DNA methylation segment combination and application for predicting hypertensive disorders complicating pregnancy

Abstract

The present invention provides a DNA methylation segment combination and application for predicting hypertensive disorder complicating pregnancy, a method and device for predicting hypertensive disorder complicating pregnancy, wherein the method utilizes screened peripheral blood DNA methylation segments and adopts a logistic regression method to construct a risk prediction model for hypertensive disorder complicating pregnancy, calculates the risk value of hypertensive disorder complicating pregnancy, and thus can effectively predict the risk of hypertensive disorder complicating pregnancy.

Description

Technical Field

[0001] The present invention relates to the field of reproductive health, and in particular to a DNA methylation segment combination and application for predicting hypertensive disorders complicating pregnancy, a prediction method and device for hypertensive disorders complicating pregnancy, a computer device, and a computer-readable storage medium. Background Art

[0002] Hypertensive disorders of pregnancy (HDP) are a group of conditions in which pregnancy and elevated blood pressure coexist. These conditions are categorized as chronic hypertension complicated by pregnancy (pre-pregnancy hypertension or elevated blood pressure that develops before 20 weeks of gestation), isolated pregnancy-induced hypertension (PIH), and preeclampsia (PE). Isolated pregnancy-induced hypertension (PIH) refers to a complex disorder that develops after 20 weeks of gestation and is characterized by elevated blood pressure (systolic blood pressure ≥140 mmHg and / or diastolic blood pressure ≥90 mmHg), proteinuria, and edema. In severe cases, it can be accompanied by seizures, coma, heart and kidney failure, and even maternal and fetal death. Preeclampsia, a clinical syndrome characterized by hypertension and proteinuria that develops after 20 weeks of gestation, has an incidence of 2% to 3% and can be accompanied by functional impairment of vital organs such as the brain, heart, liver, and kidneys. It is also a major cause of perinatal mortality for both mothers and infants, accounting for 10% to 15% of all maternal deaths.

[0003] Hypertensive disorders complicating pregnancy (HDP) severely impact maternal and fetal health. Its etiology and pathogenesis are complex, and research in this area remains inconclusive. Diagnosis varies widely, and there is no effective cure. Clinically, symptomatic management with measures such as rest, sedation, antispasmodics, blood pressure reduction, indicated diuretics, and close monitoring of the mother and fetus is employed to control the condition. Termination of pregnancy remains the only curative option. This necessitates early identification of pregnant women at high risk for HDP, enabling clinicians to monitor both the mother and the fetus, implement timely and effective interventions, control disease progression, reduce disease severity, and thus improve prognosis. However, there is currently no recognized effective method for predicting the development of HDP. Summary of the Invention

[0004] To solve the above technical problems, the present invention proposes a DNA methylation segment combination and application for predicting hypertensive disorders complicating pregnancy, a prediction method and device for hypertensive disorders complicating pregnancy, a computer device and a computer-readable storage medium, which can effectively predict the risk of developing hypertensive disorders complicating pregnancy.

[0005] One aspect of the present invention provides a DNA methylation segment combination for predicting hypertensive disorder complicating pregnancy, wherein the DNA methylation segment combination is a combination of the following six DNA methylation segments, and the amplicons, corresponding genes, and specific locations on chromosomes of the six DNA methylation segments are:

[0006] (1)Amplicon7, HMGB1, Chr13:31040015-31040215;

[0007] (2)Amplicon18, JMJD6, Chr17:74722858-74723058;

[0008] (3)Amplicon22, CTSA, Chr20:44519758-44519958;

[0009] (4)Amplicon36, PTEN, Chr10:89622381-89622581;

[0010] (5)Amplicon42, LIN28B, Chr6:105404737-105404937;

[0011] (6)Amplicon70, FADS2, Chr11:61583590-61583790.

[0012] Preferably, the six DNA methylation segments are obtained by performing methylation analysis on fasting serum samples of pregnant women in early pregnancy and using the Lasso regression method to screen the amplicons with the greatest impact on pregnancy-induced hypertension.

[0013] Another aspect of the present invention provides a use of the above-mentioned DNA methylation segment combination in predicting hypertensive disorders complicating pregnancy.

