System and method for evaluating premature rupture risk of fetal membrane based on leukocyte telomere length and application

Abstract

The invention discloses a system and a method for evaluating premature rupture risk of fetal membranes based on leukocyte telomere length and application, the system comprises a data acquisition module, a data storage module, an analysis processing module and an output module, and covariant data such as leukocyte telomere length measurement value, age and educational level of a pregnant woman to be evaluated are acquired; and calculating a risk level by using a pre-constructed risk assessment model. According to the method, the nonlinear reverse J-type positive correlation between LTL and the premature rupture (PROM) risk is found and confirmed for the first time, a key risk turning threshold value is determined, and a quantitative risk grading system based on quartile is constructed. A brand-new non-invasive early screening tool is provided, objective and quantitative evaluation results can be obtained, early recognition of high-risk pregnant women is facilitated, timely intervention is achieved, and therefore the incidence rate of PROM and complications of PROM is reduced.

Description

Technical Field

[0001] This invention relates to the field of clinical risk assessment technology for premature rupture of membranes, and in particular to a system, method and application for assessing the risk of premature rupture of membranes based on leukocyte telomere length. Background Technology

[0002] Premature rupture of membranes (PROM) refers to the spontaneous rupture of the amniotic sac before labor, with a global incidence of approximately 10%–20%. PROM is a leading cause of preterm birth. Due to the loss of the membranes' barrier function, it easily leads to serious consequences such as maternal and fetal infections, placental abruption, umbilical cord prolapse, and neonatal respiratory distress syndrome, severely threatening the lives and health of both mother and fetus. Although it is known that inflammatory responses, oxidative stress, and apoptosis play crucial roles in the development and progression of PROM, its specific pathogenesis is not yet fully understood. Therefore, establishing an effective early risk assessment method to achieve early intervention (such as enhanced monitoring and lifestyle guidance) and individualized pregnancy management is of great significance for reducing the incidence of PROM and improving pregnancy outcomes.

[0003] Currently, the diagnosis and risk assessment of premature rupture of membranes (PROM) in clinical practice mainly rely on physical examinations or invasive methods, which have many limitations. For example, vaginal secretion pH testing is a commonly used auxiliary diagnostic method, but it cannot accurately distinguish amniotic fluid from other fluids (such as urine, vaginal secretions, or semen), is easily affected by interference leading to false positive results, and is usually used for diagnosis after membrane rupture rather than for risk prediction before rupture. Amniocentesis (amniocentesis) can obtain amniotic fluid for testing, but it is an invasive procedure with high risks, potentially directly inducing PROM, miscarriage, placental abruption, or even stillbirth, and is not suitable as a routine screening method. Ultrasound examination mainly infers membrane rupture indirectly by observing the decrease in amniotic fluid volume, but cannot directly confirm the integrity of the membranes, and changes in amniotic fluid volume are affected by various factors, resulting in low sensitivity and specificity of diagnosis, and a high likelihood of false positives or false negatives. In summary, current technology lacks a non-invasive, objective early biomarker detection method that can be applied in a large-scale population.

[0004] Telomeres are DNA-protein complexes located at the ends of chromosomes, primarily maintaining genome stability. Leukocyte telomere length (LTL) is widely recognized as a biomarker for cellular aging and age-related diseases. Extensive literature reports that shorter LTLs are generally associated with an increased risk of various age-related diseases (such as cardiovascular disease and type 2 diabetes) and adverse health outcomes. In obstetrics, previous research has primarily focused on revealing the association between shortened LTLs and adverse pregnancy outcomes such as preterm birth and spontaneous abortion. However, the specific relationship between LTLs and premature rupture of membranes (PROM) remains unclear. Given the lack of early, non-invasive biomarkers for PROM in current technologies, and the gaps or even potential misleading aspects in existing theories regarding the relationship between LTLs and PROM (i.e., a tendency to focus on the risk of short telomeres), this invention aims to clarify the true association pattern between LTLs and PROM risk through large-sample data analysis, and based on this, develop a non-invasive risk assessment system based on peripheral blood testing to overcome the invasiveness and lag issues of existing detection methods. Summary of the Invention

[0005] To address the shortcomings of the existing technologies, the technical problem to be solved by this invention is: This invention aims to provide a non-invasive risk assessment scheme based on peripheral blood testing, which achieves early, objective and accurate assessment of the risk of premature rupture of membranes by measuring leukocyte telomere length (LTL) and combining it with specific covariate analysis, thereby solving the problems of invasiveness, lag and lack of biomarkers in existing testing methods.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a system for assessing the risk of premature rupture of membranes based on leukocyte telomere length, comprising: The data acquisition module is used to acquire leukocyte telomere length measurements and covariate data of pregnant women to be evaluated. The leukocyte telomere length measurements are obtained based on peripheral blood tests and are expressed as the ratio of telomere repeat sequences (T) to single-copy genes (S), T / S. This includes both intrinsic biological states and important external influencing factors, ensuring the comprehensiveness of the assessment.

