A serum pretreatment agent and its application and in vitro amplification method of alpha-synuclein body

Abstract

The present invention relates to the field of blood sample processing, and in particular to a serum pretreatment agent and its application and an in vitro amplification method of α-synuclein bodies. The present invention provides a serum pretreatment agent, which can effectively separate lipoproteins and pathological αSyn aggregates in serum, and remove interfering substances (such as lipoproteins) in serum. The serum pretreatment agent reduces serum viscosity, making it easy for lipoproteins with lower density to separate from αSyn seeds, effectively reducing its interference with subsequent detection, and then the serum sample treated with the serum pretreatment agent is subjected to RT-QuIC detection, which can accurately distinguish healthy people from patients with neurodegenerative diseases. Therefore, the serum pretreatment agent provided by the present invention can be used to prepare products for early diagnosis of neurodegenerative diseases.

Description

Technical Field

[0001] The invention relates to the field of blood sample processing, in particular to a serum pretreatment agent and application thereof and an in vitro amplification method of alpha-synuclein bodies. Background Art

[0002] α-Synuclein (αSyn) is a core marker for Parkinson's disease (PD), multiple system atrophy (MSA) and dementia with Lewy bodies (DLB), which are collectively referred to as α-synuclein spectrum disorders. Due to the complex and diverse clinical symptoms of these diseases, it is difficult to accurately diagnose them based solely on the patient's clinical manifestations, signs and routine assessments.

[0003] At present, most methods for detecting αSyn are based on the principle of antigen-antibody binding, such as chemiluminescence, ELISA, electrochemiluminescence immunoassay, etc. Although these methods can reach the nanogram level of sensitivity, their specificity is low, and they mainly target αSyn monomers and cannot effectively detect αSyn aggregates with pathological activity. Therefore, the specificity of antibody detection is poor. Although studies have shown that specific antibodies can recognize oligomers and fibrils of αSyn, their sensitivity and repeatability need to be further verified.

[0004] In recent years, emerging technologies such as protein misfolding cyclic amplification (PMCA) and real-time fluorescence oscillation-induced conversion assay (RT-QuiC) have been widely used to detect ultra-trace isomeric proteins as part of the α-synuclein seed amplification method. These technologies cyclically amplify the misfolding process of proteins through a prion-like seeding / nucleation mechanism, thereby effectively amplifying trace amounts of pathological αSyn oligomers and polymers for accurate diagnosis of α-synuclein spectrum diseases. During the detection process, the aggregation dynamics of αSyn is monitored by thioflavin T (ThT), a fluorescent dye that specifically binds to amyloid fibrils. Studies have shown that abnormal deposition of αSyn is not only present in the central nervous system, but can also be found in body fluids and peripheral tissues, including blood, cerebrospinal fluid, olfactory mucosa, skin, salivary glands, retina, adrenal medulla, heart and gastrointestinal tract. Pathological diagnosis of Parkinson's disease can be achieved by detecting αSyn in body fluids or peripheral tissues.

[0005] Currently, serum testing is one of the simplest screening methods, but direct application of amplification technology (such as RT-QuIC) to detect pathological αSyn in serum samples has not achieved ideal results. The reasons for this failure of testing may involve multiple aspects, mainly including the following:

[0006] 1. The content of pathological αSyn seeds is extremely low: In serum samples, the content of pathological αSyn is very trace, below the detection limit of the amplification technology, which significantly limits the amplification efficiency; 2. Inhibitory components exist in serum: Various components in the blood (such as lipids, proteins, etc.) have the ability to inhibit amplification reactions such as RT-QuIC. These inhibitory components will interfere with the amplification process and further reduce the detection sensitivity; without removing these inhibitory components, the amplification reaction is difficult to proceed smoothly and pathological αSyn cannot be effectively detected.

[0007] To overcome these technical challenges, some existing solutions attempt to enrich pathological αSyn in serum and remove inhibitory components through antigen-antibody methods. However, these methods have the following drawbacks:

[0008] 1. Complex experimental operation: Antigen-antibody reaction requires multiple steps, and the experimental process is cumbersome and time-consuming, which increases the possibility of experimental errors; 2. High antibody cost: High-quality antibodies are expensive, which limits the large-scale promotion and popularization of such methods.

[0009] Therefore, there is an urgent need for a preparation that can effectively remove inhibitory components in blood samples to reduce costs and error rates. Summary of the invention

[0010] The purpose of the present invention is to provide a serum pretreatment agent and its application and an in vitro amplification method of α-synuclein bodies to solve the problems existing in the above-mentioned prior art. The present invention provides a serum pretreatment agent, which can be used for preliminary separation of lipoproteins and pathological αSyn aggregates in serum, can effectively reduce costs, and will not affect the test results.

[0011] To achieve the above object, the present invention provides the following solutions:

[0012] The present invention provides a serum pretreatment agent, comprising a serum pretreatment agent 1 and a serum pretreatment agent 2;

[0013] The serum pretreatment agent 1 comprises the following components: 1×PBS buffer, 0.02wt.% sodium azide, 10-25mM 4-hydroxyethylpiperazineethanesulfonic acid, 0.1-1mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail;

[0014] The serum pretreatment agent 2 includes the following components: 1×PBS buffer, 0.02 wt.% sodium azide, 0.1-1 mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail.

