Use of SERPINA3, BACE1 or CXCL1 in the manufacture of a product related to patients with type 2 diabetes mellitus and metabolic syndrome

Abstract

The application provides a use of biomarkers in the preparation of a product for TCM syndrome typing of a type 2 diabetes mellitus patient combined with metabolic syndrome, and / or for evaluating the risk of cognitive impairment of a type 2 diabetes mellitus patient combined with metabolic syndrome, wherein the biomarkers are selected from one or more of SERPINA3, BACE1 or CXCL1. The serum SERPINA3, BACE1 and CXCL1 levels are related to TCM syndrome types, provide a laboratory basis for TCM syndrome differentiation and treatment, help to improve the accuracy and standardization of TCM diagnosis, and according to the serum index levels and characteristics, a personalized treatment plan is formulated. Secondly, the serum index has predictive value for cognitive impairment, which helps to identify high-risk patients early and delay cognitive decline. For patients with a long course and poor blood glucose control, the serum index level can be regularly detected, combined with clinical indications, and timely anti-inflammatory, nerve nutrition and insulin resistance improvement treatment is given to protect cognitive function.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the use of SERPINA3, BACE1 or CXCL1 in the preparation of products for patients with type 2 diabetes mellitus and metabolic syndrome. Background Technology

[0002] With the increase in obesity rates and sedentary lifestyles, the prevalence of chronic diseases among the elderly is gradually rising. Among them, type 2 diabetes mellitus (T2DM) combined with metabolic syndrome (MS) has become a significant threat to the health of the elderly population. Patients with T2DM and MS exhibit pathological reactions such as insulin resistance, oxidative stress, neuroinflammation, and mitochondrial dysfunction, which can cause insidious damage to the central nervous system, leading to cognitive impairment and severely affecting their quality of life.

[0003] Currently, clinical assessment of cognitive function primarily relies on neuropsychological scales, such as the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). These methods have significant limitations: they are time-consuming, require professionally trained assessors, and their results are easily influenced by the patient's education level and subjective cooperation. Furthermore, they are difficult to implement on a large scale in primary healthcare settings. While recent studies have explored the use of some serum protein biomarkers for the auxiliary assessment of cognitive impairment, most focus on single Alzheimer's disease-related biomarkers (such as β-amyloid and tau proteins), lacking a combined biomarker system specifically for the metabolically disrupted population with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS). There are currently no reports of convenient and objective predictive kits based on serological indicators for the risk of cognitive impairment in this population.

[0004] Furthermore, TCM syndrome differentiation is an important basis for the integrated TCM and Western medicine treatment of type 2 diabetes mellitus complicated with metabolic syndrome (T2DM). Different syndromes show significant differences in the incidence and severity of cognitive impairment. However, current TCM syndrome differentiation relies heavily on physicians' personal clinical experience and diagnostic information, exhibiting strong subjectivity and lacking unified objective quantitative standards. Developing an objective molecular subtyping product that can assist in TCM syndrome differentiation is of great value in promoting the standardization of integrated TCM and Western medicine diagnosis and treatment.

[0005] Currently, there is no serum testing product that can both objectively assess the risk of cognitive impairment and assist in TCM syndrome differentiation. Summary of the Invention

[0006] In view of the shortcomings of the prior art described above, the present invention provides the use of SERPINA3, BACE1, or CXCL1 in the preparation of products for patients with type 2 diabetes mellitus complicated with metabolic syndrome. This study aims to elucidate the differences in serum SERPINA3, BACE1, and CXCL1 levels in patients with different TCM syndrome types and to provide their predictive value for cognitive impairment.

[0007] The first aspect of the present invention provides the use of biomarkers in the preparation of products for TCM syndrome differentiation of patients with type 2 diabetes mellitus and / or for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome, wherein the biomarkers are selected from one or more of SERPINA3, BACE1 or CXCL1.

