Exosome protein marker combination for cerebral small vascular diseases and related cognitive impairment and application of exosome protein marker combination

Abstract

The invention belongs to the technical field of biological detection, and particularly relates to an exosome protein marker combination for cerebral small vascular diseases and related cognitive disorders and application. The invention discloses an exosome protein marker combination. The exosome protein marker combination is a combination of any one or any two or three markers of a v-type proton atp enzyme subunit, a large ribosome subunit protein eL38 and a heterogeneous ribonucleoprotein U. The exosome protein marker combination is a combination of any two or three markers of the v-type proton atp enzyme subunit, the large ribosome subunit protein eL38 and the heterogeneous ribonucleoprotein U. The combination of the three specific exosome proteins can effectively recognize CSVD related cognitive impairment, and has the potential of early warning CSVD related cognitive impairment.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection technology, and specifically relates to a combination and application of exosome protein markers for cerebral small vessel disease and related cognitive impairment. Background Art

[0002] Cerebral small vessel disease (CSVD) is a syndrome characterized by clinical, cognitive, imaging, and pathological changes caused by lesions of small cerebral vessels, including arterioles, capillaries, and venules. Characteristic imaging findings include white matter hyperintensities (WMHs), lacunar infarcts, cerebral microbleeds, and enlarged perivascular spaces. CSVD accounts for 25% to 30% of all ischemic strokes and is 6 to 10 times more common than large vessel stroke. CSVD is closely associated with cognitive impairment (CI) and is the most important vascular risk factor for dementia. CSVD accounts for approximately 36% to 67% of vascular dementia cases, severely impacting the health and quality of life of the elderly. The impact of CSVD on cognitive function develops insidiously and slowly. Early and effective intervention can effectively reduce or even reverse the onset and progression of vascular cognitive impairment. Therefore, early diagnosis (and early warning) of CSVD and its associated cognitive impairment is crucial. Based on the above problems, a new method for early identification of CSVD and its related cognitive impairment is urgently needed.

[0003] Exosomes are nanoscale extracellular vesicles derived from the plasma membrane and endosomes. They carry a variety of cell-derived proteins, lipids, DNA, mRNA, and miRNA. They participate in processes such as intercellular communication, cell migration, angiogenesis, and immune regulation, and are widely present in various body fluids, including blood, urine, saliva, and breast milk. Exosomes are secreted by various cells in the central nervous system and are crucial for intersynaptic signaling, myelination, and neural development. They can cross the blood-brain barrier and are easily detected in peripheral tissues, demonstrating high clinical specificity. Proteins are a significant component of exosomes and are highly stable. Exosomal proteomics, an analytical method for the collective quantification of proteins, is a powerful tool for discovering new biomarkers and is contributing to our understanding of the pathological mechanisms underlying CSVD and its associated cognitive impairments and their progression. Summary of the Invention

[0004] The purpose of the present invention is to provide a combination of exosomal protein markers for cerebral small vessel disease and related cognitive impairment and its application, so as to achieve early diagnosis, prediction or detection of cerebral small vessel disease and related cognitive impairment.

[0005] To this end, the present invention provides the following technical solutions.

[0006] The first aspect of the present invention provides an exosomal protein marker combination for cerebral small vessel disease and related cognitive impairment, wherein the exosomal protein marker combination is any one of the v-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U, or a combination of any two or three markers.

[0007] Preferably, the exosomal protein marker combination is a combination of three markers: v-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U.

[0008] Preferably, the exosomal protein marker is derived from the urine or blood of the subject.

[0009] A second aspect of the present invention provides a use of a reagent for detecting the aforementioned exosomal protein marker combination in the preparation of any of the following products: (1) Early diagnosis products for cerebral small vessel disease and related cognitive impairment; (2) Screening products for cerebral small vessel disease and related cognitive impairment; (3) Risk assessment products for cerebral small vessel disease and related cognitive impairment; or (4) Prognostic assessment products for cerebral small vessel disease and related cognitive impairment.

[0010] Preferably, the reagent is an antibody to the exosome protein marker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis.

[0011] Preferably, the product is a chip, a test kit, a test paper or an analysis platform.

[0012] A third aspect of the present invention provides a kit for cerebral small vessel disease and related cognitive impairment, comprising a reagent for detecting the exosome protein marker as described above. Optionally, the detection is a quantitative detection of the level of exosome protein marker in the urine or plasma of the subject.

[0013] Preferably, the reagent is an antibody to the exosome protein marker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis.

[0014] Preferably, the kit is an ELISA kit.

[0015] The fourth aspect of the present invention provides a method for evaluating whether a drug can prevent or treat cerebral small vessel disease and related cognitive impairment, comprising using any one, any two, or any three of the v-type proton ATPase subunit, the large ribosomal subunit protein eL38, and the heterogeneous ribonucleoprotein U as exosomal protein markers to evaluate the effect of the drug.

[0016] A fifth aspect of the present invention provides a method for screening compounds capable of preventing or treating cerebral small vessel disease and related cognitive impairment, comprising using any one, any two, or any three of the v-type proton ATPase subunit, the large ribosomal subunit protein eL38, and the heterogeneous ribonucleoprotein U as exosomal protein markers to evaluate the effect of the compound.

[0017] By means of the above technical solution, the present invention has at least the following advantages: The present invention provides novel molecular markers that can be used to identify cerebral small vessel disease and related cognitive impairment. The combination of these markers can be used for early detection, diagnosis and prediction of cerebral small vessel disease and related cognitive impairment, and has the potential for early warning of CSVD-related cognitive impairment, thereby achieving more precise medication.

[0018] The exosomal protein markers provided by the present invention for early detection, diagnosis and prediction of cerebral small vessel disease and related cognitive impairment are any one, two or three of three specific exosomal proteins: v-type proton ATPase subunit (ATP6V1F), large ribosomal subunit protein eL38 (RPL38) and heterogeneous nuclear ribonucleoprotein U (HNRNPU). By comparing their levels in urine or plasma with the levels in the plasma of patients with cerebral small vessel disease and related cognitive impairment, cerebral small vessel disease and related cognitive impairment can be diagnosed with high accuracy. In addition, the levels of the above three plasma exosomal proteins tend to gradually decrease with the progression of CSVD and related cognitive impairment.

[0019] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The results of exosome extraction and characterization are shown; A is the Western blot test result of exosomes isolated by EVlent technology: using cells as a control, the expression of exosome marker proteins CD9 and TSG101 was detected, and calnexin was used as a negative control. The results show the detection data of five independent samples; B is the particle size distribution characteristics of exosomes, and the data are from three independent samples; C is the transmission electron microscopy result showing that the isolated exosomes have a typical cup-shaped or concave hemispherical ultrastructure (scale bar: 200 nm).

[0021] Figure 2 Flow chart of DIA detection and analysis.

