A human aging risk score system and applications thereof

Abstract

The present disclosure relates to the technical field of medical examination and health assessment, in particular to a human aging risk scoring system and application thereof. The present disclosure provides a human aging comprehensive assessment system covering three core modules of inflammation risk (SASP), metabolic risk and oxidative stress risk. The system outputs precise aging risk score and grade through scientific weighted combination of scores of the three modules, and matches personalized intervention scheme.

Description

Technical Field

[0001] This disclosure relates to the field of medical testing and health assessment technology, specifically to a human aging risk scoring system and its application, and more specifically to a human aging risk assessment system and its application based on a weighted calculation of three modules: inflammatory risk (mainly involving the aging-associated secretory phenotype, SASP), metabolic risk, and oxidative stress risk. Background Technology

[0002] Aging is a complex biological process involving the decline of physiological functions and the disruption of homeostasis over time. It is the most significant risk factor for chronic diseases such as cardiovascular disease, neurodegenerative diseases, metabolic syndrome, and malignant tumors. Modern medical research indicates that human aging is not a single-dimensional change, but a systemic decline resulting from the cumulative effects of multiple systems. Among these, chronic low-grade inflammation (SASP), metabolic dysfunction, and oxidative stress imbalance are the three core mechanisms driving aging.

[0003] Cellular senescence is accompanied by the emergence of the senescence-associated secretory phenotype (SASP), in which senescent cells secrete large amounts of pro-inflammatory factors, chemokines, and matrix metalloproteinases, driving the decline of tissue and organ function. Metabolic risk encompasses imbalances in multiple metabolic networks, including those of carbohydrates, lipids, bones, heart, liver, and kidneys, directly reflecting damage to the body's energy and material basis. Oxidative stress is a pathological process in which the production of reactive oxygen species exceeds the antioxidant capacity to scavenge them, leading to oxidative damage to lipids, proteins, and DNA. These three mechanisms mutually promote each other: inflammation exacerbates metabolic disorders and oxidative damage, metabolic abnormalities induce oxidative stress and inflammation cascades, and oxidative damage, in turn, accelerates cellular senescence and metabolic function loss.

[0004] In existing clinical or health management systems, aging assessments are often limited to testing a single system or a single dimension. For example, only inflammatory factors are tested to assess SASP, or only routine biochemical indicators are tested to assess metabolism, or only oxidative stress markers are tested. This fragmented assessment model disconnects the holistic and interconnected nature of the aging mechanism, fails to truly reflect the body's overall aging state, and is also difficult to provide precise, personalized anti-aging intervention guidance.

[0005] Therefore, there is an urgent need to establish a multi-dimensional aging risk assessment system that integrates inflammation, metabolism, and oxidative stress to achieve quantitative classification and closed-loop intervention management of aging risks. Summary of the Invention

[0006] This disclosure aims to provide a comprehensive human aging assessment system that covers three core modules: inflammatory risk (SASP), metabolic risk, and oxidative stress risk, in order to address the technical shortcomings of existing aging assessment technologies, such as their single dimension, lack of systematic linkage, and lack of closed-loop intervention guidance.

[0007] To achieve the above-mentioned technical objectives, the technical solution adopted in this disclosure is as follows: Firstly, this disclosure provides a human aging risk scoring system, which includes an inflammation risk (SASP) scoring module, a metabolic risk scoring module, and an oxidative stress risk scoring module. The system calculates a comprehensive human aging risk score by combining the calculation results of these modules, and outputs the aging risk level and intervention measures. The risk scoring of the human aging risk scoring system includes the following steps: I. Obtain information on the subject's gender, age, menopausal status, height, weight, and waist circumference; II. Collect fresh biological samples from the subjects, provided they meet the pre-testing requirements. III. Measure the levels of various biomarkers related to inflammation, metabolism, and oxidative stress in the subjects' biological samples, and calculate the inflammation risk score, metabolic risk score, and oxidative stress risk score using the algorithms of each module; IV. Input the scores from the module into the aging risk calculation model and calculate the aging risk score according to the formula: Aging risk score = Inflammation risk score × 0.4 + Metabolic risk score × 0.5 + Oxidative stress risk score × 0.1. The weight allocation is dynamically adjusted and calibrated according to the changes in the source, composition and number of subjects to meet the needs of different groups for human aging risk assessment. V. Based on the weighted algorithm rules and aging risk rating standards, the final aging risk level, risk abnormality module, and intervention measures are output.

[0008] In some implementations, the calculation of the inflammation risk (SASP) module includes: Select any two or more of the following SASP-related biomarkers for combination: interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), growth differentiation factor-15 (GDF-15), tumor necrosis factor alpha (TNFα), interleukin-10 (IL-10), matrix metalloproteinase 3 (MMP-3), monocyte chemoattractant protein-1 (MCP-1), transforming growth factor β1 (TGF-β1), body size index (ABSI), interleukin-1β (IL-1β), interleukin-8 (IL-8), vascular endothelial growth factor (VEGF), and interferon-gamma (IFNγ). Based on the age of the subjects, four segments were determined: youth, middle age, young old age, and old age. Dynamic threshold parameters for GDF-15, MCP-1, ABSI, and IL-10 were obtained, and MMP3 differential thresholds were obtained based on gender. The scoring model is used to calculate the individual scores and then sum them up with weights. It has the ability to tolerate missing data, and automatically adjusts to the theoretical maximum score when some indicators are missing. The inflammation risk level is ultimately determined based on the ratio of the total SASP score to the theoretical maximum score.

[0009] In a preferred embodiment, SASP-related biomarkers include IL-6, hs-CRP, GDF-15, TNFα, IL-10, MMP3, MCP-1, TGF-β1, ABSI, IL-1β, IL-8, VEGF, and IFNγ; In a preferred embodiment, the scoring model includes at least one of the following: a standard unidirectional linear scoring model, an age-dynamic linear scoring model, a gender-differentiated unidirectional linear scoring model, a U-shaped 4-tuple scoring model, and a U-shaped 3-tuple scoring model.