[0008] Serum serine proteinase inhibitor A3 (SERPINA3) is an inflammatory marker that plays an important role in anti-inflammatory and antiviral responses. SERPINA3 is significantly upregulated in diabetes-related cognitive impairment (DCI), and SERPINA3-targeted therapy may have neuroprotective effects, showing potential in early intervention and treatment of DCI. Patients with type 2 diabetes mellitus (T2DM) have a higher risk of developing neurocognitive impairment. The expansion and folding of the neocortex are related to human intelligence and cognition. SERPINA3, by binding to the glyoxalase I (GLO1) promoter, regulates the proliferation of glial cells in the outer radial nerve and neocortical folding, which is associated with neuronal abundance and cognitive ability. In this invention, serum SERPINA3 levels varied in elderly T2DM patients with MS of different syndrome types, with the highest levels observed in patients with Yin-Yang deficiency syndrome. From the perspective of traditional Chinese medicine theory, chronic diseases often result from prolonged illness affecting the collaterals, leading to the accumulation of phlegm, dampness, and blood stasis within the body, forming pathological products. Due to the prolonged course of the disease, deficiency of vital energy, decline in organ function, and impaired circulation of qi, blood, and body fluids, a certain degree of inflammatory response and metabolic disorder occurs, leading to a deficiency of both yin and yang. Therefore, serum SERPINA3 levels were observed to be higher in patients during the late stage of the disease than in the early stage. When peripheral inflammation persists, SERPINA3 may cross the blood-brain barrier into the central nervous system, activating astrocytes and the GLO1 promoter, triggering neuroinflammatory responses, leading to neuronal damage and synaptic dysfunction, and consequently affecting cognitive function. In this study, patients with cognitive impairment showed higher SERPINA3 expression, further confirming the important role of SERPINA3 in cognitive function.

[0009] Optionally, the cognitive impairment includes mild cognitive impairment and / or dementia.

[0010] Optionally, the product is selected from models, systems, reagents, kits, chips, or test strips.

[0011] Preferably, the product is tested using one or more of SERPINA3, BACE1, or CXCL1.

[0012] Preferably, the SERPINA3, BACE, or CXCL1 is derived from serum.

[0013] Optionally, the TCM syndrome types include one or more of the following: liver and stomach stagnation with heat syndrome, phlegm-heat accumulation syndrome, intestinal damp-heat syndrome, or yin-yang deficiency syndrome.

[0014] The TCM syndrome differentiation is conducted according to the following rules:

[0015] (a) When the concentration of SERPINA3 is greater than 21.35 ng / mL but not greater than 27.39 ng / mL, the concentration of BACE1 is greater than 22.21 ng / mL but not greater than 29.83 ng / mL, and the concentration of CXCL1 is greater than 21.16 pg / mL but not greater than 29.32 pg / mL, it is judged as liver and stomach heat stagnation syndrome;

[0016] (b) When the concentration of SERPINA3 is greater than 26.33 ng / mL but not greater than 32.91 ng / mL, the concentration of BACE1 is greater than 27.59 ng / mL but not greater than 36.17 ng / mL, and the concentration of CXCL1 is greater than 24.77 pg / mL but not greater than 33.93 pg / mL, it is judged as phlegm and blood stasis syndrome;

[0017] (c) When the concentration of SERPINA3 is greater than 30.54 ng / mL but not greater than 40.12 ng / mL, the concentration of BACE1 is greater than 31.16 ng / mL but not greater than 43.22 ng / mL, and the concentration of CXCL1 is greater than 28.04 pg / mL but not greater than 38.36 pg / mL, it is determined to be intestinal damp-heat syndrome;

[0018] (d) When the concentration of SERPINA3 is greater than 37.39 ng / mL but not greater than 47.59 ng / mL, the concentration of BACE1 is greater than 38.16 ng / mL but not greater than 53.90 ng / mL, and the concentration of CXCL1 is greater than 33.03 pg / mL but not greater than 44.97 pg / mL, it is determined to be a syndrome of deficiency of both Yin and Yang.

[0019] Preferably, the patient is an elderly patient. An elderly patient is defined as someone whose age is not less than 60 years old.

[0020] β-amyloid precursor protein cleaving enzyme 1 (BACE1) cleaves the insulin receptor (InsR), leading to decreased InsR levels and promoting insulin resistance. In T2DM model mice, BACE1 levels are elevated and InsR levels are decreased; treatment with BACE1 inhibitors can restore InsR levels and improve insulin sensitivity and glucose tolerance. CXC motif chemokine ligand 1 (CXCL1) is associated with insulin resistance and endothelial dysfunction, reflecting an obesity-driven chronic low-grade inflammatory environment. In Traditional Chinese Medicine (TCM), based on the clinical symptoms and signs of elderly patients with T2DM complicated by MS, it is categorized under "Xiao Ke" (wasting and thirsting syndrome), "obesity," and "dizziness," and further divided into syndromes such as liver-stomach stagnation with heat and phlegm-heat accumulation. Different TCM syndromes reflect different pathophysiological states, and their clinical characteristics, disease progression, and prognostic outcomes vary.

