Method for detecting metabolic function of peripheral blood mononuclear cells by virtue of Seaharse biological energy analysis technology and application of method for detecting metabolic function of peripheral blood mononuclear cells by virtue of Seaharse biological energy analysis technology

Abstract

The invention discloses a method for detecting the metabolic function of peripheral blood mononuclear cells (PBMC) through a Seaharse biological energy analysis technology and application of the method. According to the method, firstly, a linear interval for detecting various indexes of the metabolic function of the peripheral blood mononuclear cells through a Seaharse biological energy analyzer is determined, and the determination of the linear interval provides a basis for establishing a standardized detection process, so that contrastive analysis among different samples and unification of cross-center data are facilitated; a solid technical foundation is laid for metabolic disease diagnosis, curative effect evaluation and prognosis prediction; according to the method, different disease types are further selected for analysis, the corresponding relation between the peripheral blood mononuclear cell bioenergy parameters and the clinical state is determined, and therefore the accuracy of related disease diagnosis, curative effect monitoring and prognosis prediction is remarkably improved.

Description

Technical Field

[0001] This application relates to a method and application for detecting the metabolic function of peripheral blood mononuclear cells (PBMCs) using Seahorse bioenergy analysis technology, belonging to the field of in vitro diagnostics and metabolomics detection technology. Background Technology

[0002] Mitochondria are the core site of cellular energy metabolism, and their functional status plays a crucial role in the occurrence, development, and outcome of various diseases. In recent years, extensive basic research has confirmed that mitochondrial dysfunction is not only closely related to tumors, metabolic diseases (such as diabetes, obesity, and thyroid diseases), and neurological disorders, but also significantly linked to pathological processes such as immune imbalance and abnormal inflammatory responses. Therefore, accurately assessing a patient's mitochondrial function and overall metabolic status has become an urgent need in clinical research and disease diagnosis and treatment.

[0003] Seahorse bioenergy analysis technology is an internationally recognized real-time cellular metabolism monitoring platform that comprehensively reflects mitochondrial function and glycolysis levels by measuring indicators such as oxygen consumption rate (OCR) and proton efflux rate (PER). This technology has been widely applied in basic research to analyze dynamic changes in cellular energy metabolism, explore drug mechanisms of action, and discover new molecular targets for diseases. However, currently, this technology is mainly limited to laboratory research and has not yet been truly translated into clinical diagnostic tools.

[0004] In clinical practice, disease diagnosis and efficacy assessment typically rely on biochemical indicators, hormone level testing, imaging examinations, and molecular genetic analysis. While these methods are valuable, they often have the following shortcomings: (1) they cannot directly reflect the metabolic function status of the patient's cells; (2) some methods are invasive or depend on tissue samples, making repeated testing inconvenient; and (3) they lack sufficient sensitivity in predicting early changes or recurrence of the disease. Therefore, there is a lack of a simple, sensitive, and repeatable detection method in clinical practice that can dynamically monitor the patient's energy metabolism status.

[0005] Peripheral blood mononuclear cells (PBMCs) are a widely available and readily accessible routine clinical sample, representing an important component of the body's immune system. Numerous studies have confirmed that the metabolic characteristics of PBMCs are altered in various diseases. For example, PBMCs from cancer patients often exhibit mitochondrial dysfunction; patients with metabolic diseases show reprogramming of glycolysis and oxidative phosphorylation; and PBMC metabolism also shows specific disturbances in neurological and immune diseases. This provides a solid foundation for using PBMCs as a window for assessing metabolic function.

[0006] Therefore, if Seahorse bioenergy analysis technology can be applied to the detection of PBMCs in patients, establishing a standardized and scalable clinical testing method, it can not only compensate for the shortcomings of existing testing methods but also realize the translation of basic research results into clinical practice. By detecting the metabolic function of PBMCs, it is expected to be used for early diagnosis, classification, efficacy evaluation, and prognosis prediction of diseases, thereby providing new evidence for precision medicine and personalized treatment.