[0010] In some implementations, the calculation of the metabolic risk module includes: Metabolic markers were assigned to metabolic modules for glucose metabolism, lipid metabolism, bone metabolism, cardiac metabolism, liver metabolism, kidney metabolism, and individual metabolic processes for calculation. The metabolic markers of glucose metabolism include blood glucose (Glu) and insulin (INS), which are assessed using the insulin resistance coefficient (HOMA-IR), whereby the insulin resistance coefficient (HOMA-IR) = blood glucose × insulin ÷ 22.5. The metabolic markers of lipid metabolism include triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), which are assessed using the body mass index (ABSI). The formula for calculating the body mass index is as follows: Body Mass Index (BMI) = weight (kg) ÷ height (m)² ABSI = Waist circumference (m) / (BMI) 2 / 3 × Height (m) 1 / 2 ); The metabolic markers of bone metabolism include total type I collagen N-terminal elongated peptide (Total P1NP) and β-collagen specific sequence (β-CTx). The metabolic marker for cardiac metabolism is N-terminal pro-brain natriuretic peptide (NT-proBNP); the metabolic marker for liver metabolism is albumin (ALB); the metabolic marker for kidney metabolism is the estimated glomerular filtration rate (eGFR) calculated using cystatin C (Cys-C), age, and sex. The eGFR calculation method is as follows: male: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^age If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age female: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^(age) × 0.932 If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age × 0.932; The metabolic markers for the single metabolism include 25-hydroxyvitamin D (25-OH VD), adiponectin (ADP), and insulin-like growth factor-1 (IGF-1). When any metabolic module exceeds the ideal range, it is judged as an abnormal item and scored; a weighting rule is set: when there are ≥2 abnormal items and <4 abnormal items, a weight of 20 points is added, and when there are ≥4 abnormal items, a weight of 40 points is added. The metabolic risk score is output after summing. Wherein, when the weights of Glu, INS, and HOMA-IR are 35, 30, and 35 respectively, and the total score is 100, the sugar metabolism score = the sum of the three scores × 0.6. When the sugar metabolism score > 20, the sugar metabolism is judged as an abnormal item. The scoring rules for Glu are shown in Table 1, the scoring rules for INS are shown in Table 2, and the scoring rules for HOMA-IR are shown in Table 3. When the weights of TG / HDL-C and LDL-C are 60 and 40 points respectively, and the total score is 100 points, the lipid metabolism score = the sum of the two scores × 0.6 × ABSI coefficient. When the lipid metabolism score > 20 points, lipid metabolism is judged as an abnormal item. The scoring rules for TG / HDL-C are shown in Table 4, the scoring rules for LDL-C are shown in Table 5, and the determination rules for the ABSI coefficient are shown in Table 6. When both Total P1NP and β-CTx exceed the ideal range, the bone metabolism score is 20 points, which is considered an abnormality; among them... The ideal range of Total P1NP: Premenopausal women: 14.75 ng / mL to 59.15 ng / mL Postmenopausal: 16.05 ng / mL to 76.45 ng / mL Males: 15.54 ng / mL to 70.79 ng / mL The ideal range of β-CTx: Premenopausal women: ≤0.582 ng / mL Postmenopausal: ≤1.016 ng / mL For men aged 30 to 50: ≤0.587 ng / mL >50 to 70 years old: ≤0.711 ng / mL >70 years old: ≤0.861 ng / mL; When NT-proBNP, ALB, and eGFR exceed their respective ideal ranges, the score is 7 points, and it is judged as an anomaly. The ideal range for NT-proBNP is ≤125 pg / mL. The ideal range for ALB is ≥40 g / L. The ideal range for eGFR is ≥75; When the levels of 25-OH VD, ADP, and IGF-1 each exceed the ideal range, the score is 7 points, and it is judged as an anomaly; among which... The ideal range for 25-OH VD is ≥15 ng / mL. The ideal range of ADP: Male: 5 μg / mL to 15 μg / mL Women: 6 μg / mL to 18 μg / mL The ideal range for IGF-1 is: <40 years old: ≥70ng / mL ≥40 years old: 70 ng / mL to 250 ng / mL.

[0011] In some implementations, the calculation of the oxidative stress risk module includes: Detection of biomarkers: glutathione reductase (GR), superoxide dismutase (SOD), oxidized low-density lipoprotein, 8-iso-prostaglandin F2α (8-iso-PGF2α), advanced oxidized protein products (AOPP), and 8-hydroxydeoxyguanosine (8-OHdG). For GR and SOD indices that exhibit non-normal distribution or a U-shaped relationship, Box-Cox transformation is first performed followed by Z-score standardization, and the absolute value of the Z-score is used for assignment. For GR and SOD indices that exhibit normal distribution and a U-shaped relationship, the absolute value of the Z-score is used for assignment. For other indices, the Z-score is directly assigned positively. The relative aging risk score is calculated by linear weighting. At the same time, a GR-SOD dual-indicator antioxidant defense status classifier is constructed, and the antioxidant function status is determined based on the relative levels of the two indices with the 95% reference interval.

[0012] In a preferred embodiment, the classifier is a four-phase classifier, including a balance phase, a cooperative compensation phase, an imbalance phase, and an exhaustion phase.

[0013] In some implementations, the biological samples include whole blood samples, serum samples, heparinized plasma samples, EDTA plasma samples, sodium citrate plasma samples, cerebrospinal fluid samples, urine samples, and saliva samples; the methods for determining each biomarker include chemiluminescence, biochemical analysis, enzyme-linked immunosorbent assay (ELISA), fluorescence immunochromatography, mass spectrometry, immunoassay, and biochemical analysis.

[0014] In a preferred embodiment, the types of biomarkers related to inflammation, metabolism, and oxidative stress include at least the biomarkers defined above, and / or dynamic combinations of the biomarkers; the reference ideal range, dynamic threshold parameters, and weight allocation of each module are dynamically adjusted and calibrated according to changes in the source, composition, and number of the subject population, so as to meet the needs of different groups for human aging risk assessment.

[0015] In some implementations, the system is equipped with a weighted algorithm (risk coverage rule): when either the inflammatory risk (SASP) or metabolic risk is determined to be high risk, the overall aging risk is directly determined to be high risk regardless of the calculated aging risk score; when either the inflammatory risk (SASP) or metabolic risk is determined to be medium risk, the overall aging risk is directly determined to be medium risk.

[0016] In some implementations, the aging risk rating includes the following methods: The risk level is categorized into low, medium, and high risk: a risk score ≤ 30 is considered low risk; a risk score > 30 but ≤ 60 is considered medium risk; and a risk score > 60 is considered high risk. The risk is divided into 1-6 levels: Level 1 is when the aging risk score is ≤20; Level 2 is when the aging risk score is >20 but ≤40; Level 3 is when the aging risk score is >40 but ≤60; Level 4 is when the aging risk score is >60 but ≤80; Level 5 is when the aging risk score is >80 but ≤100; and Level 6 is when the aging risk score is >100.

[0017] In some implementation plans, after appropriate interventions are implemented, the aging risk of the subjects is evaluated to determine whether it has improved. The evaluation criteria include, but are not limited to: I. Aging risk is assessed as high, medium, and low risk, with the risk level decreasing by one level; II. Aging risk is assessed on a scale of 1 to 6, with each risk level decreasing by one level. III. A decrease of 10 points or more in the aging risk score; IV. The doctor's assessment, based on the test results and the subject's own positive changes.