[0021] BACE1 is present in various cell types, and its high expression is associated with metabolic diseases such as type 2 diabetes mellitus (T2DM), obesity, and cardiovascular disease, playing a role in regulating energy metabolism and homeostasis. BACE1 knockout mouse models exhibit weight loss, increased energy expenditure, and enhanced leptin signaling. BACE1 inhibitors can improve hepatic insulin sensitivity in diabetic mice, promoting hepatic glucose regeneration and glucose homeostasis. Age-related cognitive impairment is associated with BACE1; downregulation of BACE1 can alleviate cognitive impairment in Alzheimer's disease by reducing Aβ production. In elderly patients with T2DM and MS, serum BACE1 levels are related to syndrome differentiation and cognitive function. Elevated BACE1 levels may promote Aβ protein production, leading to cognitive impairment, and may induce insulin resistance by disrupting metabolic function. Patients with Yin-Yang deficiency syndrome often exhibit more severe metabolic imbalances, which may be an important reason for their elevated BACE1 levels.

[0022] CXCL1, as a chemokine, primarily recruits inflammatory cells such as monocytes and neutrophils into brain tissue, triggering neuroinflammatory responses and pain, leading to neuronal damage and cognitive decline. CXCL1 can also regulate vascular endothelial cell function, affecting cerebral blood flow and blood-brain barrier permeability, making it a pivotal gene in regulating cognitive and emotional dysfunction and microglia activation. Inhibiting CXCL1 production can reduce neutrophil migration to the hippocampus, effectively alleviating neuroinflammatory reactions and neutrophil infiltration, and enhancing cognitive function. High serum CXCL1 expression is associated with the symptom pattern and cognitive function of elderly patients with type 2 diabetes mellitus (T2DM) complicated by metabolic syndrome (MS). As a chemokine, CXCL1 can recruit inflammatory cell aggregation; a persistent inflammatory microenvironment may stimulate excessive CXCL1 secretion, further exacerbating the inflammatory response and brain damage, leading to cognitive impairment.

[0023] The reagents and / or kits include one or more of the following: reagents that specifically recognize SERPINA3, reagents that specifically recognize BACE1, or reagents that specifically recognize CXCL1.

[0024] Preferably, the reagent that specifically recognizes SERPINA3 is selected from antibodies that specifically recognize SERPINA3 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds; the reagent that specifically recognizes BACE1 is selected from antibodies that specifically recognize BACE1 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds; or, the reagent that specifically recognizes CXCL1 is selected from antibodies that specifically recognize CXCL1 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds.

[0025] The reagent is not limited to being in liquid form.

[0026] The active ingredient in the reagents and / or kits may be solely the reagent that specifically recognizes SERPINA3, BACE1, or CXCL1, or may include other substances. That is, the reagent that specifically recognizes the Aβ oligomer may be the sole active ingredient or one of the active ingredients in the reagents and / or kits. The reagents and / or kits may be used in combination with other products or alone.

[0027] Preferably, the kit also includes a positive control and a negative control. The positive control includes SERPINA3, BACE1, and CXCL1. The negative control includes ddH2O.

[0028] The reagents and / or kits may be commercially available reagents or kits or homemade reagents. For example, a commercially available kit may be an ELISA detection kit. The kit components may include, for example, one or more antibodies or functional fragments of antibodies capable of binding to the SERPINA3, BACE1, or CXCL1, as well as enzyme-labeled solutions, stop solutions, standards, controls, buffers, etc.

[0029] The kit described in this invention may also include other commonly used reagents required for ELISA detection. Since these commonly used ELISA reagents can be purchased separately from the market or prepared in-house, the specific reagents to be included in the kit can be configured according to the customer's actual needs. For convenience, all reagents can also be included in the kit.

[0030] There are no special restrictions on the form of the reagents and / or kits; they can be in various forms such as solid, liquid, gel, semi-liquid, or aerosol.