[0014] Another aspect of the present invention provides a method for predicting hypertensive disorder complicating pregnancy, using the above-mentioned DNA methylation segment combination to predict the risk of developing hypertensive disorder complicating pregnancy, the method comprising:

[0015] Calculation steps: Based on the expression of the six DNA methylation segments of the sample to be tested, the following logistic regression model is used to calculate the risk value of pregnancy-induced hypertension in the sample to be tested:

[0016]

[0017] Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, βi is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00;

[0018] Judgment steps: When the risk value Y of the sample to be tested is greater than the threshold, the sample is judged to be at high risk for gestational hypertension; when the risk value Y of the sample to be tested is less than the threshold, the sample is judged to be at low risk for gestational hypertension.

[0019] Preferably, the amplicons, corresponding genes and regression coefficients of the six DNA methylation segments are as follows:

[0020] (1)Amplicon7, HMGB1, 51.27;

[0021] (2)Amplicon18, JMJD6, 5.81;

[0022] (3)Amplicon22, CTSA, -10.31;

[0023] (4)Amplicon36, PTEN, 5.50;

[0024] (5)Amplicon42, LIN28B, 5.35;

[0025] (6)Amplicon70, FADS2, 32.93.

[0026] Preferably, the morbidity risk value Y is calculated according to the following formula: logit(Y)=ln(Y / (1-Y)).

[0027] Preferably, the risk threshold P is 0.421.

[0028] Another aspect of the present invention provides a device for predicting hypertensive disorder complicating pregnancy, which uses the above-mentioned DNA methylation segment combination to predict the risk of developing hypertensive disorder complicating pregnancy, and the device comprises:

[0029] The calculation module is configured to calculate the risk value of hypertensive disorder complicating pregnancy based on the expression of the six DNA methylation segments of the sample to be tested using the following logistic regression model:

[0030]

[0031] Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00;

[0032] The judgment module is configured such that when the risk value Y of the sample to be tested is greater than a threshold value, the sample is judged to be at high risk for gestational hypertension; when the risk value Y of the sample to be tested is less than the threshold value, the sample is judged to be at low risk for gestational hypertension.

[0033] Another aspect of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of the above method when executing the computer program.

[0034] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0035] The DNA methylation segment combination and application for predicting hypertensive disorders complicating pregnancy, the prediction method and apparatus for hypertensive disorders complicating pregnancy, the computer equipment and the computer-readable storage medium according to the above aspects of the present invention can effectively predict the risk of developing hypertensive disorders complicating pregnancy.

[0036] These and other features, aspects and advantages of the present application will become better understood with reference to the following description.The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] This specification sets forth the complete and instructive disclosure of the present application, including its best mode of implementation, for those skilled in the art. This specification refers to the accompanying drawings, in which:

[0038] Figure 1 The present invention is a flowchart of a method for predicting hypertensive disorder complicating pregnancy according to an embodiment of the present invention.

[0039] Figure 2 3 is a ROC curve of the method for predicting hypertensive disorder complicating pregnancy according to one embodiment of the present invention.

[0040] Figure 3 This is a diagram showing the configuration of a device for predicting hypertensive disorder complicating pregnancy according to one embodiment of the present invention.

[0041] Figure 4 It is a structural diagram of a computer device according to one embodiment of the present invention. DETAILED DESCRIPTION

[0042] Reference will now be made in detail to the embodiments of the present application, with one or more examples of the embodiments of the present application illustrated in the drawings. Each example is provided for the purpose of explaining the present application, not for the purpose of limiting the present application. Indeed, it will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope or spirit of the present application. For example, features illustrated or described as part of one embodiment can be used with another embodiment to produce a still further embodiment. Therefore, it is intended that the present application covers such modifications and variations as come within the scope of the appended claims and their equivalents. As used in this specification, the terms "first," "second," and the like are used interchangeably to distinguish one component from another and are not intended to indicate the location or importance of each component. As used in this specification, unless the context clearly dictates otherwise, the terms "a," "an," "the," and "said" are intended to indicate the presence of one or more elements. The terms "including," "comprising," and "having" are intended to be inclusive and mean that there may be additional elements in addition to the listed elements. Wherein like numbers represent like elements throughout the drawings, the present invention will be further explained below with reference to specific embodiments.