[0018] In some implementation plans, corresponding interventions are provided for different aging risk levels and major abnormal modules, including: low risk: maintaining a healthy lifestyle and annual monitoring; medium risk: implementing targeted nutritional supplementation (antioxidants, Omega-3, etc.), metabolic and weight management, and stress management; high risk: medical specialist referral, senolytics targeted intervention, and standardized treatment of chronic diseases.

[0019] In some implementations, the system can continuously monitor the aging risk of individuals or groups, establish personal aging risk score profiles, and obtain more accurate aging risk assessments and aging trend analysis.

[0020] In some implementations, the aging risk calculation model is implemented by at least one of the following methods; 1) Implemented through specific software programs, it automatically calculates and outputs a test report based on input information; 2) The program is written using common office software (Office, WPS, etc.) to automatically calculate and output a test report based on the input information; 3) Input the judgment and calculation rules into the LIS system, and the system will automatically capture the information, calculate, and output a detection report.

[0021] In some implementations, the system is suitable for at least one of the following application scenarios: I. In the healthcare field, healthcare providers use the system to assess patients' inflammation, metabolism, oxidative stress, and aging-related risks, thereby providing personalized treatment recommendations and interventions; it is used in anti-aging and chronic disease management, nutrition and weight management, exercise and rehabilitation medicine, health checkups and population studies, medical research and anti-aging drug development; II. In the commercial insurance sector, insurance companies use the aging risk assessment results from the aforementioned system to adjust the premium rates for health insurance and pension insurance accordingly. III. In the field of sports and fitness, sports coaches develop targeted scientific exercise plans based on the aging and metabolic risk assessment results of the aforementioned system, so as to restore the body's functions to a healthy state. IV. In the fields of elderly care institutions and anti-aging centers, elderly care institutions can use the aging risk assessment results of the system to conduct health classification and care intervention guidance for elderly residents; anti-aging centers can develop personalized anti-aging plans and track the effectiveness of treatments based on the assessment results. V. In the field of corporate health management, companies incorporate aging risk assessment into employee health and welfare plans, providing employees with health early warnings and intervention suggestions to reduce medical expenses and productivity losses caused by aging and chronic diseases.

[0022] This disclosure has the following advantages: Compared with existing technologies, this disclosure provides a comprehensive human aging assessment system covering three core modules: inflammatory risk (SASP), metabolic risk, and oxidative stress risk. This system outputs an accurate aging risk score and level through a scientifically weighted combination of scores from these three modules, and matches personalized intervention plans accordingly. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the specific embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. The accompanying drawings are incorporated in and constitute a part of this specification, illustrating embodiments consistent with this specification, and are used together with the specification to explain the principles of this specification.

[0024] Figure 1 This embodiment of the present disclosure shows the information input and risk outcome determination in a group cohort study.

[0025] Figure 2 This disclosure displays statistical information on the risk distribution of a specific population in a cohort study.

[0026] Figure 3This displays the project reference range of the analysis model in the embodiments of this disclosure. Detailed Implementation

[0027] Definitions and Explanations To facilitate understanding of this disclosure, certain technical and scientific terms are specifically defined below. In this disclosure, unless otherwise stated, the scientific and technical terms used herein have meanings commonly understood by those skilled in the art. Furthermore, the cell and tissue culture, microbiology-related terms, and laboratory procedures used herein are all widely used terms and routine procedures in their respective fields. Meanwhile, to better understand this disclosure, definitions and explanations of relevant terms are provided below. It should be understood that this disclosure is not limited to specific methods, reagents, compounds, compositions, or biological systems, and variations thereof are certainly possible. It should also be understood that the terminology used in this application is for describing specific embodiments only and is not intended to be limiting.

[0028] Unless otherwise expressly stated, the terms “a,” “an,” and “the” as used in this specification and the appended claims cover one or more types.

[0029] As used herein, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps is not limited to the steps or modules listed, but may optionally include steps not listed, or may optionally include other steps inherent to such process, method, product, or device.

[0030] In the description herein, references to “some embodiments,” “some implementations,” or “some implementation schemes” describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0031] This disclosure provides a human aging risk scoring system, which includes an inflammation risk (SASP) scoring module, a metabolic risk scoring module, and an oxidative stress risk scoring module.

[0032] 1. Inflammation Risk (SASP) module score (maximum score 100 points): Based on 13 SASP biomarkers, the score is calculated using age-segmented dynamic thresholds, gender-differentiated thresholds, and 5 differential scoring models (unidirectional linear, age-dynamic linear, gender-differentiated unidirectional linear, U-shaped 4-tuple, and U-shaped 3-tuple), and has missing value tolerance.

[0033] 2. Metabolic Risk Module Scoring: Based on metabolic markers such as glucose, lipids, bone, heart, liver, kidney, and individual markers, the risk is divided into 7 categories for assessment. An abnormal item weighting rule is introduced (20 points are added for abnormal items ≥2 and <4, and 40 points are added for abnormal items ≥4), and a comprehensive metabolic score is calculated.

[0034] 3. Oxidative stress risk module score (out of 100): Based on 6 indicators including GR, SOD, ox-LDL, etc., the score is calculated linearly by Box-Cox transformation and Z-score standardization, and is supplemented by a GR-SOD dual-indicator four-stage antioxidant defense status classifier for functional staging.

[0035] In some implementations, the calculation of the inflammation risk (SASP) module includes: Select any two or more of the following SASP-related biomarkers for combination: interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), growth differentiation factor-15 (GDF-15), tumor necrosis factor alpha (TNFα), interleukin-10 (IL-10), matrix metalloproteinase 3 (MMP-3), monocyte chemoattractant protein-1 (MCP-1), transforming growth factor β1 (TGF-β1), body size index (ABSI), interleukin-1β (IL-1β), interleukin-8 (IL-8), vascular endothelial growth factor (VEGF), and interferon-gamma (IFNγ). Based on the age of the subjects, four segments were determined: youth, middle age, young old age, and old age. Dynamic threshold parameters for GDF-15, MCP-1, and ABSI were obtained, and MMP3 differential thresholds were obtained based on gender. The scoring model is used to calculate the individual scores and then sum them by weight. It has the ability to tolerate missing data, and automatically adjusts to the theoretical maximum score when some indicators are missing. The inflammation risk level is ultimately determined based on the ratio of the total SASP score to the theoretical maximum score.

[0036] In a preferred embodiment, SASP-related biomarkers include IL-6, hs-CRP, GDF-15, TNFα, IL-10, MMP3, MCP-1, TGF-β1, ABSI, IL-1β, IL-8, VEGF, and IFNγ.

[0037] In a preferred embodiment, the scoring model includes at least one of the following: a standard unidirectional linear scoring model, an age-dynamic linear scoring model, a gender-differentiated unidirectional linear scoring model, a U-shaped 4-tuple scoring model, and a U-shaped 3-tuple scoring model.