[0007] Based on this, the present invention proposes a method for detecting PBMC metabolic function based on Seahorse bioenergy analysis technology, which realizes the translational application of this technology at the clinical level for the first time, providing new ideas and tools for the diagnosis and prognosis management of various diseases. Summary of the Invention

[0008] The purpose of this invention is to address the limitations of existing clinical testing methods in directly, dynamically, and non-invasively reflecting the energy metabolism function of patient cells, particularly the lack of sensitive indicators for early disease diagnosis, efficacy monitoring, and prognosis prediction. The aim of this invention is to provide a peripheral blood mononuclear cell (PBMC) metabolic detection method based on Seahorse bioenergy analysis technology, establishing a standardized metabolic indicator system and risk scoring model, thereby transforming it from a research testing platform into a clinical diagnostic tool.

[0009] To achieve the above objectives, this application adopts the following technical solution:

[0010] In a first aspect, this application provides a method for detecting the metabolic function of peripheral blood mononuclear cells using the Seahorse bioenergetics analysis method, comprising: Assay for mitochondrial respiratory function: PBMCs were seeded onto a detection plate at a density of 8 × 10⁻⁶. 4 Up to 50 × 10 4 Cells / well; oligomycin, 4-trifluoromethoxyphenylhydrazone and rotenone / antimycin A mixed inhibitor were added sequentially, and the mitochondrial oxygen consumption rate was measured using a Seahorse bioenergy analyzer and various respiratory indicators, including basal respiration, ATP production, maximum respiration and reserve respiratory capacity, were calculated; And the determination of glycolysis function: PBMCs were inoculated onto a test plate, and the inoculation density was set to 8 × 10⁻⁶. 4 Up to 50 × 10 4 Cells / well; oligomycin, 2-deoxy-D-glucose, and detection buffer were added sequentially, and the mitochondrial proton efflux rate was measured using a Seahorse bioenergy analyzer, and various glycolysis indicators, including basal glycolysis, basal proton efflux rate, and compensatory glycolysis, were calculated. The detection buffer is a DMEM basal medium supplemented with 10 mM glucose, 2 mM glutamine and 1 mM sodium pyruvate.

[0011] In a second aspect, this application provides a detection reagent used in the preparation of products for early disease screening, assessment and dynamic monitoring of disease-related metabolic status, disease classification and risk stratification, efficacy assessment and monitoring, assessment of disease severity or activity, and prognosis prediction. The detection reagent is used to detect the metabolic function of peripheral blood mononuclear cells in a sample according to the method described in the first aspect.

[0012] In some embodiments, the detection reagent is the reagent used in the method described in the first aspect.

[0013] In some implementations, the diseases include tumors, endocrine disorders (such as hyperthyroidism), metabolic diseases (such as obesity and diabetes), inflammation, and cardiovascular diseases (such as heart failure).

[0014] In some implementations, the product includes a reagent kit, system, or device.

[0015] Thirdly, this application provides a disease assessment system, comprising: The detection module is used to detect metabolic function indicators of peripheral blood mononuclear cells in the sample; An evaluation module, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the following steps: 1) acquiring various metabolic function indicators detected by the detection module, and 2) determining the disease status of the sample based on the metabolic function indicators of 1).

[0016] Compared with the prior art, this application has the following beneficial effects: (1) Compared with existing detection technologies, this application is the first to perform Seahorse metabolic function detection on peripheral blood mononuclear cells (PBMCs), which can obtain multiple key mitochondrial function indicators and correlate them with clinical status, thereby significantly improving the accuracy of early disease screening, assessment and dynamic monitoring of disease-related metabolic status, efficacy monitoring and evaluation, assessment of disease severity or activity, prognosis prediction, disease classification and risk stratification.

