Pneumoconiosis health management system based on susceptibility risk level

Abstract

The invention relates to the technical field of pneumoconiosis health management, in particular to a pneumoconiosis health management system based on susceptible risk levels. The pneumoconiosis health management system based on the susceptible risk level aims at providing an accurate health management scheme by integrating individual genetic factors. The system comprises four core modules: a genetic factor information input module collects related data and transmits the data to a pneumoconiosis polygene genetic risk scoring module, and the module calculates a polygene risk score by using the data; the pneumoconiosis susceptibility risk grade judgment module performs susceptibility risk grade division on the individuals according to the scores; and the health management suggestion output module provides specific health management and prevention suggestions for the individuals according to the risk levels. According to the technical scheme, the technical problem that a health management system for pneumoconiosis is lacked in the prior art can be solved, pneumoconiosis is effectively prevented through personalized evaluation and guidance, and a health management strategy is provided for high-risk people.

Description

Technical Field

[0001] The present invention relates to the technical field of pneumoconiosis health management, and in particular to a pneumoconiosis health management system based on susceptibility risk levels. Background Art

[0002] Pneumoconiosis is a systemic disease characterized by diffuse fibrosis of the lungs, caused by long-term inhalation of dust particles. It is particularly common among miners, stone processing workers, and other occupational groups exposed to high concentrations of dust. With the acceleration of industrialization and the growing awareness of labor protection, the effective prevention, early detection, and scientific management of pneumoconiosis have become important issues in public health. Pneumoconiosis poses a significant threat to workers' health. The need to establish a pneumoconiosis health management system based on susceptibility risk levels is becoming increasingly prominent. Once pneumoconiosis develops, there is currently no specific treatment, and preventive measures are the primary means of reducing the occurrence and progression of the disease. Therefore, early identification of high-risk groups and the implementation of effective intervention measures are key to reducing morbidity.

[0003] The shortcomings of the existing health management system are mainly reflected in the following aspects: Lack of personalized assessment: Most systems fail to conduct detailed risk assessments based on individual susceptibility factors (such as genetic background, medical history, lifestyle habits, etc.), and are unable to provide personalized prevention recommendations and health management plans for people at different risk levels.

[0004] Limited data integration and analysis capabilities: Although modern medical and environmental monitoring technologies can generate large amounts of personal health and environmental monitoring data, efficiently integrating this data and extracting valuable information to guide health management practices remains a challenge. Current technologies often struggle to achieve in-depth mining and real-time analysis of this data.

[0005] Inadequate continuous monitoring and feedback mechanisms: Effective pneumoconiosis health management requires a continuous data collection, monitoring, and feedback loop. However, existing systems often lack such a dynamic adjustment mechanism, resulting in a delay in implementing targeted intervention measures even when problems are identified.

[0006] Given these challenges, establishing a dedicated health management system for pneumoconiosis is urgent. This system must not only fully leverage modern information technology for accurate risk assessment and prediction, but also provide effective health management recommendations for patients based on the assessment results. Only in this way can we comprehensively improve the prevention and treatment of pneumoconiosis and effectively protect the health of workers. Summary of the Invention

[0007] The purpose of the present invention is to provide a pneumoconiosis health management system based on susceptibility risk level to solve the technical problem that the prior art lacks a health management system for pneumoconiosis.

[0008] To achieve the above object, the technical solution adopted by the present invention is as follows: A pneumoconiosis health management system based on susceptibility risk levels includes a genetic factor information input module, a pneumoconiosis polygenic genetic risk scoring module, a pneumoconiosis susceptibility risk level determination module, and a health management advice output module. The genetic factor information input module is used to input genetic factor data into the pneumoconiosis polygenic genetic risk scoring module; The pneumoconiosis polygenic genetic risk score module is used to calculate the polygenic risk score based on the data from the genetic factor information input module; The pneumoconiosis susceptibility risk level determination module is used to determine the pneumoconiosis susceptibility risk level of the subject according to the polygenic risk score; The health management advice output module is used to output specific advice content based on the level determination results of the pneumoconiosis susceptibility risk level determination module.

[0009] Furthermore, for the pneumoconiosis susceptibility risk level determination module: When the polygenic risk score is less than -2.774721, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is low; When -2.774721≤polygenic risk score≤1.012231, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is intermediate; When 1.012231 is less than the polygenic risk score, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is high.

[0010] Furthermore, when the pneumoconiosis susceptibility risk level is low, the output of the health management advice output module includes: career advice and health management advice; The output of occupational advice includes: as long as you do not have active pulmonary tuberculosis, chronic obstructive pulmonary disease, chronic interstitial lung disease, or diseases with impaired lung function, you can engage in work related to exposure to dust; Health management recommendations include personal protection recommendations, health monitoring recommendations and lifestyle recommendations.

[0011] Furthermore, when the pneumoconiosis susceptibility risk level is intermediate, the output of the health management advice output module includes: career advice and health management advice; The output of occupational advice includes: engaging in non-dust-contact work, or engaging in related work with exposure to productive dust classified as Level II or below.

[0012] Health management recommendations include personal protection recommendations, health monitoring recommendations, lifestyle recommendations, and traditional Chinese medicine conditioning recommendations; The output of health monitoring recommendations includes: if you are preparing to engage in or have already engaged in a dust-exposed occupation, you should undergo occupational health examinations before taking up the job, during the job, and when leaving the job, as well as follow-up health examinations after leaving the job. The monitoring cycle is once a year.