[0015] Preferably, the pH of the serum pretreatment agent 1 is 7.2; this pH is close to physiological pH and is suitable for the physiological environment of most cells and proteins;

[0016] The pH of the serum pretreatment agent 2 is 6.0.

[0017] The present invention provides the use of the serum pretreatment agent in preparing a product for early diagnosis of neurodegenerative diseases.

[0018] Preferably, the product includes a detection reagent, a detection kit and a detection chip.

[0019] Preferably, the neurodegenerative diseases include Parkinson's disease, multiple system atrophy and dementia with Lewy bodies.

[0020] The present invention provides a product for early diagnosis of neurodegenerative diseases, which comprises the above-mentioned serum pretreatment agent.

[0021] Preferably, the product includes a detection reagent, a detection kit and a detection chip.

[0022] Preferably, the neurodegenerative diseases include Parkinson's disease, multiple system atrophy and dementia with Lewy bodies.

[0023] The present invention provides an in vitro amplification method of α-synuclein bodies for non-diagnostic and / or therapeutic purposes, comprising the following steps:

[0024] After mixing the serum pretreatment agent 1 and the serum sample to be tested, a first centrifugation is performed to obtain a first centrifugation product; the serum pretreatment agent 1 comprises the following components: 1×PBS buffer, 0.02wt.% sodium azide, 0.5-2.0wt.% 4-hydroxyethylpiperazineethanesulfonic acid, 0.1-1mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail;

[0025] The first centrifuged product and serum pretreatment agent 2 are mixed, and then subjected to a second centrifugation and inactivation to obtain a product to be tested; the serum pretreatment agent 2 comprises the following components: 1×PBS buffer, 0.02wt.% sodium azide, 0.1-1mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail;

[0026] The product to be tested is subjected to RT-QuIC detection.

[0027] Preferably, the RT-QuIC detection system includes: 0.1 mg / mL mouse αSyn monomer, 10% sodium sulfate, 20 mM Thioflavin T, 40 mM NaCl and 15 mM Tris; the RT-QuIC detection temperature is 50° C., and the oscillation mode is oscillation for 1 min and rest for 14 min.

[0028] In the first centrifugation process of the present invention, low-density lipoproteins (such as low-density lipoproteins (LDL)) have been removed, but some high-density lipoproteins (HDL) remain; in order to further process the sample, the pH of the serum sample pretreatment solution 2 can be set to 6.0, so that the sample is incubated under pH 6.0 conditions, at which time the apolipoproteins undergo conformational changes and unfold, resulting in the release of lipid-deficient apoA-I and free lipids. Since lipids are insoluble in water, free lipids are more easily separated from water-soluble components by centrifugation, thereby achieving more effective lipid removal.

[0029] The present invention discloses the following technical effects:

[0030] The present invention provides a serum pretreatment agent, which can effectively separate lipoproteins and pathological αSyn aggregates in serum and remove interfering substances (such as lipoproteins) in serum. The serum pretreatment agent reduces serum viscosity, making it easy for lipoproteins with lower density to separate from αSyn seeds, effectively reducing their interference with subsequent detection. After that, RT-QuIC detection is performed on serum samples treated with the serum pretreatment agent, which can accurately distinguish healthy people from patients with neurodegenerative diseases. Therefore, the serum pretreatment agent provided by the present invention can be used to prepare products for early diagnosis of neurodegenerative diseases.

[0031] αSyn is a protein mainly located in the central nervous system and is widely present in the presynaptic terminals of nerve cells. Under normal circumstances, the αSyn monomer structure is loose and harmless, but under pathological conditions, αSyn will fold abnormally and gradually form toxic amyloid fibers. This pathological αSyn aggregate not only has a destructive effect on nerve cells, but also can induce other normal αSyn monomers to aggregate to form self-replicating "seeds", similar to the characteristics of prion-like proteins. This abnormal aggregation process plays an important role in neurodegenerative diseases such as Parkinson's disease. The traditional RT-QuIC method can be used to detect αSyn aggregation, but the presence of inhibitory components such as lipoproteins in serum samples will interfere with the detection reaction and reduce the sensitivity and specificity of the detection. Therefore, the present invention provides an in vitro amplification method for α-synuclein bodies, which significantly improves the detection performance of RT-QuIC by improving the following aspects:

[0032] 1. Optimize the serum sample preparation process:

[0033] 1.1. Use of serum pretreatment agent: The present invention introduces a special serum pretreatment agent for preliminary separation of lipoproteins and pathological αSyn aggregates in serum. The serum pretreatment agent reduces serum viscosity, making it easier for lipoproteins with lower density to separate from αSyn seeds, effectively reducing their interference with subsequent detection.

[0034] 1.2. Multiple centrifugation and precise pH control: Lipoproteins and pathological αSyn aggregates are further separated by two high-speed centrifugations and precise pH control. This method is more effective in removing lipoproteins and other impurities with lower density than single centrifugation. The present invention evaluates the removal effect of lipoproteins by adjusting different pH values ​​(5.2, 6.2, 7.2) and different centrifugation times. The results showed that under the conditions of pH 7.2 and one centrifugation, the removal effect of low-density lipoprotein (LDL) was the best, with a reduction of about 80%, while high-density lipoprotein cholesterol (HDL) was reduced by only 20%; in order to further improve the removal efficiency of HDL, a second centrifugation was performed and the pH was adjusted to 5.0, 6.0 and 7.2. It was finally found that under the conditions of pH 6.0 and two centrifugations, the LDL content dropped to 10% before centrifugation, and HDL was significantly reduced by 70%. In summary, precise adjustment of pH and number of centrifugation times can effectively remove different types of lipoproteins in stages. The initial centrifugation is suitable for removing LDL, while the secondary centrifugation significantly improves the HDL removal efficiency, avoids the problem of low detection positivity rate, and can better enrich pathological αSyn aggregates, thereby improving the sensitivity of detection.