[0017] (2) This application realizes the transformation from scientific research metabolic detection technology to clinical diagnostic tool, which is non-invasive, sensitive and scalable, and provides new technical means for the individualized management of various diseases. Attached Figure Description Figure 1The results and linear detection intervals for mitochondrial respiratory function (oxygen consumption rate, OCR) and glycolytic function (proton efflux rate, PER) of PBMCs with different inoculation densities in Example 1 are as follows: (a) Overall OCR level; (be) Detection results and linear curves of various respiratory indicators: basal respiration (b), ATP production (c), maximal respiration (d), and reserve respiratory capacity (e); (f) Overall PER level; (gi) Detection results and linear curves of various glycolytic indicators: basal glycolysis (g), basal PER (h), and compensatory glycolysis (i).

[0018] Figure 2 To illustrate Example 2, the Seahorse metabolic assay results of PBMCs in pheochromocytoma patients were combined with plasma norepinephrine levels to compare the metabolic characteristics of patients under different clinical conditions. Among them, (a) comparison of OCR metabolic profiles before and after surgery between healthy controls and pheochromocytoma patients; (b) comparison of metabolic risk scores among groups; (c) comparison of baseline OCR levels among groups; (d) comparison of norepinephrine levels among groups; (e) comparison of OCR curves for different gene mutation types; and (f) statistical comparison of respiratory indicators (including baseline breathing, maximum respiratory volume, ATP production, and reserve respiratory capacity) for different gene mutation types.

[0019] Figure 3 The results of PBMC metabolic function testing in patients with hyperthyroidism in Example 3 include: (a) comparison of maximum respiratory capacity between healthy controls and hyperthyroid patients; (b) comparison of baseline respiratory function testing results among the groups; and (c) comparison of metabolic risk scores among the groups. Figure 4 The results of mitochondrial metabolic characteristics detection in different solid tumor tissues in Example 4 are as follows: (a) Comparison of OCR curves between normal tissues and tumor tissues from breast cancer patients; (b) Quantitative statistical results of OCR levels in tumor tissues between normal tissues and tumor tissues from breast cancer patients; (c) Comparison of OCR curves between normal tissues and tumor tissues from lung cancer patients; (d) Quantitative statistical results of OCR levels in tumor tissues between normal tissues and tumor tissues from lung cancer patients.

[0020] Figure 5 Example 5 shows the mitochondrial metabolism detection of PBMCs in healthy volunteers before and after exercise and in obese individuals; (a) comparison of OCR curves before and after exercise in healthy volunteers; (b) quantitative statistical results of OCR levels in healthy volunteers before and after exercise; (c) comparison of OCR curves between healthy controls and obese individuals; (d) quantitative statistical results of OCR levels in healthy controls and obese individuals. Detailed Implementation

[0021] To make the technical solution of this application clearer and easier to understand, preferred embodiments are described in detail below with reference to the accompanying drawings.

[0022] Unless otherwise specified, the experimental or testing methods described in the following examples are conventional methods; the reagents and materials described are obtained from conventional commercial sources unless otherwise specified.

[0023] Example 1: Verification of the linear range of PBMC metabolic function To verify the applicability and accuracy of the method of the present invention in the clinical detection of peripheral blood mononuclear cells (PBMCs), this embodiment uses Seahorse bioenergy analysis technology to detect PBMCs with different seeding densities, and measures mitochondrial respiratory function (oxygen consumption rate, OCR) and glycolysis function (proton efflux rate, PER) to determine a reasonable linear detection range.

[0024] 1. OCR (Oxygen Consumption Rate) Detection Results In the experiment, PBMCs were seeded onto a Seahorse XFe detection plate, with a seeding density range of 8 × 10⁻⁶. 4 Up to 50 × 10 4 Cells / well. By sequentially adding Oligomycin, FCCP, and Rotenone / Antimycin A, key parameters such as basal respiration, ATP production, maximal respiration, and respiratory reserve were calculated.

[0025] The results show: 1) Overall OCR level ( Figure 1 a): In 8 × 10 4 Up to 50 × 10 4 Within the specified range, the OCR value exhibits a highly linear relationship with the increase in cell number (R). 2 A value >0.95 indicates a stable and reproducible test result. When the cell count is below 8 × 10⁻⁵... 4 or higher than 50 × 10 4 When the OCR value deviates from the linear range, it indicates that there is a systematic error in the detection outside this range.