[0013] Furthermore, when the pneumoconiosis susceptibility risk level is high, the output of the health management advice output module includes: career advice and health management advice; The output of career advice includes: dust-exposed occupations are not recommended; or for those who are engaged in dust-exposed jobs, it is recommended to transfer out of dust-exposed positions or engage in work with production dust exposure classified as Class I or below with low dust concentrations, and exposure to silica dust is strictly prohibited; Health management recommendations include personal protection recommendations, health monitoring recommendations, lifestyle recommendations, and traditional Chinese medicine conditioning recommendations; The output content of health monitoring recommendations includes: If you are preparing to engage in or have already engaged in a dust-exposed occupation, you should strictly undergo occupational health examinations before taking up the job, during the job, and when leaving the job, as well as follow-up health examinations after leaving the job. The monitoring cycle should be no less than once a year.

[0014] Furthermore, the health management advice output module includes a display for displaying advice content.

[0015] Furthermore, the genetic factor information input module is provided with an information collection channel for genetic factor information collection; There are 23 genetic factors in total, which are the copy numbers of the effect alleles of SNP sites rs3748067, rs8193036, rs4691896, rs2292832, rs2672794, rs12812500, rs2067051, rs2289477, rs26538, rs1864182, rs510432, rs7195830, rs689466, rs20417, rs2227956, rs1800470, rs11466345, rs73329476, rs4320486, rs117626015, rs1539019, rs2243250, and rs361525; the copy numbers of the effect alleles are 0, 1, and 2; Furthermore, the pneumoconiosis polygenic genetic risk scoring module is provided with an input terminal for inputting the numerical values ​​of the genetic factors respectively, and is also provided with an output terminal for outputting the polygenic risk score; The polygenic genetic risk score module for pneumoconiosis incorporates a polygenic risk score calculation model as shown in Formula I:

[0016] Formula I in, ModelScore i W1 represents the polygenic risk score of the i-th individual; ij is the weight of the jth SNP of the i-th individual, a ij is the allele copy number of the jth SNP in the i-th individual.

[0017] Furthermore, in the polygenic genetic risk score module for pneumoconiosis, the allele copy number of SNP a ij The value range is 0, 1 or 2.

[0018] Furthermore, the weight value of the SNP site W1 i1 - W1 i23 They are -0.210721031315653, -0.210721031315653, 0.636576829071551, 0.27002713721306, 0.198850858745165, 0.371563556432483, -0.415515443961666, -0.23572233352107, -0.544727175441672, -0.27443684570176, -0.198450938723838, and 0.4382 54930931155, -0.23572233352107, -0.127833371509885, 2.74791173452734, -0.693147180559945, 0.806475865866949, 0.774727167552368, -0.527632742082372, 0.887891257352457, 0.198850858745165, -0.22314355131421, 1.33236601909433.

[0019] In summary, the principles and beneficial effects of this technical solution are: (1) The technical principle is as follows: The construction of a pneumoconiosis health management system based on susceptibility risk level aims to accurately assess the risk of pneumoconiosis by integrating individual genetic factors and provide personalized health management recommendations. The system mainly consists of four modules: Genetic factor information input module: This module is responsible for collecting genetic information of the subjects (for example, gene variation data related to pneumoconiosis, SNP data), which provides the basis for subsequent risk assessment.

[0020] Pneumoconiosis Polygenic Genetic Risk Score Module: Using data from the Genetic Factor Information Input Module, this module uses an algorithmic model to calculate a polygenic risk score that comprehensively reflects an individual's risk of developing pneumoconiosis. This score considers variations at multiple gene loci and their interactions (PRS model, polygenic risk score model) to achieve more accurate risk prediction.

[0021] Pneumoconiosis Susceptibility Risk Level Determination Module: Based on the results of the polygenic risk score, this module categorizes individuals into different susceptibility risk levels. By setting certain thresholds or standards, high-risk groups can be identified and differentiated into different risk levels, facilitating the implementation of appropriate preventive measures.

[0022] Health Management Recommendations Output Module: Based on the conclusions drawn by the Pneumoconiosis Susceptibility Risk Level Determination Module, this module provides users with personalized health management recommendations. These recommendations range from strengthening protective measures, regular health checkups, to lifestyle adjustments, aiming to reduce the risk of disease or mitigate its progression.

[0023] (2) The specific beneficial effects are: Personalized health management: Through comprehensive analysis of individual genetic background and living environment, we can provide each person with a tailored health management plan, significantly improving the effectiveness and pertinence of preventive measures.

[0024] Early risk warning: The system can identify high-risk individuals before symptoms appear, thereby achieving early detection and early intervention of the disease, greatly improving the patient's prognosis.

[0025] Improve the efficiency of public health activities: With the help of accurate risk assessment and management strategies, medical resources can be allocated more effectively, public health intervention measures can be optimized, and unnecessary expenses can be reduced.

[0026] Enhance workers' awareness of protection: Through specific and feasible health advice, help workers better understand their own health conditions and potential risks, motivate them to take proactive protective measures, and jointly create a safe working environment.

[0027] In summary, the pneumoconiosis health management system based on susceptibility risk level not only helps to improve the scientificity and effectiveness of individual health management, but also provides strong technical support for the field of public health. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1This is a schematic diagram of the overall system of the pneumoconiosis health management system based on susceptibility risk level in Example 1. DETAILED DESCRIPTION

[0029] The present invention will be further described in detail below with reference to the examples, but the embodiments of the present invention are not limited thereto. Unless otherwise specified, the technical means used in the following examples and experimental examples are conventional means well known to those skilled in the art, and the materials, reagents, etc. used are all commercially available. Unless otherwise specified, the technical means used in the following examples are conventional means well known to those skilled in the art.

[0030] Example 1: Pneumoconiosis health management system based on susceptibility risk level The pneumoconiosis health management system based on susceptibility risk level includes a genetic factor information input module, a pneumoconiosis multi-gene genetic risk scoring module, a pneumoconiosis susceptibility risk level determination module and a health management advice output module.