[0035] 1.3. Sample heating to inactivate impurity proteins: Given that αSyn has a strong tolerance to high temperatures and will not denature or lose biological activity under high temperature conditions, we heated the centrifuged product at 70°C for 5 minutes to effectively inactivate the biological activity of other proteins.

[0036] 2. Optimization of RT-QuIC conditions for aggregation reaction:

[0037] 2.1. Temperature optimization: RT-QuIC needs to be performed at a specific temperature. The present invention optimizes the incubation temperature of the RT-QuIC reaction. In the prior art, the incubation temperature of RT-QuIC is usually between 30°C and 42°C. The present invention increases the incubation temperature to 50°C, which can effectively reduce the effect of impurity proteins on the formation of pathological αSyn aggregates, making the reaction more specific and rapid.

[0038] 2.2. Adding sodium sulfate: Sodium sulfate completely dissociates into ions in aqueous solution, increasing the ionic strength in the amplification system, which can significantly accelerate the aggregation reaction of αSyn.

[0039] 2.3 Application of Thioflavin T (ThT) in fluorescence signal monitoring: ThT is a fluorescent dye that binds to the β-folded structure of amyloid fibers. When pathological αSyn aggregates to form amyloid fibers, ThT binds to them and emits a fluorescent signal. By real-time monitoring of the changes in fluorescence intensity, the occurrence and progress of the aggregation reaction can be accurately determined.

[0040] Compared with the prior art, the present invention also has the following advantages:

[0041] 1. Simplified operation process: Compared with the antigen-antibody enrichment method, the present invention adopts a simplified sample processing process and reduces costs. The lipid centrifugation method removes the interference of lipoproteins in serum, making the detection steps more intuitive and easy to operate, suitable for promotion and application in various laboratory environments, and has low requirements for equipment and technicians. It can be seen that the method provided by the present invention has the advantages of simple and fast operation steps and reduced experimental complexity and time cost.

[0042] 2. Reduce detection costs: The present invention significantly reduces the amount of raw materials and reagents required for the experiment, optimizes the process flow, reduces energy consumption and experimental costs, does not require expensive antibodies, greatly reduces the economic cost of detection, and improves the scalability of the technology. At the same time, the simplified operation steps of the present invention shorten the detection cycle, making the technology economical and efficient, and can be widely used in the early diagnosis of neurodegenerative diseases such as Parkinson's disease.

[0043] 3. Improve detection sensitivity: The present invention significantly improves the detection ability of pathological αSyn seeds by removing inhibitory components and enriching αSyn seeds.

[0044] 4. Rapid detection: By optimizing the aggregation reaction conditions, the present invention significantly shortens the reaction time of RT-QuIC from the traditional 72h-168h to less than 24h. This improvement speeds up the detection speed, provides a fast and reliable tool for clinical applications, greatly improves the diagnostic efficiency, and meets the needs of disease screening.

[0045] 5. Improvement of pollution control and sample processing: The present invention successfully separated lipoproteins that inhibit αSyn aggregation in serum by developing a lipid centrifugation method, thereby overcoming the inhibitory effect of complex components in serum on detection. This innovative method effectively reduces interfering components in the sample, ensures the reliability and repeatability of the detection, improves the errors that may be caused during sample processing, and significantly improves the detection quality.

[0046] In summary, the present invention optimizes the RT-QuIC detection method based on an in-depth study of the aggregation characteristics of αSyn, and provides an efficient and accurate means for detecting pathological αSyn in serum samples. By removing interference, enriching pathological seeds and optimizing aggregation reactions through lipid centrifugation, the present invention not only improves the accuracy and sensitivity of detection, but also simplifies the operating procedures, making it more suitable for rapid clinical screening and early diagnosis. It can be seen that the present invention provides a simple, economical and efficient method for detecting serum pathological αSyn, which is expected to become an effective tool for the early diagnosis of neurodegenerative diseases (such as Parkinson's disease, etc.). This groundbreaking technology provides a new diagnostic tool for the early detection and intervention of neurodegenerative diseases such as Parkinson's disease. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 It is a temperature screening diagram for RT-QuIC detection; A is the amplification curve of 35℃-60℃; B is the statistical diagram of amplification efficiency;

[0049] Figure 2 It is a screening diagram of additives for RT-QuIC detection; A is the effect of different additives on the amplification efficiency of pathological αSyn; B is a statistical diagram of amplification efficiency;

[0050] Figure 3 The amplification curves of pathological αSyn in the same PD serum sample under different oscillation modes;

[0051] Figure 4 The effect of the residual chemical reagents used in the method provided by the present invention and the chloroform-methanol method on the reaction; wherein, this scheme is the method provided by the present invention, and chloroform-methanol is the chloroform-methanol method;