[0038] In some implementations, the calculation of the metabolic risk module includes: Metabolic markers were assigned to metabolic modules for glucose metabolism, lipid metabolism, bone metabolism, cardiac metabolism, liver metabolism, kidney metabolism, and individual metabolic processes for calculation. The metabolic markers of glucose metabolism include blood glucose (Glu) and insulin (INS), which are assessed using the insulin resistance coefficient (HOMA-IR), whereby the insulin resistance coefficient (HOMA-IR) = blood glucose × insulin ÷ 22.5. The metabolic markers of lipid metabolism include triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), which are assessed using the body mass index (ABSI). The formula for calculating the body mass index is as follows: Body Mass Index (BMI) = weight (kg) ÷ height (m)² ABSI = Waist circumference (m) / (BMI) 2 / 3 × Height (m) 1 / 2 ); The metabolic markers of bone metabolism include total type I collagen N-terminal elongated peptide (Total P1NP) and β-collagen specific sequence (β-CTx). The metabolic marker for cardiac metabolism is N-terminal pro-brain natriuretic peptide (NT-proBNP); the metabolic marker for liver metabolism is albumin (ALB); the metabolic marker for kidney metabolism is the estimated glomerular filtration rate (eGFR) calculated using cystatin C (Cys-C), age, and sex. The eGFR calculation method is as follows: male: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^age If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age female: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^(age) × 0.932 If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age × 0.932; The metabolic markers for the single metabolism include 25-hydroxyvitamin D (25-OH VD), adiponectin (ADP), and insulin-like growth factor-1 (IGF-1). When any metabolic module exceeds the ideal range, it is judged as an abnormal item and scored; a weighting rule is set: when there are ≥2 abnormal items and <4 abnormal items, a weight of 20 points is added, and when there are ≥4 abnormal items, a weight of 40 points is added. The metabolic risk score is output after summing. Wherein, when the weights of Glu, INS, and HOMA-IR are 35, 30, and 35 respectively, and the total score is 100, the sugar metabolism score = the sum of the three scores × 0.6. When the sugar metabolism score > 20, the sugar metabolism is judged as an abnormal item. The scoring rules for Glu are shown in Table 1, the scoring rules for INS are shown in Table 2, and the scoring rules for HOMA-IR are shown in Table 3. When the weights of TG / HDL-C and LDL-C are 60 and 40 points respectively, and the total score is 100 points, the lipid metabolism score = the sum of the two scores × 0.6 × ABSI coefficient. When the lipid metabolism score > 20 points, lipid metabolism is judged as an abnormal item. The scoring rules for TG / HDL-C are shown in Table 4, the scoring rules for LDL-C are shown in Table 5, and the determination rules for the ABSI coefficient are shown in Table 6. I. The Glu score conforms to a J-shaped curve (asymmetric risk), and the scoring rules are as follows: Table 1 II. The INS score needs to be determined based on the Glu test results. The scoring rules are as follows: Table 2 III. The HOMA-IR scoring rules are as follows: Table 3 The scoring rules for the IV and TG / HDL-C ratio are as follows: Table 4 V. The LDL-C scoring rules are as follows: Table 5 VI. Rules for determining ABSI coefficients: Table 6 When both Total P1NP and β-CTx exceed the ideal range, the bone metabolism score is 20 points, which is considered an abnormality; among them... The ideal range of Total P1NP: Premenopausal women: 14.75 ng / mL to 59.15 ng / mL Postmenopausal: 16.05 ng / mL to 76.45 ng / mL Males: 15.54 ng / mL to 70.79 ng / mL The ideal range of β-CTx: Premenopausal women: ≤0.582 ng / mL Postmenopausal: ≤1.016 ng / mL For men aged 30 to 50: ≤0.587 ng / mL >50 to 70 years old: ≤0.711 ng / mL >70 years old: ≤0.861 ng / mL; When NT-proBNP, ALB, and eGFR exceed their respective ideal ranges, the score is 7 points, and it is judged as an anomaly. The ideal range for NT-proBNP is ≤125 pg / mL. The ideal range for ALB is ≥40 g / L. The ideal range for eGFR is ≥75; When the levels of 25-OH VD, ADP, and IGF-1 each exceed the ideal range, the score is 7 points, and it is judged as an anomaly; among which... The ideal range for 25-OH VD is ≥15 ng / mL. The ideal range of ADP: Male: 5 μg / mL to 15 μg / mL Women: 6 μg / mL to 18 μg / mL The ideal range for IGF-1 is: <40 years old: ≥70ng / mL ≥40 years old: 70 ng / mL to 250 ng / mL.

[0039] In some implementations, the calculation of the oxidative stress risk module includes: Detection of biomarkers: glutathione reductase (GR), superoxide dismutase (SOD), oxidized low-density lipoprotein, 8-iso-prostaglandin F2α (8-iso-PGF2α), advanced oxidized protein products (AOPP), and 8-hydroxydeoxyguanosine (8-OHdG). For GR and SOD indices that exhibit non-normal distribution or a U-shaped relationship, Box-Cox transformation is first performed followed by Z-score standardization, and the absolute value of the Z-score is used for assignment. For GR and SOD indices that exhibit normal distribution and a U-shaped relationship, the absolute value of the Z-score is used for assignment. For other indices, the Z-score is directly assigned positively. The relative aging risk score is calculated by linear weighting. At the same time, a GR-SOD dual-indicator antioxidant defense status classifier is constructed, and the antioxidant function status is determined based on the relative levels of the two indices with the 95% reference interval.

[0040] In a preferred embodiment, the classifier is a four-phase classifier, including a balance phase, a cooperative compensation phase, an imbalance phase, and an exhaustion phase.

[0041] In some implementations, the biological samples include whole blood samples, serum samples, heparinized plasma samples, EDTA plasma samples, sodium citrate plasma samples, cerebrospinal fluid samples, urine samples, and saliva samples; the methods for determining each biomarker include chemiluminescence, biochemical analysis, enzyme-linked immunosorbent assay (ELISA), fluorescence immunochromatography, mass spectrometry, immunoassay, and biochemical analysis.

[0042] In a preferred embodiment, the types of biomarkers related to inflammation, metabolism, and oxidative stress include at least the biomarkers defined above, and / or dynamic combinations of the biomarkers; the reference ideal range, dynamic threshold parameters, and weight allocation of each module are dynamically adjusted and calibrated according to changes in the source, composition, and number of the subject population, so as to meet the needs of different groups for human aging risk assessment.