[0031] The genetic factor information input module is used to input genetic factor data into the pneumoconiosis polygenic genetic risk scoring module. The pneumoconiosis polygenic genetic risk scoring module is used to calculate the polygenic risk score based on the data from the genetic factor information input module. The pneumoconiosis susceptibility risk level determination module determines the pneumoconiosis susceptibility risk level of the subject based on the polygenic risk score. The health management advice output module outputs specific advice content based on the level determination results of the pneumoconiosis susceptibility risk level determination module. See the overall system diagram for details. Figure 1 .

[0032] The following is a detailed description of each of the above modules: (1) Genetic factor information input module The genetic factor information input module is provided with an information collection channel for genetic factor information collection channel elements.

[0033] There are 23 genetic factors in total, which are the copy numbers of the effect alleles of SNP sites rs3748067, rs8193036, rs4691896, rs2292832, rs2672794, rs12812500, rs2067051, rs2289477, rs26538, rs1864182, rs510432, rs7195830, rs689466, rs20417, rs2227956, rs1800470, rs11466345, rs73329476, rs4320486, rs117626015, rs1539019, rs2243250, and rs361525. The copy number of the effect allele (variant allele) can be 0, 1, or 2.

[0034] (2) Pneumoconiosis polygenic genetic risk scoring module The pneumoconiosis polygenic genetic risk scoring module is provided with an input terminal for inputting the numerical values ​​of genetic factors respectively, and an output terminal for outputting the polygenic risk score.

[0035] The formula for calculating the polygenic risk score is (Formula I can be used, considering only genetic factors):

[0036] Formula I in, ModelScore i represents the polygenic risk score of the i-th individual. i represents the i-th individual, j represents the j-th SNP, W1 ij is the weight of the jth SNP of the i-th individual, a ij is the allele copy number of the jth SNP of the i-th individual (a ij =0 / 1 / 2, the human body is diploid, and at a SNP site, the copy numbers of the disease-related effect / mutant alleles are 0 / 1 / 2). The number of SNPs used for scoring is N, preferably N=23, and the following SNP sites are used: rs3748067, rs8193036, rs4691896, rs2292832, rs2672794, rs12812500, rs2067051, rs2289477, rs26538, rs1864182, rs510432, rs7195830, rs689466, rs20417, rs2227956, rs1800470, rs11466345, rs73329476, rs4320486, rs117626015, rs1539019, rs2243250, and rs361525. The copy number of the SNP allele can be obtained by conventional methods such as first-generation sequencing in the prior art, or information on the copy number of the SNP allele in a sample can be obtained by other conventional means in the prior art.

[0037] Table 1: 23 SNPs used for the prediction and diagnosis of pneumoconiosis

[0038] In Table 1, the ">" in the Allele column indicates the major allele to the left, and the minor allele to the right. The major allele is the most common or most frequent nucleotide at a specific SNP position in a population. In other words, it is the dominant form at that position. The minor allele is the nucleotide that occurs less frequently at the same position and represents a relatively rare variant. MAF stands for Minor Allele Frequency, which refers to the proportion of alleles with a lower frequency at a specific SNP position in a given population. MAF Case refers to the frequency of the minor allele at a specific SNP position in a population of individuals with a certain disease or condition (i.e., the case group). MAF Control refers to the frequency of the minor allele at the same SNP position in a population of individuals without the disease or condition (i.e., the control group). Beta (β) refers to the regression coefficient and represents an estimate of the magnitude of the phenotypic effect of each additional copy of a particular SNP allele (minor allele). Beta reflects the magnitude of the effect of a genetic variant on a particular trait or disease. The sign of the beta value indicates the direction of the allele's effect. A positive value indicates that an increase in the allele is associated with an increased phenotypic effect (e.g., increased disease risk), while a negative value indicates the opposite effect (e.g., decreased disease risk). P A value of ≤0.05 indicates that the association between the SNP and the phenotype is unlikely to occur by chance. The OR (odds ratio) is used to assess the relationship between a specific genetic variant (such as a SNP allele) and disease risk. The OR for rs3748067 is 0.81, meaning that for each additional copy of the effect allele, an individual's chance of developing pneumoconiosis is reduced by 19% compared to individuals without that allele.

[0039] More specifically, for 23 SNP sites, the W1 ij The weight values ​​are shown in Table 2. The specific values ​​of the above weights are derived from the variable risk effect values ​​in the largest sample size pneumoconiosis GWAS published in the Chinese population.

[0040] Table 2: Weight values ​​of the PRS model

[0041] (3) Pneumoconiosis susceptibility risk level determination module The polygenic risk score obtained according to (2) ModelScore i (polygenic risk score) to determine the susceptibility risk level of pneumoconiosis.

[0042] When the calculation formula of the polygenic risk score of the polygenic genetic risk score module for pneumoconiosis adopts Formula I, the susceptibility risk level of pneumoconiosis is determined in the following manner: When the polygenic risk score is less than -2.774721, the pneumoconiosis susceptibility risk level determination module outputs the pneumoconiosis risk level as "low (pneumoconiosis risk)"; When -2.774721≤polygenic risk score≤1.012231, the pneumoconiosis susceptibility risk level determination module outputs the pneumoconiosis risk level as "intermediate (pneumoconiosis risk)"; When 1.012231 is less than the polygenic risk score, the pneumoconiosis risk level output by the pneumoconiosis susceptibility risk level determination module is “high-level (pneumoconiosis risk)”.

[0043] The cutoff values ​​for each of the above determinations are selected based on 20% of the top and bottom of the total population. In the pneumoconiosis susceptibility risk level determination module of the present invention, in order to achieve further stratified management of the genetic risk of pneumoconiosis of the subjects, the output of the polygenic risk score (PRS) model is adopted. ModelScore i Individuals are categorized into high, medium, and low risk groups. Specifically, the cutoff values ​​for each assessment are determined based on the distribution of the top 20% and bottom 20% of the population. Individuals with scores above the 80th percentile are classified as high-risk, those below the 20th percentile as low-risk, and the middle 60% as medium-risk. The cutoff value between medium and high risk is 1.012231, and between medium and low risk is -2.774721.

