Application of alpha-Syn polymerization form in predicting occurrence and progress of Alzheimer's disease

Abstract

The invention provides application of an alpha-Syn polymerization form in prediction of occurrence and progress of the Alzheimer's disease, and further provides a prediction system and a computer readable storage medium capable of realizing prediction steps of the system. The method provided by the invention can provide a new thought for early diagnosis of AD by accurately detecting alpha-Syn in different aggregation states in cerebrospinal fluid. Compared with a traditional diagnosis means, abnormal aggregation of alpha-Syn can be recognized before disease symptoms are obvious, pathological changes of neurodegenerative diseases are revealed from the source, and the method has high prognosis value. Compared with iconography and genetic detection methods, detection based on the alpha-Syn aggregation state has higher sensitivity and specificity, and false negative or false positive results can be effectively reduced. The method is easy and convenient to operate and low in cost, can provide more accurate early disease recognition and personalized intervention strategies for clinic, and has wide application prospects.

Description

Technical Field

[0001] The present invention belongs to the technical field of Alzheimer's disease treatment, and specifically relates to the application of an α-Syn aggregation form in predicting the occurrence and progression of Alzheimer's disease. Background Art

[0002] Patients with Alzheimer's disease (AD) often experience significant cognitive decline, especially in memory, language, and executive function. Because the symptoms of AD are relatively hidden in the early stages, early diagnosis and risk prediction are crucial for effective intervention and treatment. Mild cognitive impairment (MCI) is a state of cognitive decline and an early stage in the development of AD. It usually manifests as a mild decline in memory or other cognitive abilities, but has not yet reached the diagnostic criteria for AD. Early identification of MCI is crucial for intervention to slow the progression of AD.

[0003] In the pathological process of AD, in addition to the classic deposition of β-amyloid protein (Aβ) and abnormal phosphorylation of Tau protein, there is also aggregation of α-Syn. 30-50% of AD patients also show signs of α-Syn pathology. Patients with AD Lewy body variant confirmed by autopsy tend to experience more rapid cognitive decline.

[0004] α-Synuclein (α-Syn) is a small protein mainly found in the presynaptic terminals of neurons. It is involved in the release of neurotransmitters and intracellular signaling. It is abundant in the brain and exists mainly as an unstructured monomer in its soluble native form. α-Syn monomers are associated with the distal reserve pool of synaptic vesicles, and the synaptic transmission defects observed in the knockdown or overexpression of α-Syn suggest that α-Syn plays a role in the regulation of neurotransmitter release, synaptic function, and plasticity. In contrast to the above physiological conformations, α-Syn allows misfolded α-Syn conformers to persist and aggregate into pathogenic assemblies under pathological conditions, which is an important pathological process in degenerative diseases such as Parkinson's disease (PD) and dementia with Lewy bodies (DLB). High levels of soluble oligomeric forms of α-Syn are considered to be an important pathogenic species, leading to cytoskeletal changes, increased membrane permeability, increased generation of reactive oxygen species, and synaptic toxicity. Therefore, the apparent multifunctionality of α-Syn may arise from its conformational flexibility.

[0005] Recent studies have shown that the aggregated form of α-Syn in cerebrospinal fluid (CSF) is closely related to the pathological features and clinical symptoms of AD. In current studies, the functional differences of α-Syn in different conformational states in AD have not been concerned, and there is a lack of in-depth understanding of the role of different structural forms of α-Syn in predicting the conversion of MCI to AD. Therefore, we first studied the correlation between different aggregation types of α-Syn in CSF and AD-related pathological proteins, as well as their differences in AD clinical phenotypes. Summary of the Invention

[0006] The object of the present invention is to provide an application of the aggregated form of α-Syn in predicting the occurrence and progression of Alzheimer's disease. The potential role of CSF α-Syn in different conformational states in the conversion of mild cognitive impairment (MCI) to AD was explored, and the predictive ability of CSF α-Syn in the conversion of MCI in the α-Syn0 and α-Syn1 groups was studied; the risk of different aggregation forms of α-Syn in the progression of AD was further studied.

[0007] In the study of the present invention, for the first time, the correlation between different aggregation types of CSF α-Syn and AD-related pathological proteins

[0008] and their differences in the clinical feature phenotypes of AD were concerned. When aggregated CSF α-Syn is detected, it indicates that α-Syn in the cerebrospinal fluid has misfolded. We stratified the subjects according to the results of α-Syn seed amplification assay (SAA) combined with α-Syn protein misfolding cyclic amplification (PMCA) assay. Patients without detectable CSF α-Syn aggregation were classified into the Syn0 group, while patients with detectable CSF α-Syn aggregation consistent with PD were classified into the Syn1 group (hereinafter referred to as these two CSF α-Syn aggregation states as α-Syn0 and α-Syn1).

