A combined detection kit for detecting Alzheimer's and its application

Abstract

The present invention discloses a combined detection kit for detecting Alzheimer's disease and its application, and discloses the application of at least two of Tau phosphorylated protein, blood protein or DNA molecular markers in detecting Alzheimer's disease. The beneficial effects of the present invention are as follows: The research and development of the kit based on non-invasive and easy-to-operate biomarkers such as blood, saliva and urine will provide more convenient and feasible early diagnosis measures. The present invention realizes the early diagnosis and screening of AD by detecting peripheral blood samples instead of invasive cerebrospinal fluid, and has good diagnosis at the stage of mild cognitive impairment. The combined detection technology of protein markers and molecular gene mutations in blood has excellent performance. Under the condition of 95% specificity, the diagnostic accuracy reaches more than 90%, far higher than the very rare single detection products of AD blood or urine on the market, filling the international gap. This detection system is reported for the first time internationally, and its technology and diagnostic performance reach the advanced level at home and abroad.

Description

Technical Field

[0001] The present invention belongs to the technical field of biomedicine, and particularly relates to a joint detection kit for detecting Alzheimer's disease and its application. Background Art

[0002] Alzheimer's disease (AD) is a chronic neurodegenerative disease of unknown cause. Its pathological changes are mainly manifested as the deposition of β-amyloid protein (Aβ) leading to senile plaques, abnormal phosphorylation of Tau protein leading to neurofibrillary tangles, and the loss of neurons and synapses. The clinical manifestations are progressive cognitive decline and non-cognitive neuropsychiatric symptoms.

[0003] In recent years, with the increasing attention to dementia in various countries, research on the early diagnosis, prevention and treatment of Alzheimer's disease has been reported. Although imaging techniques including magnetic resonance imaging, PET and tracers can be used to assist in the early diagnosis of AD, the detection cost is expensive, the requirements for detection personnel are high, and it cannot be used as a routine early detection method. Detecting Aβ and tau proteins through cerebrospinal fluid can also achieve a similar purpose, but it is an invasive examination, which causes great psychological burden and harm to patients, and is still difficult to be widely used in the early screening of AD. Therefore, an ideal biomarker detection should have the advantages of clear indication, low cost, and basically non-invasive, etc., and is convenient for a large number of clinical screenings.

[0004] Although there are many reports on the diagnosis of Alzheimer's disease through blood samples or urine tests, most of them focus on the detection of blood samples or urine tests around traditional cerebrospinal fluid markers such as Aβ42, total tau (t-tau) and phosphorylated tau (p-tau). There are few research reports on the discovery of new AD detection markers, and there are even fewer AD diagnostic products that have obtained corresponding medical device registration certificates and are on the market for sale.

[0005] Epidemiological investigations also show that the prevalence of Alzheimer's disease in the elderly population over 65 years old is about 4% - 8%. The prevalence in women is higher than that in men. With the increase of age, the prevalence of Alzheimer's disease gradually rises. For every 6.1-year increase in age, the prevalence doubles. After the age of 85, the prevalence of AD can be as high as 20% - 30%. In 2018, there were 50 million patients globally and 12 million patients in China, and it is growing rapidly at a rate of more than 300,000 new cases per year. It was found through research that a top-three hospital receives 2,000 - 3,000 suspected AD patients for diagnosis per month. At the end of 2019, the population aged 65 and above in China reached 176.03 million (about 176 million), an increase of 9.45 million compared with the previous year (about 167 million in 2018); accounting for 12.6% of the total population. The prevalence of Alzheimer's disease in the elderly population over 65 years old is about 4% - 8%. The number of people to be screened is large, so the market demand is huge.

[0006] At present, invasive cerebrospinal fluid detection is not accepted by most patients. There is no very good method on the market for accurate AD diagnosis. The use of peripheral markers for the early diagnosis of Alzheimer's disease has become increasingly popular and important among end physicians. The company's developed technology for the accurate diagnosis of AD through the combined detection of 7 protein markers based on blood meets the market demand and fills an international gap.