[0007] A storage module is used to store a pre-built risk assessment model. This risk assessment model is built based on multi-center cross-sectional survey data and is constructed based on the association between leukocyte telomere length and covariates with the risk of premature rupture of membranes (PROM). This risk assessment model is a mathematical model pre-built from large-scale population data (such as the UK Biobank cohort) capable of characterizing the complex association between LTL, covariates, and PROM risk. Preferably, the multi-center cross-sectional survey data includes a sample size of at least 100,000 pregnant women.

[0008] The analysis and processing module is used to input the measured values ​​of leukocyte telomere length and covariate data into the risk assessment model to obtain the risk assessment results.

[0009] The output module is used to output the premature rupture of membranes risk assessment results for the pregnant woman to be evaluated.

[0010] Preferably, the covariates include age and education level, and the risk assessment model includes interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level. The system introduces "age" and "education level" as key covariates because research has confirmed a significant interaction between these two factors and LTL (P<0.05). By incorporating the interaction term between leukocyte telomere length and these covariates into the risk assessment model, it is shown that these factors moderate the impact of LTL on PROM risk, significantly improving the model's accuracy in individualized assessment. Furthermore, through multi-parameter correction, the system can eliminate prediction biases caused by differences in subjects' lifestyles or physical conditions.

[0011] Preferably, the risk assessment model is configured with a risk threshold, and the analysis and processing module is configured to compare the measured leukocyte telomere length with the risk threshold and determine the risk level based on the comparison result. Specifically, the risk threshold is 0.691; in the risk assessment model, there is an inverse J-shaped nonlinear positive correlation between LTL and PROM risk: when the T / S ratio is less than 0.691, the PROM risk is determined to be lower than the baseline risk (OR=1); when the T / S ratio is greater than 0.691, the PROM risk is determined to be higher than the baseline risk, initially rising sharply, then slowly decreasing and gradually leveling off, and a high-risk warning is output in conjunction with the covariate data. In this way, by setting a precise threshold of 0.691, the system can accurately distinguish between "safe populations" and "high-risk populations," avoiding missed diagnoses or misdiagnoses caused by blindly applying traditional linear models, significantly improving the sensitivity of screening, and overcoming the technical bias in existing technologies that "the shorter the telomere, the higher the risk."

[0012] Preferably, the risk assessment model is configured with a grading strategy based on the distribution of leukocyte telomere length in a reference population; the analysis and processing module is configured to determine the corresponding risk level based on the interval in which the leukocyte telomere length measurement of the pregnant woman to be assessed falls within the distribution. Specifically, the distribution of LTL values ​​is divided into four groups, Q1 to Q4, with Q1 as the reference benchmark. Q1 represents the LTL measurement value falling within the 0th to 25th percentile of the overall sample distribution; Q2 represents the LTL measurement value falling within the 25th to 50th percentile of the overall sample distribution; Q3 represents the LTL measurement value falling within the 50th to 75th percentile of the overall sample distribution; and Q4 represents the LTL measurement value falling within the 75th to 100th percentile of the overall sample distribution. "Large-scale population" and "total sample size" refer to the large benchmark dataset of the reference population used to pre-build the model and set grading thresholds, such as the UK Biobank cohort.

[0013] Another object of the present invention is to provide a method for assessing the risk of premature rupture of membranes based on leukocyte telomere length, comprising the following steps: S1: Obtain leukocyte telomere length measurements and covariate data from the pregnant woman to be evaluated; the leukocyte telomere length measurements are obtained based on peripheral blood testing and are expressed as the ratio T / S of telomere repeat sequences (T) to single-copy genes (S).

[0014] S2: Input the measured leukocyte telomere length and covariate data into a pre-constructed premature rupture of membranes risk assessment model to obtain the risk assessment results; wherein, the risk assessment model is established based on multi-center cross-sectional survey data and constructed based on the association between leukocyte telomere length and covariates and the risk of premature rupture of membranes; the covariates include age and education level; and the risk assessment model includes interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level.

[0015] S3: Based on the results of the risk assessment model, output the risk assessment results corresponding to the pregnant woman to be assessed.

[0016] Preferably, the T / S is obtained by multiplex quantitative polymerase chain reaction; the telomere repeat sequence can be selected from (TTAGGG)n, and the single-copy gene can be selected from 36b4, albumin gene or β-globin gene.