[0043] In some implementations, the system is equipped with a weighted algorithm (risk coverage rule): when either the inflammatory risk (SASP) or metabolic risk is determined to be high risk, the overall aging risk is directly determined to be high risk regardless of the calculated aging risk score; when either the inflammatory risk (SASP) or metabolic risk is determined to be medium risk, the overall aging risk is directly determined to be medium risk.

[0044] Formula for calculating the comprehensive aging risk score: Aging risk score = Inflammation risk score × 0.4 + Metabolic risk score × 0.5 + Oxidative stress risk score × 0.1.

[0045] This disclosure posits that metabolic homeostasis is fundamental to survival (weight 0.5), chronic inflammation is the core effect driving aging and related diseases (weight 0.4), and oxidative stress is the underlying pathological damage mechanism (weight 0.1). This weighting allocation scientifically reflects the contribution of each dimension to overall aging. Furthermore, this weighting allocation can be dynamically adjusted and calibrated based on changes in the source, composition, and number of subjects to meet the aging risk assessment needs of different groups.

[0046] Aging risk assessment criteria: Rating Method 1 (Three-Level Classification): 1. When the aging risk score is ≤30, it is considered low risk; 2. When the aging risk score is >30 but ≤60, it is considered medium risk; 3. When the aging risk score is >60, it is considered high risk.

[0047] Rating Method 2 (Six-Level Classification): 1. Score ≤ 20 points: Level 1; 2. Score > 20 points but ≤ 40 points: Level 2; 3. Score > 40 points but ≤ 60 points: Level 3; 4. Score > 60 but ≤ 80: Level 4; 5. Score > 80 points but ≤ 100 points: Level 5; 6. Score > 100 points: Level 6.

[0048] Weighted Algorithm (Risk Coverage Rules): Since inflammation and metabolism are key determinants of the aging process, this disclosure sets weighted coverage rules: 1. When either the inflammatory risk (SASP) or metabolic risk is determined to be high, the overall aging risk is directly determined to be "high risk".

[0049] 2. When either the inflammatory risk (SASP) or metabolic risk is determined to be of medium risk, the overall aging risk is directly determined to be "medium risk".

[0050] Interventions targeting the risks of aging: Based on the output aging risk level and major abnormal modules, the following intervention guidelines are provided: I. Low risk: Intervention goals: Maintain homeostasis and prevent accelerated aging.

[0051] 1. Lifestyle intervention: Maintain a regular sleep schedule (7-8 hours of sleep) and avoid staying up late; persist in 150 minutes of moderate-intensity aerobic exercise and 2-3 resistance training sessions per week to maintain muscle mass and metabolic activity.

[0052] 2. Dietary intervention: The Mediterranean diet is recommended, with an intake of dark green vegetables and berries rich in antioxidants, and appropriate amounts of high-quality protein and healthy fats (such as deep-sea fish and olive oil).

[0053] 3. Monitoring Recommendations: Conduct a comprehensive assessment of aging risk annually and monitor trends dynamically.

[0054] II. Medium risk: Intervention goals: To block the pathological process and correct systemic imbalances.

[0055] 1. Targeted nutritional supplementation: If oxidative stress is high, supplement with antioxidants such as vitamin C, vitamin E, coenzyme Q10, and alpha-lipoic acid; if SASP is high, supplement with natural anti-inflammatory components such as Omega-3 fatty acids (EPA+DHA 1-2g / day) and curcumin; if metabolism is abnormal, supplement with vitamin D (1000-2000 IU / day) and specific dietary fiber.

[0056] 2. Metabolic and weight management: For individuals with abdominal obesity (high ABSI), a 5%-10% weight loss through a calorie deficit and exercise can significantly improve insulin resistance and adiponectin levels.

[0057] 3. Emotion and Stress Management: Long-term elevated cortisol levels can exacerbate SASP and oxidative stress. It is recommended to relieve chronic stress through meditation, mindfulness, and other methods.

[0058] 4. Monitoring Recommendations: Conduct a follow-up review every 3-6 months, focusing on monitoring the improvement of any abnormal items.

[0059] III. High Risk: Intervention goals: Medical intervention to delay irreversible damage and prevent age-related diseases.

[0060] 1. Medical specialist referral: High risk usually indicates the presence of organic lesions or severe functional decline. It is recommended to immediately refer to a specialist (such as endocrinology, cardiology, geriatrics) for a comprehensive and in-depth physical examination and disease screening.

[0061] 2. Senolytics and Targeted Interventions: Under the guidance of a specialist, explore the use of drugs or therapies to eliminate senescent cells and control the cascade effects of SASP.

[0062] 3. Standardized treatment of chronic diseases: For concurrent chronic diseases such as diabetes, hypertension, and osteoporosis, strictly follow the doctor's prescription for drug treatment (such as hypoglycemic drugs, antihypertensive drugs, bone resorption inhibitors, etc.).

[0063] 4. Strengthen monitoring: Retest core indicators every 1-3 months to assess the effectiveness of the intervention program and make timely adjustments.

[0064] The above method can also be used when classifying and rating according to the six levels, and intervention measures can be specified for each level.

[0065] Example To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The following is merely a further description of this disclosure, and the scope of protection of this disclosure is not limited thereto. In the embodiments and experimental examples of this disclosure, the technical means or methods, etc., not specifically described, are conventional technical means or methods in the art. Unless otherwise specified, the materials, reagents, experimental equipment, etc., used in the embodiments and experimental examples of this disclosure can all be obtained commercially.

[0066] Example 1: Calculation and rating of subject aging risk 1.1 Sample Collection and Testing The subject was a 52-year-old male. Fasting venous blood and first-morning urine were collected.

[0067] Inflammation module detection: 13 indicators including IL-6, hs-CRP, GDF-15, etc.

[0068] Metabolic module detection: 13 indicators including Glu, INS, TG, HDL-C, etc.

[0069] Oxidative stress module detection: 6 indicators including GR, SOD, ox-LDL, etc.

[0070] 1.2 Scoring results for each module: Inflammation Risk (SASP) score: 45 points (risk ratio 45%, classified as medium risk).

[0071] Metabolic risk score calculation result: 52 points (classified as medium risk).

[0072] Oxidative stress risk score: 60 points (risk level 3).

[0073] 1.3 Calculation of Comprehensive Aging Risk Score Aging risk score = 45×0.4 + 52×0.5 + 60×0.1 = 18 + 26 + 6 = 50 points.

[0074] 1.4 Rating Determination Based on rating method 1: 50 points > 30 points and ≤ 60 points, it is initially judged as medium risk.

[0075] According to rating method 2: 50 points > 40 points and ≤ 60 points, it is judged as level 3.

[0076] 1.5 Intervention Program Output: System output report: Overall aging risk is medium risk (level 3). The main abnormal modules are inflammation and metabolism. Recommended medium-risk intervention measures: adjust work and rest schedule and diet, supplement with Omega-3 fatty acids and antioxidant nutrients, control waist circumference and weight, and have a follow-up examination in 3 months.