[0007] As of August 2021, there were very few Alzheimer's diagnostic kits listed in China. Among them, there were 3 diagnostic kit products based on the traditional enzyme-linked immunosorbent assay method from Shenzhen Anqun Biotech (related neurofilament protein (AD7C-NTP), beta-amyloid 1-42 (Aβ1-42), phosphorylated tau-181 protein), 1 diagnostic product related to neurofilament protein based on chemiluminescence method from Nanjing Norman, and 1 detection kit for urine beta-amyloid based on colloidal gold immunochromatography method from Hunan Qiankang.

[0008] The research and development of non-invasive and easy-to-operate biomarkers such as blood, saliva, and urine will provide more convenient and feasible early diagnosis measures. Evidence shows that about one-third of dementia can be prevented. Early diagnosis of dementia is very important and can greatly improve the success rate of disease-modifying therapies. Summary of the Invention

[0009] The main purpose of this application is to provide an Alzheimer's combined detection kit, including combined detection in both the immunological and molecular dimensions. By detecting peripheral blood samples instead of invasive cerebrospinal fluid, it realizes the early diagnosis and screening of AD. The combined detection technology of protein markers and molecular gene mutations in blood has excellent performance. Under the condition of 95% specificity, its diagnostic accuracy reaches over 90%, far higher than the very rare single detection products of AD blood or urine on the market (such as beta-amyloid (1-42), Alzheimer's related neurofilament protein (AD7C-NTP), total tau protein, etc.), filling an international gap. This detection system was first reported internationally, and its technology and diagnostic performance have reached the advanced level at home and abroad.

[0010] To achieve the above object, the present invention provides the following technical solution:

[0011] Application of at least two of Tau phosphorylated protein, blood protein or DNA molecular marker in the detection of Alzheimer's disease.

[0012] For the above application, as a preferred embodiment, the Tau phosphorylated protein is at least one of: P-TAU 181, P-TAU 231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404 or P-TAU 205.

[0013] P-TAU 181: Phosphorylation of tau protein at threonine 181 site;

[0014] P-TAU 231: Phosphorylation of tau protein at threonine 231 site;

[0015] P-TAU 217: Phosphorylation of tau protein at threonine 217 site;

[0016] P-TAU 199: Phosphorylation of tau protein at threonine 199 site;

[0017] P-TAU 202: Phosphorylation of tau protein at threonine 202 site;

[0018] P-TAU 404: Phosphorylation of tau protein at threonine 404 site;

[0019] P-TAU 205: Phosphorylation of tau protein at threonine 231 site.

[0020] In the above-mentioned application, as a preferred embodiment, the blood protein is at least one of alpha-synuclein, brain-derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), or neurogenic differentiation protein 6 (NEUROD6).

[0021] In the above-mentioned application, as a preferred embodiment, the DNA molecular marker is at least one of presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP).

[0022] Early diagnosis and screening of AD are achieved by detecting peripheral blood samples instead of invasive cerebrospinal fluid. The performance of the combined detection technology of protein markers and molecular gene mutations in blood is excellent. Detection and diagnosis in both molecular and immune dimensions can greatly improve the accuracy of Alzheimer's diagnosis.

[0023] In the second aspect of the present application, a detection method for Alzheimer's disease is provided, including the following steps:

[0024] (1) Detect at least two of the concentrations of Tau phosphorylated protein, blood protein, or DNA molecular marker in the sample;

[0025] (2) Perform logistic regression or support vector machine (SVM) analysis algorithm on the marker concentrations measured in the sample to establish a calculation model.

[0026] The logistic regression equation is as follows:

[0027]

[0028] Where Logit(P) is the result of the logistic regression model of Alzheimer's markers;

[0029] C is the natural constant obtained by regression;

[0030] α is the coefficient of each marker obtained by regression analysis;

[0031] The concentration of marker i is the concentration of each protein marker, and n is an integer greater than or equal to 2. Support vector machines is a binary classification model that finds a hyperplane to divide the data into one class and other classes, with the largest separation margin, which is different from the perceptron. The present invention uses Python or R language programming and calls relevant data packets for analysis and model construction.