[0009] Based on the changes in the different aggregation forms of α-Synuclein (α-Syn) in cerebrospinal fluid (CSF), the present invention proposes a diagnostic method for predicting the conversion of patients with mild cognitive impairment (MCI) to Alzheimer's disease (AD) and the progression of AD. By identifying and quantifying the aggregated forms of α-Syn in CSF (Syn0 and Syn1), a new diagnostic method is provided. Specifically, Syn0 indicates that no α-Syn aggregates are detected, while Syn1 indicates the presence of α-Syn aggregates similar to those in Parkinson's disease. It has been found that these different α-Syn aggregation forms are closely related to the risk of conversion of MCI to AD. We first discovered that in the AD stage, Syn0 in CSF is associated with faster cognitive decline and greater hippocampal atrophy. However, in the MCI stage, MCI patients with the aggregated state of Syn1 in CSF have a higher risk of converting to AD. Therefore, by analyzing the main aggregation forms of α-Syn in the CSF of MCI and AD patients, it is possible to evaluate whether MCI patients have a high risk of AD conversion and the risk of AD progression. This technology not only provides important biomarkers for the early diagnosis of MCI, but also helps predict the disease progression of patients, thereby providing a scientific basis for personalized treatment and intervention.

[0010] Based on the above research, the technical solutions to be protected by the present invention are as follows:

[0011] In the first aspect of the present invention, there is provided the use of the aggregated form of α-Syn as a biomarker in the preparation of a system for predicting the occurrence and progression of Alzheimer's disease.

[0012] Among them, the aggregated form of α-Syn is divided into the Syn1 form in which α-Syn aggregates can be detected in cerebrospinal fluid (CSF) and the Syn0 form in which no detectable α-Syn aggregates are present in the cerebrospinal fluid.

[0013] The system for predicting the occurrence and progression of Alzheimer's disease is used to predict the conversion of patients with mild cognitive impairment (MCI) to Alzheimer's disease (AD), or to predict whether patients with Alzheimer's disease are likely to further develop.

[0014] Preferably, the system for predicting the occurrence and progression of Alzheimer's disease predicts by the following method: for patients with mild cognitive impairment (MCI), when the aggregated form of α-Syn is Syn1, the risk of conversion to Alzheimer's disease increases; for patients with Alzheimer's disease, when the aggregated form of α-Syn is Syn0, compared with the Syn1 aggregated form, the risk of further development increases; when the aggregated form of α-Syn is Syn1, under certain conditions, the patient has the risk of further development.

[0015] Specifically, the system for predicting the occurrence and progression of Alzheimer's disease predicts by the following method:

[0016] For MCI patients with CSF α-Syn1, those with CSF Aβ42 level higher than 730.0 pg / mL, CSF p-tau level higher than 29.0 pg / mL, and CSF T-tau level higher than 310.0 pg / mL are predicted to be more likely to develop AD;

[0017] For AD patients with CSF α-Syn1, those with CSF α-Syn level higher than 0.48 ng / ml, CSF α-Syn / T-tau ratio higher than 0.0016, or CSF α-Syn / p-tau ratio higher than 0.016 have the risk of further progression.

[0018] In the second aspect of the present invention, a system for predicting the occurrence and progression of Alzheimer's disease is provided, including an input display module, a calculation module, an extraction and determination module, a storage module, and a control module.

[0019] Among them, the input display module is at least used to input the disease diagnosis type, α-Syn aggregation form, α-Syn level, Aβ42 level, p-tau level, and T-tau level of the patient, and display the determination result of the determination module;

[0020] The calculation module calculates the α-Syn / T-tau ratio and the α-Syn / p-tau ratio;

[0021] The extraction and determination module extracts the disease diagnosis type, α-Syn aggregation form, α-Syn level, Aβ42 level, p-tau level, T-tau level, α-Syn / T-tau ratio, and α-Syn / p-tau ratio of the patient, and predicts the conversion of mild cognitive impairment patients to Alzheimer's disease based on pre-stored rules, or predicts whether Alzheimer's disease patients are prone to further progression;

[0022] The storage module pre-stores the corresponding thresholds of the α-Syn / T-tau ratio and the α-Syn / p-tau ratio, as well as the prediction rules, and stores the basic information and diagnosis results of the detection object;

[0023] The control module is used to control the normal operation of the input display module, the calculation module, and the extraction and determination module.

