient elution program

[0036]

[0037] Mass spectrometry conditions: The positive ion MRM multiple reaction monitoring mode was used. The heating module temperature was 550 °C, GS1 / GS2 was 55 psi, the gas curtain gas was 35 psi, and the ESI ion source voltage was 5500 V. The ion pair, declustering voltage DP, and collision energy CE parameters are shown in Table 3.

[0038] Table 3 Ion pair, declustering voltage DP, and collision energy CE parameters

[0039]

[0040] Determination of the concentration of the diagnostic marker to be tested: In the embodiments of the present application, the target analyte is six ceramide substances, specifically including 16:0 Ceramide, 18:0 Ceramide, 18:1 Ceramide, 20:0 Ceramide, 22:0 Ceramide, and 24:1 Ceramide. The ceramide concentration to be tested is quantified by establishing an external standard curve and combining a stable isotope internal standard (Table 4). The standard curve is established based on the series of concentration gradients of each ceramide standard and its response peak area in mass spectrometric analysis, and the internal standard is Cer-d7 or a functionally equivalent stable isotope-labeled ceramide substance. The internal standard is added to all samples during the pretreatment stage to correct sample processing loss and matrix effect, ensuring the accuracy and repeatability of the data.

[0041] Table 4 Ceramide detection results of follicular fluid

[0042]

[0043] Example 2 Ceramide combination distinguishes normal ovarian reserve function group and reduced ovarian reserve function group

[0044] To distinguish between patients with normal ovarian reserve function and patients with reduced ovarian reserve function, we used the Mann-Whitney U test to select and identify candidate biomarkers, and the results are shown in Table 5. The results show that six ceramide subtypes have significant differences. We selected the six ceramide subtypes with significant differences between the two groups as candidate variables, and used a random forest model to evaluate the candidate variables and establish a model.

[0045] Table 5 Differences in ceramides in follicular fluid between healthy controls and DOR groups

[0046]

[0047] Random forest model building method and related parameter selection: The related model was built in the R-Studio environment of R language. First, the original data was preprocessed, and the data was divided into training set and test set according to the ratio of 5:5. Further, six kinds of ceramides (Cer(d18:1 / 16:0), Cer(d18:1 / 18:0), Cer(d18:1 / 18:1), Cer(d18:1 / 20:0), Cer(d18:1 / 22:0), Cer(d18:1 / 24:1(15Z))) with significant differences between the two groups were selected as input features to build the random forest model, and the diagnostic model was built based on the randomForest function (Ntree = 500 and mtry = 2). pROC was used to draw the receiver operating characteristic (ROC) curve and evaluate the 95% confidence interval (CI) of the area under the curve (AUCs) to measure the prediction performance of the random forest in the training set and the external validation set.

[0048] 50 cases of normal ovarian reserve function (NOR) patients (normal people) and 50 cases of confirmed ovarian reserve function decline (DOR) patients, using the biomarker combination random forest model, the possibility of the above subjects suffering from ovarian reserve function decline can be output, and the best cutoff value can be found by the Youden optimal point in ROC analysis, which can evaluate the total ability of the model to distinguish between ovarian reserve function decline patients and healthy people. The results are shown in Figure 1 The area under the ROC curve is 0.974, the best cutoff value is 0.480, and the specificity and sensitivity percentages at the best cutoff value are 88.0% and 100%, respectively. After these measured values are brought into the random forest model, the specific calculation is as follows: let the biomarker measured value of a subject be represented as a feature vector: The model consists of 500 decision trees, and the output of each tree is: ,

[0049] The DOR risk probability of the individual is:

[0050]

[0051] If the individual score threshold is greater than 0.480, it indicates that the individual has a higher risk of ovarian reserve function decline; if the individual score threshold is less than or equal to 0.480, it indicates that the individual has a lower risk of ovarian reserve function decline.

[0052] To verify the effectiveness of ceramide as a biomarker for detecting diminished ovarian reserve, we further included 15 healthy controls (NOR) and 15 patients with diminished ovarian reserve (DOR), and detected the ceramide concentration in follicular fluid using the kit of the application, and the detection results are shown in Table 6. After substituting these measured values into the diagnostic model, the results are shown in Figure 2 Fig. 6. The area under the ROC curve is 0.951, and the specificity and sensitivity percentages at the cutoff value of 0.480 are 86.7% and 93.3%, respectively. The detection results meet our expectations, and the diagnostic model can still very well distinguish DOR patients and normal people in the external validation set.

[0053] Table 6. Follicular fluid ceramide detection results

[0054]

[0055] The above merely describes preferred embodiments of the present application and is not used to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. The application of a biomarker in the preparation of an in vitro diagnostic kit for assessing ovarian reserve function, characterized in that, The biomarkers include Cer(d18:1 / 16:0), Cer(d18:1 / 18:0), Cer(d18:1 / 18:1), Cer(d18:1 / 20:0), Cer(d18:1 / 22:0) and Cer(d18:1 / 24:1(15Z)).

2. The application according to claim 1, characterized in that, The in vitro diagnostic kit contains a standard solution of the biomarker and an isotope internal standard solution corresponding to the biomarker.

3. The application according to claim 2, characterized in that, The isotopic internal standard is Ce(d18:1 / 16:0), Ce(d18:1 / 18:0), Ce(d18:1 / 18:1), Ce(d18:1 / 20:0), Ce(d18:1 / 22:0) and Ce(d18:1 / 24:1(15Z)) labeled with deuterium (^2H) or carbon-13 (^13C).

4. The application according to claim 2, characterized in that, The kit also includes an extraction solution composed of chloroform and methanol.

5. The application according to claim 2, characterized in that, The kit further includes a 96-well plate for sample processing, a V-shaped 96-well plate, sealing silicone, and a 96-well sealing aluminum film.

6. The application according to any one of claims 1-5, characterized in that, The method of using the kit is as follows: (1) Collect biological samples from the subjects; (2) The concentrations of Cere (d18:1 / 16:0), Cere (d18:1 / 18:0), Cere (d18:1 / 18:1), Cere (d18:1 / 20:0), Cere (d18:1 / 22:0), and Cere (d18:1 / 24:1(15Z)) in biological samples were detected using the kit described above; (3) Input the detected biomarker concentrations into the random forest model for calculation and output the risk assessment results of predicted ovarian reserve decline.

7. The application according to claim 6, characterized in that, The optimal cutoff value for the random forest model is 0.

480.

8. The application according to claim 6, characterized in that, The biological samples are selected from follicular fluid, serum, urine, or feces.

9. The application according to claim 6, characterized in that, The detection described in step (2) is mass spectrometry detection.

10. The application according to claim 9, characterized in that, The mass spectrometry detection was performed using an LC-MS / MS platform with a UPLC system and a CSH C18 column. Separation was performed using gradient elution, and quantification was performed using positive ion mode and multiple reaction monitoring mode.

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