[0077] Example 2: Triggering of System Weighted Coverage Rules and Output of Detailed Intervention Scheme 2.1 Sample Collection and Testing The subject was a 65-year-old female who presented with a history of chronic joint pain and unexplained fatigue. Fasting venous blood and first-morning urine were collected.

[0078] Inflammation module detection: IL-6 measured 8.5 pg / mL (senescence threshold 5.0 in the ultra-old age group), hs-CRP measured 4.2 mg / L (exceeding threshold 3.0), GDF-15 measured 2500 pg / mL (senescence threshold 2200 in the ultra-old age group), and the total SASP score calculated according to the algorithm was 68 (risk ratio 68%).

[0079] Metabolic module test results: Glu=5.0, TG=1.2, HDL=1.4, other indicators are basically normal, metabolic score is calculated as 25 points.

[0080] Oxidative stress module detection: GR measured 36.7 U / L (low), SOD measured 182 U / mL (normal), ox-LDL and other parameters were normal, the GR-SOD classifier determined it to be "disequilibrium period", and the oxidative stress score was 66 points.

[0081] 2.2 Calculation of Comprehensive Aging Risk Score Aging risk score = 68×0.4 + 25×0.5 + 66×0.1 = 27.2 + 12.5 + 6.6 = 46.3 points.

[0082] 2.3 Rating Determination and Weighting Rule Triggering: According to rating method 1, a score of 46.3 usually corresponds to medium risk. However, according to the weighted algorithm (risk coverage rule) disclosed in this publication, since the single item of inflammation risk (SASP) has reached 68 points (judged as high risk), the system directly covers the calculation of the score, and finally determines that the subject's comprehensive aging risk is "high risk".

[0083] 2.4 Intervention Program Output: The system outputs a detailed assessment report: The overall risk of aging is high. This indicates accelerated aging, severe inflammatory aging, and an imbalance in the antioxidant system.

[0084] Intervention recommendations trigger high-risk contingency plans, emphasizing comprehensive management from lifestyle and daily routines to medical interventions: (1) Adjustment of work and rest and lifestyle: Ensure 7-8 hours of high-quality sleep every day and avoid staying up late to restore endocrine rhythm; due to joint pain, stop running and other strenuous weight-bearing exercises, and switch to swimming, Tai Chi and other gentle exercises for 20-30 minutes every day; strictly adopt an anti-inflammatory diet, reduce the intake of red meat, refined carbohydrates and trans fats, and increase the proportion of deep-sea fish, olive oil and dark antioxidant vegetables.

[0085] (2) Basic nutrition and antioxidant supplementation: For high SASP, supplement with high-purity Omega-3 fatty acids (EPA+DHA 1-2g / day) and curcumin daily to reduce systemic inflammation; for the GR-SOD imbalance period, focus on supplementing riboflavin (vitamin B2) and trace elements such as copper, zinc and manganese to support the synthesis of antioxidant enzymes, in combination with basic doses of vitamin C and vitamin E.

[0086] (3) Medical intervention: It is recommended to refer to a general practitioner or internist for routine cardiovascular disease risk assessment and bone and joint X-ray examination; under the guidance of a doctor, nonsteroidal anti-inflammatory drugs may be used to relieve acute joint pain symptoms if necessary.

[0087] (4) Enhanced monitoring: One month after the above intervention, core inflammatory markers and oxidative stress markers (GR, SOD) were retested, and subsequent plans were adjusted according to the trend of indicator changes.

[0088] Example 3: Premium rate adjustment and health cohort management for commercial insurance 3.1 Assessment Background: To optimize its health insurance product pricing model, a commercial insurance company conducted an aging risk assessment on 5,000 applicants aged 35-60.

[0089] 3.2 Assessment Implementation: The medical examination center collects fasting venous blood and morning urine samples from applicants, measures indicators of inflammation, metabolism, and oxidative stress, and inputs them into the system to calculate the aging risk score and risk level for each applicant.

[0090] 3.3 Application of Results and Queue Creation: System statistics show that among the 5,000 people, 65% are low-risk, 25% are medium-risk, and 10% are high-risk.

[0091] (1) Premium rate adjustment: Low-risk groups enjoy a 10% discount on the standard premium; medium-risk groups are insured at the standard premium, but need to sign a health management agreement; high-risk groups need to pay an additional premium of 20% or be deferred from insurance.

[0092] (2) Health management intervention: Insurance companies establish health cohort files for medium- and high-risk policyholders and push targeted diet and exercise intervention programs. For medium-risk individuals with metabolic disorders, weight loss guidance is provided by partner institutions.

[0093] (3) Long-term follow-up study: The insurance company will continue to track the actual incidence rate of major diseases and medical claims rate of the 5,000-person cohort in the next 5 years, conduct correlation analysis with the risk classification of this assessment system, further verify and dynamically adjust the weight allocation and threshold parameters of the model in insurance actuarial science, and achieve precise risk control.

[0094] Example 4: Population Stratification and Treatment Tracking in Anti-Aging Centers 4.1 Assessment Background: A high-end anti-aging health center conducted an annual comprehensive aging assessment for its 100 VIP clients (aged 40-75) in order to develop personalized anti-aging plans and track the intervention effects.

[0095] 4.2 Evaluation Implementation and Group Analysis: The system collects biological samples from clients and inputs them into an aging risk calculation model, outputting a risk distribution map of 100 people.

[0096] (1) Group stratification: The assessment results show that 35% of customers are low-risk, 50% are medium-risk, and 15% are high-risk.

[0097] (2) Risk subtype analysis: Further analysis of the main abnormal modules revealed that 50% of medium-risk customers belong to "metabolic-dominated aging" (metabolic score contributes the most), 30% belong to "inflammatory-dominated aging", and 20% belong to "oxidative stress-dominated aging".

[0098] 4.3 Personalized intervention and efficacy tracking: (1) Treatment plan: For clients with "metabolism-dominant" conditions, the center develops a treatment plan based on fasting therapy and metabolic regulation nutrients; for clients with "inflammation-dominant" conditions, a treatment plan combining hyperbaric oxygen therapy with high-dose Omega-3 intravenous infusion is developed; for high-risk clients, in-depth screening and senolytics intervention are conducted in conjunction with internal medicine and surgery doctors.

[0099] (2) Efficacy evaluation: After the 3-month intervention period, 100 clients underwent another aging risk assessment. The system output an efficacy analysis report by comparing the data before and after the intervention. Statistics showed that the average aging risk score of the medium-risk group decreased from 48 to 39, with 65% of the clients experiencing a decrease of one level in risk, proving the effectiveness of the intervention program. The system successfully achieved quantitative tracking and closed-loop management of the anti-aging effect.