[0026] 2) Various respiratory indicators ( Figure 1 be): Within a defined linear range, basal respiration, ATP production, maximal respiration, and reserve respiration capacity are all directly proportional to cell number, and the correlation of linear fit is significant (Rb). 2 All values ​​were greater than 0.9. This indicates that within this range, the mitochondrial functional parameters of PBMCs can be accurately reflected.

[0027] 2. PER (Proton Escape Rate) Detection Results Under the same experimental conditions, the glycolytic function of PBMCs was further determined. The basal glycolysis, basal proton efflux rate and compensatory glycolysis were calculated after the addition of glucose, oligomycin and 2-deoxy-D-glucose (2-DG) and detection buffer (DMEM basal medium supplemented with 10 mM glucose, 2 mM glutamine and 1 mM sodium pyruvate, Seahorse XF DMEM basal medium).

[0028] The results show: 1) Overall PER level ( Figure 1 f): Consistent with OCR, in 8 × 10 4 Up to 50 × 10 4 Within the range of cells / well, the PER value maintains a high linear correlation with the number of cells, while it deviates from the linear trend when it exceeds this range.

[0029] 2) Various glycolysis indicators ( Figure 1 gi): Basal glycolysis, basal proton efflux rate, and compensatory glycolysis all increase linearly with increasing cell number, and the correlation remains stable (R). 2 >0.9), indicating that the detection within this range can accurately reflect the glycolytic state of PBMCs.

[0030] 3. Results Analysis and Conclusions This embodiment demonstrates, through dual-path detection using OCR and PER, that: 1) The linear detection interval is clearly defined: 8 × 10 4 Up to 50 × 10 4 The optimal range for PBMC Seahorse detection is one cell per well; exceeding this range can easily lead to data distortion or increased error.

[0031] 2) Stable and reliable test results: Within this range, the parameters related to mitochondrial respiration and glycolysis all showed high linearity and consistency, ensuring the comparability and reproducibility of the data.

[0032] 3) Clinical application value: The determination of the linear interval provides a basis for establishing a standardized testing process, which helps to compare and analyze different samples and unify cross-center data, and lays a solid technical foundation for the assessment and dynamic monitoring of disease-related metabolic status, efficacy assessment and monitoring, and prognosis prediction.

[0033] Example 2: Application of Pheochromocytoma Disease Status and Postoperative Recovery Assessment Based on Combined Analysis of PBMC Metabolic Detection and Norepinephrine Levels To further verify the application value of this invention in the assessment and dynamic monitoring of disease-related metabolic status, this embodiment uses patients with pheochromocytoma as the research subjects, and jointly analyzes the Seahorse metabolic characteristics of peripheral blood mononuclear cells (PBMCs) and the changes in plasma norepinephrine levels under different clinical conditions, so as to assess the overall energy metabolic load of the body and its dynamic changes before and after treatment intervention.

[0034] 1. Research subjects and grouping Several newly diagnosed pheochromocytoma patients were included, and comparative analyses were conducted between these patients before and after surgery, as well as among healthy controls. Peripheral blood was collected from all subjects, and PBMCs were isolated for Seahorse assay, while plasma norepinephrine levels were also measured.

[0035] 2. Seahorse metabolic assay results 1) Comparison of OCR metabolic profiles ( Figure 2 a) In healthy controls, PBMCs showed stable basal respiration and high respiratory reserve; in newly diagnosed pheochromocytoma patients, PBMC OCR levels were generally elevated, indicating a state of hypermetabolic mitochondrial respiration; while postoperative OCR curves in patients were significantly lower than preoperative levels and approached those of healthy controls, suggesting that the body's metabolic state is somewhat reversible and significantly improved after tumor burden relief. Figure 2 As shown in a.