[0022] Figure 3Figure 5 is the exosomal proteomic characteristics of cerebral small vessel disease and related cognitive impairment; A is a comparison of the number of exosomal proteins detected in the control group and the CSVD group with or without cognitive impairment; B is an unsupervised t-SNE score plot, showing the overall plasma exosomal proteomic characteristics of the control group and the CSVD group with or without cognitive impairment; C is the mFuzz clustering analysis identifying specific expression clusters of exosomal proteins in patients with CSVD and related cognitive impairment, revealing the differential expression pattern of the proteome; DF are volcano plots showing differentially expressed proteins between different groups: D is the control group vs. the CSVD-normal cognitive group, E is the control group vs. the CSVD-cognitive impairment group, and F is the CSVD-normal cognitive group vs. the CSVD-cognitive impairment group; G is the biological and protein pathway enrichment results of differentially expressed exosomal proteins that show progressive changes with the progression of CSVD and related cognitive impairment; H is the PPI protein interaction network, and three functional categories were identified by k-means clustering.

[0023] Figure 4 Random forest algorithm screens exosomal proteins that can simultaneously identify CSVD and related cognitive impairments. AB are variable importance plots generated by the random forest algorithm (measured by the mean decrease in accuracy of each variable), with the most important predictors having the highest mean decrease in accuracy; A is the CSVD vs. control group; B is the CSVD-normal cognition group vs. the CSVD cognitive impairment group; C is the number of exosomal proteins that simultaneously identify CSVD and related cognitive impairments (left) and their expression levels in the three groups (right).

[0024] Figure 5 The stability and specificity of the changes in plasma exosomal proteins were evaluated for the independent validation set; AC is the target protein chromatogram showing the change trend of the mass spectrometry signal intensity of the exosomal proteins ATP6V1F (A), HNRNPU (B) and RPL38 (C) with the retention time; DF is the expression difference of the exosomal proteins ATP6V1F (D), HNRNPU (E) and RPL38 (F) in the control group, CSVD normal cognitive group and CSVD cognitive impairment group in the discovery set and validation set, respectively; GI is the expression difference of the exosomal proteins ATP6V1F (G), HNRNPU (H) and RPL38 (I) in the control group, CSVD normal cognitive group and AD-induced cognitive impairment group in the validation set.

[0025] Figure 6Figure 3 is the correlation between exosomal proteins and CSVD white matter damage burden and cognitive function; A is the correlation between exosomal RPL38 and frontal lobe WMH volume; B is the correlation between exosomal RPL38 and parietal lobe WMH volume; C is the correlation between exosomal RPL38 and occipital lobe WMH volume; D is the correlation between exosomal RPL38 and corpus callosum WMH volume; E is the correlation between exosomal ATP6V1F and MMSE score; F is the correlation between exosomal ATP6V1F and MoCA score; G is the correlation between exosomal ATP6V1F and memory function; H is the correlation between exosomal ATP6V1F and language function; I is the correlation between exosomal HNRNPU and MoCA; J is the correlation between exosomal HNRNPU and executive function; K is the correlation between exosomal HNRNPU and visual-spatial function; L is the correlation between exosomal HNRNPU and MoCA score.

[0026] Figure 7 The ability of exosomal proteins to identify CSVD and related cognitive impairment and to predict clinical cognitive progression of CSVD; A is the receiver operating characteristic curve (ROC) of the combination of exosomal HNRNPU and RPL38 with age, gender, and vascular risk factors for differentiating CSVD-cognitively normal from healthy controls; B is the ranking of feature importance for differentiating CSVD-cognitively normal from healthy controls; longer bars and darker colors indicate more important features; C is the ROC of the combination of exosomal ATP6V1F and HNRNP with demographics (age, gender, and years of education), vascular risk factors, and CSVD imaging markers for differentiating CSVD-cognitively normal from CSVD-cognitively impaired; D is the ranking of feature importance for differentiating CSVD-cognitively normal from CSVD-cognitively impaired; longer bars and darker colors indicate more important features; E is the ability of the combination of exosomal proteins ATP6V1F, HNRNPU, and RPL38 with demographics (age, gender, and years of education), vascular risk factors, and CSVD imaging markers for predicting clinical cognitive progression of CSVD patients; (F) Unadjusted Kaplan-Meier survival curves show the time to clinical cognitive progression in patients with CSVD based on exosomal protein, stratified by risk score (low-risk group: red line; high-risk group: green line). Risk stratification cutoffs were determined using the maximum Youden index method. Cox proportional hazards model analysis (after adjusting for age, sex, years of education, and vascular risk factors) showed a significant association between risk score and cognitive decline in CSVD. Note: OC denotes optimal protein combination. DETAILED DESCRIPTION

[0027] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0028] CSVD is closely associated with cognitive impairment (CI) and is a significant risk factor for stroke, vascular dementia, or death, severely jeopardizing the health and quality of life of the elderly. To address this phenomenon, the present invention provides a combination of exosomal protein markers associated with CSVD and related cognitive impairments. The combination comprises any one of the following: V-type proton ATPase subunit (ATP6V1F), large ribosomal subunit protein eL38 (RPL38), and heterogeneous nuclear ribonucleoprotein U (HNRNPU), or a combination of any two or three of these markers.

[0029] It should be noted that the v-type proton ATPase subunit, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U in the present invention are all known proteins in the human body, and their specific information can be queried through public protein databases. Their sequence information is shown in the following table: The V-type proton ATPase (ATP6V) is a multi-subunit complex primarily found in the membranes of organelles in eukaryotic cells (such as lysosomes, endosomes, and the Golgi apparatus) and in some prokaryotes. It uses the energy generated by ATP hydrolysis to pump protons (H⁺) into organelles against the concentration gradient, maintaining intracellular pH and membrane potential. Its structure is similar to that of F-type ATP synthase (mitochondrial ATP synthase), but its function is reversed (hydrolyzing ATP rather than synthesizing it). V-type proton ATPase subunit F (ATP6V1F) is one of the core subunits of the V-type proton ATPase. Studies have shown that impaired lysosomal acidification is associated with Alzheimer's disease and Parkinson's disease, but no studies have demonstrated a correlation between V-type proton ATPase subunit F and CSVD and related cognitive impairments.

[0030] Large ribosomal subunit protein eL38 (RPL38) is a component of the 60S large ribosomal subunit and plays a crucial role in protein translation. Although ribosomal proteins are generally considered structural components, a growing body of research indicates that they also participate in translational regulation, cell proliferation, and development. As a component of the 60S large subunit, it participates in ribosome biogenesis. It may affect translational fidelity or elongation rate, particularly in the translational regulation of certain mRNAs, such as Hox genes. Currently, no direct pathogenic mutations in RPL38 have been identified. However, abnormalities in ribosomal proteins (RPs) have been associated with a variety of diseases, including ribosomopathies (such as Diamond-Blackfan anemia (DBA)), developmental disorders (such as skeletal deformities and growth retardation), and cancer (ribosomal proteins are often dysregulated in tumors, affecting protein synthesis and cell proliferation). However, no studies have demonstrated a link between large ribosomal subunit protein eL38 and CSVD and related cognitive impairments.