[0044] (4) Health management advice output module According to the determination result of the pneumoconiosis susceptibility risk level determination module, the health management advice output module outputs different health advices and displays the health advices on a display, or prints the health advices in paper form through a printer for the subjects to read and refer to.

[0045] (4.1) Regarding “low-grade pneumoconiosis risk”, which means the risk of developing the disease is lower than that of the general population, the health advice provided (output) to the subjects is: (4.1.1) Career advice As long as you do not have active pulmonary tuberculosis, chronic obstructive pulmonary disease, chronic interstitial lung disease, or other diseases that impair lung function, you can engage in work related to exposure to dust.

[0046] (4.1.2) Health management recommendations (4.1.2.1) Personal protection If you work in a dust-exposed environment, you should fully understand the nature of the dust you are exposed to and the appropriate protective measures. Wear and use protective equipment and facilities correctly and appropriately to avoid inhaling dust. Do not smoke at the work site and avoid bringing dust-contaminated work clothes home. If you live in a windy and sandy environment, take appropriate measures to prevent dust indoors. Wear a mask for personal protection when going out in windy and sandy weather.

[0047] (4.1.2.2) Health monitoring If you are planning to work in or already work in a dust-exposed occupation, you should undergo occupational health examinations before, during, and upon leaving your job, as well as follow-up health examinations after leaving your job, in accordance with relevant occupational requirements. Monitor your health regularly and seek medical attention promptly if you experience symptoms such as coughing, sputum production, wheezing, chest pain, difficulty breathing, or shortness of breath. If you work in a dust-exposed occupation, you should proactively share your occupational history with your doctor.

[0048] (4.1.2.3) Develop a good lifestyle (4.1.2.3.1) Quit smoking and limit alcohol consumption Quitting smoking plays a positive role in preventing pneumoconiosis. Smoking impairs bronchial epithelium and ciliary motility, reducing their ability to clear dust particles. It also damages respiratory defenses such as the mucus layer, reducing the body's ability to defend against dust particles. Try to limit alcohol consumption, as it can damage both the liver and lungs.

[0049] (4.1.2.3.2) Reasonable diet Ensure adequate and balanced nutritional intake, eat a light diet, eat more fresh vegetables and fruits to supplement vitamins and fiber, and appropriately increase the intake of high-quality proteins such as eggs and milk.

[0050] (4.1.2.3.3) Keep warm Avoid colds and rhinitis in winter, as these conditions can cause poor nasal ventilation. Mouth breathing prevents the nasal hairs and mucus from filtering out dust, allowing dust to enter the lungs directly from the mouth. Burning coal and wood creates dust, so avoid using them indoors for heating. Utilize clean and safe heating methods whenever possible.

[0051] (4.1.2.3.4) Exercise Increase your time outdoors and strengthen your physical activity. Aerobic exercise, including jogging, walking, swimming, and yoga, is a great way to boost your immune system and cardiopulmonary function. Stick to traditional exercises like Tai Chi, Ba Duan Jin, Wu Qin Xi, and Yi Jin Jing, combined with effective breathing patterns. The longer you practice, the more noticeable the improvement in your cardiopulmonary function. Also, maintain a regular work and rest schedule and avoid staying up late.

[0052] (4.2) Regarding the “intermediate risk of pneumoconiosis”, it means that the risk of developing the disease is slightly higher than that of the general population and that appropriate attention should be paid to the progression of the disease. The health advice provided to the subjects is: (4.2.1) Career advice On the premise that there is no active pulmonary tuberculosis, chronic obstructive pulmonary disease, chronic interstitial lung disease, or diseases with impaired lung function, it is also recommended to engage in non-dust exposure work, or engage in related work with exposure to productive dust classified as Level II or below.

[0053] (4.2.2) Health management recommendations (4.2.2.1) Personal protection If you work in a dust-prone environment, you should fully understand the nature of the dust you are exposed to and the appropriate protective measures. Wear and use appropriate protective equipment and facilities to avoid inhaling dust. Do not smoke at the work site and avoid bringing dust-contaminated work clothes home. If you live in a windy and sandy environment, take appropriate measures to prevent dust indoors. Wear a mask for personal protection when going out in windy and sandy weather.

[0054] (4.2.2.2) Health monitoring If you are planning to work in or are already working in a dust-exposed occupation, you should undergo occupational health examinations before, during, and upon leaving your job, as well as follow-up health examinations after leaving your job, in accordance with relevant occupational requirements. Annual monitoring is recommended. If you experience any clinical symptoms, please seek medical attention promptly at a reputable hospital and remove yourself from the dust-exposed environment. Monitor your health regularly and seek medical attention promptly if you experience symptoms such as coughing, sputum production, wheezing, chest pain, difficulty breathing, or shortness of breath. If you work in a dust-exposed environment, you should proactively share your occupational history with your doctor.

[0055] (4.2.2.3) Develop a good lifestyle (4.2.2.3.1) Quit smoking and limit alcohol consumption Quitting smoking plays a positive role in preventing pneumoconiosis. Smoking impairs bronchial epithelium and ciliary motility, reducing their ability to clear dust particles. It also damages respiratory defenses such as the mucus layer, reducing the body's ability to defend against dust particles. Try to avoid alcohol, as it can damage both the liver and lungs.

[0056] (4.2.2.3.2) Reasonable diet Ensure adequate and balanced nutritional intake, eat a light diet, eat more fresh vegetables and fruits to supplement vitamins and fiber, and increase the intake of high-quality protein such as eggs, lean meat, and beans. Adequate protein helps maintain the integrity of the basic structure of lung tissue and the body's normal immune function.