[0017] Preferably, the risk assessment model is configured with a risk threshold; during assessment, the measured value of leukocyte telomere length is compared with the risk threshold, and the risk level is determined based on the comparison result.

[0018] Preferably, the risk assessment model is configured with a grading strategy based on the distribution of leukocyte telomere length in a reference population; during assessment, the corresponding risk level is determined according to the interval in the distribution where the measured leukocyte telomere length of the pregnant woman to be assessed falls.

[0019] Another object of the present invention is to provide a computer-readable storage medium that stores computer instructions which, when executed by a processor, implement the method described herein.

[0020] Another object of the present invention is the application of reagents or kits for detecting leukocyte telomere length in the preparation of products for assisting in the assessment of the risk of premature rupture of membranes in pregnant women, the assessment being based on the method described above.

[0021] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention, for the first time, discovers and confirms a non-linear positive correlation between telomeres (LTL) and prolapsed uterine bleeding (PROM) risk using large-scale population data, and precisely characterizes its "inverse J-shaped" trend. This discovery breaks through the linear mindset and technical bias that "shorter telomeres mean higher risk," providing a completely new perspective for understanding the biological mechanisms of PROM. This invention identifies key inflection points in the association (e.g., T / S ratio ≈ 0.691), providing clear and operable quantitative thresholds for risk stratification. Furthermore, it constructs a specific and objective risk grading system (quartile grading), which can classify pregnant women into different levels such as "low risk," "low-to-medium risk," and "high risk," outputting standardized and quantitative assessment results, greatly improving the operability and consistency of clinical diagnosis.

[0022] 2. This invention not only focuses on LTL itself, but also discovers and verifies for the first time the significant interaction between age and education level in the relationship between LTL and PROM. Based on this, by introducing an interaction term between leukocyte telomere length and this covariate into the risk assessment model to characterize it, the influence of LTL on PROM risk is moderated, significantly improving the accuracy of the model in individualized assessment. Through joint analysis and statistical correction of multidimensional parameters, the system can be dynamically adjusted according to the specific circumstances of individuals. The system can eliminate prediction bias caused by differences in subjects' lifestyles or physical conditions, providing truly personalized risk assessment. Compared with single-indicator model detection, the multi-factor joint model constructed in this invention shows higher consistency and stability in different characteristic populations, and its predictive specificity and sensitivity are significantly improved.

[0023] 3. This invention transforms LTL from a basic research indicator into a biomarker with potential clinical application value, providing a novel diagnostic / screening tool and target for early screening and risk assessment of PROM. This offers a new, non-invasive (through blood testing) approach and method, and opens up new directions for exploring the pathogenesis of PROM. Furthermore, by identifying high-risk pregnant women early, earlier intervention and monitoring can be achieved, potentially reducing the incidence of PROM and its complications (such as preterm birth and infection), resulting in significant social and health benefits. Attached Figure Description

[0024] Figure 1 A flowchart for the screening process of participants in a UK biobank.

[0025] Figure 2 This diagram illustrates the non-linear correlation between leukocyte telomere length and premature rupture of membranes.

[0026] Figure 3 Forest plot showing the association between leukocyte telomere length and the risk of premature rupture of membranes. Detailed Implementation

[0027] The present invention will be further described in detail below with reference to the embodiments.

[0028] Example 1: Construction of a risk assessment model: S1: Obtain sample data of women with a history of pregnancy from the UKB database and clean the sample data. The sample data includes leukocyte telomere length, whether or not the patient has PROM, and covariate data. Divide the samples into case group and control group according to whether or not the patient has had PROM. The covariates include demographic variables, body composition indicators, and health behavior factors.

[0029] 1) Samples and Cleaning: Based on the UK Biobank (UKB) database, which contains questionnaires, anthropometric data, and biosample data from approximately 500,000 participants recruited between 2006 and 2010. The inclusion and exclusion criteria for the subjects of this invention are as follows: Figure 1 As shown, women who had experienced pregnancy and provided informed consent at baseline between 2006 and 2010 were selected as study participants. Participants with missing LTL at baseline, missing covariate data, or those diagnosed with PROM after baseline were excluded. Furthermore, all "don't want to answer" and "don't know" options were treated as missing values. After the above screening, a total of 170,841 participants were ultimately included in the cross-sectional analysis. The study has received ethical approval, approval number 103654.

[0030] 2) Sample data acquisition: Sample data, including leukocyte telomere length (LTL), premature rupture of membranes (PROM), and covariates, were searched and downloaded from the UK Biobank database.