[0031] Heterogeneous nuclear ribonucleoprotein U (HNRNPU, also known as hnRNP U or SAF-A) belongs to the hnRNP family and is a class of RNA-binding proteins (RBPs) that are extensively involved in RNA metabolism, such as splicing, transport, stability, and translation. HNRNPU, due to its unique DNA / RNA binding ability and chromatin regulatory functions, plays a key role in gene expression regulation, genome stability, and neurodevelopment. Studies have shown that mutations or deletions in HNRNPU lead to abnormal RNA metabolism (such as EIEE, ASD, and intellectual disability). However, no studies have demonstrated a correlation between HNRNPU and cerebral small vessel disease and related cognitive impairment.

[0032] It should be noted that the three exosomal proteins mentioned above can not only serve as early diagnostic markers for SVD and related cognitive impairment, but can also serve as screening markers, risk assessment products, or prognostic assessment markers for SVD and related cognitive impairment. They may also become targets for drug treatment.

[0033] Any one of these markers alone can be used as a basis for early diagnosis of SVD and related cognitive impairment. However, because a single marker may lead to misdiagnosis, a combination of these three markers is preferred to improve diagnostic accuracy and reliability.

[0034] The combination of V-type proton ATPase subunit, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U can improve the sensitivity and specificity of cerebral small vessel disease and related cognitive impairment. This combination strategy helps reduce the possibility of misdiagnosis and improve the accurate diagnosis rate of cerebral small vessel disease and related cognitive impairment, providing a more reliable basis for patient treatment and management.

[0035] Therefore, although a single marker also has certain diagnostic value, it is still preferred to use a combination of three markers as the basis for the diagnosis of cerebral small vessel disease and related cognitive impairment to ensure the accuracy and reliability of the diagnostic results.

[0036] In another embodiment of the present invention, a reagent for detecting the above-mentioned combination of three exosome protein markers is provided for use in preparing any of the following products: (1) Early diagnosis products for cerebral small vessel disease and related cognitive impairment; (2) Screening products for cerebral small vessel disease and related cognitive impairment; (3) Risk assessment products for cerebral small vessel disease and related cognitive impairment; or (4) Prognostic assessment products for cerebral small vessel disease and related cognitive impairment.

[0037] Since the above-mentioned markers of cerebral small vessel disease and related cognitive impairment may be a single marker or a combination of multiple markers, the corresponding diagnostic kits or detection devices may also be presented in various forms. For example, it can be a diagnostic kit or detection device for a single marker, that is, a product specifically used to detect any one of the v-type proton ATPase subunits, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U. Further exemplarily, it can also be a combination of diagnostic products containing multiple markers, that is, a product that simultaneously detects v-type proton ATPase subunits, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U. Exemplary products include but are not limited to chips, kits, test strips or analysis platforms.

[0038] This diverse design allows for greater applicability and flexibility in diagnostic products, allowing for the selection of appropriate testing protocols based on specific clinical needs and diagnostic requirements. However, whether a diagnostic kit is based on a single marker or a combination of multiple markers, it is expected to provide relatively reliable and accurate diagnostic results.

[0039] The reagents included in the specific kit of the present invention can be set according to the detection method of each marker. This means that for the three markers of v-type proton ATPase subunit, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U, specific methods and reagents suitable for their detection can be selected.

[0040] The reagents included in the specific kit of the present invention can be set according to the detection method of each exosome marker. This means that for two different exosome markers, namely v-type proton ATPase subunit, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U, specific methods and reagents suitable for their detection can be selected.

[0041] Since these three markers are known substances, a wide range of reliable detection methods already exist in the prior art. For example, immunological methods such as enzyme-linked immunosorbent assay (ELISA) and immunofluorescence analysis can be used to detect the levels of these markers. Molecular biology techniques such as polymerase chain reaction (PCR) and in situ hybridization can also be used to detect the gene expression levels of these markers. Furthermore, mass spectrometry analysis and other methods can also be used.

[0042] Based on the rich experience and mature methods of the existing technology, the most suitable method for detecting the above-mentioned markers can be selected by referring to existing detection methods and reagents. Then, based on the selected detection method, the corresponding diagnostic kit or detection device can be designed according to the standards and processes of the existing technology.

[0043] ELISA is a commonly used biomarker detection method that utilizes specific antibodies to bind to the biomarker being detected, followed by an enzymatic reaction to produce a measurable signal. The ELISA method is highly sensitive and specific and can be applied to the detection of a single biomarker or multiple biomarkers.

[0044] Immunofluorescence analysis uses fluorescently labeled antibodies to bind to the biomarker to be detected and detects the intensity of the fluorescent signal using a fluorescence microscope or fluorescence photometer to quantitatively analyze the presence of the biomarker.

[0045] Mass spectrometry can accurately quantify biomarkers and includes methods such as proton nuclear magnetic resonance (NMR) and mass spectrometry (MS), which can provide very precise molecular structure and relative content information.

[0046] PCR technology can be used to detect biomarker RNA transcripts. The RNA or its fragments to be detected are amplified by PCR and then quantitatively analyzed by methods such as gel electrophoresis or real-time fluorescence quantitative PCR.

[0047] Protein chip technology can detect multiple biomarkers simultaneously by immobilizing multiple antibodies on the chip surface, which then bind to proteins in the sample to be tested (such as tissue), and finally detect the biomarkers through fluorescent or radioactive labeled signals.

[0048] Exemplarily, considering detection efficiency and convenience, the kit may be an ELISA kit.

[0049] In another embodiment of the present invention, the use of the aforementioned exosomal markers for non-prognostic assessment, pathological diagnosis, or treatment of cerebral small vessel disease and related cognitive impairment is provided. Non-prognostic assessment, pathological diagnosis, or treatment of cerebral small vessel disease and related cognitive impairment may be for scientific research, non-medical commercial detection, or testing, etc.

[0050] For example, exosomal biomarkers for cerebral small vessel disease and related cognitive impairment can be used to study disease mechanisms, pathophysiological processes, and potential therapeutic targets. By analyzing changes in these markers during the disease process, we can gain a deeper understanding of the development and metastasis of the disease, providing a deeper understanding of disease prevention and treatment.

[0051] Biomarkers also play a crucial role in drug development. They can serve as indicators for evaluating drug efficacy, helping researchers assess the safety and effectiveness of new drugs. By monitoring the effects of drugs on biomarkers, potential drug toxicities and adverse reactions can be identified early, guiding dosage adjustments and optimization.

[0052] Biomarkers can also be used in individual health management and preventive medicine. By regularly monitoring specific biomarkers, changes in individual health status can be detected, disease risk can be predicted, and appropriate health management measures can be taken, such as adjusting lifestyle, dietary habits, or taking medication, to maintain health and slow disease progression.

[0053] Biomarkers can be used to assess the impact of lifestyle on health. By monitoring changes in these biomarkers, we can evaluate the extent to which different lifestyles affect health and guide individuals to adopt appropriate lifestyle interventions, such as weight loss, smoking cessation, and increased physical activity, thereby improving health and reducing disease risk.

[0054] The present invention also provides a method for assessing the prognosis of cerebral small vessel disease and related cognitive impairment in a subject. The key to this method is to detect the levels of V-type proton ATPase subunits, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U in the subject's urine or blood.