[0032] For the above detection method of Alzheimer's disease, as a preferred embodiment, in step (1), the sample is: tissue, cerebrospinal fluid, blood, urine, saliva or feces of a human or animal body; the Tau phosphorylated protein is at least one of P-TAU 181, P-TAU 231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404 or P-TAU 205; the blood protein is at least one of α-synuclein, brain-derived neurotrophic factor, glial fibrillary acidic protein, neurofilament light chain or neurogenic differentiation protein; the DNA molecular marker is at least one of presenilin 1, presenilin 2 or amyloid precursor protein.

[0033] For the above detection method of Alzheimer's disease, as a preferred embodiment, in step (1), the detection methods of Tau phosphorylated protein and blood protein are: at least one of radioassay, immunoassay, fluorescence assay, flow fluorescence assay, latex turbidimetry, biochemical assay, enzymatic assay, hybridization assay, gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, chromatography, chemiluminescence assay, magnetoelectric assay or photoelectric conversion assay.

[0034] For the above detection method of Alzheimer's disease, as a preferred embodiment, in step (1), the detection methods of DNA molecular markers are: at least one of PCR method, QPCR method, sequencing method.

[0035] In the third aspect of the present application, a kit for detecting Alzheimer's disease is provided. The kit includes at least two of Tau phosphorylated protein, blood protein or DNA molecular markers. Among them, the kit for detecting Tau phosphorylated protein and blood sample protein includes R1 antibody reagent, R2 antibody reagent, protein calibrators with 2 - 10 concentration gradients, and quality control products with 2 - 6 concentration gradients. The kit for detecting DNA molecular markers includes reaction solution, primer probes, mixed enzyme solution, negative quality control product, and positive quality control product.

[0036] The beneficial effects of the present invention are as follows: The kit for detecting Alzheimer's disease according to the present invention is developed based on non-invasive and easy-to-operate biomarkers such as blood, saliva and urine, which will provide more convenient and feasible early diagnosis measures. Evidence shows that about one-third of dementia can be prevented, and early diagnosis of dementia is very important, which can greatly improve the success rate of disease-modifying therapies.

[0037] The present invention realizes the early diagnosis and screening of AD by detecting peripheral blood samples instead of non-invasive cerebrospinal fluid. It has good diagnosis at the stage of mild cognitive impairment. The combined detection technology of protein markers and molecular gene mutations in blood has excellent performance. Under the condition of 95% specificity, its diagnostic accuracy reaches 90%, far higher than the very rare single detection products of AD blood or urine on the market (such as β-amyloid (1 - 42), Alzheimer's related neurofilament protein (AD7C-NTP), total tau protein, etc.), filling the international gap. This detection system is reported for the first time internationally, and its technology and diagnostic performance reach the advanced level at home and abroad. Description of the Drawings

[0038] Figure 1 : ROC curve graph of the test performance of some Alzheimer's markers. The detection results of AD01 - AD06 correspond to the following markers.

[0039] AD01: Detection result of the ⑨th marker in plasma;

[0040] AD02: Detection result of the th marker in plasma;

[0041] AD03: ①②③⑨⑩ Combined detection result in plasma;

[0042] AD04: Detection result of ⑩ in plasma; AD05:

[0043] Detection result of ② in plasma;

[0044] AD06: Detection result in plasma. Detailed Embodiments

[0045] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with examples. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0046] The present invention discloses the application of at least two of Tau phosphorylated protein, blood protein or DNA molecular marker in the detection of Alzheimer's disease.