[0024] Preferably, (a) the rule for predicting the conversion of mild cognitive impairment patients to Alzheimer's disease is as follows: for mild cognitive impairment patients, when the α-Syn aggregation form is Syn1, the risk of conversion to Alzheimer's disease is increased compared to the Syn0 form;

[0025] For MCI patients with CSF α-Syn1, those with CSF Aβ42 level higher than 730.0 pg / mL, CSF p-tau level higher than 29.0 pg / mL, and CSF T-tau level higher than 310.0 pg / mL are predicted to be more likely to develop into AD;

[0026] (b)The rules for predicting whether Alzheimer's disease patients are likely to progress further are as follows: For Alzheimer's disease patients, when the aggregated form of α-Syn is Syn0, the risk of further progression is increased compared to the Syn1 form;

[0027] When the aggregated form of α-Syn is Syn1, patients are at risk of further progression under the following conditions: For AD patients with CSF α-Syn1, those with CSF α-Syn level higher than 0.48 ng / ml, CSF α-Syn / T-tau ratio higher than 0.0016, or CSF α-Syn / p-tau ratio higher than 0.016 are at risk of further progression.

[0028] In the third aspect of the present invention, a method for predicting the occurrence and progression of Alzheimer's disease is provided, including the following steps:

[0029] (1)Input the basic information of the patient, the type of disease diagnosis of the patient, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, and the T-tau level into the input display module;

[0030] (2)The calculation module calculates the α-Syn / T-tau ratio and the α-Syn / p-tau ratio;

[0031] (3)The extraction determination module extracts the type of disease diagnosis of the patient, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, the T-tau level, the α-Syn / T-tau ratio, and the α-Syn / p-tau ratio, and predicts the conversion of mild cognitive impairment patients to Alzheimer's disease or whether Alzheimer's disease patients are likely to progress further based on the following pre-stored rules:

[0032] a)For mild cognitive impairment patients, when the aggregated form of α-Syn is Syn1, the risk of conversion to Alzheimer's disease is increased compared to the Syn0 form;

[0033] For MCI patients with CSF α-Syn1, those with CSF Aβ42 level higher than 730.0 pg / mL, CSF p-tau level higher than 29.0 pg / mL, and CSF T-tau level higher than 310.0 pg / mL are predicted to be more likely to develop into AD;

[0034] b) The rules for predicting whether Alzheimer's disease patients are prone to further progression are as follows: For Alzheimer's disease patients, when the aggregated form of α-Syn is Syn0, the risk of further progression is increased compared to the Syn1 form;

[0035] When the aggregated form of α-Syn is Syn1, patients are at risk of further progression under the following conditions: For AD patients with CSF α-Syn1, when the CSF α-Syn level is higher than 0.48 ng / ml, the CSF α-Syn / T-tau ratio is higher than 0.0016, or the CSF α-Syn / p-tau ratio is higher than 0.016, the patients are at risk of further progression.

[0036] (4) Display the determination result of the determination module in the input display module.

[0037] In the fourth aspect of the present invention, a computer-readable storage medium is provided, which has executable code embedded therein; when the code is executed, the steps in the prediction method described above are implemented.

[0038] The computer-readable storage medium can be an APP, a mini-program, etc., and is installed in electronic devices such as computers, mobile phones, and pads.

[0039] Compared with other detection methods for Alzheimer's disease, the present invention has the following advantages:

[0040] The present invention provides the application of the aggregated form of α-Syn in predicting the occurrence and progression of Alzheimer's disease. This study shows that the detection method based on the aggregation state of α-Syn has significant technical advantages for diagnosing the pathological progression of AD and the transformation of MCI-AD: First, this method can provide new ideas for the early diagnosis of AD by accurately detecting different aggregated states of α-Syn in cerebrospinal fluid. Compared with traditional diagnostic methods, this method can identify abnormal aggregation of α-Syn before obvious disease symptoms, revealing the pathological changes of neurodegenerative diseases from the source. Second, by directly detecting the aggregation state of α-Syn, the risk of patient transformation to AD can be predicted at the MCI stage, which has strong prognostic value. In addition, compared with imaging and genetic detection methods, the detection based on the aggregation state of α-Syn has high sensitivity and specificity, which can effectively reduce the occurrence of false negative or false positive results. This method is simple to operate, has low cost, and can provide more accurate early disease identification and personalized intervention strategies for clinical practice, and has broad application prospects. Brief Description of the Drawings

[0041] Figure 1Shows CSF α-Syn levels in the MCI and Alzheimer's disease cohorts: A, B: Quantitative analysis of CSF α-Syn levels at baseline in the overall group (A) and α-Syn0 and α-Syn1 groups (B) in different diagnostic groups; C, D: Analysis of α-Syn levels in CSF α-Syn0 (C) and CSF α-Syn1 (D) groups between different subgroups according to the ATN framework. *P < 0.05, using one-way ANOVA and least significant difference (LSD) post hoc test;

[0042] Figure 2 Shows the association between CSF α-Syn levels and CSF Aβ and tau pathological levels: A, B: Association between CSF α-Syn and Aβ42 levels in the α-Syn0 (A) and α-Syn1 (B) groups; C, D: Association between CSF α-Syn and T-tau levels in the α-Syn0 (C) and α-Syn1 (D) groups; E, F: Association between CSF α-Syn and p-tau levels in the α-Syn0 (E) and α-Syn1 (F) groups. *P < 0.05, using one-way ANOVA and least significant difference (LSD) post hoc test and Pearson correlation test.