[0055] First, the implementation of this method involves sample collection and processing. The sample is extracted from the subject's urine or blood, and this process requires following strict standard operating procedures to ensure the quality and integrity of the sample.

[0056] Secondly, for samples already obtained, appropriate techniques and reagents can be used to detect the levels of V-type proton ATPase subunits, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U, which are involved in cerebral small vessel disease and related cognitive impairment. These detection methods can include immunological techniques such as ELISA and immunofluorescence analysis, molecular biology techniques such as PCR and in situ hybridization, and mass spectrometry. These methods can accurately quantify the levels of specific markers in the subject's tissues.

[0057] After obtaining marker test results, they need to be compared and analyzed with relevant data from healthy patients. Based on these comparisons, the subject's prognosis can be determined. If the level of a particular marker or combination of markers is significantly below the normal range, it can be inferred that the subject is more likely to have a poor prognosis.

[0058] The reliability and accuracy of this method depend on the sensitivity and specificity of the selected detection method, as well as the determination of the reference range or threshold. Therefore, when implementing this method, it is necessary to strictly control the experimental conditions and combine clinical practice experience and data analysis to interpret the results and make a diagnosis. In addition, the test results of any one marker should be carefully evaluated and interpreted to avoid uncertainty in the diagnostic results due to the possibility of misdiagnosis due to the potential for misdiagnosis of a single marker.

[0059] The present invention provides a method for pre-evaluating whether a drug can prevent or treat cerebral small vessel disease and related cognitive impairment, which includes using biomarkers of v-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U to evaluate the effect of the drug, so as to achieve the purpose of precision medicine.

[0060] Implementation of this method begins with experimental design and sample collection. During the design phase of a study or clinical trial, the drug to be evaluated, the treatment regimen, and the evaluation criteria must be clearly defined. Furthermore, subject selection criteria must be determined, and appropriate biological samples, such as plasma, tissue, or cell samples, must be collected for subsequent experimental analysis.

[0061] After obtaining a biological sample, appropriate techniques and reagents can be used to detect the levels of the selected markers. These detection methods can include immunological techniques such as ELISA and immunofluorescence analysis, molecular biology techniques such as PCR and in situ hybridization, or mass spectrometry. These methods can accurately quantify the levels of the markers in the subject's biological sample.

[0062] Next, the drug or treatment regimen is administered to the subject, and treatment is continued according to the prescribed regimen. During treatment, the subject's biological samples are regularly monitored, and the levels of selected markers are repeatedly measured. This allows for timely monitoring of the drug's therapeutic effects and whether the intended treatment goals have been achieved.

[0063] Finally, based on the test results obtained, the therapeutic effect of the drug can be evaluated and determined. If the levels of the selected markers change significantly, with a clear difference compared to pre-treatment levels, it can be inferred that the drug may have the potential to prevent or treat SVD and related cognitive impairment. Conversely, if the changes in marker levels are not significant or the expected effect is not achieved, it may be necessary to re-evaluate the treatment plan or try other treatment strategies.

[0064] The present invention provides a method for screening compounds that can prevent or treat cerebral small vessel disease and related cognitive impairment, which includes using v-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U as biomarkers of cerebral small vessel disease and related cognitive impairment to evaluate the effects of the compounds, so as to achieve the purpose of precision medicine.

[0065] First, the implementation of this method requires the establishment of an appropriate experimental system and model. Cell lines or animal models of SVD and related cognitive impairment can be used to simulate the physiological processes of SVD and related cognitive impairment and evaluate the effects of compounds on them.

[0066] Secondly, appropriate biomarkers should be selected to assess the efficacy of the compound. V-type proton ATPase subunit, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U serve as biomarkers for SVD and related cognitive impairment, reflecting the biological processes and pathological states of SVD and related cognitive impairment. Therefore, they can be used as biomarkers to screen compounds and assess their efficacy in interventions for SVD and related cognitive impairment.

[0067] Next, compound screening experiments are conducted. The compounds to be screened are added to cells or animals to observe their effects on the expression of V-type proton ATPase subunits, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U, which are associated with SVD and related cognitive impairment. Appropriate techniques and reagents, such as immunological and molecular biological techniques, can be used to measure the levels of these markers. Based on the test results, a preliminary assessment of the compound's potential therapeutic effect on SVD and related cognitive impairment can be conducted.

[0068] After obtaining preliminary screening results, further verification and confirmation experiments can be conducted. By using more sophisticated and rigorous experimental designs and operational procedures, the effects of the compounds on marker levels can be verified and their therapeutic effects on SVD and related cognitive impairment can be further evaluated.

[0069] Finally, based on the experimental results, compounds with potential therapeutic effects are further researched and developed. Their pharmacological properties, toxicity, side effects, pharmacokinetics, and other drug attributes can be further evaluated, and preclinical studies and clinical trials can be conducted.

[0070] The present invention further illustrates the selection principle, process and effect of the above-mentioned biomarkers through a specific example below, so that those skilled in the art can understand the essence of the present invention.

[0071] Antibodies mentioned in the following examples: Example 1: Data Source and Grouping 1. Data Source This example includes two independent datasets, a discovery set and a validation set, both of which were recruited by Nanjing Drum Tower Hospital in community settings, outpatient clinics, or inpatient departments in Nanjing. All subjects or their legal guardians obtained full informed consent and signed written consent. This invention was approved by the Institutional Review Board of Nanjing University Medical School Affiliated Drum Tower Hospital. Discovery set: included 36 healthy controls, 28 CSVD normal cognitive group, and 36 CSVD cognitive impairment group.

[0072] Validation set: included 55 healthy controls, 45 normal CSVD cognition groups, 76 cognitive impairment CSVD groups, and 48 AD-induced cognitive impairment cases.

[0073] 2. Diagnostic criteria for CSVD This study enrolled patients with CSVD (small artery sclerosis) according to the criteria of the "Chinese Expert Consensus on the Diagnosis and Treatment of Cerebral Small Vessel Disease 2021." Specific inclusion criteria included: 1) age ≥50 years; 2) cranial MRI demonstrating moderate to severe vascular white matter hyperintensities on T2WI / FLAIR sequences, assessed as grade 2-3 on the Fazekas scale (Fazekas F, Barkhof F, Wahlund L O, et al. CT and MRI rating of white matter lesions[J]. Cerebrovascular diseases, 2002, 13(Suppl. 2): 31-36), with or without CSVD imaging findings such as lacunar infarcts, microbleeds, and enlarged perivascular spaces. All imaging assessments were performed independently by two experienced radiologists in a blinded manner, i.e., visual assessment was performed without knowledge of the subjects' clinical data. Based on cognitive function assessment results, CSVD patients were divided into a normal cognitive group and a CSVD cognitive impairment group.

[0074] Exclusion criteria for CSVD include: 1) previous ischemic stroke with an infarct diameter >1.5 cm or cardiogenic cerebral embolism; 2) subarachnoid hemorrhage or intraparenchymal hemorrhage; 3) internal carotid artery or vertebral artery stenosis (>50%); 4) white matter hyperintensities caused by immune-mediated demyelinating diseases (multiple sclerosis, neuromyelitis optica, acute disseminated encephalomyelitis), metabolic leukodystrophy, or hereditary leukoencephalopathy; 5) cognitive impairment caused by other neurological diseases (such as Parkinson's disease, epilepsy, frontotemporal dementia, or dementia with Lewy bodies); 6) all-cause dementia; 7) systemic disease (such as malignancy, shock, or anemia); 8) rapid cognitive decline possibly caused by prion disease, tumor, or metabolic disease; and 9) cognitive impairment caused by trauma or medical factors.