[0036] 2) Metabolic Risk Score (MRS) Figure 2 b): Multiple PBMC mitochondrial metabolic parameters obtained from Seahorse bioenergetics analysis are used to comprehensively characterize the overall metabolic state of peripheral cells and may reflect the overall metabolic level of the body. In this example, the metabolic risk score showed significant differences among the three groups. The MRS level was highest in newly diagnosed patients, indicating that PBMCs were in a state of high metabolic load; the lowest was in healthy controls; the MRS level of postoperative patients was between the two, indicating that this combination of metabolic indicators can be used to reflect the dynamic changes in disease-related metabolic status and the metabolic recovery trend after treatment intervention. OCR metabolic profile and metabolic risk score can distinguish between healthy status, tumor-related hypermetabolic status and postoperative metabolic recovery status at the overall metabolic level, demonstrating its application value in disease-related metabolic assessment. 3) Baseline OCR level ( Figure 2 c): Baseline OCR was significantly elevated in newly diagnosed patients, but decreased postoperatively and approached that of healthy controls, further demonstrating that baseline respiratory parameters can serve as one of the indicators reflecting changes in disease-related metabolic status, such as... Figure 2 As shown in c.

[0037] 3. Comparison of norepinephrine levels Plasma norepinephrine test ( Figure 2 d): Plasma norepinephrine levels in newly diagnosed pheochromocytoma patients were significantly higher than in healthy controls; postoperatively, levels in patients decreased significantly, with some returning to the normal range. This trend is highly consistent with the dynamic changes in PBMC metabolic function, suggesting a correlation between hormone level changes and the body's energy metabolism status, such as... Figure 2 As shown in d.

[0038] 4. Genotype and mitochondrial function differences ( Figure 2 ef): Mitochondrial respiration curves of PBMCs were analyzed in groups based on the gene mutation type (SDHx, RET, EPAS1, and no mutation) in pheochromocytoma patients. The results showed significant differences in OCR curves among different gene mutation types, such as... Figure 2 As shown in Figure e, the PBMCs of patients without mutations exhibited the highest maximum respiration and spare respiratory capacity, suggesting strong metabolic potential in their mitochondria; the SDH mutation group was second, and the RET mutation group was slightly lower; while the PBMCs of patients with EPAS1 mutations showed significantly decreased respiratory activity, exhibiting characteristics of suppressed mitochondrial function. Corresponding quantitative analysis results showed that these differences were statistically significant, such as... Figure 2 As shown in f.

[0039] These results suggest that different molecular subtypes of pheochromocytoma exhibit specific metabolic characteristics at the peripheral immune cell level, which may reflect differences in their intrinsic energy metabolism regulation and provide a potential basis for personalized metabolic assessment.

[0040] 5. Comprehensive Analysis and Clinical Significance The results of this embodiment show that: 1) PBMC metabolic function can reflect the overall metabolic status related to the disease. The OCR metabolic profile and comprehensive metabolic score showed stable and reproducible differences across different disease states (new diagnosis, postoperative recovery, and healthy status), indicating that this method can reflect the metabolic changes in the body before and after tumor burden and treatment intervention.

[0041] 2) Applicable to dynamic monitoring of postoperative recovery and changes in disease burden. Postoperative PBMC metabolic levels returned to a healthy state, suggesting that this method can be used to assess the degree of recovery of the body's metabolic state after surgical intervention, providing a basis for postoperative follow-up and recovery assessment.

[0042] 3) Combined indicators enhance the explanatory power of metabolic status: PBMC metabolic parameters and plasma norepinephrine levels showed consistent changes, indicating that this method can serve as a functional supplement to traditional hormone testing and be used to comprehensively assess the body's stress and energy metabolism status.

[0043] 4) Not used as the sole basis for diagnosis This method is mainly used for metabolic status assessment and dynamic monitoring. It does not rely on a single threshold to determine the existence of disease, but emphasizes its application value in individual follow-up and comparison before and after treatment.