[0100] The foregoing description of specific exemplary embodiments of this disclosure is for illustrative and explanatory purposes. These descriptions are not intended to limit this disclosure to the precise forms disclosed, and it will be apparent that many changes and variations can be made in accordance with the foregoing teachings. The exemplary embodiments were chosen and described in order to explain the specific principles of this disclosure and their practical application, thereby enabling those skilled in the art to implement and utilize various different exemplary embodiments of this disclosure, as well as various different choices and variations. The scope of this disclosure is intended to be defined by the claims and their equivalents.

Claims

1. A human aging risk scoring system, characterized in that, The system includes an inflammation risk (SASP) scoring module, a metabolic risk scoring module, and an oxidative stress risk scoring module. By combining the calculation results of these modules, a comprehensive human aging risk score is calculated, and the aging risk level and intervention measures are output. The risk assessment of the human aging risk assessment system includes the following steps: I. Obtain information on the subject's gender, age, menopausal status, height, weight, and waist circumference; II. Collect fresh biological samples from the subjects, provided they meet the pre-testing requirements. III. Measure the levels of various biomarkers related to inflammation, metabolism, and oxidative stress in the subjects' biological samples, and calculate the inflammation risk score, metabolic risk score, and oxidative stress risk score using the algorithms of each module; IV. Input the scores from the module into the aging risk calculation model and calculate the aging risk score according to the formula: Aging risk score = Inflammation risk score × 0.4 + Metabolic risk score × 0.5 + Oxidative stress risk score × 0.

1. The weight allocation is dynamically adjusted and calibrated according to the changes in the source, composition and number of subjects to meet the needs of different groups for human aging risk assessment. V. Based on the weighted algorithm rules and aging risk rating standards, the final aging risk level, risk abnormality module, and intervention measures are output.

2. The system according to claim 1, characterized in that, The calculation of the inflammation risk (SASP) module includes: Select any two or more of the following SASP-related biomarkers for combination: interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), growth differentiation factor-15 (GDF-15), tumor necrosis factor alpha (TNFα), interleukin-10 (IL-10), matrix metalloproteinase 3 (MMP-3), monocyte chemoattractant protein-1 (MCP-1), transforming growth factor β1 (TGF-β1), body size index (ABSI), interleukin-1β (IL-1β), interleukin-8 (IL-8), vascular endothelial growth factor (VEGF), and interferon-gamma (IFNγ). Based on the age of the subjects, four segments were determined: youth, middle age, young old age, and old age. Dynamic threshold parameters for GDF-15, MCP-1, ABSI, and IL-10 were obtained, and MMP3 differential thresholds were obtained based on gender. The scoring model is used to calculate the individual scores and then sum them by weight. It has the ability to tolerate missing data, and automatically adjusts to the theoretical maximum score when some indicators are missing. The inflammation risk level is ultimately determined based on the ratio of the total SASP score to the theoretical maximum score. Preferably, SASP-related biomarkers include IL-6, hs-CRP, GDF-15, TNFα, IL-10, MMP3, MCP-1, TGF-β1, ABSI, IL-1β, IL-8, VEGF, and IFNγ; Preferably, the scoring model includes at least one of the following: a standard unidirectional linear scoring model, an age-dynamic linear scoring model, a gender-differentiated unidirectional linear scoring model, a U-shaped 4-tuple scoring model, and a U-shaped 3-tuple scoring model.

3. The system according to claim 1 or 2, characterized in that, The calculation of the metabolic risk module includes: Metabolic markers were assigned to metabolic modules for glucose metabolism, lipid metabolism, bone metabolism, cardiac metabolism, liver metabolism, kidney metabolism, and individual metabolic processes for calculation. The metabolic markers of glucose metabolism include blood glucose (Glu) and insulin (INS), which are assessed using the insulin resistance coefficient (HOMA-IR), whereby the insulin resistance coefficient (HOMA-IR) = blood glucose × insulin ÷ 22.

5. The metabolic markers of lipid metabolism include triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), which are assessed using the body mass index (ABSI). The formula for calculating the body mass index is as follows: Body Mass Index (BMI) = weight (kg) ÷ height (m)² ABSI = Waist circumference (m) / (BMI) 2 / 3 × Height (m) 1 / 2 ); The metabolic markers of bone metabolism include total type I collagen N-terminal elongated peptide (Total P1NP) and β-collagen specific sequence (β-CTx). The metabolic marker for cardiac metabolism is N-terminal pro-brain natriuretic peptide (NT-proBNP); the metabolic marker for liver metabolism is albumin (ALB); the metabolic marker for kidney metabolism is the estimated glomerular filtration rate (eGFR) calculated using cystatin C (Cys-C), age, and sex. The eGFR calculation method is as follows: male: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^age If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age female: If CysC ≤ 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-0.499) × (0.996)^(age) × 0.932 If CysC > 0.8 mg / L: eGFR = 133 × (CysC / 0.8)^(-1.328) × (0.996)^age × 0.932; The metabolic markers for the single metabolism include 25-hydroxyvitamin D (25-OH VD), adiponectin (ADP), and insulin-like growth factor-1 (IGF-1). When any metabolic module exceeds the ideal range, it is judged as an abnormal item and scored; a weighting rule is set: when there are ≥2 abnormal items and <4 abnormal items, a weight of 20 points is added, and when there are ≥4 abnormal items, a weight of 40 points is added. The metabolic risk score is output after summing. Wherein, when the weights of Glu, INS, and HOMA-IR are 35, 30, and 35 respectively, and the total score is 100, the sugar metabolism score = the sum of the three scores × 0.

6. When the sugar metabolism score > 20, the sugar metabolism is judged as an abnormal item. The scoring rules for Glu are shown in Table 1, the scoring rules for INS are shown in Table 2, and the scoring rules for HOMA-IR are shown in Table 3. When the weights of TG / HDL-C and LDL-C are 60 and 40 points respectively, and the total score is 100 points, the lipid metabolism score = the sum of the two scores × 0.6 × ABSI coefficient. When the lipid metabolism score > 20 points, lipid metabolism is judged as an abnormal item. The scoring rules for TG / HDL-C are shown in Table 4, the scoring rules for LDL-C are shown in Table 5, and the determination rules for the ABSI coefficient are shown in Table 6. When both Total P1NP and β-CTx exceed the ideal range, the bone metabolism score is 20 points, which is considered an abnormality; among them... The ideal range of Total P1NP: Premenopausal women: 14.75 ng / mL to 59.15 ng / mL Postmenopausal: 16.05 ng / mL to 76.45 ng / mL Males: 15.54 ng / mL to 70.79 ng / mL The ideal range of β-CTx: Premenopausal women: ≤0.582 ng / mL Postmenopausal: ≤1.016 ng / mL For men aged 30 to 50: ≤0.587 ng / mL >50 to 70 years old: ≤0.711 ng / mL >70 years old: ≤0.861 ng / mL; When NT-proBNP, ALB, and eGFR exceed their respective ideal ranges, the score is 7 points, and it is judged as an anomaly. The ideal range for NT-proBNP is ≤125 pg / mL. The ideal range for ALB is ≥40 g / L. The ideal range for eGFR is ≥75; When the levels of 25-OH VD, ADP, and IGF-1 each exceed the ideal range, the score is 7 points, and it is judged as an abnormal item; among which... The ideal range for 25-OH VD is ≥15 ng / mL. The ideal range of ADP: Male: 5 μg / mL to 15 μg / mL Women: 6 μg / mL to 18 μg / mL The ideal range for IGF-1 is: <40 years old: ≥70ng / mL ≥40 years old: 70 ng / mL to 250 ng / mL.