[0075] Dementia was identified using the Mini-Mental State Examination (MMSE, Katzman R, Zhang M, Wang Z, et al. A Chinese version of the Mini-Mental State Examination; impact of illiteracy in a Shanghai dementia survey. Journal of clinical epidemiology 1988; 41:971-978). Illiterate patients were diagnosed with an MMSE score of <18, primary school students with an MMSE score of <21, and junior high school students and above with an MMSE score of <25. For patients without dementia, mild cognitive impairment (MCI) was diagnosed using the Montreal Cognitive Assessment (MoCA, Lu J, Li D, Li F, Zhou A, Wang F, Zuo X, et al. Montreal cognitive assessment in detecting cognitive impairment in Chinese elderly individuals: a population-based study. Journal of geriatric psychiatry and neurology. 2011;24(4):184-90). MCI), that is, illiterate MoCA score ≤ 13 points, primary school MoCA score ≤ 19 points, junior high school and above, MoCA score ≤ 24 points.

[0076] Dementia and mild cognitive impairment due to Alzheimer's disease (AD) were diagnosed according to the criteria of the National Institute on Aging-Alzheimer's Association (NIA-AA 2011). Patients who met the diagnostic criteria for dementia or mild cognitive impairment due to AD were classified as having AD-related cognitive impairment. It is important to note that for subjects with AD-related cognitive impairment, we excluded subjects with cognitive impairment due to other neurological conditions (such as Parkinson's disease, epilepsy, frontotemporal dementia, or dementia with Lewy bodies); all-cause dementia; systemic diseases (such as malignancy, shock, or anemia); rapid cognitive decline possibly caused by prion disease, tumors, or metabolic diseases; cognitive impairment due to trauma or medical factors; moderate to severe white matter hyperintensities, multiple lacunar infarcts, or a modified Hachinski ischemic score greater than 4.

[0077] 3. Clinical information of subjects All subjects completed demographic data, cognitive function assessment, and peripheral blood biomarker testing. Table 1-2 lists the clinical characteristics of the study subjects as follows: Table 1 Clinical characteristics of discovery set participants Note: Age, years of education, MMSE and MoCA scores, white matter hyperintensity volume, lacunar infarction, and microbleeding are expressed as means (standard deviations). CSVD, cerebral small vessel disease; WMH, white matter hyperintensity; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; SD, standard deviation. * Indicates P < 0.05. a indicates P < 0.05 compared with the healthy control group; b Denotes P < 0.05 compared with the CSVD normal cognitive group.

[0078] Table 2 Clinical characteristics of the validation set subjects Note: Age, years of education, MMSE and MoCA scores, white matter lesion volume, lacunae, and microbleeds are expressed as means (standard deviations). AD, Alzheimer's disease; WMH, white matter hyperintensities; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; SD, standard deviation. * Indicates P < 0.05. a indicates P < 0.05 compared with the healthy control group; b indicates P < 0.05 compared with the CSVD cognitively normal group; c Indicates comparison with the CSVD cognitive impairment group.

[0079] As shown in Tables 1 and 2 above, there were no significant differences in age, gender, years of education, and vascular risk factors among the groups. The WMH volume in the CSVD group was significantly higher than that in the healthy control group, and the MMSE and MoCA scores in the CSVD cognitive impairment group were significantly lower than those in the healthy control group and the CSVD cognitively normal group. There were no significant differences in WMH volume, lacunar infarcts, or number of cerebral microbleeds between the CSVD cognitively normal and cognitive impairment groups. In the validation set, there were no significant differences in age, gender, diabetes, hyperlipidemia, or smoking history among the four groups. The years of education and WMH volume in the CSVD cognitive impairment group were significantly lower than those in the healthy control group and the CSVD cognitively normal group, and the proportion of patients with a history of hypertension in the CSVD group was higher than that in the healthy control group and the AD-induced cognitive impairment group. The MMSE and MoCA scores in the CSVD cognitive impairment and AD-induced cognitive impairment groups were significantly lower than those in the healthy control group and the CSVD cognitively normal group.

[0080] Example 2: Screening of markers 1. Collection of Peripheral Blood Plasma Samples Collect 5 mL of peripheral blood from the subject using a purple EDTA anticoagulant tube and centrifuge within 2 hours. Centrifuge the resulting peripheral blood at 3000 rpm for 10 minutes at 4°C. Aspirate the supernatant into 2-3 Eppendorf tubes (500 μL each) and store at -80°C for future testing.

[0081] 2. Extraction and Characterization of Exosomes from Peripheral Blood Plasma 2.1 Exosome extraction Exosomes were extracted from the samples using Yiwei Jianhua's plasma exosome affinity extraction kit (EVLiXiR#EV02-05-01). The specific steps include: First, centrifuge the plasma samples (2000 g, 5-10 minutes) and collect the supernatant. Add 200 μL of plasma from each sample to 800 μL of pre-chilled Incubation Buffer I and mix thoroughly at room temperature. After mixing, add 40 μL of Evlent magnetic beads to each sample and incubate at room temperature with shaking for 2-3 hours. After incubation, aspirate the beads using a magnetic rack for 3 minutes, separate, and discard the supernatant. Add 1 mL of Incubation Buffer II to the resulting pellet, shake the pellet upside down 20 times, separate the beads using a magnetic rack, and discard the supernatant. Add 1 mL of Washing Buffer to the resulting pellet, shake the pellet upside down 20 times, separate the beads using a magnetic rack for 3 minutes, and discard the supernatant. Repeat this step twice. The resulting pellet contains the exosome-bound magnetic beads.

[0082] Note: The above dosages are for a single sample.

[0083] 2.2 Exosome extraction and characterization 2.2.1 Western blot identification of exosomes Western blot was used to identify exosome surface markers. The specific steps included adding the exosome-adsorbed magnetic beads obtained above to 4×LDS loading buffer (B0007, Invitrogen), boiling at 95°C for 5 minutes, followed by magnetic separation, and the supernatant was aspirated and loaded onto a polyacrylamide gel (PAGE). First, 15 μL of 1×SDS loading buffer was added, and the sample was boiled at 95°C for 10 minutes. After cooling, the sample was centrifuged. Then, 15 μL of the sample was added to the entire lane, and markers were added to the beginning and end of the sample. After addition, electrophoresis was performed at 190V for 70 minutes. After electrophoresis, the PVDF membrane was activated with methanol 10 minutes in advance, and the transfer buffer was pre-chilled. The membrane was then transferred at 275 mA for 70 minutes. After transfer, a 1% BSA solution in TBST was added and the membrane was blocked at room temperature for 1 hour. After blocking, the primary antibody incubation was performed, that is, the appropriate membrane was cut according to the molecular weight of the target protein, and 1% BSA solution containing CD81 (Rabbit monoclonal, 1: 1000), TSG101 (Rabbit polyclonal, 1: 1000), CD9 (Rabbit polyclonal, 1: 1000) and Calnexin (Rabbit polyclonal, 1: 1000) antibodies was added respectively, and incubated at 4°C overnight. After the incubation, the membrane was washed three times with 1xTBST, 10 minutes each time. Then the secondary antibody incubation was performed, that is, goat anti-rabbit secondary antibody (1: 5000) was added, diluted with 1% BSA TBST solution, and incubated on a shaker at room temperature for 1 hour. After the incubation was completed, the membrane was washed three times with 1xTBST, 10 minutes each time. Finally, the exposure and photography were performed, and the results are shown in the figure. Figure 1 A.