[0044] Example 3: Detection and analysis of PBMC metabolic function in patients with hyperthyroidism 1. Research Subjects and Detection Methods A number of patients diagnosed with hyperthyroidism and several age- and sex-matched healthy controls were selected. Peripheral blood samples were collected, and PBMCs were isolated. The oxygen consumption rate (OCR) was measured using a Seahorse bioenergy analyzer. Simultaneously, based on multiple mitochondrial metabolic parameters derived from Seahorse, the overall metabolic status of PBMCs was comprehensively analyzed, and a metabolic risk score (MRS) was constructed as a composite metabolic indicator. All tests were performed under standardized conditions to ensure consistency and comparability between experiments.

[0045] 2. Test Results and Data Analysis 1) Maximum respiration: such as Figure 3 As shown in a, the maximum OCR of PBMCs in hyperthyroid patients was significantly higher than that in healthy controls, suggesting that the mitochondrial respiratory chain of peripheral blood immune cells in hyperthyroid patients is in a state of continuous activation, reflecting the increased energy demand under the background of systemic hypermetabolism.

[0046] 2) Basal respiration: such as Figure 3 As shown in b, the baseline respiratory rate of hyperthyroid patients was significantly higher than that of the healthy control group, suggesting that their mitochondrial oxygen consumption rate was increased at rest, which may be related to the enhanced metabolism and accelerated cellular energy turnover caused by excessive thyroid hormones.

[0047] 3) Metabolic Risk Score (MRS): such as Figure 3 As shown in Figure c, the metabolic risk score (MRS) showed a more significant difference between the hyperthyroidism group and the healthy control group (Figure c), suggesting that this combination of metabolic indicators has a high ability to distinguish disease-related metabolic activation status.

[0048] 3. Interpretation of Results and Speculation of Mechanisms Thyroid hormones can directly act on mitochondria, increasing cellular metabolic rate by upregulating the activity of respiratory chain complexes and promoting oxidative phosphorylation. The results of this embodiment show that PBMCs in hyperthyroid patients exhibited characteristics such as increased basal metabolism, enhanced maximal respiration, and decreased metabolic reserves in Seahorse assays, which are highly consistent with the systemic metabolic acceleration driven by thyroid hormones. This indicates that this method can effectively reflect cellular energy dynamics under endocrine metabolic disorders.

[0049] 4. Clinical significance and application prospects 1) Non-invasive dynamic detection: The mitochondrial functional status of patients can be obtained through simple peripheral blood PBMC separation without the need for tissue biopsy.

[0050] 2) Disease activity assessment: MRS score can be used as a quantitative indicator of the metabolic status of hyperthyroidism, and can help determine the severity of the disease and the response to treatment.

[0051] 3) Cross-disease applicability: The results of this embodiment are consistent with those of pheochromocytoma, further demonstrating that the method of the present invention can be widely applied to metabolic monitoring of metabolic hyperactivity-related diseases (such as hyperthyroidism, diabetes, obesity, endocrine tumors, etc.).

[0052] Example 4: Application of Seahorse technology in detecting metabolic characteristics of different solid tumor tissues 1. Experimental Objective To verify the applicability of the method in solid tumor tissues and its ability to distinguish different tumor metabolic characteristics, tumor tissues and paired adjacent normal tissues from lung cancer and breast cancer patients were selected. The mitochondrial oxygen consumption rate (OCR) was detected using Seahorse bioenergy analysis technology, and key metabolic indicators such as basal respiration, ATP production, maximal respiration, and reserve respiration capacity were systematically evaluated.

[0053] 2. Experimental Methods Several surgically removed lung and breast cancer tissue samples were collected, with tumor tissue and adjacent adjacent normal tissue obtained from each sample. After processing, the tissue samples were placed in islet plates and immediately loaded onto Seahorse XFe detection plates for OCR analysis. The experiment was conducted under standard Mito Stress Test conditions, with Oligomycin, FCCP, and Rotenone / Antimycin A injected sequentially to obtain parameters for each stage of mitochondrial respiration. All data were normalized to unit protein content.