[0057] Practitioners can also increase their intake of vitamin A, which maintains the integrity and function of respiratory epithelial cells, helping to prevent or reduce lung damage from dust. Most animal livers and kidneys are rich in vitamin A. Additionally, red, orange, and yellow vegetables, such as carrots, pumpkins, mangoes, apricots, tomatoes, and persimmons, are rich in carotenoids, which can be converted into vitamin A in the body. Increase your intake accordingly.

[0058] Choose more foods that have the effects of clearing heat, removing phlegm, strengthening the spleen and moistening the lungs, such as lotus root, lotus seeds, lily, mung bean, pear, yam, etc.; which are beneficial to alleviating clinical symptoms; and kelp, oyster meat, seaweed, etc. that have the effects of removing phlegm, softening and dispersing nodules, which are beneficial to eliminating nodules.

[0059] (4.2.2.3.3) Keep warm In winter, we should avoid diseases such as colds and rhinitis, as these diseases can cause poor nasal ventilation. At this time, breathing through the mouth will prevent the nasal hair and mucus in the nasal cavity from filtering out dust, allowing dust to enter the lungs directly from the mouth.

[0060] Coal and wood will produce dust when burned. Avoid burning coal and firewood for heating indoors. Try to use clean and safe heating measures.

[0061] (4.2.2.3.4) Exercise Increase your time outdoors and strengthen your physical activity. Aerobic exercise, including jogging, walking, swimming, and yoga, is a great way to boost your immune system and cardiopulmonary function. Stick to traditional exercises like Tai Chi, Ba Duan Jin, Wu Qin Xi, and Yi Jin Jing, combined with effective breathing patterns. The longer you practice, the more noticeable the improvement in your cardiopulmonary function. Also, maintain a regular work and rest schedule and avoid staying up late.

[0062] (4.2.2.4) Traditional Chinese Medicine Treatment Traditional Chinese medicines such as ginseng, American ginseng, Adenophora adenophora, Ophiopogon japonicus, Schisandra chinensis, and black fungus have the effects of invigorating qi and nourishing yin, moistening the lungs and resolving phlegm. Modern medical experiments have shown that they can enhance the body's scavenging of oxygen free radicals, effectively adjust the oxidation / antioxidation imbalance, reduce pathological damage to lung tissue, enhance the body's ability to resist oxidative damage, thereby preventing pneumoconiosis and delaying the progression of lung fibrosis.

[0063] (4.3) Regarding the “high-level pneumoconiosis risk,” which indicates a slightly higher risk than the general population, and requires appropriate attention to the progression of the disease, the health advice provided to the subjects is: (4.3.1) Career advice Dust-exposed occupations are not recommended. If you work in a dust-exposed position, it is recommended that you transfer out of the dust-exposed position or engage in work with production dust exposure classified as Level I or below with lower dust concentrations. Exposure to silica dust is strictly prohibited.

[0064] (4.3.2) Health management and protection (4.3.2.1) Personal protection If you work in a dust-exposed environment, you should fully understand the nature of the dust you are exposed to and the appropriate protective measures. Wear and use appropriate protective equipment and facilities correctly and appropriately to avoid inhaling industrial dust and minimize exposure to dust. Do not smoke at the work site and avoid bringing dust-contaminated work clothes home. If you live in a windy and sandy environment, take appropriate measures to prevent dust indoors and wear a mask for personal protection when going out in windy and sandy weather.

[0065] (4.3.2.2) Health monitoring If you are planning to work in or are already working in a dust-exposed occupation, you should strictly follow occupational health requirements and undergo occupational health examinations before, during, and upon leaving your job, as well as follow-up health examinations after leaving your job. We recommend that you conduct at least one monitoring examination annually. If you experience any clinical symptoms, please seek medical attention promptly at a reputable hospital and remove yourself from the dust-exposed environment.

[0066] Monitor your health and seek medical attention promptly if you experience symptoms such as coughing, sputum, wheezing, chest pain, difficulty breathing, or shortness of breath. If you work in a job involving exposure to dust, you should proactively share your occupational history with your doctor.

[0067] (4.3.2.3) Develop a good lifestyle (4.3.2.3.1) Quit smoking and drinking Quitting smoking plays a positive role in preventing pneumoconiosis. Smoking impairs bronchial epithelium and ciliary motility, reducing their ability to clear dust particles. It also damages respiratory defenses such as the mucus layer, reducing the body's ability to defend against dust particles. Avoid drinking alcohol, as it can cause damage to both the liver and lungs.

[0068] (4.3.2.3.2) Reasonable diet Ensure adequate and balanced nutritional intake, with a light diet. Eat more fresh vegetables and fruits to supplement vitamins and fiber, and increase the intake of high-quality protein such as eggs, lean meat, beans, and milk. Adequate protein helps maintain the integrity of the basic structure of lung tissue and normal immune function. Be mindful of reducing fat intake. Excessive fat can lead to fat accumulation in lung tissue, which in turn increases dust deposition and promotes pulmonary fibrosis. Practitioners can also increase their intake of vitamin A, which helps maintain the morphological integrity and function of respiratory mucosal epithelial cells, helping to prevent or reduce damage to the lungs caused by dust. Most animal livers and kidneys are rich in vitamin A. In addition, red, orange, and yellow vegetables are rich in carotenoids, which can be converted into vitamin A in the body. Increase your intake appropriately, such as carrots, pumpkins, mangoes, apricots, tomatoes, and persimmons.

[0069] Choose more foods that have the effects of clearing heat, removing phlegm, strengthening the spleen and moistening the lungs, such as lotus root, lotus seeds, lily, mung bean, pear, yam, etc.; which are beneficial to alleviating clinical symptoms; and kelp, oyster meat, seaweed, etc. that have the effects of removing phlegm, softening and dispersing nodules, which are beneficial to eliminating nodules.