[0031] The second aspect of the present invention provides the use of one or more of the following reagents that specifically recognize SERPINA3, BACE1, or CXCL1 in the preparation of a product for TCM syndrome differentiation of patients with type 2 diabetes mellitus complicated with metabolic syndrome, and / or, in the preparation of a product for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0032] like Figure 1 As shown, a third aspect of the present invention provides a cognitive impairment risk assessment system for patients with type 2 diabetes mellitus complicated with metabolic syndrome, the system comprising:

[0033] The data acquisition module 11 is used to acquire the test data of the subject, the test data including data of any of the aforementioned biomarkers;

[0034] The result output module 12 is communicatively connected to the data acquisition module and is used to compare the detection data with a preset threshold and output risk classification information based on the comparison result.

[0035] Furthermore, in the result output module, when the detected data is greater than a preset threshold, "high risk" classification information is output; when the detected data is equal to or less than the preset threshold, "low risk" classification information is output.

[0036] Optionally, the preset threshold is selected from one or more of the SERPINA3 preset threshold, BACE1 preset threshold, or CXCL1 preset threshold.

[0037] Preferably, the preset threshold for SERPINA3 is 31.74 ng / mL; the preset threshold for BACE1 is 35.04 ng / mL; or, the preset threshold for CXCL1 is 30.31 pg / mL.

[0038] like Figure 2 As shown, the fourth aspect of the present invention provides a method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome, the method comprising the following steps:

[0039] S1, Obtain the test data of the subject, wherein the test data includes at least the aforementioned biomarker data;

[0040] S2, take the detection data mentioned in step S1 as input, compare the detection data with a preset threshold, and output risk classification information based on the comparison result.

[0041] Furthermore, in step S3, when the detected data is greater than a preset threshold, "high risk" classification information is output; when the detected data is equal to or less than the preset threshold, "low risk" classification information is output.

[0042] Optionally, the preset threshold is selected from one or more of the SERPINA3 preset threshold, BACE1 preset threshold, or CXCL1 preset threshold.

[0043] Preferably, the preset threshold for SERPINA3 is 31.74 ng / mL; the preset threshold for BACE1 is 35.04 ng / mL; or, the preset threshold for CXCL1 is 30.31 pg / mL.

[0044] The fifth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0045] A sixth aspect of the present invention provides a computer processing device, including a processor and the aforementioned computer-readable storage medium, wherein the processor executes a computer program on the computer-readable storage medium to implement the steps of the aforementioned method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0046] A seventh aspect of the present invention provides an electronic terminal, comprising: a processor, a memory, and a communicator; the memory is used to store a computer program, the communicator is used to communicate with an external device, and the processor is used to execute the computer program stored in the memory to enable the terminal to perform the aforementioned method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0047] The eighth aspect of the present invention provides a kit for classifying patients with type 2 diabetes mellitus and metabolic syndrome according to traditional Chinese medicine syndrome types, and / or for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome, including a reagent that specifically recognizes SERPINA3, a reagent that specifically recognizes BACE1, or a reagent that specifically recognizes CXCL1.

[0048] As described above, SERPINA3, BACE1, or CXCL1 of the present invention have the following beneficial effects for use in the preparation of products for patients with type 2 diabetes mellitus complicated with metabolic syndrome:

[0049] The serum SERPINA3, BACE1, and CXCL1 of this invention predicted cognitive impairment in elderly patients with type 2 diabetes mellitus and MS with AUCs of 0.715, 0.744, and 0.728, respectively, and the combined AUC was 0.903, which is higher than that of individual indicators (Z=8.210, 7.513, 7.772, P<0.001).

[0050] Serum SERPINA3, BACE1, and CXCL1 levels are associated with TCM syndrome differentiation, providing laboratory evidence for TCM syndrome differentiation and treatment, and helping to improve the accuracy and standardization of TCM diagnosis. Personalized treatment plans can be developed based on serum index levels and characteristics. Secondly, serum indices have predictive value for cognitive impairment, helping to identify high-risk patients early and delay cognitive decline. For patients with a long disease course and poor glycemic control, regular monitoring of serum index levels, combined with clinical indications, can provide timely anti-inflammatory, neurotrophic, and insulin resistance-improving treatments to protect cognitive function. Attached Figure Description

[0051] Figure 1 This is an embodiment of the present invention: a risk assessment system for cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0052] Figure 2 This is an embodiment of the present invention of a method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome.