[0052] Figure 5 The results of αSyn Seed Amplification Assay in lipid-free serum samples;

[0053] Figure 6 Comparison of protein aggregation efficiency of HC and PD in lipid-free serum samples;

[0054] Figure 7 is the receiver operating curve;

[0055] Figure 8Schematic diagram of the processing and centrifugation process of serum samples; wherein the first diluent is serum sample pretreatment agent 1, and the second diluent is serum pretreatment agent 2;

[0056] Fig. 9 The amplification efficiency of the method provided by the present invention is compared with that of traditional RT-QuIC. DETAILED DESCRIPTION

[0057] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0058] It should be understood that the terms described in the present invention are only for describing a particular embodiment and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. The intermediate value in any stated value or stated range, and each smaller range between any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0059] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0060] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present invention description and examples are exemplary only.

[0061] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0062] The effects of the material used in the present invention are as follows:

[0063] 1. Microplate reader: used to observe and record the aggregation process of αSyn; the FITC channel in the fluorescence microscope is used to detect the fluorescence signal after thioflavin T (ThT) binds to pathological αSyn; the occurrence of aggregation and fiber formation are observed in real time under a microscope.

[0064] 2. PBS (phosphate buffered saline): As a basic buffer solution, it maintains the ionic strength and stability of the solution.

[0065] 3. NaN3 (sodium azide): used as a preservative to prevent the growth of bacteria or other microorganisms.

[0066] 4. 4-Hydroxyethylpiperazineethanesulfonic acid (HEPES): used to provide stable buffering capacity and can maintain the stability of the solution under conditions close to physiological pH.

[0067] 5. Protease inhibitor PMSF: used to inhibit the activity of serine proteases in samples and prevent protein degradation.

[0068] 6. Protein Inhibitor Cocktail: Contains a variety of broad-spectrum protease inhibitors to prevent various types of proteases (such as cysteine, metalloproteinases, etc.) in the sample from degrading the target protein.

[0069] 7. αSyn substrate: As the key substrate in the RT-QuIC reaction, αSyn monomers will rapidly aggregate in the presence of pathological αSyn aggregates, simulating the aggregation process in vivo.

[0070] 9. Human protein preformed fibers (hPFFs): hPFFs are aggregates of artificial αSyn and serve as a positive control for RT-QuIC reactions.

[0071] 10. Sodium sulfate (SS): Sodium sulfate acts as a promoter for RT-QuIC reaction, accelerating the aggregation of pathological αSyn by increasing the ionic strength of the solution environment.

[0072] 11. Thioflavin T (ThT): ThT is a fluorescent probe that can bind to the β-folded structure of amyloid fibers. During the detection process, after ThT binds to αSyn aggregates, it will emit fluorescence, indicating the occurrence of the aggregation process.

[0073] 12. Centrifuge: used to separate lipids and pathological αSyn aggregates in serum. High centrifugal force (14,000g) can effectively remove interfering substances and purify pathological αSyn.

[0074] 13. Sterile pipettes and test tubes: used to accurately transfer samples and reagents, avoid cross contamination, and ensure the accuracy of the sample processing process.

[0075] Example 1 Optimization of sample pretreatment agent components

[0076] 1. Setting of serum sample pretreatment agent components

[0077] Different combinations of serum sample pretreatment agents were designed, as shown in Table 1.

[0078] Table 1 Combinations of different serum sample pretreatment agents

[0079]

[0080] Note: After purchase, the protein inhibitor Protease Inhibitor Cocktail needs to be diluted at a volume ratio of 1:100 before use.

[0081] 2. Experimental design

[0082] See the process for details Figure 8 , the specific steps are:

[0083] 2.1. Blood collection

[0084] 1) Signing the informed consent form: Ensure that all participants understand the purpose and process of the experiment and sign the relevant consent form.

[0085] 2) Preparation of items: prepare blood collection needles, vacuum blood collection tubes and dry ice.

[0086] 3) Personal protection: wash hands, wear mask and headgear.

[0087] 4) Blood collection: Use a blood collection needle to collect a blood sample and place it in a collection tube containing an appropriate amount of anticoagulant.

[0088] 5) Mixing: Invert the blood collection tube repeatedly to ensure that the anticoagulant and blood are fully mixed.

[0089] 6) Centrifugation: Centrifuge at 2500 rpm for 10 min (Note: blood samples should be centrifuged within 1 h at room temperature after collection) to further remove lipoproteins and purify pathological αSyn aggregates; then carefully extract 100 μL of the lower layer of the centrifuge tube to ensure that no precipitate is mixed in. After centrifugation, the supernatant is the serum sample.

[0090] 7) Storage: Store serum samples in a -80°C refrigerator.

[0091] 2.2. Serum sample pretreatment and storage

[0092] 1) Sample dilution: 200 μL of serum sample (serum sample obtained in step 2.1) was thoroughly mixed with an equal volume of serum sample pretreatment agent 1 and allowed to stand at room temperature for 5 min; wherein the components and pH of each serum sample pretreatment agent 1 are shown in Table 1.

[0093] 2) Initial centrifugation: Centrifuge at 14,000 g for 30 min at room temperature.