[0084] 2.2.2 Exosome NTA detection The exosomes were evenly dispersed by shaking, and diluted with PBS to an appropriate multiple. The sample name and dilution multiple were marked to complete the sample dilution preparation. Before testing, the diluent was tested. 200 μL of diluent was aspirated with a pipette to confirm that the components and the instrument were operating normally. After the dilution measurement was completed and the test results were normal, the sample was tested. 200 μL of the diluted sample was added to the instrument. When the number of particles reached 100 or more, the test was stopped, and the required data results were exported to complete the test. Figure 1 B.

[0085] 2.2.3 TEM identification of exosomes Transmission electron microscopy (TEM) was used to identify the morphology of exosomes. The specific steps included: adding 100 μL Elution Buffer to the magnetic beads adsorbed with exosomes obtained above, vortexing for 10 minutes, and collecting the supernatant by magnetic attraction for 3 minutes. Add 100 μL Elution Buffer to the obtained magnetic beads again, vortexing for 10 minutes, and collecting the supernatant by magnetic attraction for 3 minutes, and combine the supernatants obtained twice. Take 20 μL of supernatant from each sample, place the sample face down in the circular groove at the tip of the sample rod, and perform electron microscopy detection using Hitachi HT7800. Finally, start the software, take and save the picture, and the results are shown in the figure. Figure 1 C.

[0086] 3. Plasma Exosome Protein Extraction and Digestion The extracted exosomes were lysed using an exosome lysis buffer (EVLiXiR#EV02-08-01) adapted for mass spectrometry detection. Lys-C enzyme (EVLiXiR#EV01-02) was added at a ratio of 1:100 (enzyme:sample) and incubated at 37°C for 3 hours. Trypsin (EVLiXiR#EV01-01-02) was then added at a ratio of 1:50 (enzyme:sample) and incubated overnight at 37°C in a water bath. Desalting was then performed using a desalting column. The eluted sample was freeze-dried in a refrigerated vacuum centrifuge and stored at -80°C until further use.

[0087] 4. High-resolution liquid chromatography-tandem mass spectrometry (LC-MS / MS) analysis DIA (data-independent acquisition) is a new mass spectrometry technique developed in recent years and is a label-free proteomics approach. Using a data-independent scanning mode, the full mass spectrometer scan range is divided into several windows. All ions in each window are then detected and fragmented, enabling comprehensive and accurate ion information to be obtained without omission or discrepancy. This reduces missing values ​​in sample detection while improving quantitative accuracy and reproducibility, enabling highly stable and accurate proteomic quantitative analysis in large sample cohorts.

[0088] DIA detection and analysis flow chart Figure 2After loading the DIA sample onto the instrument, the lyophilized sample was reconstituted with 0.1% formic acid, and 500 ng of peptide fragments were separated by chromatography using the nanoliter flow rate Easy-nLC 1200 chromatography system. Buffer A (0.1% formic acid in water) and buffer B (80% acetonitrile / 0.1% formic acid) were used. The LC elution conditions are shown in the table below. After peptide separation, DIA mass spectrometry analysis was performed using a QE HF-X mass spectrometer. The analysis time was 60 min, detection mode: positive ion, precursor ion scan range: 400-1200 m / z, primary mass spectrometry, resolution: 60,000, AGC target: 1e6, Maximum IT: 60 ms; secondary mass spectrometry: resolution: 15,000, AGC target: 1e6, Maximum IT: 20 ms. The chromatographic gradient is shown in Table 3 below: Table 3 Chromatographic gradient 5. Protein Identification and Quantification The samples were freeze-dried and concentrated, then lysed with lysis buffer and boiled at 95°C for 10 min before protein quantification. 1 μL of each sample was taken and quantified using Nanodrap.

[0089] 6. Exosome Proteomic Analysis Spectronaunt software was used to analyze the raw data against the uniprot database, and the search parameters were set as shown in Table 4 below: Table 4 Search parameters 7. Statistical Analysis Methods (1) Intergroup comparison of general information and neuropsychological test scores SPSS 22.0 (IBM Corp., Armonk, NY) was used to analyze demographic data, WMH volumes, whole brain volumes, and neuropsychological test scores of the three groups. All measurement data were tested for normality. One-way analysis of variance was used for comparisons between groups that met normal distributions, while nonparametric tests were used for comparisons between groups that did not meet normal distributions. Chi-square tests were used for comparisons between groups for count data. Differences were considered statistically significant when P < 0.05. Measurement data that met normal distributions were presented as mean ± standard deviation, while those that did not meet normal distributions were presented as median (minimum, maximum). Count data were presented as absolute values ​​(percentages).

[0090] (2) Statistical analysis of differential exosomal proteins and establishment of diagnostic / predictive models Before differential exosomal protein analysis in the discovery set, missing values ​​(NA) in the raw data were imputed using the nearest neighbor (KNN) algorithm using R software (v4.4.1). Protein abundance was then log-transformed to base 2. To eliminate experimental error, the raw data were further quantile-normalized. Differences in exosomal protein expression among the three groups were compared using the limma package, with a logFC > 1 or < -1 and P < 0.05 (FDR correction) considered statistically significant. Furthermore, time-series analysis of exosomal proteins was performed using the Mfuzz package to explore the patterns of exosomal protein expression during the progression of CSVD-related cognitive impairment. Integrating the results of differential protein and time-series analyses identified exosomal proteins that exhibited progressive changes with disease progression, and bio-enrichment and protein interaction network analyses were performed. A random forest algorithm was then used to identify exosomal proteins that could be used to diagnose both CSVD and its related cognitive impairments. Targeted mass spectrometry was then used in the validation set to detect candidate exosomal proteins identified in the discovery set, and their trends were compared between the discovery and validation sets. The XGboost-based machine learning algorithm was used to explore the ability of exosomal proteins with consistent changing trends during the progression of CSVD-related cognitive impairment in the two datasets to distinguish between CSVD with and without cognitive impairment and to construct a diagnostic model. ROC curve analysis was used to explore the ability of the above exosomal proteins to predict the clinical cognitive progression of CSVD patients.

[0091] 8. Results and Analysis 1) Transmission electron microscopy (TEM) was used to identify the morphology of exosomes. Under TEM, it was observed that the exosomes in peripheral blood were round or oval in shape, with uneven sizes and a diameter of about 30-200 nm. Their membranous structure was visible, with a low electron density component in the center (see Figure 1 AB).