[0053] Figure 3 This is a schematic diagram of an electronic terminal according to an embodiment of the present invention.

[0054] Figure 4 This is an ROC curve of serum SERPINA3, BACE1, and CXCL1 levels predicting cognitive function according to an embodiment of the present invention.

[0055] Figure 5 This is a calibration curve of a joint prediction model according to an embodiment of the present invention. Detailed Implementation

[0056] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0057] Before further describing specific embodiments of the present invention, it should be understood that the scope of protection of the present invention is not limited to the specific embodiments described below; it should also be understood that the terminology used in the embodiments of the present invention is for describing specific embodiments and not for limiting the scope of protection of the present invention; in the specification and claims of the present invention, unless otherwise expressly stated in the text, the singular forms "a", "an" and "this" include the plural forms.

[0058] When numerical ranges are given in the embodiments, it should be understood that, unless otherwise stated in the present invention, both endpoints of each numerical range and any value between the two endpoints may be selected. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. In addition to the specific methods, apparatus, and materials used in the embodiments, based on the knowledge of the prior art possessed by one of ordinary skill in the art and the description of this invention, any prior art methods, apparatus, and materials similar to or equivalent to those described, apparatus, and materials in the embodiments of this invention may be used to implement the present invention.

[0059] Unless otherwise stated, the experimental methods, detection methods, and preparation methods disclosed in this invention all employ conventional techniques in molecular biology, biochemistry, chromatin structure and analysis, analytical chemistry, cell culture, recombinant DNA technology, and related fields.

[0060] Unless otherwise expressly stated, the technical features, embodiments, and beneficial effects described in this specification for any independent claim or its dependent claims shall, without conflict, also apply to the same or corresponding technical features in the other independent claims and their dependent claims. To avoid repetition, identical content will not be repeated.

[0061] It should be noted that the division of modules in the system of this invention is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. These modules can be implemented entirely in software through processing element calls; they can also be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. For example, the acquisition module can be a separate processing element, or it can be integrated into a chip. Alternatively, it can be stored in memory as program code, and its functions can be called and executed by a processing element. The implementation of other modules is similar. Furthermore, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through the integrated logic circuits in the hardware of the processor element or through software instructions.

[0062] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more digital signal processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs, or Graphics Processing Units, GPUs). As another example, when a module is implemented through processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together to form a system-on-a-chip (SOC).

[0063] like Figure 3 The diagram illustrates an electronic terminal provided by the present invention. The electronic terminal includes a processor 31, a memory 32, a communicator 33, a communication interface 34, and a system bus 35. The memory 32 and the communication interface 34 are connected to the processor 31 and the communicator 33 via the system bus 35 and communicate with each other. The memory 32 stores computer programs, the communicator 34 and the communication interface 34 communicate with other devices, and the processor 31 and the communicator 33 run the computer programs, enabling the electronic terminal to execute the various steps of the image analysis method described above.

[0064] The system bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write libraries, and read-only libraries). Memory may include Random Access Memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0065] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), graphics processing units (GPUs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0066] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented using hardware related to a computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; the computer-readable storage medium may include, but is not limited to, floppy disks, optical disks, CD-ROMs (Read-Only Optical Disk Memory), magneto-optical disks, ROMs (Read-Only Memory), RAMs (Random Access Memory), EPROMs (Erasable Programmable Read-Only Memory), EEPROMs (Electrically Erasable Programmable Read-Only Memory), magnetic cards or optical cards, flash memory, or other types of media / machine-readable media suitable for storing machine-executable instructions. The computer-readable storage medium can be a product not connected to a computer device or a component used in a computer device.

[0067] In practice, the computer program is a routine, program, object, component, data structure, etc., that performs a specific task or implements a specific abstract data type.

[0068] the term:

[0069] Sensitivity: also known as the true positive rate, which is the ratio of true positives to true positives plus false negatives.

[0070] Specificity: that is, the true negative rate, which is the ratio of true negatives to true negatives plus false positives.

[0071] The sensitivity described in this invention has the same definition as the sensitivity degree.

[0072] Example 1

[0073] This embodiment constructs a kit for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome using SERPINA3, BACE1, and CXCL1 as biomarkers. The kit includes: a reagent specifically recognizing SERPINA3, a reagent specifically recognizing BACE1, or a reagent specifically recognizing CXCL1. The reagent specifically recognizing SERPINA3 includes an antibody specifically recognizing SERPINA3; the reagent specifically recognizing BACE1 includes an antibody specifically recognizing BACE1; or the reagent specifically recognizing CXCL1 includes an antibody specifically recognizing CXCL1.