[0047] Preferably, the Tau phosphorylated protein is at least one of: P-TAU 181, P-TAU 231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404 or P-TAU 205; the protein in the blood is at least one of α-synuclein, brain-derived neurotrophic factor, glial fibrillary acidic protein, neurofilament light chain or neurogenic differentiation protein 6; the DNA molecular marker is at least one of presenilin 1, presenilin 2 or amyloid precursor protein.

[0048] The present invention also provides a method for detecting Alzheimer's disease, comprising the following steps:

[0049] (1) Detect at least two of the concentrations of Tau phosphorylated protein, blood protein or DNA molecular marker in the sample;

[0050] (2) Perform logistic regression or support vector machine (SVM) analysis algorithm on the measured marker concentrations in the sample to establish a calculation model.

[0051] Preferably, the sample is: tissue, cerebrospinal fluid, blood, urine, saliva or feces of a human or animal body.

[0052] The logistic regression equation is:

[0053]

[0054] Where Logit(P) is the result of the logistic regression model of the Alzheimer's marker;

[0055] C is the natural constant obtained by regression;

[0056] α is the coefficient of each marker obtained by regression analysis;

[0057] The marker concentration i is the concentration of each protein marker, and n is an integer greater than or equal to 2.

[0058] Support vector machines are a binary classification model that finds a hyperplane to divide data into one class and other classes, differing from perceptrons in that the separation margin is maximized.

[0059] Applicable to:

[0060] Data can be directly divided into two classes (using the error-correcting output codes method to distinguish multiple classes);

[0061] Data that is not linearly separable in high dimensions;

[0062] Simple classification.

[0063] Categories of support vector machines:

[0064] Linearly separable support vector machine (linear support vector machine in linearly separable case) - hard margin maximization

[0065] Linear support vector machine - soft margin maximization

[0066] Non-linear support vector machine - kernel trick

[0067] The present invention uses Python or R language for programming and calls relevant SVM data packets to construct a model. Among them: The detection methods for Tau phosphorylated protein and blood protein are: at least one of radioassay, immunoassay, fluorescence assay, flow cytometry fluorescence assay, latex turbidimetry, biochemical assay, enzymatic assay, hybridization assay, gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, nucleic acid mass spectrometry, chromatography, chemiluminescence method, magnetoelectric method or photoelectric conversion method; The detection methods for DNA molecular markers are: at least one of PCR method, QPCR method, sequencing method.

[0068] The present invention also provides a kit for detecting Alzheimer's disease: The kit includes at least two of Tau phosphorylated protein, blood protein or DNA molecular markers. Among them, the detection of Tau phosphorylated protein and blood sample protein includes R1 antibody reagent, R2 antibody reagent, protein calibrator with 2 - 10 concentration gradients, quality control product with 2 - 6 concentration gradients, and the kit for detecting DNA molecular markers includes reaction solution, primer probe, mixed enzyme solution, negative quality control product, positive quality control product.

[0069] According to different methodologies, the components of the detection kits vary slightly and are prepared in accordance with national industry standards or enterprise standards.

[0070] Example 1

[0071] The samples are cerebrospinal fluid of Alzheimer's disease patients and normal cerebrospinal fluid. The genders and ages of the samples of cerebrospinal fluid from Alzheimer's disease patients and normal cerebrospinal fluid are comparable (to avoid errors caused by gender and age). The concentrations of phosphorylated Tau protein, blood protein, and DNA molecular markers in the samples are detected. The methods used for detecting phosphorylated Tau protein and blood protein are chemiluminescence immunoassay with magnetic microparticles, and the method used for detecting DNA molecular markers is QPCR.