[0031] As an exposure variable, LTL was used in the UKB database. Peripheral blood samples were collected from participants during the baseline survey, and DNA was extracted from leukocytes. Multiplex quantitative polymerase chain reaction (qPCR) was used to determine the copy number of telomere repeats (T) and single-copy genes (S). Specific primer combinations were used: telomere (T) primers targeted the human telomere repeat sequence (TTAGGG)n, and the single-copy gene (S) primer used the internal reference gene 36b4 as the core (albumin gene, β-globin gene, etc., can also be used). The sequences were consistent with the classic qPCR method to ensure amplification specificity. The leukocyte telomere length was ultimately expressed as the ratio of telomere repeats (T) to single-copy genes (S) (i.e., the T / S ratio). To ensure the accuracy and reliability of the measurement, the influence of technical parameters, including enzymes, PCR equipment, primers, operator, temperature, and DNA purity, was further adjusted. The LTL used in this invention is the adjusted T / S ratio (UKB data field 22191).

[0032] PROM was used as the outcome variable. The diagnosis of PROM was defined by participants' self-reports at baseline or by the "First Occurrence Field" (data category: 2415) provided by UKBiobank. The "First Occurrence Field" includes data from primary care, hospital inpatient records, self-reported medical conditions, and death registries, and primarily uses the 10th edition of the International Classification of Diseases (ICD10) for disease diagnosis. In this study, we used UKBiobank data field 132230 for PROM.

[0033] Participants provided personal information as covariates regarding age, race, body mass index (BMI), waist circumference, hip circumference, alcohol consumption status, smoking status, health score, education level, and basal metabolic rate through a touchscreen questionnaire and body measurements during the baseline survey. The age at which patients first visited the assessment center was selected as the age variable in this study. BMI was categorized according to international standards as underweight (BMI < 18.5 kg / m²), normal weight (18.5 kg / m² ≤ BMI < 25 kg / m²), overweight (25 kg / m² ≤ BMI < 30 kg / m²), and obese (BMI ≥ 30 kg / m²). Alcohol consumption status was categorized as never drinking, past drinking, and current drinking. Smoking status was categorized as never smoking, past smoking, and current smoking. Health score was categorized as excellent, good, average, and poor. Educational level was categorized into undergraduate or associate degrees, UK A / AS levels or equivalent, UK O levels / GCSE or equivalent, UK CSE certificates or equivalent, National Vocational Qualifications (NVQ) / Higher National Diplomas (HND) / Higher National Certificates (HNC) or equivalent, and other professional qualifications. We also collected waist circumference, hip circumference, and basal metabolic rate as continuous variables for analysis.

[0034] S2: Baseline analysis of leukocyte telomere length and covariate data in the sample data was performed using R software.

[0035] Specifically, the study population was divided into case and control groups based on whether they had a history of PROM. Baseline analysis of the LTL and covariate data was performed using R software to observe whether there were significant differences in LTL and covariates between the case and control groups (see Table 1). Specifically: for normally distributed continuous variables, analysis of variance was used, and the results were expressed as mean ± standard deviation (mean ± SD); for non-normally distributed continuous variables, nonparametric tests were used, and the results were expressed as median and interquartile range (IQR); for categorical variables, chi-square test or Fisher's exact test was used, and the results were expressed as frequency and percentage (n, %). All statistical analyses were performed using R software (version 4.3.3). A two-tailed p-value < 0.05 was considered statistically significant, and the same applies below.

[0036] Table 1 Baseline characteristics of participants in the UK Biobank

[0037] The results showed that the LTL in the case group was longer than that in the control group, and this was statistically significant.

[0038] S3: Restricted cubic spline analysis was performed using the RMS package in R software, with three nodes: LTL as exposure and PROM as outcome, to assess the potential nonlinear relationship between the two. The results are as follows: Figure 2 As shown.

[0039] The results show a non-linear relationship between LTL and PROM risk, exhibiting an inverse J-shaped trend. Furthermore, as LTL increases, PROM risk initially rises and then falls. When LTL is less than 0.691, PROM risk increases significantly but remains below the baseline risk (OR=1), indicating relatively low PROM risk. When LTL is greater than 0.691, PROM risk initially rises sharply, then slowly declines and gradually levels off, but the overall risk remains significantly higher than the baseline level. This suggests that LTL may have different impacts on PROM risk within different ranges.

[0040] S4: Based on steps S2 and S3, a logistic regression model is used to establish a risk assessment model between LTL and PROM, and the correlation and strength of the correlation between the two are analyzed.