[0043] An embodiment of the present invention provides a DNA methylation segment combination for predicting hypertensive disorders complicating pregnancy. Based on epigenetic and DNA methylation-related research, the inventors of the present invention collected fasting serum samples from pregnant women in early pregnancy, packaged the samples according to whether they had HDP, constructed a prospective pregnancy cohort biological sample library for hypertensive disorders complicating pregnancy, and used, for example, the Infinium Human Methylation EPIC BeadChip (Illumina) 850K chip for analysis to obtain its DNA methylation segments. The Lasso regression method (least absolute shrinkage and selection operator, minimum absolute value convergence and selection operator algorithm) was used to screen the amplicons that had the greatest impact on the disease, thereby screening the DNA methylation segments with predictive value, and determined an optimized combination of DNA methylation segments to be tested, as the DNA methylation segment combination for predicting hypertensive disorders complicating pregnancy of the present invention. The DNA methylation segment combination is a combination of the following 6 DNA methylation segments, and the amplicons, corresponding genes, and specific locations on chromosomes of the 6 DNA methylation segments are shown in Table 1 below.

[0044] Table 1: DNA methylation region combinations for predicting hypertensive disorders in pregnancy

[0045] Amplicon Gene name Chromosome and corresponding segment interval Amplicon7 HMGB1 Chr13:31040015-31040215 Amplicon18 JMJD6 Chr17:74722858-74723058 Amplicon22 CTSA Chr20:44519758-44519958 Amplicon36 PTEN Chr10:89622381-89622581 Amplicon42 LIN28B Chr6:105404737-105404937 Amplicon70 FADS2 Chr11:61583590-61583790

[0046] An embodiment of the present invention also provides an application of the DNA methylation segment combination of the above embodiment in predicting hypertension complicating pregnancy.

[0047] An embodiment of the present invention further provides a method for predicting hypertensive disorder complicating pregnancy, which uses the DNA methylation segment combination of the above embodiment to predict the risk of developing hypertensive disorder complicating pregnancy. Figure 1 FIG. 1 is a flow chart of a method for predicting hypertensive disorder complicating pregnancy according to an embodiment of the present invention. Figure 1 As shown, the method for predicting hypertension complicating pregnancy according to the embodiment of the present invention includes a calculation step S1 and a judgment step S2.

[0048] In the calculation step S1, the risk value Y of gestational hypertension in the sample to be tested is calculated based on the expression of the six DNA methylation segments in the sample to be tested using the following logistic regression model:

[0049]

[0050] Formula (1) can be regarded as using a straight line to fit the Logit function, and the x in the formula is obtained by maximum likelihood estimation. i , β i with c, where x i is the expression level of the i-th DNA methylation segment, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00, so that under this parameter, the current training sample can be generated with the maximum probability. In addition, n is the number of DNA methylation segments, n = 6. The prediction result of pregnancy-induced hypertension in the pregnant woman to be tested can be calculated and output using formula (1).

[0051] Preferably, the amplicons, corresponding genes and regression coefficients of the six DNA methylation segments are shown in Table 2 below.

[0052] Table 2: Regression coefficients of DNA methylation segments

[0053] Amplicon Gene name Coefficient β Amplicon7 HMGB1 51.27 Amplicon18 JMJD6 5.81 Amplicon22 CTSA -10.31 Amplicon36 PTEN 5.50 Amplicon42 LIN28B 5.35 Amplicon70 FADS2 32.93

[0054] Then calculate the risk value Y according to the following formula (2):

[0055] logit(Y)=ln(Y / (1-Y)) (2)

[0056] According to Table 2 and formula (2), the risk prediction formula for hypertensive disorders complicating pregnancy is as follows:

[0057] ln(Y_HDP / (1-Y_HDP))=-2.00+51.27×Amplicon7+5.81×Amplicon18-10.31×Amplicon22+5.50×Amplicon36+5.35×Amplicon42+32.93×Amplicon70 (Formula 3).