[0094] 3) Sampling: After centrifugation, carefully extract 100 μL of the lower layer of the centrifuge tube using a sterile pipette to avoid stirring. Transfer this liquid to a new sterile test tube and mix it with another 100 μL of serum sample pretreatment agent 2. Let it stand at room temperature for 5 minutes to make the total volume reach 200 μL; wherein, the components and pH of each serum sample pretreatment agent 2 are shown in Table 1.

[0095] 4) Second centrifugation: Centrifuge again at 14,000 g for 30 min at room temperature.

[0096] 5) Final sampling: Carefully extract 100 μL of the lower layer of the centrifuge tube to ensure that no floating impurities are mixed in. Aliquot the sample to be tested; at the same time, heat the lower layer of the centrifuge tube at 70°C for 5 minutes to effectively inactivate the biological activity of other proteins.

[0097] 6) Sample processing: The pH of the collected samples was adjusted to 7.5 to obtain pre-treated serum samples, which were immediately used for RT-QuiC analysis or stored in a -80°C refrigerator.

[0098] 2.3 RT-QuIC detection

[0099] 1) Prepare the reaction system in a 384-well plate and add 45 μL of reaction solution to each well, including 0.1 mg / mL mouse αSyn monomer (produced independently after bacterial prokaryotic expression and purification), 10% sodium sulfate, 20 mM Thioflavin T (ThT), 40 mM NaCl, and 15 mM Tris (pH 6.8).

[0100] 2) Add 5 μL of pretreated serum sample to each reaction well and set up 4 replicate wells. Shake the reaction at 50°C, usually at a shaking speed of 500 rpm, shake for 1 minute and rest for 14 minutes, for 16-24 hours; hPFFs (produced independently by shaking 5 mg / mL mouse αSyn monomer at room temperature for 7 days) were used as positive controls.

[0101] 3) Regularly detect the fluorescence intensity and record the changes in fluorescence intensity to evaluate the pathological αSyn aggregation. Specifically, the instrument will regularly detect the fluorescence signal intensity in each reaction well at a set time interval (every 30 minutes); the microplate reader will automatically record the changes in the fluorescence signal and store the fluorescence intensity data at each time point in the experimental software; as αSyn aggregates are formed, the fluorescence signal will gradually increase to generate a dynamic fluorescence curve; by monitoring the changes in fluorescence intensity over time, the aggregation process can be evaluated; a typical amplification curve includes a lag phase, an exponential phase, and a plateau phase; the length of the lag phase and the rate of increase in fluorescence intensity can reflect the presence and concentration of pathological αSyn seeds in the sample, an earlier increase in fluorescence represents a higher seed concentration, and vice versa, a lower concentration; by analyzing the fluorescence intensity change curves of different samples, the pathological αSyn aggregation can be evaluated.

[0102] 4) By measuring the intensity of the fluorescence signal and comparing it with the time to reach the threshold (the threshold time in this example is: 9h), it is determined whether there are pathological αSyn aggregates in the sample. In actual experiments, researchers set a fixed fluorescence threshold intensity (such as 10 times the background fluorescence) and record the time when the sample reaches the fluorescence value; assuming that the positive threshold time is set to 12h, it means that samples that reach the fluorescence threshold within 12h are considered positive, and samples that have not reached the fluorescence threshold after more than 12h are negative.

[0103] 3. Results Analysis

[0104] The test results of different serum sample pretreatment agent combinations are shown in Table 2. The results show that the serum sample pretreatment agent combination No. 1 has the best effect. Therefore, the subsequent experiments are to study the concentration of each component in the serum sample pretreatment agent combination No. 1.

[0105] Table 2 Detection results of different serum sample pretreatment agent combinations

[0106] serial number Test results 1 Positive (time to threshold 7.5 hours) 2 Positive (time to threshold 8.5 hours) 3 Negative 4 Negative 5 Negative 6 Positive (time to reach threshold 8 hours)

[0107] Example 2 Optimization of the concentration of each component in the sample pretreatment agent

[0108] 1. Setting the concentration of each component of serum sample pretreatment agent

[0109] Different combinations of serum sample pretreatment agents were designed, as shown in Table 3.

[0110] Table 3 Combinations of different serum sample pretreatment agents

[0111]

[0112]

[0113] 2. Experimental design

[0114] Same as Example 1.

[0115] 3. Results Analysis

[0116] The test results of different combinations of serum sample pretreatment agents are shown in Table 4. The results show that the pretreatment agent combination No. 1 has the best effect. Therefore, the concentration of PBS buffer in serum sample pretreatment agent 1 is set to 1×, the concentration of NaN3 is set to 0.02wt.%, the concentration of 4-hydroxyethylpiperazineethanesulfonic acid (HEPES) is set to 10-25mM, the concentration of protease inhibitor PMSF is set to 0.1-1mM, and the concentration of protein inhibitor Protease Inhibitor Cocktail is set to 1×; the concentration of PBS buffer in serum sample pretreatment agent 2 is set to 1×, the concentration of NaN3 is set to 0.02wt.%, the concentration of protease inhibitor PMSF is set to 0.1-1mM, and the concentration of protein inhibitor Protease Inhibitor Cocktail is set to 1×.