[0041] Specifically, three progressively adjusted regression models were constructed: Model 1 was an unadjusted coarse analysis model that directly assessed the original association between LTL and PROM risk; Model 2, based on Model 1, incorporated demographic variables and basal metabolic rate; Model 3, based on Model 2, further incorporated body composition indicators and health behavior factors. The demographic variables included age, ethnicity, and education level; the body composition indicators included BMI, waist circumference, and hip circumference; and the health behavior factors included alcohol consumption status, smoking status, health score, and basal metabolic rate. All results were quantified using odds ratios (OR) and their 95% confidence intervals (95% CI) to assess the strength of the association between LTL and PROM risk. Furthermore, we divided the distribution of LTL values ​​into quartiles (Q1~Q4), using Q1 as the reference benchmark. Specifically, Q1 represents the LTL measurement value falling within the 0th to 25th percentile of the overall sample distribution; Q2 represents the LTL measurement value falling within the 25th to 50th percentile; Q3 represents the LTL measurement value falling within the 50th to 75th percentile; and Q4 represents the LTL measurement value falling within the 75th to 100th percentile, as shown in Table 2 and... Figure 3 As shown.

[0042] Table 2. Association between leukocyte telomere length and premature rupture of membranes among UK Biobank participants.

[0043] The results showed that from Model 1 (unadjusted) to Model 3 (fully adjusted), the odds ratio for each standard deviation (SD) increase in LTL decreased from 5.36 to 1.97. This significant decrease indicates that factors such as age, race, education level, metabolism, and lifestyle are important confounding variables, and their effects would be severely overestimated if not controlled. Furthermore, after maximally adjusting for confounding factors (Model 3), the association remained highly significant (P=0.001, OR=1.97), demonstrating that the association between LTL and PROM is independent and robust, and not driven by other common risk factors. Comparing the results of Model 1, Model 2, and Model 3, Model 3 was ultimately used to accurately assess the independent association between LTL and PROM risk. After adjusting for all covariates, the risk of PROM significantly increased for each unit standard deviation (0.132) increase in LTL (OR=1.97, 95%CI: 1.30–2.95, P=0.001). Compared to Q1, the risk of PROM was not significantly increased in Q2 (OR=1.16, P=0.12), indicating that a slight increase in LTL may not pose an additional risk relative to the shortest LTL. However, the risk of PROM increased significantly in both Q3 and Q4 LTLs (OR=1.33, 95%CI: 1.11–1.59, P=0.003; OR=1.31, 95%CI: 1.09–1.56, P=0.003), with a significant increase of 33% in Q3 and 31% in Q4. This indicates that a longer LTL is an independent risk factor for PROM, and there is a complex non-linear pattern between the two. In conclusion, a slightly longer LTL does not necessarily lead to risk; rather, the risk only increases significantly after exceeding a certain level. Therefore, the analysis and processing module is configured as follows: when the T / S ratio to be evaluated falls into Q1, the output module outputs "low risk"; when the T / S ratio to be evaluated falls into Q2, the output module outputs "low to medium risk"; when the T / S ratio to be evaluated falls into Q3, the output module outputs "high risk" and indicates that compared with the reference benchmark, the PROM risk has increased significantly, with an odds ratio of 1.33; when the T / S ratio to be evaluated falls into Q4, the output module outputs "high risk" and indicates that compared with the reference benchmark, the PROM risk has increased significantly, with an odds ratio of 1.31, and for every unit increase in LTL, the overall risk increases by 1.97 times.

[0044] S5: By conducting subgroup analysis and interaction tests on the categorical variables in the covariates, we can verify and quantify the moderating effect of the covariates on the risk relationship between LTL and PROM, and ensure the stability and consistency of the association between LTL and PROM risk under different population characteristics.

[0045] Specifically, based on the research subjects, the covariates such as age, race, BMI, alcohol consumption status, smoking status, health score, and education level were divided into multiple subgroups. BMI was categorized according to international standards into underweight (BMI < 18.5 kg / m²), normal weight (18.5 kg / m² ≤ BMI < 25 kg / m²), overweight (25 kg / m² ≤ BMI < 30 kg / m²), and obese (BMI ≥ 30 kg / m²). Alcohol consumption status was categorized into non-drinkers, former drinkers, and current drinkers. Smoking status was categorized into non-smokers, former smokers, and current smokers. Health score was categorized into excellent, good, average, and poor. Education level was categorized into undergraduate or associate degree, UK A / AS level or equivalent, UK O level / GCSE or equivalent, UK CSE certificate or equivalent, National Vocational Qualification (NVQ) / Higher National Diploma (HND) / Higher National Certificate (HNC) or equivalent, and other professional qualifications. The study aimed to detect the relationship between LTL and PROM in different subgroups and to identify which variables might play a role in the relationship between LTL and PROM. The results are shown in Table 3.