[0054] 3. Experimental Results 1) Metabolic characteristics of lung cancer tissue ( Figure 4 ab): like Figure 4As shown in Figure a, the overall OCR level of lung cancer tissue was significantly lower than that of the paired adjacent normal tissue, indicating a decline in mitochondrial respiratory function. Quantitative analysis results ( Figure 4 (b) shows that among the four major metabolic indicators, the maximum respiration and spare respiratory capacity (SRC) of lung cancer tissue were significantly lower than those of adjacent normal tissue, while the differences in basal respiration and ATP production were smaller. These results suggest that the mitochondrial metabolic potential of lung cancer tissue is limited and in a state of functional inhibition, possibly reflecting a decreased dependence on oxidative phosphorylation and a greater reliance on glycolysis for energy.

[0055] 2) Metabolic characteristics of breast cancer tissue ( Figure 4 cd): Conversely, the results in breast cancer tissue show a completely different trend. For example... Figure 4 As shown in c, the overall OCR of breast cancer tissue was higher than that of adjacent normal tissue, suggesting enhanced mitochondrial activity. Corresponding quantitative analysis indicated ( Figure 4 d) Breast cancer tissue showed significantly higher levels of basal respiration, ATP production, and maximum respiration than adjacent normal tissue, indicating that breast cancer cells not only maintain a high basal energy requirement but also possess stronger mitochondrial metabolic capacity to support energy consumption under high tumor proliferation.

[0056] 4. Results Analysis and Discussion 1) Metabolic heterogeneity reflects differences in tissue characteristics: This embodiment reveals significant differences in mitochondrial metabolic pathways among different types of solid tumors. Lung cancer tissues showed suppressed oxidative phosphorylation (decreased OCR), while breast cancer tissues showed enhanced oxidative phosphorylation (increased OCR). This indicates that different tumors exhibit tissue specificity in their metabolic pathway selection, which may be closely related to their location, oxygen supply status, and tumor microenvironment.

[0057] 2) Key parameters reflect energy metabolism patterns: Decreased maximal respiration and SRC in lung cancer tissues suggest impaired mitochondrial reserve function; significantly increased basal respiration and ATP production in breast cancer tissues reflect their high metabolic and high energy consumption biological characteristics. These indicators can provide quantitative metabolic characterization tools for clinical practice.

[0058] 3) The clinical translational value of Seahorse technology: This invention provides a method for rapidly assessing the mitochondrial functional status of fresh or short-term preserved tumor tissue, offering novel biomarkers for tumor subtyping, metabolic targeted therapy formulation, and efficacy prediction. It is particularly advantageous in distinguishing between "metabolic repressive" and "metabolic activating" tumors.

[0059] Example 5: Mitochondrial metabolism detection in PBMCs of healthy volunteers before and after exercise and in obese individuals 1) Changes in OCR before and after exercise in healthy volunteers (Figures ab): like Figure 5 As shown in figure a, the OCR curves of PBMCs in healthy volunteers shifted upwards overall after exercise, indicating enhanced mitochondrial respiratory activity. Quantitative analysis ( Figure 5 (b) showed that after exercise, the maximum respiration and spare respiratory capacity (SRC) of peripheral blood mononuclear cells (PBMCs) were significantly higher than before exercise, while basal respiration and ATP production increased slightly but without statistical significance. This indicates that short-term exercise can activate mitochondrial function in peripheral blood mononuclear cells and enhance their energy metabolism potential.

[0060] 2) Metabolic characteristics of PBMCs in obese individuals ( Figure 5 cd): like Figure 5 As shown in c, the OCR curve of PBMC in obese individuals was generally higher than that in healthy controls, reflecting an increased basal metabolic rate. The corresponding bar chart analysis ( Figure 5 (d) The results showed that the obese group had significantly higher levels of basal respiration, ATP production, maximum respiratory rate, and respiratory reserve than the healthy group, with statistically significant differences. This suggests that PBMCs in obese individuals are in a state of sustained high metabolic activation, which may be related to systemic energy metabolism disorders and chronic low-grade inflammation.

[0061] In summary, this application establishes the following correspondence between PMBC respiratory indices obtained from Seahorse energy analysis and clinical status: 1) Basal respiration This indicator reflects the minimum energy level required for cell survival. An elevated basal respiration rate suggests a high metabolic load, such as in cases of tumors or inflammation; a decreased rate suggests impaired mitochondrial function, such as in diabetes or neurodegenerative diseases. Basal respiration can be used for early disease screening and diagnosis.