4. The system according to any one of claims 1-3, characterized in that, The calculation of the oxidative stress risk module includes: Detection of biomarkers: glutathione reductase (GR), superoxide dismutase (SOD), oxidized low-density lipoprotein, 8-iso-prostaglandin F2α (8-iso-PGF2α), advanced oxidized protein products (AOPP), and 8-hydroxydeoxyguanosine (8-OHdG). For GR and SOD indices that exhibit non-normal distribution or a U-shaped relationship, Box-Cox transformation is first performed followed by Z-score standardization, and the absolute Z-score value is used for assignment. For GR and SOD indices that exhibit normal distribution and a U-shaped relationship, the absolute Z-score value is used for assignment. For other indices, the Z-score is directly assigned positively. The relative aging risk score is calculated through linear weighting. At the same time, a GR-SOD dual-indicator antioxidant defense status classifier is constructed, and the antioxidant function status is determined based on the relative levels of the two indices with the 95% reference interval. Preferably, the classifier is a four-phase classifier, including a balance phase, a cooperative compensation phase, an imbalance phase, and an exhaustion phase.

5. The system according to any one of claims 1-4, characterized in that, The biological samples include whole blood samples, serum samples, heparinized plasma samples, EDTA plasma samples, sodium citrate plasma samples, cerebrospinal fluid samples, urine samples, and saliva samples; The methods for determining each biomarker include chemiluminescence immunoassay, biochemical analysis, enzyme-linked immunosorbent assay (ELISA), fluorescence immunochromatography, mass spectrometry, immunoassay, and biochemical analysis. Preferably, the types of biomarkers related to inflammation, metabolism, and oxidative stress include at least the biomarkers defined in claims 1-4, and / or dynamic combinations of the biomarkers; the reference ideal range, dynamic threshold parameters, and weight allocation of each module are dynamically adjusted and calibrated according to changes in the source, composition, and number of the subject population, so as to meet the needs of different groups for human aging risk assessment.

6. The system according to any one of claims 1-5, characterized in that, The system is equipped with a weighted algorithm (risk coverage rule): when either the inflammation risk (SASP) or metabolic risk is determined to be high risk, the overall aging risk is directly determined to be high risk, regardless of the calculated aging risk score; when either the inflammation risk (SASP) or metabolic risk is determined to be medium risk, the overall aging risk is directly determined to be medium risk.

7. The system according to any one of claims 1-6, characterized in that, The aging risk assessment includes the following methods: The risk level is categorized into low, medium, and high risk: a risk score ≤ 30 is considered low risk; a risk score > 30 but ≤ 60 is considered medium risk; and a risk score > 60 is considered high risk. The risk is divided into 1-6 levels: Level 1 is when the aging risk score is ≤20; Level 2 is when the aging risk score is >20 but ≤40; Level 3 is when the aging risk score is >40 but ≤60; Level 4 is when the aging risk score is >60 but ≤80; Level 5 is when the aging risk score is >80 but ≤100; and Level 6 is when the aging risk score is >100.

8. The system according to any one of claims 1-7, characterized in that, After appropriate interventions are implemented, the aging risk of the subjects is evaluated to determine whether it has improved. Evaluation criteria include, but are not limited to: I. Aging risk is assessed as high, medium, and low risk, with the risk level decreasing by one level; II. Aging risk is assessed on a scale of 1 to 6, with each risk level decreasing by one level. III. A decrease of 10 points or more in the aging risk score; IV. The doctor's assessment, based on the test results and the subject's own positive changes.

9. The system according to any one of claims 1-7, characterized in that, For different aging risk levels and major abnormal modules, corresponding intervention measures are provided, including: low risk: maintaining a healthy lifestyle and annual monitoring; medium risk: implementing targeted nutritional supplementation (antioxidants, Omega-3, etc.), metabolic and weight management, and stress management; high risk: medical specialist referral, senolytics targeted intervention, and standardized treatment of chronic diseases.

10. The system according to any one of claims 1-7, characterized in that, The system can continuously monitor the aging risk of individuals or groups, establish personal aging risk score profiles, and obtain more accurate aging risk assessment and aging trend analysis.

11. The system according to any one of claims 1-7, characterized in that, The aging risk calculation model is implemented by at least one of the following methods; 1) Implemented through specific software programs, it automatically calculates and outputs a test report based on input information; 2) The program is written using common office software (Office, WPS, etc.) to automatically calculate and output a test report based on the input information; 3) Input the judgment and calculation rules into the LIS system, and the system will automatically capture the information, calculate, and output a detection report.

12. The system according to any one of claims 1-7, characterized in that, The system is suitable for at least one of the following application scenarios: I. In the healthcare field, healthcare providers use the system to assess patients' inflammation, metabolism, oxidative stress, and aging-related risks, thereby providing personalized treatment recommendations and interventions; it is used in anti-aging and chronic disease management, nutrition and weight management, exercise and rehabilitation medicine, health checkups and population studies, medical research and anti-aging drug development; II. In the commercial insurance sector, insurance companies use the aging risk assessment results from the aforementioned system to adjust the premium rates for health insurance and pension insurance accordingly. III. In the field of sports and fitness, sports coaches develop targeted scientific exercise plans based on the aging and metabolic risk assessment results of the aforementioned system, so as to restore the body's functions to a healthy state. IV. In the fields of elderly care institutions and anti-aging centers, elderly care institutions can use the aging risk assessment results of the system to conduct health classification and care intervention guidance for elderly residents; anti-aging centers can develop personalized anti-aging plans and track the effectiveness of treatments based on the assessment results. V. In the field of corporate health management, companies incorporate aging risk assessment into employee health and welfare plans, providing employees with health early warnings and intervention suggestions to reduce medical expenses and productivity losses caused by aging and chronic diseases.

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