[0058] After obtaining the disease risk value Y of the sample to be tested in the calculation step S1, in the judgment step S2, when the disease risk value Y of the sample to be tested is greater than the threshold, the sample is judged to be at high risk of gestational hypertension; when the disease risk value Y of the sample to be tested is less than the threshold, the sample is judged to be at low risk of gestational hypertension.

[0059] The risk threshold for hypertensive disorders complicating pregnancy can be determined based on the point closest to the upper left corner of the prediction model curve. The optimal risk threshold for hypertensive disorders complicating pregnancy is P = 0.421.

[0060] The following examples illustrate the method for predicting hypertensive disorder complicating pregnancy according to the embodiment of the present invention.

[0061] Experimental samples: The training group included 189 samples of hypertensive disorders complicating pregnancy and 199 healthy controls; the validation group included 94 samples of hypertensive disorders complicating pregnancy and 99 healthy controls.

[0062] The prediction method for hypertensive disorder complicating pregnancy according to the embodiment of the present invention was operated to statistically analyze the accuracy, sensitivity and specificity of the prediction method.

[0063] The results showed that the prediction method for hypertensive disorder complicating pregnancy according to the embodiment of the present invention can effectively identify patients with hypertensive disorder complicating pregnancy before the onset of the disease in both the training group and the validation group.

[0064] The calculation results are as follows:

[0065] Sample 1 (pre-onset sample from a pregnant woman diagnosed with gestational hypertension):

[0066] ln(Y1 / (1-Y1))=-2.00+51.27×0.0925+5.81×0.1185-10.31×0.4337+5.50×0.005394+5.35×0.200+32.93×0.02275=0.808

[0067] Y1=0.671

[0068] The sample value is greater than the threshold value of hypertensive disorders complicating pregnancy (P) (0.421), and is judged to be a high-risk sample for hypertensive disorders complicating pregnancy. The result is accurate.

[0069] Sample 2 (healthy sample):

[0070] ln(Y2 / (1-Y2))=-2.00+51.27×0.0769+5.81×0.13674-10.31×0.521+5.50×0.016646+5.35×0.159+32.93×0.01012=-1.359

[0071] Y2=0.204

[0072] The sample value is less than the threshold value P (0.421) for hypertensive disorders complicating pregnancy, and is judged to be a low-risk sample for hypertensive disorders complicating pregnancy. The result is accurate.

[0073] Table 3 shows the relevant indicators for judging patients with hypertension complicating pregnancy in the training group and the validation group using the prediction method for hypertension complicating pregnancy according to the embodiment of the present invention. Figure 2 3 is a receiver operating characteristic curve (ROC) of the method for predicting hypertensive disorder complicating pregnancy according to an embodiment of the present invention.

[0074] In Table 3, the area under the curve (AUC) represents the probability that the predicted value for the diseased sample is greater than that for the healthy sample, given a random sample of healthy and a random sample of diseased patients. Common prediction models include the following descriptive variables: correctly predicted diseased (TP), incorrectly predicted diseased (FP), correctly predicted healthy (TN), and incorrectly predicted healthy (FN). Accuracy is calculated as (TP + TN) / (TP + TN + FP + FN), which measures the degree to which the measured result closely matches the true result. Sensitivity is calculated as TP / (TP + TN + FP + FN), which reflects the model's prediction of diseased conditions. Specificity is calculated as TN / (TP + TN + FP + FN), which reflects the model's prediction of healthy patients.

[0075] Table 3: Relevant indicators for judging patients with hypertension complicating pregnancy according to the embodiment of the present invention

[0076] AUC (95% CI) accuracy Sensitivity Specificity Training Group 0.824(0.782-0.867) 0.776 0.772 0.779 Validation Group 0.784(0.719-0.848) 0.746 0.883 0.616

[0077] Figure 2 For the intuitive expression of ROC curve, Figure 1 In the example, starting from (0, 0) and ending at (1.0, 1.0), the AUC under the function is calculated to reflect the comprehensive effectiveness of the model, where the horizontal axis is 1-specificity and the vertical axis is sensitivity.