[0074] 1. Materials and Methods

[0075] 1.1 Research Subjects

[0076] This study included 460 elderly patients with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS) admitted to our hospital between May 2024 and December 2025. Inclusion criteria: (1) meeting the diagnostic criteria for T2DM (Chinese Diabetes Society. Guidelines for the Prevention and Treatment of Type 2 Diabetes in China (2020 Edition) [J]. Chinese Journal of Diabetes, 2021, 13(4):315-409) and the diagnostic criteria for MS (Joint Committee for the Revision of Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults. Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults (2016 Revised Edition) [J]. Chinese Journal of General Practitioners, 2017, 16(1):15-35); (2) age ≥ 60 years; (3) clear consciousness and able to cooperate in completing cognitive function assessment and related examinations; (4) voluntarily participating in this study and signing an informed consent form. Exclusion criteria: (1) Patients with type 1 diabetes, special types of diabetes, and gestational diabetes; (2) Patients with major organ failure, malignant tumors, autoimmune diseases, or infectious diseases; (3) Patients with neurological diseases or a clear history of cognitive impairment; (4) Patients with a history of acute diabetic complications within the past 3 months; (5) Patients who have used drugs that affect cognitive function within the past 1 month; (6) Patients with unclear TCM diagnosis or incomplete clinical data. This study was reviewed and approved by the hospital ethics committee.

[0077] 1.2 Methods

[0078] 1.2.1 Detection of serum SERPINA3, BACE1, and CXCL1 levels

[0079] Fasting venous blood was collected from patients before treatment. Serum was collected and prepared into a serum suspension. Protein levels were detected using SERPINA3 (Zike Biotechnology, ZK-H1640), BACE1 (Yaji Biotechnology, YS01932B), and CXCL1 (Duma Biotechnology, DM121512) ELISA kits.

[0080] 1.2.2 Traditional Chinese Medicine Syndrome Differentiation

[0081] According to the TCM syndrome differentiation guidelines, two TCM physicians with the title of associate chief physician or above independently diagnosed the patient and categorized the syndromes into four types: Liver and Stomach Heat Stagnation Syndrome (n=189), Phlegm-Heat Accumulation Syndrome (n=94), Intestinal Damp-Heat Syndrome (n=86), and Yin-Yang Deficiency Syndrome (n=91). If the diagnostic results were inconsistent, the final syndrome type was determined through discussion or by inviting a senior physician for consultation.

[0082] 1.2.3 Cognitive Function Assessment

[0083] The MoCA was used to assess patients' cognitive function 3 months after discharge. The scale covers 8 cognitive domains with a total score of 30. A score <26 indicated cognitive impairment and was recorded as the impaired group (n=215), while the rest were recorded as the normal group (n=245). The assessment was conducted by a professionally trained neurologist.

[0084] 1.2.4 Data Collection

[0085] We collected data on the following patients enrolled in this study: place of residence, education level, gender, duration of type 2 diabetes mellitus (T2DM), age, total cholesterol (TC), body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), waist circumference, triglycerides (TG), fasting plasma glucose (FPG), and high-density lipoprotein cholesterol (HDL-C).

[0086] 1.3 Statistical Analysis

[0087] The data were statistically analyzed using the Chinese version of SPSS 25.0 software. Quantitative data were expressed as follows: The numbers (n, %) indicate that independent samples t-tests are performed for comparisons between the two groups; count data are expressed as [n (%)], and χ² tests are used for comparisons between the two groups. 2 The study included: multivariate logistic regression analysis to identify factors influencing cognitive impairment; ROC curve analysis to assess the predictive value of serum SERPINA3, BACE1, and CXCL1 levels for cognitive impairment; internal validation of the predictive model using the Bootstrap method with 1000 repeated sampling cross-validation; and the Hosmer-Lemeshow test to assess model fit. P < 0.05 was considered statistically significant.

[0088] 2 Results

[0089] 2.1 Comparison of serum SERPINA3, BACE1, and CXCL1 levels in patients with different syndrome types

[0090] Serum SERPINA3, BACE1, and CXCL1 levels were elevated in the following order among patients with liver-stomach stagnation-heat syndrome, phlegm-heat accumulation syndrome, intestinal damp-heat syndrome, and yin-yang deficiency syndrome (P < 0.05). See Table 1.