[0072] After the kits for each marker are prepared as required, cerebrospinal fluid is drawn from healthy individuals and Alzheimer's patients, and the protein markers and DNA markers involved in the present invention are extracted:

[0073] P-TAU 181, P-TAU 231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404, P-TAU205; alpha-synuclein, brain-derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), neurogenic differentiation protein 6 (NEUROD6); presenilin 1 (PSEN1), presenilin 2 (PSEN2), amyloid precursor protein (APP); Each marker is detected separately and in combination with different markers. The process is to add the samples of relevant healthy individuals or Alzheimer's patients to the components of each kit, and the instrument automatically mixes them, shakes and washes them for detection. The concentration results of each marker are directly read. Further, the concentrations of the above-mentioned relevant markers are subjected to natural logarithm transformation, and logistic regression analysis (programmed in R language or using Medcalc software) is performed to obtain a regression equation. Through the regression equation, the corresponding AUC value, specificity, and sensitivity are analyzed simultaneously. The results are shown in Table 1:

[0074] For the specific application of logistic regression analysis in this example, the following is an example:

[0075] Example 1. The regression equation for the combined detection of ①②③ (P-TAU 181 + P-TAU 231 + P-TAU 217):

[0076] Logit(P) = 0.656 + 0.912 * Ln(P-TAU 181) + 0.876 * Ln(P-TAU 231) + 0.973 * Ln(P-TAU 217)

[0077] ①②③(P-TAU 181 + P-TAU 231 + P-TAU 217) combined detection panel, AUC = 0.90. At a specificity of 96%, the sensitivity is 90%, which is much better than the single non-combined detection panel. See Table 1 for details.

[0078] Example 2: ①②③⑦⑧⑨⑩ Regression equation for the combined detection panel (① - Each represents the name of the biomarker. See Table 1 for details):

[0079] Logit(P) = 0.987 + 0.812*Ln(①) + 0.576*Ln(②) + 0.673*Ln(③) + 0.534*Ln(⑦) + 0.766*Ln(⑧) - 1.833*Ln(⑨) 0.735*Ln(⑩) + 0.876*Ln( ) + 1.476*Ln( ) + 0.387*Ln( ) + 0.578*Ln( ) + 0.7*Ln( )

[0080] ①②③⑦⑧⑨⑩ Combined detection panel, AUC = 0.97. At a specificity of 97%, the sensitivity is 97%, which is much better than the single non-combined detection panel. See Table 1 for details.

[0081] Table 1

[0082]

[0083]

[0084] Example 2

[0085] The samples are Alzheimer's disease plasma and normal human plasma. The gender and age of the samples selected from Alzheimer's disease plasma and normal plasma are comparable (to avoid errors caused by gender and age). The concentrations of Tau phosphorylated protein, blood protein, and DNA molecular markers in the samples are detected. The methods used for detecting Tau phosphorylated protein and blood protein are magnetic particle chemiluminescence methods, and the method used for detecting DNA molecular markers is the QPCR method.

[0086] After each biomarker kit is prepared according to the requirements, plasma from healthy people and Alzheimer's patients is drawn, and the protein markers and DNA markers involved in the present invention are drawn out:

[0087] P-TAU 181, P-TAU 231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404, P-TAU205; alpha synuclein, brain-derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), neurogenic differentiation protein 6 (NEUROD6); presenilin 1 (PSEN1), presenilin 2 (PSEN2), amyloid precursor protein (APP); each biomarker was detected separately and in combination with different biomarkers, and the concentrations in Alzheimer's plasma and normal population plasma were measured. Further, the concentrations of the above-mentioned related biomarkers were subjected to natural logarithm transformation, and logistic regression analysis was performed using software such as Medcalc to obtain a regression equation. At the same time, the AUC values, specificity, and sensitivity of single or combined detections were obtained. The results are shown in Table 2:

[0088] For the specific application of logistic regression analysis in this example, the following is an illustration:

[0089] 1. ①②③⑨ (P-TAU 181 + P-TAU 231 + P-TAU 217 + BDNF + NEUROD6) combined detection combination regression equation:

[0090] Logit(P) = 0.783 + 0.713*Ln(P-TAU 181) + 0.646*Ln(P-TAU 231) + 0.844*Ln(P-TAU 217) - 0.706*Ln(BDNF) + 0.647*Ln(NEUROD6)

[0091] Its combined detection combination AUC = 0.88. At a specificity of 95%, the sensitivity is 93%, which is much better than the combination of single non-combined detections. See Table 2 for details.