[0117] Table 4 Detection results of different serum sample pretreatment agent combinations

[0118] serial number Test results 1 Positive (time to threshold 7.2 hours) 2 Positive (time to threshold 8.5 hours) 3 Positive (time to threshold 8.8 hours) 4 Positive (time to threshold 8.2 hours) 5 Positive (time to threshold 8.5 hours) 6 Negative

[0119] Example 3 Optimization of sample pretreatment pH and centrifugation times

[0120] 1. Setting the pH of serum sample pretreatment agent

[0121] A combination of serum sample pretreatment agents with different pH values ​​was designed, wherein the components of serum sample pretreatment agent 1 were: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 25mM 4-hydroxyethylpiperazineethanesulfonic acid (HEPES), 1mM protease inhibitor PMSF, and 1× protein inhibitor Protease Inhibitor Cocktail; the components of serum sample pretreatment agent 2 were: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 1mM protease inhibitor PMSF, and 1× protein inhibitor Protease Inhibitor Cocktail. The specific pH values ​​of the serum sample pretreatment agents are shown in Table 5.

[0122] Table 5 Combinations of different serum sample pretreatment agents

[0123]

[0124] 2. Experimental design

[0125] The experimental steps were the same as "2.1. Blood collection" and "2.2. Serum sample pretreatment and storage" in Example 1. Afterwards, the ELISA method was used to detect the content of low-density lipoprotein (LDL) and high-density lipoprotein (HDL) in the centrifuged samples.

[0126] 3. Results Analysis

[0127] This embodiment evaluates the removal effect of lipoprotein by adjusting different pH values ​​(5.2, 6.2, 7.2) and the number of centrifugation, and the results are shown in Table 6. The results show that under the conditions of pH 7.2 and centrifugation once, the removal effect of LDL is the best, reducing by about 80%, while HDL is reduced by only 20%. Although the removal efficiency of LDL is very high, the removal effect of HDL is relatively low. In order to further improve the removal efficiency of HDL, the present invention also performs secondary centrifugation and adjusts the pH to 6.0, 6.5 and 7.0, and detects again by ELISA. It was finally found that under the conditions of pH 6.0 and centrifugation twice, the lipoprotein removal efficiency is the best, the LDL content is reduced to 10% before centrifugation, and HDL is significantly reduced by 70%. It can be seen that accurately adjusting the pH value and the number of centrifugation can effectively remove different types of lipoproteins in stages. In summary, when the pH of serum sample pretreatment agent 1 is 7.2 and the pH of serum sample pretreatment agent 2 is 6.0, the effect is best. At the same time, the first centrifugation is suitable for removing LDL, while the second centrifugation significantly improves the efficiency of HDL removal, avoids the problem of low positive detection rate, and can better enrich pathological aggregates, thereby improving the sensitivity of detection. Compared with the single centrifugation method, the method of centrifuging the sample twice can more effectively remove lipoproteins and other low-density impurities.

[0128] Table 6 Test results of different serum sample pretreatment agent combinations and centrifugation times

[0129]

[0130]

[0131] Based on the results of Example 1 to Example 3, the concentration of PBS buffer in serum sample pretreatment agent 1 was set to 1×, the concentration of NaN3 was set to 0.02wt.%, the concentration of 4-hydroxyethylpiperazineethanesulfonic acid (HEPES) was set to 10-25mM, the concentration of protease inhibitor PMSF was set to 0.1-1mM, the concentration of protein inhibitor Protease Inhibitor Cocktail was set to 1×, and the pH was set to 7.2; the concentration of PBS buffer in serum sample pretreatment agent 2 was set to 1×, the concentration of NaN3 was set to 0.02wt.%, the concentration of protease inhibitor PMSF was set to 0.1-1mM, the concentration of protein inhibitor Protease Inhibitor Cocktail was set to 1×, and the pH was set to 6.0; the number of centrifugation times was set to 2 times.

[0132] Example 4 Optimization of Monomer Types in RT-QuIC Detection

[0133] 1. Setting of serum sample pretreatment agent

[0134] The components of serum sample pretreatment agent 1 are: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 25mM 4-hydroxyethylpiperazineethanesulfonic acid (HEPES), 1mM protease inhibitor PMSF, 1× protein inhibitor Protease Inhibitor Cocktail, pH 7.2;

[0135] The components of serum sample pretreatment agent 2 are: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 1mM protease inhibitor PMSF, 1× protein inhibitor Protease Inhibitor Cocktail, pH 6.0.

[0136] 2. Experimental design

[0137] 2.1. Blood collection

[0138] Same as Example 1.

[0139] 2.2. Serum sample pretreatment and storage

[0140] Same as Example 1.

[0141] 2.3 RT-QuIC detection

[0142] Steps 2)-4) are the same as in Example 1, except that the monomers in step 1) are of the same species (mouse αSyn monomer, human αSyn monomer) and human αSyn monomers carrying αSyn mutation sites (carrying A53T and G51D mutations). The monomer preparation method refers to the document "Addition of exogenous alpha-synuclein preformed fibrils toprimary neuronal cultures to seed recruitment of endogenous alpha-synucleinto Lewy body and Lewy neurite-like aggregates" (Volpicelli-Daley LA, Luk KC, Lee VM. Addition of exogenous alpha-synuclein preformed fibrils to primaryneuronal cultures to seed recruitment of endogenous alpha-synuclein to Lewybody and Lewy neurite-like aggregates. Nat Protoc. 2014; 9(9): 2135-46.).