[0078] In summary, the present invention constructs a new-onset hypertensive disorder complicating pregnancy risk prediction model by utilizing the screened DNA methylation segments in the patient's peripheral blood. This prediction model is fast, convenient, highly accurate, and reasonably designed. It provides a theoretical basis for the early prediction and prevention of HDP progression, thereby enabling early detection and strict management of high-risk groups, alleviating the disease, prolonging gestational age, improving prognosis, and ultimately reducing maternal and infant mortality.

[0079] The present invention also provides a device for predicting hypertensive disorder complicating pregnancy, which uses the DNA methylation segment combination of the above-mentioned embodiment of the present invention to predict the risk of developing hypertensive disorder complicating pregnancy. Figure 3 FIG. 1 is a diagram showing a configuration of a device for predicting hypertensive disorder complicating pregnancy according to an embodiment of the present invention. Figure 3 As shown, the prediction device for hypertensive disorder complicating pregnancy according to the embodiment of the present invention comprises:

[0080] The calculation module 101 is configured to calculate the risk value of hypertensive disorder complicating pregnancy based on the expression of the six DNA methylation segments of the sample to be tested using the following logistic regression model:

[0081]

[0082] Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00;

[0083] The judgment module 102 is configured to judge the sample as being at high risk for gestational hypertension when the risk value Y of the sample to be tested is greater than a threshold; and judge the sample as being at low risk for gestational hypertension when the risk value Y of the sample to be tested is less than the threshold.

[0084] Specific embodiments of the device for predicting hypertensive disorders complicating pregnancy in this embodiment can be found in the above-mentioned definition of the method for predicting hypertensive disorders complicating pregnancy and will not be further elaborated here. Each module in the device for predicting hypertensive disorders complicating pregnancy can be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, allowing the processor to call and execute the corresponding operations of each module.

[0085] The embodiment of the present invention further provides a computer device, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 2As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store operating parameter data of each framework. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the steps of the method for predicting hypertensive disorder complicating pregnancy of this embodiment are implemented.

[0086] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0087] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for predicting hypertensive disorder complicating pregnancy according to an embodiment of the present invention.

[0088] The above is a preferred embodiment of the present invention. For those skilled in the art, other variations and improvements can be made based on the technical solutions and inventive essence disclosed in the present invention, but these variations and improvements based on the present invention should all be included in the scope of protection of the present invention. This specification uses embodiments to disclose the present application, including the best embodiments, and also enables those skilled in the art to practice the present application, including making and using any device or system and performing any incorporated method. The patentable scope of this application is defined by the claims and may include other embodiments that occur to those skilled in the art. If such other embodiments include structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are not substantially different from the literal language of the claims, then they are defined to be within the scope of the claims.

Claims

1. A device for predicting hypertensive disorder complicating pregnancy, characterized in that: The device is used to predict the risk of developing hypertensive disorders complicating pregnancy using a combination of DNA methylation segments, the device comprising: The calculation module is configured to calculate the risk value of hypertensive disorders complicating pregnancy based on the expression of the six DNA methylation segments of the sample to be tested using the following logistic regression model: Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00; The judgment module is configured to judge the sample as being at high risk for gestational hypertension when the risk value Y of the sample to be tested is greater than a threshold; and judge the sample as being at low risk for gestational hypertension when the risk value Y of the sample to be tested is less than the threshold; The DNA methylation segment combination is a combination of the following 6 DNA methylation segments, and the amplicons, corresponding genes, and specific locations on chromosomes of the 6 DNA methylation segments are: (1)Amplicon7, HMGB1, Chr13:31040015-31040215; (2)Amplicon18, JMJD6, Chr17:74722858-74723058; (3)Amplicon22, CTSA, Chr20:44519758-44519958; (4)Amplicon36, PTEN, Chr10:89622381-89622581; (5)Amplicon42, LIN28B, Chr6:105404737-105404937; (6)Amplicon70, FADS2, Chr11:61583590-61583790; The amplicons, corresponding genes and regression coefficients of the six DNA methylation segments are as follows: (1)Amplicon7, HMGB1, 51.27; (2)Amplicon18, JMJD6, 5.81; (3)Amplicon22, CTSA, -10.31; (4)Amplicon36, PTEN, 5.50; (5)Amplicon42, LIN28B, 5.35; (6)Amplicon70, FADS2, 32.93; Then calculate the risk value Y according to the following formula: logit(Y)=ln(Y / (1-Y)); The risk threshold P is 0.