[0092] 2. ①②③④⑤⑥⑦⑧⑨⑩ Combined detection combination regression equation (① - Each represents the biomarker name. See Table 2 for details):

[0093] Logit(P) = 1.012 + 0.712*Ln(①) + 0.676*Ln(②) + 0.723*Ln(③) + 0.723*Ln(③) + 1.673*Ln(④) + 1.673*Ln(⑤) + 0.833*Ln(⑥) + 0.547*Ln(⑦)

[0094] + 0.861*Ln(⑧) - 1.713*Ln(⑨) 0.735*Ln(⑩) + 0.673*Ln( ) + 1.246 * Ln( ) + 0.587 * Ln( ) + 0.742 * Ln( ) + 0.712 * Ln( )

[0095] The AUC of its combined detection is 0.98. At a specificity of 98%, the sensitivity is 96%, which is much better than the combination of single non - combined detections. See Table 2 for details.

[0096] Table 2

[0097]

[0098]

[0099] Example 3

[0100] The samples are plasma of mild cognitive impairment (MCI) and normal plasma. The genders and ages of the selected samples of MCI plasma and normal plasma are comparable (to avoid errors caused by gender and age).

[0101] Detect the concentrations of Tau phosphorylated protein, blood protein, and DNA molecular markers in the samples. The methods used for detecting Tau phosphorylated protein and blood protein are enzyme - linked immunosorbent assay, and the method used for detecting DNA molecular markers is nucleic acid mass spectrometry.

[0102] After preparing each marker kit according to the requirements, plasma is drawn from the mild cognitive impairment population and the normal population, and the protein markers and DNA markers involved in the present invention are extracted:

[0103] P - TAU 181, P - TAU 231, P - TAU 217, P - TAU 199, P - TAU 202, P - TAU 404, P - TAU205; alpha - synuclein, brain - derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), neurogenic differentiation protein 6 (NEUROD6); presenilin 1 (PSEN1), presenilin 2 (PSEN2), amyloid precursor protein (APP); The concentrations of each marker and different marker combinations are detected in Alzheimer's plasma and normal population plasma. Further, the concentrations of the above - mentioned related markers are subjected to natural logarithm transformation, and after logistic regression analysis, a regression equation is obtained. The test result data is analyzed using Medcalc software. Its AUC value, specificity, and sensitivity. The results are shown in Table 3:

[0104] Table 3

[0105]

[0106] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the method of the present invention, several improvements and supplements can be made, and these improvements and supplements should also be regarded as the protection scope of the present invention.

Claims

1. Use of a biomarker combination for preparing a reagent for detecting Alzheimer's disease, characterized in that, The biomarker is composed of P-TAU 181, P-TAU231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404, P-TAU 205, α-synuclein, brain-derived neurotrophic factor, glial fibrillary acidic protein, neurofilament light chain, neurogenic differentiation protein 6, presenilin 1, presenilin 2, and amyloid precursor protein; the use of the reagent for detecting Alzheimer's disease is achieved through a logistic regression equation, and the logistic regression equation is: ; Where Logit(P) is the result of the logistic regression model of Alzheimer's markers; C is the natural constant obtained by regression; α is the coefficient of each marker obtained by regression analysis; The concentration of marker i is the concentration of each marker, and n is an integer greater than or equal to 2.

2. The use according to claim 1, wherein The samples for detecting Alzheimer's disease are: cerebrospinal fluid, blood.

3. A kit for detecting Alzheimer's disease, characterized in that, The kit includes detection reagents for P-TAU 181, P-TAU231, P-TAU 217, P-TAU 199, P-TAU 202, P-TAU 404, P-TAU 205, α-synuclein, brain-derived neurotrophic factor, glial fibrillary acidic protein, neurofilament light chain, neurogenic differentiation protein 6, presenilin 1, presenilin 2, and amyloid precursor protein.

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