[0046] Table 3 Subgroup analysis of the association between leukocyte telomere length and premature rupture of membranes

[0047] The results showed that the interaction p-values ​​between variables such as smoking, alcohol consumption, health score, BMI, and race and LTL were all greater than 0.05, indicating that there was no interaction between these variables and LTL in these subgroups. However, there was a significant interaction between age and education level and LTL (p for interaction < 0.05), suggesting that age and education level play an important role in moderating the relationship between LTL and the risk of premature rupture of membranes. Specifically, in women <45 years of age, each unit increase in LTL was slightly associated with a non-significant increase in the risk of PROM (OR = 1.18, 95% CI: 0.7–1.99, P = 0.535). However, in women ≥45 years of age, the same increase in LTL was significantly associated with a 4-fold increase in the risk of PROM (OR = 4.04, 95% CI: 2.31–7.07, P < 0.001). The highest risk group among the education level subgroups was "Other professional qualifications" (OR=49.77, extremely wide CI, indicating a small sample size but a very strong effect), followed by "British O-levels / GCSE or equivalent qualifications" (OR=2.80). The risk association for the "University or University degree" group was not significant (OR=1.23, P=0.514). Therefore, the risk assessment system of this invention is configured to incorporate the aforementioned covariates with significant moderating effects as interaction terms into the model along with the T / S ratio to accurately characterize their moderating effects and ensure the individualized accuracy of the assessment results.

[0048] Example 2: A system for assessing the risk of premature rupture of membranes based on leukocyte telomere length, comprising: The data acquisition module is used to acquire the white blood cell telomere length measurement value and covariate data of the pregnant woman to be evaluated; the white blood cell telomere length measurement value is obtained based on peripheral blood detection and is expressed as the ratio of telomere repeat sequence (T) to single copy gene (S) T / S; the covariates include age and education level.

[0049] In a specific embodiment, T / S is obtained by multiplex quantitative polymerase chain reaction. Primers are specifically combined. The telomere (T) primer targets the human telomere repeat sequence (TTAGGG)n, and the single-copy gene (S) uses the internal reference gene 36b4 as the core (albumin gene, β-globin gene, etc. can also be selected). The sequence is consistent with the classic qPCR method to ensure amplification specificity. The PCR temperature program adopts a two-step method. The enzyme activation stage is 95℃ for 10 minutes. The telomere (T) amplification cycle is 95℃ denaturation for 15 seconds and 54℃ annealing / extension for 2 minutes (30 cycles in total). The single-copy gene (S) amplification cycle is 95℃ denaturation for 15 seconds and 58℃ annealing / extension for 1 minute (30 cycles in total). Some procedures include a final extension stage of 72℃ for 10 minutes.

[0050] In specific implementations, educational levels are categorized as undergraduate or associate degree, UK A / AS level or equivalent, UK O level / GCSE or equivalent, UK CSE certificate or equivalent, National Vocational Qualification (NVQ) / Higher National Diploma (HND) / Higher National Certificate (HNC) or equivalent, and other professional qualification certificates.

[0051] A storage module is used to store a pre-built risk assessment model. The risk assessment model is established based on multi-center cross-sectional survey data and is constructed based on the association between leukocyte telomere length and covariates with the risk of premature rupture of membranes; the covariates include age and education level; and the risk assessment model includes interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level.

[0052] In a specific embodiment, the risk assessment model is configured with a risk threshold. The risk threshold is 0.691.

[0053] In a specific embodiment, the risk assessment model is configured with a grading strategy based on the telomere length distribution of white blood cells in a reference population. The distribution of LTL values ​​is divided into four groups, Q1 to Q4, with Q1 as the reference benchmark. Q1 represents the LTL measurement value falling within the 0th to 25th percentile of the overall sample distribution; Q2 represents the LTL measurement value falling within the 25th to 50th percentile of the overall sample distribution; Q3 represents the LTL measurement value falling within the 50th to 75th percentile of the overall sample distribution; and Q4 represents the LTL measurement value falling within the 75th to 100th percentile of the overall sample distribution. "Large-scale population" and "total sample size" refer to the large benchmark dataset of the reference population used to pre-build the model and set the grading thresholds.

[0054] The analysis and processing module is used to input the measured values ​​of leukocyte telomere length and covariate data into the risk assessment model to obtain the risk assessment results; wherein, the risk assessment model is constructed based on the association between leukocyte telomere length and covariates and the risk of premature rupture of membranes.

[0055] In a specific embodiment, the measured leukocyte telomere length is compared with the risk threshold, and the risk level is determined based on the comparison result. In the risk assessment model, there is a non-linear positive correlation between LTL and PROM risk with an inverse J-shaped trend: when the T / S ratio is less than 0.691, the PROM risk is determined to be lower than the baseline risk (OR=1); when the T / S ratio is greater than 0.691, the PROM risk is determined to be higher than the baseline risk, initially rising sharply, then slowly decreasing and gradually leveling off. A high-risk warning is output based on the interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level.