[0091] Table 1. Comparison of serum SERPINA3, BACE1, and CXCL1 levels in patients with different syndrome types ( )

[0092]

[0093] Note: Compared with liver and stomach heat stagnation syndrome. * P < 0.05; compared with phlegm-heat syndrome, # P < 0.05; compared with intestinal damp-heat syndrome, @ P < 0.05.

[0094] 2.2 Univariate analysis of normal and damaged groups

[0095] There were no statistically significant differences in residence, education level, gender, T2DM duration, age, TC, BMI, and LDL-C between the normal group and the affected group (P > 0.05). The affected group had higher waist circumference, TG, FBG, and serum SERPINA3, BACE1, and CXCL1 levels, and lower HDL-C levels compared to the normal group (P < 0.05). See Table 2.

[0096] Table 2 Univariate analysis [( ) / n(%)]

[0097]

[0098] 2.3 Multivariate Logistic Regression Analysis

[0099] Using the presence of cognitive impairment in elderly patients with type 2 diabetes mellitus (T2DM) and meningococcal meningitis (MS) as the dependent variable (yes = 1; no = 0), and waist circumference, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting blood glucose (FBG), and serum levels of serapina3, baceoprotein acetylcholine (SCA1), and cyclophosphamide (CXCL1) as independent variables (all measured values), a multivariate logistic regression analysis was performed. The results confirmed that all of the aforementioned indicators were influencing factors for cognitive impairment (P < 0.05). See Table 3.

[0100] Table 3 Multivariate Logistic Regression Analysis

[0101]

[0102] 2.4 Predictive value of serum SERPINA3, BACE1, and CXCL1 levels for cognitive impairment

[0103] Using a pre-constructed kit that uses SERPINA3, BACE1, and CXCL1 as biomarkers to assess the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome, 460 clinical samples were tested to determine whether they were at risk of cognitive impairment.

[0104] In the sample:

[0105] A SERPINA3 level greater than 31.74 ng / mL is a diagnostic criterion for SERPINA3 alone.

[0106] A BACE1 level greater than 35.04 ng / mL is a diagnostic criterion for BACE1 alone.

[0107] A CXCL1 level greater than 30.31 pg / mL is a diagnostic criterion for CXCL1 alone.

[0108] A combined diagnostic criterion is a SERPINA3 level greater than 31.74 ng / mL, a BACE1 level greater than 35.04 ng / mL, and a CXCL1 level greater than 30.31 pg / mL, indicating a risk of cognitive impairment; otherwise, the risk is low.

[0109] The results show that

[0110] In the SERPINA3 diagnosis alone, 178 samples were considered to be at high risk of cognitive impairment; 282 samples were considered to be at low risk.

[0111] In the BACE1 diagnosis alone, 172 samples were considered high-risk for cognitive impairment; 288 samples were considered low-risk.

[0112] In the CXCL1 diagnosis alone, 174 samples were considered to be at high risk of cognitive impairment; 286 samples were considered to be at low risk.

[0113] In the combined diagnosis, 215 samples were classified as high-risk for cognitive impairment, and 245 samples were classified as low-risk.

[0114] Based on the data from 460 cases described in section 1.1, the AUCs of serum SERPINA3, BACE1, and CXCL1 in predicting cognitive impairment in elderly patients with type 2 diabetes mellitus (T2DM) and MS were 0.715, 0.744, and 0.728, respectively, with a combined AUC of 0.903. This combined AUC was significantly higher than that of any single indicator (Z = 8.210, 7.513, and 7.772, P < 0.001 for all). See [link / reference]. Figure 4 And Table 4.

[0115] Table 4. Predictive value analysis of serum SERPINA3, BACE1, and CXCL1 levels for cognitive impairment.

[0116]

[0117] 2.5 Calibration Curve Analysis

[0118] The predictive ability of serum indicators for cognitive impairment was evaluated using calibration curves, and the Hosmer-Lemeshow goodness-of-fit test (χ²) was used. 2 =15.028, P=0.059, indicating a good fit, demonstrating the high accuracy of the joint prediction model. See Figure 5 .