421.

2. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the following steps of the method for predicting hypertensive disorder complicating pregnancy are implemented: Calculation steps: Based on the expression of the six DNA methylation segments of the sample to be tested, the following logistic regression model is used to calculate the risk value of pregnancy-induced hypertension in the sample to be tested: Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00; Judgment step: when the risk value Y of the sample to be tested is greater than the threshold, the sample is judged to be at high risk for hypertensive disorder complicating pregnancy; when the risk value Y of the sample to be tested is less than the threshold, the sample is judged to be at low risk for hypertensive disorder complicating pregnancy; The DNA methylation segment combination is a combination of the following 6 DNA methylation segments, and the amplicons, corresponding genes, and specific locations on chromosomes of the 6 DNA methylation segments are: (1)Amplicon7, HMGB1, Chr13:31040015-31040215; (2)Amplicon18, JMJD6, Chr17:74722858-74723058; (3)Amplicon22, CTSA, Chr20:44519758-44519958; (4)Amplicon36, PTEN, Chr10:89622381-89622581; (5)Amplicon42, LIN28B, Chr6:105404737-105404937; (6)Amplicon70, FADS2, Chr11:61583590-61583790; The amplicons, corresponding genes and regression coefficients of the six DNA methylation segments are as follows: (1)Amplicon7, HMGB1, 51.27; (2)Amplicon18, JMJD6, 5.81; (3)Amplicon22, CTSA, -10.31; (4)Amplicon36, PTEN, 5.50; (5)Amplicon42, LIN28B, 5.35; (6)Amplicon70, FADS2, 32.93; Then calculate the risk value Y according to the following formula: logit(Y)=ln(Y / (1-Y)); The risk threshold P is 0.

421.

3. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the following steps of the method for predicting hypertensive disorder complicating pregnancy are implemented: Calculation steps: Based on the expression of the six DNA methylation segments of the sample to be tested, the following logistic regression model is used to calculate the risk value of pregnancy-induced hypertension in the sample to be tested: Among them, Y is the risk value of disease, x i is the expression level of the i-th DNA methylation segment, n is the number of DNA methylation segments, n = 6, β i is the regression coefficient of the i-th DNA methylation segment; c is a constant with a value of -2.00; Judgment step: when the risk value Y of the sample to be tested is greater than the threshold, the sample is judged to be at high risk for hypertensive disorder complicating pregnancy; when the risk value Y of the sample to be tested is less than the threshold, the sample is judged to be at low risk for hypertensive disorder complicating pregnancy; The DNA methylation segment combination is a combination of the following 6 DNA methylation segments, and the amplicons, corresponding genes, and specific locations on chromosomes of the 6 DNA methylation segments are: (1)Amplicon7, HMGB1, Chr13:31040015-31040215; (2)Amplicon18, JMJD6, Chr17:74722858-74723058; (3)Amplicon22, CTSA, Chr20:44519758-44519958; (4)Amplicon36, PTEN, Chr10:89622381-89622581; (5)Amplicon42, LIN28B, Chr6:105404737-105404937; (6)Amplicon70, FADS2, Chr11:61583590-61583790; The amplicons, corresponding genes and regression coefficients of the six DNA methylation segments are as follows: (1)Amplicon7, HMGB1, 51.27; (2)Amplicon18, JMJD6, 5.81; (3)Amplicon22, CTSA, -10.31; (4)Amplicon36, PTEN, 5.50; (5)Amplicon42, LIN28B, 5.35; (6)Amplicon70, FADS2, 32.93; Then calculate the risk value Y according to the following formula: logit(Y)=ln(Y / (1-Y)); The risk threshold P is 0.421.

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