[0056] In a specific embodiment, the risk level is determined based on the range of the leukocyte telomere length measurement of the pregnant woman to be evaluated within the distribution. When the T / S ratio to be evaluated falls into Q1, the output module outputs "low risk"; when the T / S ratio to be evaluated falls into Q2, the output module outputs "low to medium risk"; when the T / S ratio to be evaluated falls into Q3, the output module outputs "high risk" and indicates: compared with the reference baseline, the PROM risk is significantly increased, with an odds ratio of 1.33; when the T / S ratio to be evaluated falls into Q4, the output module outputs "high risk" and indicates: compared with the reference baseline, the PROM risk is significantly increased, with an odds ratio of 1.31, and for every unit increase in LTL, the overall risk increases by 1.97 times.

[0057] The output module is used to output the premature rupture of membranes risk assessment results for the pregnant woman to be evaluated.

[0058] In a specific implementation, a test report is generated based on the analysis, which specifies the premature rupture of membranes risk level of the pregnant woman to be evaluated and the probability of increased risk compared to the baseline population.

[0059] Example 3: A method for assessing the risk of premature rupture of membranes based on leukocyte telomere length, comprising the following steps: S1: Obtain leukocyte telomere length measurements and covariate data from the pregnant woman to be evaluated; the leukocyte telomere length measurements are obtained based on peripheral blood testing and are expressed as the ratio of telomere repeat sequences (T) to single-copy genes (S), T / S; the covariates include age and education level.

[0060] In a specific embodiment, T / S is obtained by multiplex quantitative polymerase chain reaction. Primers are specifically combined. The telomere (T) primer targets the human telomere repeat sequence (TTAGGG)n, and the single-copy gene (S) uses the internal reference gene 36b4 as the core (albumin gene, β-globin gene, etc. can also be selected). The sequence is consistent with the classic qPCR method to ensure amplification specificity. The PCR temperature program adopts a two-step method. The enzyme activation stage is 95℃ for 10 minutes. The telomere (T) amplification cycle is 95℃ denaturation for 15 seconds and 54℃ annealing / extension for 2 minutes (30 cycles in total). The single-copy gene (S) amplification cycle is 95℃ denaturation for 15 seconds and 58℃ annealing / extension for 1 minute (30 cycles in total). Some procedures include a final extension stage of 72℃ for 10 minutes.

[0061] In specific implementations, educational levels are categorized as undergraduate or associate degree, UK A / AS level or equivalent, UK O level / GCSE or equivalent, UK CSE certificate or equivalent, National Vocational Qualification (NVQ) / Higher National Diploma (HND) / Higher National Certificate (HNC) or equivalent, and other professional qualification certificates.

[0062] S2: Input the measured leukocyte telomere length and covariate data into a pre-constructed premature rupture of membranes risk assessment model to obtain the risk assessment results; wherein, the risk assessment model is constructed based on the correlation between leukocyte telomere length and covariates and the risk of premature rupture of membranes.

[0063] In a specific embodiment, the risk assessment model is configured with a risk threshold. The risk threshold is 0.691. The measured leukocyte telomere length is compared with the risk threshold, and the risk level is determined based on the comparison result. In the risk assessment model, there is a non-linear positive correlation between LTL and PROM risk with an inverse J-shaped trend: when the T / S ratio is less than 0.691, the PROM risk is determined to be lower than the baseline risk (OR=1); when the T / S ratio is greater than 0.691, the PROM risk is determined to be higher than the baseline risk, initially rising sharply, then slowly decreasing and gradually leveling off, and a high-risk warning is output in conjunction with the covariate data.

[0064] In a specific embodiment, the risk assessment model is configured with a grading strategy based on the leukocyte telomere length distribution of a reference population. The distribution of LTL values ​​is divided into four groups, Q1 to Q4, with Q1 as the reference benchmark. Q1 represents the LTL measurement value falling within the 0th to 25th percentile of the overall sample distribution; Q2 represents the LTL measurement value falling within the 25th to 50th percentile; Q3 represents the LTL measurement value falling within the 50th to 75th percentile; and Q4 represents the LTL measurement value falling within the 75th to 100th percentile. "Large-scale population" and "total sample size" refer to the large benchmark dataset of the reference population used to pre-build the model and set grading thresholds. The corresponding risk level is determined based on the range within which the leukocyte telomere length measurement value of the pregnant woman to be assessed falls within this distribution. When the T / S ratio to be evaluated falls into Q1, the output module outputs "low risk"; when the T / S ratio to be evaluated falls into Q2, the output module outputs "low to medium risk"; when the T / S ratio to be evaluated falls into Q3, the output module outputs "high risk" and indicates that compared with the reference benchmark, the PROM risk has increased significantly, with an odds ratio of 1.33; when the T / S ratio to be evaluated falls into Q4, the output module outputs "high risk" and indicates that compared with the reference benchmark, the PROM risk has increased significantly, with an odds ratio of 1.31, and for every unit increase in LTL, the overall risk increases by 1.97 times.