[0119] In summary, the detection kit of this invention can be used to jointly detect SERPINA3, BACE1 and CXCL1 in serum, thereby assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome. The detection results have good sensitivity and high specificity, and have good prospects for clinical application.

[0120] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any form or substance. It should be noted that those skilled in the art can make various improvements and additions without departing from the method of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention. Any modifications, alterations, and equivalent changes made by those skilled in the art based on the above-disclosed technical content without departing from the spirit and scope of the present invention are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, and evolutions made to the above embodiments based on the essential technology of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. Use of a biomarker in the preparation of a product for the classification of patients with type 2 diabetes mellitus and metabolic syndrome by traditional Chinese medicine, and / or for the assessment of the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome, wherein the biomarker is selected from one or more of SERPINA3, BACE1 or CXCL1.

2. The use as described in claim 1, characterized in that, It also includes one or more of the following features: a) The cognitive impairment mentioned includes mild cognitive impairment and / or dementia; (b) The product is selected from models, systems, reagents, kits, chips, or test strips; c) The SERPINA3, BACE, or CXCL1 mentioned are derived from serum; d) The TCM syndrome types mentioned include one or more of the following: liver and stomach stagnation with heat syndrome, phlegm-heat accumulation syndrome, intestinal damp-heat syndrome, or yin-yang deficiency syndrome; e) The patient mentioned is an elderly patient.

3. The use as described in claim 2, characterized in that, In feature b), the reagents and / or kits include one or more of the following: reagents that specifically recognize SERPINA3, reagents that specifically recognize BACE1, or reagents that specifically recognize CXCL1; preferably, the reagents that specifically recognize SERPINA3 are selected from antibodies that specifically recognize SERPINA3 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds; the reagents that specifically recognize BACE1 are selected from antibodies that specifically recognize BACE1 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds; or, the reagents that specifically recognize CXCL1 are selected from antibodies that specifically recognize CXCL1 or their antigen-binding fragments, nucleic acid aptamers, peptides, or small molecule compounds.

4. Use of one or more of the following reagents that specifically recognize SERPINA3, BACE1, or CXCL1 in the preparation of products for TCM syndrome differentiation of patients with type 2 diabetes mellitus and / or in the preparation of products for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome.

5. A system for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome, characterized in that, The system includes: A data acquisition module is used to acquire the test data of the subject, wherein the test data includes data of the biomarkers according to any one of claims 1-3; The result output module is communicatively connected to the data acquisition module and is used to compare the detection data with a preset threshold and output risk classification information based on the comparison result.

6. The cognitive impairment risk assessment system for patients with type 2 diabetes mellitus complicated with metabolic syndrome as described in claim 5, characterized in that, It also includes one or more of the following features: a. In the result output module, when the detected data is greater than a preset threshold, "high risk" classification information is output; when the detected data is equal to or less than the preset threshold, "low risk" classification information is output. b. The preset threshold is selected from one or more of the SERPINA3 preset threshold, BACE1 preset threshold, or CXCL1 preset threshold; preferably, the SERPINA3 preset threshold is 31.74 ng / mL; the BACE1 preset threshold is 35.04 ng / mL; or, the CXCL1 preset threshold is 30.31 pg / mL.

7. A method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome, characterized in that, The method includes the following steps: S1, acquire the test data of the subject, the test data including data of the biomarkers according to any one of claims 1-3; S2, take the detection data mentioned in step S1 as input, compare the detection data with a preset threshold, and output risk classification information based on the comparison result.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome as described in claim 7.

9. A computer processing device or electronic terminal, characterized in that, The electronic device includes a processor and the computer-readable storage medium of claim 8, wherein the processor executes a computer program on the computer-readable storage medium to implement the method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome of claim 7. The electronic terminal includes: a processor, a memory, and a communicator; the memory is used to store computer programs, the communicator is used to communicate with external devices, and the processor is used to execute the computer programs stored in the memory, so that the terminal executes the method for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus complicated with metabolic syndrome as described in claim 7.

10. A kit for classifying patients with type 2 diabetes mellitus and metabolic syndrome according to traditional Chinese medicine syndrome differentiation, and / or for assessing the risk of cognitive impairment in patients with type 2 diabetes mellitus and metabolic syndrome, comprising a reagent that specifically recognizes SERPINA3, a reagent that specifically recognizes BACE1, or a reagent that specifically recognizes CXCL1.

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