[0070] Increase the amount of water you drink. Drinking more water can promote metabolism in the body. The amount of water you drink should be kept between 2500 ml and 3000 ml per day. Drinking too little water will cause the secretions in the respiratory tract to dry up, forming sputum plugs, blocking the bronchi and trachea, and affecting respiratory function.

[0071] (4.3.2.3.3) Keep warm Avoid colds and rhinitis in winter, as these conditions can cause poor nasal ventilation. Mouth breathing prevents the nasal hairs and mucus from filtering out dust, allowing dust to enter the lungs directly from the mouth. Burning coal and wood creates dust, so avoid using them indoors for heating. Utilize clean and safe heating methods whenever possible.

[0072] (4.3.2.3.4) Exercise Increase your time outdoors and strengthen your physical activity. Aerobic exercise, including jogging, walking, swimming, and yoga, is a great way to boost your immune system and cardiopulmonary function. Stick to traditional exercises like Tai Chi, Ba Duan Jin, Wu Qin Xi, and Yi Jin Jing, combined with effective breathing patterns. The longer you practice, the more noticeable the improvement in your cardiopulmonary function. Also, maintain a regular work and rest schedule and avoid staying up late.

[0073] (4.3.2.4) Traditional Chinese Medicine Traditional Chinese medicines such as ginseng, American ginseng, Adenophora adenophora, Ophiopogon japonicus, Schisandra chinensis, and black fungus have the effects of invigorating qi and nourishing yin, moistening the lungs and resolving phlegm. Modern medical experiments have shown that they can enhance the body's scavenging of oxygen free radicals, effectively adjust the oxidation / antioxidation imbalance, alleviate pathological damage to lung tissue, and enhance the body's ability to resist oxidative damage, thereby preventing pneumoconiosis and delaying the progression of lung fibrosis.

[0074] Example 2: Establishment and performance testing of the calculation formula for the polygenic risk score in the polygenic genetic risk scoring module for pneumoconiosis (1) Screening of SNP sites for model construction The polygenic risk score calculation formula for the pneumoconiosis polygenic genetic risk score module incorporates multiple genetic factors, which are detected using specific single-nucleotide polymorphisms (SNPs). This technical solution investigated and screened genetic variants associated with pneumoconiosis susceptibility, providing candidate SNPs for constructing a Chinese-specific polygenic risk score (PRS) for pneumoconiosis and providing insights for identifying high-risk individuals and early screening for the disease. Screening revealed 62 SNPs associated with pneumoconiosis, as shown in Table 3. These SNPs all met the following criteria: a genetic variant association P value < 0.05 and an effect allele frequency greater than 0.01 in the control population. However, direct application of these 62 SNPs to construct a polygenic risk score model for pneumoconiosis yielded suboptimal predictive accuracy, necessitating further screening, refinement, and research. After further site-by-site correlation studies, 23 SNPs were ultimately selected for the prediction and diagnosis of pneumoconiosis, as detailed in Table 1.

[0075] Table 3: 62 SNPs associated with pneumoconiosis

[0076] Comparing Table 3 with Table 1, it is clear that not all of the 62 candidate SNPs associated with pneumoconiosis, obtained through screening of published literature, are suitable for pneumoconiosis risk prediction. Table 1 only incorporates the 18 SNPs from Table 3 into the model, and additional SNPs for pneumoconiosis prediction were added, such as rs2292832, rs2289477, rs689466, rs20417, rs2227956, and rs361525. Selecting appropriate SNPs for model construction is crucial for model prediction accuracy. As can be seen from the above, while existing technologies can provide some information on SNPs associated with pneumoconiosis, selecting valid and applicable SNPs from this vast amount of information is challenging. Furthermore, the aforementioned screening approach can miss some SNPs that play a crucial role in building risk prediction models. After extensive research, the SNPs for pneumoconiosis prediction, shown in Table 1, were ultimately identified.

[0077] (2) Model performance research The risk prediction efficacy of Formula I was verified, and the polygenic risk score of each sample was calculated according to the above formula (Formula I) ( ModelScore iModel performance is evaluated using the Receiver Operating Characteristic Curve (ROC) curve. The True Positive Rate (TPR) and False Positive Rate (FPR) are calculated at different classification thresholds and plotted with the FPR on the X-axis and the TPR on the Y-axis. The area under the ROC curve (AUC) is a single numerical metric used to quantify the overall performance of a classifier. AUC values ​​range from 0 to 1, with larger values ​​indicating better classifier performance. An AUC of 1 indicates a perfectly accurate classifier, while an AUC of 0.5 is equivalent to random guessing. By comparing the ROC curves or AUC values ​​of different models, one can intuitively determine which model has superior classification performance. More specifically, the following criteria are generally used to determine the diagnostic effectiveness of a model: AUC ≥ 0.7 indicates that the model's diagnostic effectiveness is feasible, with larger values ​​indicating optimal model effectiveness; 0.7 > AUC > 0.5 indicates that the model's diagnostic effectiveness is suboptimal. The samples used for model validation were from the research group's GWAS database, including 202 patients and 198 controls. Among the 202 patients, 68 had no smoking history, 134 had a smoking history, and the average dust exposure duration was 10.30±11.91 years (mean±SD). Among the 198 healthy controls, 62 had no smoking history, 136 had a smoking history, and the average dust exposure duration was 21.57±12.83 years (mean±SD).

[0078] The polygenic risk score of the i-th subject (substitute the weight value into formula I to obtain formula I-I): ModelScore i =-0.210721031315653a i1 -0.210721031315653a i2 +0.636576829071551a i3 +0.27002713721306a i4 +0.198850858745165a i5 +0.371563556432483a i6 -0.415515443961666a i7 -0.23572233352107a i8 -0.544727175441672a i9 -0.27443684570176ai10 -0.198450938723838a i11 +0.438254930931155a i12 -0.23572233352107a i13 +-0.127833371509885a i14 +2.74791173452734a i15 -0.693147180559945a i16 +0.806475865866949a i17 +0.774727167552368a i18 -0.527632742082372a i19 +0.887891257352457a i20 +0.198850858745165a i21 -0.22314355131421a i22 +1.33236601909433a i23 .