[0062] 2) ATP production This indicator directly reflects the cell's energy supply capacity. A decrease in ATP levels suggests impaired energy synthesis, commonly seen in heart failure, metabolic diseases, or drug resistance in tumor cells; while an increase in ATP levels suggests activation of immune cell metabolism. Clinically, it can be used to monitor treatment efficacy; for example, the recovery of ATP after drug treatment or surgical intervention indicates good therapeutic effect.

[0063] 3) Maximum respiration This indicator reflects the energy supply potential of mitochondria under extreme demands. A decrease in maximum respiratory capacity suggests insufficient metabolic reserves, often associated with malignant tumor progression or chronic metabolic diseases; higher levels indicate stronger metabolic adaptability. Therefore, it can serve as an important reference for assessing disease severity and predicting prognosis.

[0064] 4) Spare respiratory capacity (SRC) SRC (Surrounded Respiratory Rate) is the difference between maximal respiration and basal respiration, reflecting the metabolic reserves of cells in response to stress. A low SRC indicates that cells are nearing their metabolic limits, often predicting a higher risk of disease progression or relapse; a high SRC indicates healthy metabolism and strong adaptability. SRC is a key indicator for risk stratification and prognostic prediction.

[0065] The clinical applications of each indicator are shown in the table below:

[0066] The above description is merely a preferred embodiment of this application and is not intended to limit this application in any form or substance. It should be noted that those skilled in the art can make several improvements and additions without departing from this application, and these improvements and additions should also be considered within the scope of protection of this application.

Claims

1. A method for detecting the metabolic function of peripheral blood mononuclear cells (PBMCs) using the Seahorse bioenergetics method, characterized in that, include: Assay for mitochondrial respiratory function: PBMCs were seeded onto a detection plate at a density of 8 × 10⁻⁶. 4 Up to 50 × 10 4 Cells / well; oligomycin, 4-trifluoromethoxyphenylhydrazone, and rotenone / antimycin A mixed inhibitor were added sequentially. Mitochondrial oxygen consumption rate was measured using a Seahorse bioenergy analyzer, and various respiratory indicators, including basal respiration, ATP production, maximal respiration, and reserve respiration capacity, were calculated. Glycolytic function was also measured: PBMCs were seeded onto a test plate at a density of 8 × 10⁻⁶ cells / well. 4 Up to 50 × 10 4 Cells / well; oligomycin, 2-deoxy-D-glucose and detection buffer were added sequentially, and the mitochondrial proton efflux rate was measured using a Seahorse bioenergy analyzer to calculate various glycolysis indicators, including basal glycolysis, basal proton efflux rate and compensatory glycolysis; wherein, the detection buffer was DMEM basal medium supplemented with 10 mM glucose, 2 mM glutamine and 1 mM sodium pyruvate.

2. The application of a diagnostic reagent in the preparation of products for early disease screening, assessment and dynamic monitoring of disease-related metabolic status, disease typing and risk stratification, efficacy evaluation and monitoring, assessment of disease severity or activity, and prognosis prediction, characterized in that, The detection reagent is used to detect the metabolic function of peripheral blood mononuclear cells in a sample according to the method described in claim 1.

3. The application according to claim 2, characterized in that, The detection reagent is the same reagent used in the method described in claim 1.

4. The application according to claim 2, characterized in that, The diseases mentioned include tumors, endocrine disorders, metabolic diseases, inflammation, and cardiovascular diseases.

5. The application according to any one of claims 2 to 4, characterized in that, The products include reagent kits, systems, or devices.

6. A disease assessment system, characterized in that, include: The detection module is used to detect metabolic function indicators of peripheral blood mononuclear cells in the sample; An evaluation module, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the following steps: 1) acquiring various metabolic function indicators detected by the detection module, and 2) determining the disease status of the sample based on the metabolic function indicators of 1).

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