[0143] 3. Results Analysis

[0144] The test results under different monomers are shown in Table 7. The results show that the mouse-derived αSyn monomer has the highest amplification efficiency. This example determines that the mouse-derived αSyn monomer among these monomers is the best choice for serum seed amplification, and the specific reaction of the mouse-derived αSyn monomer with the serum sample significantly improves the amplification efficiency.

[0145] Table 7 Detection results of different monomers

[0146]

[0147] Example 5 Optimization of temperature in RT-QuIC detection

[0148] 1. Setting of serum sample pretreatment agent

[0149] Same as Example 4.

[0150] 2. Experimental design

[0151] 2.1. Blood collection

[0152] Same as Example 1.

[0153] 2.2. Serum sample pretreatment and storage

[0154] Same as Example 1.

[0155] 2.3 RT-QuIC detection

[0156] Steps 1), 3) and 4) are the same as those in Example 1, except that step 2) is subjected to shaking reaction at different temperatures, specifically 35°C, 40°C, 45°C, 50°C, 55°C and 60°C.

[0157] 3. Results Analysis

[0158] The test results at different temperatures are as follows Figure 1 As shown. The results show that in the RT-QuIC detection experiment, the optimal reaction temperature of the amplification system was determined to be 50°C. This temperature not only significantly increases the rate of the chemical reaction, but also ensures the specificity of the experimental results, making the entire reaction process more efficient.

[0159] Example 6 Optimization of additives in RT-QuIC detection

[0160] 1. Setting of serum sample pretreatment agent

[0161] Same as Example 4.

[0162] 2. Experimental design

[0163] 2.1. Blood collection

[0164] Same as Example 1.

[0165] 2.2. Serum sample pretreatment and storage

[0166] Same as Example 1.

[0167] 2.3 RT-QuIC detection

[0168] Steps 2)-4) are the same as in Example 1, except that in step 1), 10% sodium sulfate is set to one of: 10% sodium sulfate, 10% ethanol, 5% glycerol, 5% PEG 400, 0.4% SDS, 0.4% Triton and 0.4% Tween, and the same volume of healthy human serum is used as a control (NC).

[0169] 3. Results Analysis

[0170] The test results under different additives are as follows Figure 2 As shown. The results show that the additive that can significantly improve the amplification efficiency is 10% sodium sulfate. The optimized additive not only speeds up the amplification reaction, but also ensures the high specificity and sensitivity of the RT-QuIC technology, providing more ideal conditions for the amplification system.

[0171] Example 7 Optimization of oscillation mode in RT-QuIC detection

[0172] 1. Setting of serum sample pretreatment agent

[0173] Same as Example 4.

[0174] 2. Experimental design

[0175] 2.1. Blood collection

[0176] Same as Example 1.

[0177] 2.2. Serum sample pretreatment and storage

[0178] Same as Example 1.

[0179] 2.3 RT-QuIC detection

[0180] Steps 1), 3) and 4) are the same as those in Example 1, except that step 2) is subjected to oscillation reaction under different oscillation modes, wherein the different oscillation modes are: oscillation for 1 min and rest for 14 min, oscillation for 5 min and rest for 10 min, or continuous oscillation for 15 min.

[0181] 3. Results Analysis

[0182] The test results under different oscillation modes are as follows: Figure 3 The results show that too long shaking time does not improve the aggregation efficiency, while the scheme of shaking for 1 minute and stopping for 14 minutes can effectively improve the aggregation efficiency and ensure the smooth progress of amplification.

[0183] The results of Examples 4 to 7 show that through comprehensive optimization of the above four aspects, the present invention significantly improves the sensitivity, specificity and stability of the amplification system, and develops an αSyn seed amplification detection method suitable for serum samples, namely the Serum Seed Amplification Assay (SAA).

[0184] Example 8 Comparison of the detection method provided by the present invention with the traditional lipoprotein removal method

[0185] The detection method provided by the present invention:

[0186] 1. Setting of serum sample pretreatment agent

[0187] The components of serum sample pretreatment agent 1 are: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 25mM 4-hydroxyethylpiperazineethanesulfonic acid (HEPES), 1mM protease inhibitor PMSF, 1× protein inhibitor Protease Inhibitor Cocktail, pH 7.2;

[0188] The components of serum sample pretreatment agent 2 are: 1× phosphate buffer (PBS buffer), 0.02wt.% sodium azide (NaN3), 1mM protease inhibitor PMSF, 1× protein inhibitor Protease Inhibitor Cocktail, pH 6.0.

[0189] 2. Experimental design

[0190] 2.1. Blood collection

[0191] As in Example 1, 105 serum samples from healthy subjects (HC) and 80 serum samples from patients with Kinson's disease (PD) were collected.

[0192] 2.2. Serum sample pretreatment and storage

[0193] Same as Example 1.

[0194] 2.3 RT-QuIC detection

[0195] Same as Example 1.

[0196] Traditional lipoprotein removal method: using chloroform-methanol mixed solvent method (Folch method), chloroform and methanol are mixed in a specific ratio (1:2), and the specific steps refer to the literature "A simple method for the isolation and purification of total lipides from animal tissues" (Folch J, Lees M, Sloane Stanley GH. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem. 1957; 226 (1): 497-509.).