[0065] S3: Based on the results of the risk assessment model, output the risk assessment results corresponding to the pregnant woman to be assessed.

[0066] In a specific implementation, an analysis report is generated that specifies the premature rupture of membranes risk level of the pregnant woman to be assessed and the probability of increased risk compared to the baseline population. Example 4: This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used for a method to assess the risk of premature rupture of membranes based on leukocyte telomere length.

[0067] Furthermore, unless otherwise specified, the functional modules in the various embodiments of this application can be integrated into one module, or each module can exist physically separately, or two or more modules can be integrated together. The integrated modules described above can be implemented in hardware or as software program modules.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A system for assessing the risk of premature rupture of membranes based on leukocyte telomere length, characterized in that, include: The data acquisition module is used to acquire the leukocyte telomere length measurement value and covariate data of the pregnant woman to be evaluated; the leukocyte telomere length measurement value is obtained based on peripheral blood detection and is expressed as the ratio T / S of telomere repeat sequences (T) to single-copy genes (S); the storage module is used to store the pre-constructed risk assessment model; the risk assessment model is established based on multicenter cross-sectional survey data and is constructed based on the association between leukocyte telomere length and covariates and the risk of premature rupture of membranes. The analysis and processing module is used to input the measured values ​​of leukocyte telomere length and covariate data into the risk assessment model to obtain the risk assessment results; The output module is used to output the premature rupture of membranes risk assessment results for the pregnant woman to be evaluated.

2. The system for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 1, characterized in that, The covariates include age and education level; and the risk assessment model includes interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level.

3. The system for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 1, characterized in that, The risk assessment model is configured with a risk threshold, and the analysis and processing module is configured to compare the measured value of leukocyte telomere length with the risk threshold and determine the risk level based on the comparison result.

4. The system for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 1, characterized in that, The risk assessment model is configured with a grading strategy based on the distribution of leukocyte telomere length in a reference population; the analysis and processing module is configured to determine the corresponding risk level based on the interval in the distribution where the leukocyte telomere length measurement of the pregnant woman to be assessed falls.

5. A method for assessing the risk of premature rupture of membranes based on leukocyte telomere length, characterized in that, Includes the following steps: S1: Obtain leukocyte telomere length measurements and covariate data from the pregnant woman to be evaluated; the leukocyte telomere length measurements are obtained based on peripheral blood testing and are expressed as the ratio of telomere repeat sequences (T) to single-copy genes (S), T / S. S2: Input the measured leukocyte telomere length and covariate data into a pre-constructed premature rupture of membranes risk assessment model to obtain the risk assessment results; wherein, the risk assessment model is established based on multi-center cross-sectional survey data and constructed based on the association between leukocyte telomere length and covariates and the risk of premature rupture of membranes; the covariates include age and education level; and the risk assessment model includes interaction terms between leukocyte telomere length and age and / or leukocyte telomere length and education level; S3: Based on the results of the risk assessment model, output the risk assessment results corresponding to the pregnant woman to be assessed.

6. The method for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 5, characterized in that, The T / S is obtained by multiplex quantitative polymerase chain reaction; the telomere repeat sequence can be selected from (TTAGGG)n, and the single-copy gene can be selected from 36b4, albumin gene or β-globin gene.

7. The method for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 5 or 6, characterized in that, The risk assessment model is configured with a risk threshold; during the assessment, the measured value of leukocyte telomere length is compared with the risk threshold, and the risk level is determined based on the comparison result.

8. The method for assessing the risk of premature rupture of membranes based on leukocyte telomere length according to claim 5 or 6, characterized in that, The risk assessment model is configured with a grading strategy based on the distribution of leukocyte telomere length in the reference population; during the assessment, the corresponding risk level is determined according to the interval in the distribution where the measured leukocyte telomere length of the pregnant woman to be assessed falls.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method described in any one of claims 5 to 8.

10. The use of a reagent or kit for detecting leukocyte telomere length in the preparation of products for assisting in the assessment of the risk of premature rupture of membranes in pregnant women, said assessment being based on the method as described in any one of claims 5 to 8.

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