[0079] The corresponding test data of the aforementioned 202 patients + 198 controls (a ij Substituting the polygenic risk score (value: SNP allele copy number) into the above formula I-I, the polygenic risk score for each patient can be calculated. A receiver operating characteristic (ROC) curve is then generated based on the polygenic risk score values ​​for each patient and control, as well as the actual test results (whether or not the sample has pneumoconiosis). The predictive efficacy of the above model is evaluated using the area under the curve (AUC). For example, the AUC value of the model shown in formula I-I is 0.79, indicating that the model presented in formula I-I has reasonable diagnostic performance and can be used for the prediction of pneumoconiosis.

[0080] It can be seen that the calculation formula of the polygenic risk score in the polygenic genetic risk scoring module of pneumoconiosis adopted in this scheme can better distinguish pneumoconiosis patients from healthy people, and thus can effectively and accurately reflect the health risk of pneumoconiosis, and thus form an effective pneumoconiosis health management system.

[0081] Comparative Example 1: Effectiveness evaluation of scoring models constructed based on different SNP sites Before determining the 23 SNP sites of this scheme, the inventors evaluated different SNP sites that may be associated with pneumoconiosis and attempted to model them.

[0082] Test 1: Use the 62 SNP sites shown in Table 3 to establish a polygenic risk scoring model and a scoring model for the risk prediction unit (i.e., the form of Formula I). ​​The weight values ​​of the 62 SNP sites are directly based on the variable risk effect values ​​in the largest sample size pneumoconiosis GWAS reported in the prior art for the Chinese population, which will not be elaborated here. The corresponding test data of the aforementioned 202 patients + 198 controls (a ij Substituting the value (value: SNP allele copy number) into the formula established in this test to obtain the ROC curve and evaluate the model effectiveness, the AUC value of this test model is <0.7. This shows that the prediction effect of the scoring model established using 62 SNP loci is not ideal and is inferior to the scoring model established using 23 SNP loci in this technical solution. Therefore, the risk prediction model in the risk prediction unit of this solution should be constructed using the 23 SNP loci in this solution.

[0083] Test 2: A polygenic risk scoring model was established using the SNPs listed in Table 1, excluding rs2292832, rs2289477, rs689466, rs20417, rs2227956, and rs361525, to establish a scoring model for the risk prediction unit (i.e., the form of Formula I). ​​The SNPs rs2292832, rs2289477, rs689466, rs20417, rs2227956, and rs361525 are newly included in this study and associated with pneumoconiosis, and have not been reported in the prior art (reported SNPs potentially associated with pneumoconiosis can be found in Table 3). Of the 23 SNPs in this patent proposal, only 17 of the SNPs listed in Table 3 were incorporated into the model, and additional SNPs for pneumoconiosis prediction (the aforementioned 6 sites) were added.

[0084] Specifically, the new model obtained by omitting the terms corresponding to the above 6 SNP sites in formula Ⅰ-Ⅰ (omitting a i4 Item, a i8 Item, a i13 Item, a i14 Item, a i15 Item, a i23 Item). The corresponding test data of the aforementioned 202 patients + 198 controls (a ij Substituting the value (value: SNP allele copy number) into the formula established for this test, an ROC curve was generated to evaluate model effectiveness. The AUC value for this test model was <0.65. This demonstrates that the inclusion of the six SNPs mentioned above as genetic factors in the model is crucial to the model's diagnostic and predictive efficacy. These SNPs are not readily available through conventional screening.

[0085] Test 3: Use the six SNP sites rs2292832, rs2289477, rs689466, rs20417, rs2227956, and rs361525 to establish a polygenic risk scoring model and a scoring model for the risk prediction unit (i.e., the form of Formula I). ​​That is, retain the above six SNP sites in Formula I-I to obtain the new model (retain a i4 Item, a i8 Item, a i13 Item, a i14 Item, a i15 Item, a i23 Items, other items omitted). The corresponding test data of the aforementioned 202 patients + 198 controls (a ij Substituting the AUC (value: SNP allele copy number) into the formula established for this test yielded a receiver operating characteristic (ROC) curve to assess model effectiveness. The AUC for this model was <0.6. This demonstrates that using only the aforementioned six SNPs to establish a model is not ideal for risk prediction. This suggests that all 23 SNPs must be combined for model construction.

[0086] In addition, the inventors also attempted to construct a model by adding the SNP sites in Table 3 to the 23 SNPs in this protocol (the added SNP sites were different from the 23 SNPs in this protocol). However, after multiple attempts (trying to add multiple SNP sites that appear in Table 3 but not in Table 1 to construct multiple models), the AUC values ​​of the ROC curves of the obtained multiple models were difficult to significantly improve on the AUC value of Formula I-I. Therefore, using the 23 SNP sites in this protocol to construct a prediction model is the optimal approach. This approach can effectively predict the risk of pneumoconiosis while reducing the complexity of experimental operations. Effective risk prediction can be achieved by detecting the copy number of as few SNP sites as possible.

[0087] It can be seen that the selection of 23 specific SNP sites in this solution is very critical for constructing an ideal prediction model. Although there are many SNP sites related to pneumoconiosis reported in the prior art, after being used for model construction, it was found that the model effectiveness was not ideal. By using the 23 SNP sites in this solution, the AUC value of the constructed model can reach a level close to 0.8. If further combined with two macro factors, the AUC value of the model can reach above 0.8. This technical solution provides a new pneumoconiosis risk prediction tool, which solves the problem of the lack of a method for accurately predicting the incidence of pneumoconiosis in the prior art, and has important theoretical significance and practical application value.