[0197] Test results such as Figure 4It can be seen that although the chloroform-methanol mixed solvent method can effectively extract lipids from samples, it may cause changes in the physical and chemical properties of αSyn seeds. In addition, residual chemical reagents will seriously interfere with subsequent amplification experiments, resulting in the inability to effectively distinguish between healthy people and patients with Kinson's disease; the method provided by the present invention can effectively distinguish between healthy people and patients with Kinson's disease ( Figure 4 ).

[0198] Example 9 Clinical Data and αSyn SAA Results in Delipidated Serum Samples

[0199] 80 healthy subjects and 105 Parkinson's disease patients (PD patients) were collected from the First Affiliated Hospital of Guangzhou Medical University. Serum samples of all research subjects were collected. The specific steps were the same as "2. Experimental design" in Example 1. The optimal conditions screened by Examples 4 to 7 were used for RT-QuIC detection. The data of the research subjects are shown in Table 8. The results of RT-QuIC detection are shown in Tables 8 and Figure 5 As shown; at the same time, the protein aggregation efficiency of HC and PD in lipid-free serum samples was compared, and the results were as follows Figure 6 shown.

[0200] Table 8 Detailed information of the subjects and RT-QuIC test results

[0201] information PD (n=105) Healthy controls (n=80) Age, mean (SD) 65.3(9.7) 67.1(9.5) Gender, male (female) 55(50) 45(35) Duration of illness 5.9(4.46) NA HoehnandYahr Rating 2.7(0.94) NA UPDRSIII 34.6(20.6) NA SAA positive in lipid-free serum samples 87 5 Delipidated serum sample SAA negative 18 75 Sensitivity 82.28％ - Specificity 93.75％ -

[0202] Note: NA: not applicable; SAA: serum seed amplification assay.

[0203] According to clinical data and the results of αSyn SAA in lipid-free serum samples, the sensitivity and specificity of serum αSyn SAA detection are high: in patients with Parkinson's disease, the sensitivity of SAA detection is 82.28%, while the specificity is 93.75%. This shows that SAA detection has a high accuracy in distinguishing patients with Parkinson's disease from healthy controls. The results of serum αSyn SAA detection are helpful for the diagnosis of Parkinson's disease, especially when compared with healthy individuals, showing significant differences (Table 8 and Figure 5 ). In conclusion, αSyn SAA test in lipid-free serum samples is an effective biomarker that can be used for the diagnosis and differentiation of Parkinson's disease. Figure 6 It can be seen that the aggregation efficiency (protein aggregation rate) of pathological αSyn in the patient's serum is significantly higher than that in the control group, and the result is statistically significant.

[0204] At the same time, in order to evaluate the diagnostic performance of the RT-QuIC test provided by the present invention, the ROC (Receiver Operating Characteristic) curve was used to set thresholds according to different peak onset times, calculate the sensitivity and specificity, and generate the receiver operating characteristic curve. Figure 7 As shown. This method helps to determine the best diagnostic threshold to distinguish disease samples from control samples. The results show that the AUC of the RT-QuIC test method provided by the present invention reaches 0.8936, the sensitivity is 82.5%, and the specificity is 93.2%.

[0205] Example 9 Amplification efficiency of the detection method provided by the present invention and traditional RT-QuIC

[0206] The samples used in Example 8 were compared with the traditional RT-QuIC amplification method (reference "Seed amplication assay for the detection of pathologic alpha-synuclein aggregates in cerebrospinaluid") used in Example 8. After the same pretreatment, the amplification efficiency of pathological αSyn in the serum of Parkinson's disease patients (PD) and a control group (non-PD, healthy people) was compared. The results are as follows: Fig. 9 The results show that the time taken by this application is significantly shortened, from the traditional 72h-168h to less than 24h.

[0207] In summary, the serum sample pretreatment agent provided by the present invention can remove inhibitory components and enrich pathological αSyn seeds in serum without significantly changing the physicochemical properties of serum components. At the same time, combined with the RT-QuIC test method screened by the present invention, it can well distinguish healthy people from patients with neurodegenerative diseases, and it is more suitable for rapid clinical screening and early diagnosis. This breakthrough technology provides a new diagnostic tool for the early detection and intervention of neurodegenerative diseases such as Parkinson's disease.

[0208] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for in vitro amplification of α-synuclein bodies for non-diagnostic and / or therapeutic purposes, characterized in that: The following steps are involved: After mixing the serum pretreatment agent 1 and the serum sample to be tested, performing a first centrifugation to obtain a first centrifugation product; The serum pretreatment agent 1 comprises the following components: 1×PBS buffer, 0.02wt.% sodium azide, 10-25mM 4-hydroxyethylpiperazineethanesulfonic acid, 0.1-1mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail; The first centrifuged product and serum pretreatment agent 2 are mixed, and then subjected to a second centrifugation and inactivation to obtain a product to be tested; the serum pretreatment agent 2 comprises the following components: 1×PBS buffer, 0.02wt.% sodium azide, 0.1-1mM protease inhibitor PMSF and 1×protein inhibitor Protease Inhibitor Cocktail; The product to be tested is subjected to RT-QuIC detection.

2. The in vitro amplification method according to claim 1, characterized in that The RT-QuIC detection system includes: 0.1 mg / mL mouse αSyn monomer, 10% sodium sulfate, 20 mM Thioflavin T, 40 mM NaCl and 15 mM Tris; the RT-QuIC detection temperature is 50° C., and the shaking mode is shaking for 1 min and stopping for 14 min.

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