[0092] 2) Western blot was used to identify the surface markers of exosomes, including membrane proteins of CD9, CD63 and CD81. In this study, the expression of exosome marker proteins CD9 and CD81 was detected by Western blot. It was found that all exosomes expressed CD9 and CD81 (see Figure 1 C).

[0093] 3) Screening for exosomal proteins that change progressively with disease progression. Using liquid chromatography-tandem mass spectrometry (LC-MS / MS) technology, 2257, 2409, and 2042 exosomal proteins were detected in the three groups of the discovery set, respectively. The number of proteins identified in the CSVD-NC group was significantly higher than that in the CSVD-CI group ( Figure 3 A). Unsupervised clustering algorithm based on t-SNE can distinguish healthy controls from CSVD patients ( Figure 3B). First, the Mfuzz package was used to analyze the exosome proteomes of the healthy control group, the CSVD normal cognitive group, and the CSVD cognitive impairment group to identify plasma exosome proteins that showed progressive changes with the progression of CSVD-related cognitive impairment. The results showed the presence of two exosome protein clusters whose expression levels showed a trend of progressive downregulation or upregulation with disease progression ( Figure 3 C). In addition, based on the limma test, log2FC > 1 or log2FC < -1, P < 0.05 (FDR correction), there were 97 differentially expressed proteins between the healthy control group and the CSVD normal cognitive group ( Figure 3 D), there are 127 differential exosomal proteins between the healthy control group and the CSVD cognitive impairment group ( Figure 3 E), there are 52 different exosomal proteins between the CSVD normal cognitive group and the CSVD cognitive impairment group ( Figure 3 F). By integrating the results of differential EV protein analysis using the limma test and the Mfuzz package, 12 and 60 exosomal proteins were found to be progressively upregulated and downregulated with CSVD-related cognitive impairment, respectively. Further bio-enrichment analysis suggested that these exosomal proteins were mainly related to adaptive immune response, ribosome function, signal amplification, and metabolism of vitamins and cofactors ( Figure 3 G). Subsequently, protein interaction network analysis and k-means clustering were performed using STRING, resulting in three different functional categories ( Figure 3 H). The first category includes 17 proteins, which are closely related to the assembly of protein-RNA complexes and the process of RNA splicing through transesterification reactions. The second category includes 8 proteins involved in signal amplification, metabolism of water-soluble vitamins and cofactors, and intercellular adhesion. The third category includes 5 proteins involved in the organization of the extracellular matrix and differentiation of muscle cells. In order to screen exosomal proteins that can simultaneously identify CSVD and CSVD-related cognitive impairment. In addition, the random forest algorithm was used to analyze the diagnostic ability of the above 72 exosomal proteins for CSVD and CSVD-related cognitive impairment respectively. The intersection of the top 30 exosomal proteins with the highest diagnostic weight was taken, and 14 candidate exosomal proteins (including RPL38, NEDD4L, SRPK2, NEBL, DMXL2, HNRNPU, DNAAF1, TM6SF1, ATP6V1F, CEP78, CUTA, BIN3, RPL18, SNRPE) were found to be able to simultaneously identify CSVD and CSVD-related cognitive impairment ( Figure 4 Therefore, we further used targeted mass spectrometry-parallel reaction monitoring (PRM) to detect the 14 plasma exosomal proteins screened above in a new dataset to further verify the reproducibility and robustness of these proteins as well as their specificity for CSVD-related cognitive impairment.

[0094] Example 3: Validation of markers The 14 exosome protein markers obtained by screening the discovery set in Example 2 were further verified by using the validation set in Example 1. The results are shown in Figure 5 In the validation set, the above 14 exosomal proteins were detected using a targeted mass spectrometry method, of which 9 exosomal proteins (ATP6V1F, BIN3, CUTA, HNRNPU, NEDD4L, RPL18, RPL38, SNRPE, and SRPK2) met the quality control standards. Further comparison of the change trends of the above 9 exosomal proteins in healthy controls, CSVD normal cognition groups, and CSVD cognitive impairment groups revealed that only ATP6V1F ( Figure 5 A and D), HNRNPU ( Figure 5 B and E) and RPL38 ( Figure 5 C and F) showed the same trend of change in the discovery set and validation set. These three exosomal proteins in CSVD patients were significantly lower than those in the healthy control group in both the discovery set and validation set (P < 0.01). In the two CSVD groups, the levels of exosomal proteins ATP6V1F and HNRNPU in the CSVD cognitive impairment group were significantly lower than those in the CSVD-normal cognitive group (P < 0.001). In the discovery set, the level of exosomal protein RPL38 in the CSVD cognitive impairment group was significantly lower than that in the CSVD-normal cognitive group (P < 0.05), but this change did not reach statistical significance in the validation set (P > 0.05). In addition, the expression levels of the above three exosomal proteins in AD-induced cognitive impairment were also compared. The results showed that the level of exosomal RPL38 in the AD-induced cognitive impairment group was significantly higher than that in the healthy control group (P < 0.05) ( Figure 5 I); There was no significant difference in the expression levels of exosomal ATP6V1F and HNRNPU between the AD-induced cognitive impairment group and the healthy control group ( Figure 5 G and H, P > 0.05). Finally, by further comparing the expression differences of the above three exosomal proteins in CSVD-related cognitive impairment and AD-derived cognitive impairment, it was found that the expression levels of the above three exosomal proteins in patients with CSVD cognitive impairment were significantly lower than those in patients with AD-derived cognitive impairment ( Figure 5 GI, P < 0.001), further indicating the specificity of these exosomal proteins for CSVD-related cognitive impairment.

[0095] The correlation between exosome proteins and CSVD white matter damage burden and cognitive function was analyzed by using age, gender, years of education or whole brain volume as covariates in the discovery set and validation set respectively. The correlation between the above three exosome proteins and MMSE, MoCA and various cognitive domains was then meta-analyzed on the results of the two datasets. The results showed that after FDR multiple comparison correction, exosome RPL38 was significantly negatively correlated with CSVD white matter damage burden in the frontal lobe, occipital lobe, parietal lobe and corpus callosum ( Figure 6 AD); Exosomal ATP6V1F was significantly positively correlated with MMSE, MoCA, memory function and language function ( Figure 6 EH); Exosomal HNRNPU was significantly positively correlated with MoCA scores, executive function, and visual-spatial function ( Figure 6 IK), RPL38 was significantly positively correlated with MoCA score ( Figure 6 L). These results suggest that the above three proteins may be involved in the occurrence and development of CSVD-related cognitive impairment.