[0088] The above is only an embodiment of the present invention, and the common knowledge such as the specific structure and characteristics of the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several variations and improvements can be made without departing from the structure of the present invention, and these should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A pneumoconiosis health management system based on susceptibility risk level, characterized by: Genetic factor information input module, pneumoconiosis polygenic genetic risk scoring module, pneumoconiosis susceptibility risk level determination module and health management advice output module; The genetic factor information input module is used to input genetic factor data into the pneumoconiosis polygenic genetic risk scoring module; The pneumoconiosis polygenic genetic risk score module is used to calculate the polygenic risk score based on the data from the genetic factor information input module; The pneumoconiosis susceptibility risk level determination module is used to determine the pneumoconiosis susceptibility risk level of the subject according to the polygenic risk score; The health management advice output module is used to output specific advice content based on the level determination results of the pneumoconiosis susceptibility risk level determination module.

2. The pneumoconiosis health management system based on susceptibility risk level according to claim 1 is characterized by: Module for determining the susceptibility risk level of pneumoconiosis: When the polygenic risk score is less than -2.774721, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is low; When -2.774721≤polygenic risk score≤1.012231, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is intermediate; When 1.012231 is less than the polygenic risk score, the pneumoconiosis susceptibility risk level determined by the pneumoconiosis susceptibility risk level determination module is high.

3. The pneumoconiosis health management system based on susceptibility risk level according to claim 2 is characterized by: When the pneumoconiosis susceptibility risk level is low, the output of the health management advice output module includes: career advice and health management advice; The output of occupational advice includes: as long as you do not have active pulmonary tuberculosis, chronic obstructive pulmonary disease, chronic interstitial lung disease, or diseases with impaired lung function, you can engage in work related to exposure to dust; Health management recommendations include personal protection recommendations, health monitoring recommendations and lifestyle recommendations.

4. The pneumoconiosis health management system based on susceptibility risk level according to claim 2 is characterized by: When the pneumoconiosis susceptibility risk level is medium, the output of the health management advice output module includes: career advice and health management advice; The output of occupational advice includes: engaging in non-dust-contact work, or engaging in related work with exposure to productive dust classified as Level II or below. Health management recommendations include personal protection recommendations, health monitoring recommendations, lifestyle recommendations, and traditional Chinese medicine conditioning recommendations; The output of health monitoring recommendations includes: if you are preparing to engage in or have already engaged in a dust-exposed occupation, you should undergo occupational health examinations before taking up the job, during the job, and when leaving the job, as well as follow-up health examinations after leaving the job. The monitoring cycle is once a year.

5. The pneumoconiosis health management system based on susceptibility risk level according to claim 2 is characterized by: When the pneumoconiosis susceptibility risk level is high, the output of the health management advice output module includes: career advice and health management advice; The output of career advice includes: dust-exposed occupations are not recommended; or for those who engage in dust-exposed jobs, it is recommended to transfer from dust-exposed positions or engage in jobs with production dust exposure classified as Class I or below and with low dust concentrations, and exposure to silica dust is strictly prohibited; Health management recommendations include personal protection recommendations, health monitoring recommendations, lifestyle recommendations, and traditional Chinese medicine conditioning recommendations; The output content of health monitoring recommendations includes: If you are preparing to engage in or have already engaged in a dust-exposed occupation, you should strictly undergo occupational health examinations before taking up the job, during the job, and when leaving the job, as well as follow-up health examinations after leaving the job. The monitoring cycle should be no less than once a year.

6. The pneumoconiosis health management system based on susceptibility risk level according to any one of claims 1 to 5, characterized in that: The health management advice output module includes a display for displaying advice content.

7. The pneumoconiosis health management system based on susceptibility risk level according to any one of claims 1 to 5, characterized in that: The genetic factor information input module is provided with a genetic factor information collection channel; There are 23 genetic factors in total, which are the copy numbers of the effect alleles of SNP sites rs3748067, rs8193036, rs4691896, rs2292832, rs2672794, rs12812500, rs2067051, rs2289477, rs26538, rs1864182, rs510432, rs7195830, rs689466, rs20417, rs2227956, rs1800470, rs11466345, rs73329476, rs4320486, rs117626015, rs1539019, rs2243250, and rs361525; the copy numbers of the effect alleles are 0, 1, and 2.

8. The pneumoconiosis health management system based on susceptibility risk level according to claim 7 is characterized by: The pneumoconiosis polygenic genetic risk scoring module is provided with an input terminal for inputting the numerical values ​​of the genetic factors respectively, and is also provided with an output terminal for outputting the polygenic risk score; The polygenic genetic risk score module for pneumoconiosis incorporates a polygenic risk score calculation model as shown in Formula I: Formula I in, ModelScore i W1 represents the polygenic risk score of the i-th individual; ij is the weight of the jth SNP of the i-th individual, a ij is the allele copy number of the jth SNP in the i-th individual.

9. The pneumoconiosis health management system based on susceptibility risk level according to claim 8 is characterized by: In the polygenic genetic risk score module for pneumoconiosis, the allele copy number of SNP a ij The value range is 0, 1 or 2.

10. The pneumoconiosis health management system based on susceptibility risk level according to claim 9 is characterized by: Weight value of SNP site W1 i1 - W1 i23 They are -0.210721031315653, -0.210721031315653, 0.636576829071551, 0.27002713721306, 0.198850858745165, 0.371563556432483, -0.415515443961666, -0.23572233352107, -0.544727175441672, -0.27443684570176, -0.198450938723838, and 0.4382 54930931155, -0.23572233352107, -0.127833371509885, 2.74791173452734, -0.693147180559945, 0.806475865866949, 0.774727167552368, -0.527632742082372, 0.887891257352457, 0.198850858745165, -0.22314355131421, 1.33236601909433.

Images