[0096] To further evaluate the diagnostic ability of the three exosomal proteins for CSVD and related cognitive disorders, we used an XGBoost-based machine learning method to test all possible combinations of the three exosomal proteins (n ​​= 8) and performed a ten-fold cross-validation to ensure model robustness. The results showed that among all combinations, the combination of exosomal proteins HNRNPU and RPL38 performed best in distinguishing CSVD-normal cognitive status from healthy controls, with a test set AUC of 0.849 ( Figure 7 A). After adding age, gender, and vascular risk factors (hypertension, diabetes, hyperlipidemia, and smoking history) to the model, the diagnostic performance was significantly improved, and the exosomal proteins HNRNPU and RPL38 had the highest diagnostic weights in the model ( Figure 7 B). In terms of distinguishing CSVD with or without cognitive impairment, the combination of exosomal proteins ATP6V1F and HNRNPU performed best, with a test set AUC of 0.897 ( Figure 7 A) After demographics, CSVD markers (such as WMH volume, lacunar infarcts, and number of cerebral microbleeds), and vascular risk factors (hypertension, diabetes, hyperlipidemia, and smoking history) were added to the model, the two proteins still had the highest diagnostic weight ( Figure 7 D), but the diagnostic efficiency was not significantly improved ( Figure 7C). In addition, this application also conducted a longitudinal analysis of a prospective dataset of 63 CSVD patients who completed 0.5-5 years of follow-up. Among these CSVD patients, 21 patients showed clinical cognitive progression after follow-up (i.e., the MoCA score decreased by 3 points or more after follow-up compared with that before follow-up. The baseline information of CSVD patients who completed follow-up is shown in Table 5). Using ROC curve analysis, it was found that the above three exosome protein combinations can effectively predict longitudinal cognitive decline in CSVD, with an AUC of 0.777 ( Figure 7 E), combined with demographics (age, sex, and years of education), CSVD markers, and vascular risk factors, the model's predictive ability was further improved ( Figure 5 E). By calculating the exosomal protein risk score, we divided WMH patients into high-risk and low-risk groups. The Kaplan-Meier curve showed that the risk of cognitive decline in the high-risk group was significantly higher than that in the low-risk group ( Figure 7 F). In summary, the exosomal proteins discovered in this study not only performed well in the diagnosis of CSVD and its related cognitive impairments, but also effectively predicted disease progression, providing an important basis for the early identification and intervention of CSVD-related cognitive impairments.

[0097] Table 5 Clinical characteristics of CSVD patients with cognitive progression and non-progression Note: Age, years of education, MMSE, and MoCA scores are expressed as mean (standard deviation); gender is expressed as the number of females (percentage). MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment. SD, standard deviation. * indicates P < 0.05.

[0098] Example 4: ELISA kit for CSVD and related cognitive impairment This example provides an ELISA kit for early prediction or diagnosis of CSVD and its related cognitive impairment. The kit is designed to detect the levels of V-type proton ATPase subunits, large ribosomal subunit protein eL38, and heterogeneous ribonucleoprotein U in the urine or blood of a subject, thereby achieving accurate diagnosis of CSVD and its related cognitive impairment.

[0099] 1. Kit composition: a) ELISA analysis of V-type proton ATPase subunit (ATP6V1F): Includes reagents and materials such as antibodies, standards, substrates, and wash buffers for detecting V-type proton ATPase subunits.

[0100] Used to detect the level of V-type proton ATPase subunits in the subject's urine or blood, and perform quantitative analysis based on the standard curve.

[0101] b) ELISA analysis of large ribosomal subunit protein eL38 (RPL38): Includes reagents and materials such as antibodies, standards, substrates, washing buffer, etc. for detecting large ribosomal subunit protein eL38.

[0102] Used to detect the level of large ribosomal subunit protein eL38 in the subject's urine or blood, and perform quantitative analysis based on the standard curve.

[0103] c) Heterogeneous nuclear ribonucleoprotein U (HNRNPU) ELISA analysis: Includes reagents and materials such as antibodies, standards, substrates, and wash buffers for detecting heterogeneous ribonucleoprotein U.

[0104] Used to detect the level of heterogeneous ribonucleoprotein U in the urine or blood of the subject and perform quantitative analysis based on the standard curve.

[0105] 2. The testing process can be as follows: Take the subject's urine or blood sample and perform specimen processing and pretreatment steps according to the kit instructions.

[0106] The pretreated samples were added to the respective ELISA plate wells and reacted specifically with antibodies against the V-type proton ATPase subunit, the large ribosomal subunit protein eL38, and the heterogeneous ribonucleoprotein U.

[0107] Wash the plate with wash buffer to remove unbound material.

[0108] A substrate is added and the reaction is allowed to proceed under appropriate conditions to produce a measurable color.

[0109] The absorbance of the reaction product was measured using a microplate reader, and the contents of v-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U in the sample were calculated based on the standard curve.

[0110] Based on the levels of each marker and combined with the preset diagnostic criteria, the progression of subjects' cerebral small vessel disease and related cognitive impairment was assessed.

[0111] The embodiment described above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Persons skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent substitution or equivalent transformation falls within the scope of protection of the present invention.

[0112] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0114] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with this profession can make slight changes or modifications to equivalent embodiments of the methods and technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A combination of exosomal protein markers for cerebral small vessel disease and related cognitive impairment, characterized in that: The exosomal protein marker combination is any one of the v-type proton ATPase subunit, the large ribosomal subunit protein eL38 and the heterogeneous ribonucleoprotein U, or a combination of any two or three markers.

2. The exosome protein marker combination according to claim 1, characterized in that The exosome protein marker combination is a combination of three markers: V-type proton ATPase subunit, large ribosomal subunit protein eL38 and heterogeneous ribonucleoprotein U.

3. The exosome protein marker combination according to claim 1 or 2, characterized in that: The exosomal protein markers are derived from the urine or blood of the subject.

4. Use of a reagent for detecting the exosomal protein marker combination according to any one of claims 1 to 3 in the preparation of any of the following products: (1) Early diagnosis products for cerebral small vessel disease and related cognitive impairment; (2) Screening products for cerebral small vessel disease and related cognitive impairment; (3) Risk assessment products for cerebral small vessel disease and related cognitive impairment; or (4) Prognostic assessment products for cerebral small vessel disease and related cognitive impairment.

5. The use according to claim 4, characterized in that The reagent is an antibody for the exosome protein marker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis; The product is a chip, a test kit, a test paper or an analysis platform.

6. A kit for treating cerebral small vessel disease and related cognitive impairment, characterized in that: Comprising a reagent for detecting the exosome protein marker according to any one of claims 1 to 3, optionally, the detection is a quantitative detection of the level of the exosome protein marker in the urine or plasma of the subject.

7. The kit according to claim 6, characterized in that The reagent is an antibody to the exosome protein marker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis.

8. The kit according to claim 6, characterized in that The kit is an ELISA kit.

9. A method for evaluating whether a drug can prevent or treat cerebral small vessel disease and related cognitive impairment, characterized in that: This includes using any one, any two, or any three of the v-type proton ATPase subunit, the large ribosomal subunit protein eL38, and the heterogeneous ribonucleoprotein U as exosomal protein markers to evaluate the effect of the drug.

10. A method for screening compounds capable of preventing or treating cerebral small vessel disease and related cognitive impairment, characterized in that: The effects of the compounds were evaluated using any one, any two, or any three of the v-type proton ATPase subunit, the large ribosomal subunit protein eL38, and the heterogeneous ribonucleoprotein U as exosomal protein markers.

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