[0043] Figure 3 Shows the correlation analysis between CSF α-Syn and cognitive decline in AD patients: A: In the α-Syn0 group, patients experienced significantly faster cognitive decline. In contrast, patients in the α-Syn1 group had a slower rate of cognitive decline; B: In the α-Syn1 group, patients with CSF α-Syn levels higher than 0.48 ng / ml experienced faster cognitive impairment; C: In the α-Syn1 group, patients with a CSF α-Syn / T-tau ratio higher than 0.0016 experienced faster cognitive impairment; D: In the α-Syn1 group, patients with a CSF α-Syn / p-tau ratio higher than 0.016 experienced faster cognitive impairment. These cut-off values were determined by using the ROC curve and Youden index. Multivariate analysis was performed using the Cox proportional hazards model.

[0044] Figure 4Shows the correlation analysis of cerebrospinal fluid (CSF) α-Syn and cognitive decline in Alzheimer's disease patients: A: Patients with CSF α-Syn levels higher than 0.48 pg / ml experienced faster cognitive impairment; B: Patients with CSF α-Syn / T-tau ratio higher than 0.0016 experienced faster cognitive impairment; C: Patients with CSF α-Syn / p-tau ratio higher than 0.016 experienced faster cognitive impairment; D, E, F: In the α-Syn0 group, there was no correlation between α-Syn level, α-Syn / T-tau ratio, and α-Syn / p-tau ratio and cognitive decline. The cut-off value was determined by using the ROC curve and Youden index. Multivariate analysis was performed using the Cox proportional hazards model.

[0045] Figure 5 Shows the correlation analysis of CSF α-Syn and hippocampal volume changes in AD patients: A: In the α-Syn0 group, the hippocampal volume of patients decreased faster than that of patients in the α-Syn1 group; B: In the α-Syn0 group, high levels of α-Syn were associated with a rapid decline in hippocampal volume; C: In the α-Syn0 group, a high CSF α-Syn / T-tau ratio was associated with a decrease in hippocampal volume; D: In the α-Syn0 group, a high CSF α-Syn / p-tau ratio was associated with a decrease in hippocampal volume.

[0046] Figure 6 Shows the correlation analysis of cerebrospinal fluid (CSF) α-Syn0 and α-Syn1 and hippocampal volume changes in Alzheimer's disease patients: A: Higher total α-Syn levels were associated with a rapid decline in hippocampal volume; B: Higher cerebrospinal fluid total α-Syn / T-tau ratio was associated with a decrease in hippocampal volume; C: Higher cerebrospinal fluid total α-Syn / p-tau ratio was associated with a decrease in hippocampal volume;

[0047] D, E, F: In the α-Syn1 group, there was no correlation between α-Syn level, α-Syn1 / T-tau ratio, and α-Syn1 / p-tau ratio and hippocampal volume changes. Multivariate analysis was performed using the Cox proportional hazards model.

[0048] Figure 7 Shows the Kaplan-Meier curves of AD-free survival in MCI patients under different CSF α-Syn aggregation types (α-Syn0 and α-Syn1).

[0049] Figure 8 Shows the structural block diagram of the system for predicting the occurrence and progression of Alzheimer's disease. Detailed implementation

[0050] The following examples and experimental examples further illustrate the present invention and should not be construed as limiting the present invention. The examples do not include a detailed description of traditional methods, such methods being well known to those of ordinary skill in the art and having been described in many publications.

[0051] Unless otherwise defined, all professional and scientific terms used herein have the same meaning as those familiar to persons skilled in the art. In addition, any methods and materials similar or equivalent to those described may be applied to the present invention, and the preferred methods and materials described in the specific embodiments are for illustrative purposes only.

[0052] I. Materials and Methods

[0053] 1.1 Study Setup and Participants

[0054] This study mainly analyzed data from the ADNI database, including 70 healthy controls (HCs), 119 individuals diagnosed with MCI, and 61 individuals diagnosed with AD. All participants underwent a Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Functional Activities Questionnaire (FAQ) score, Alzheimer's Disease Assessment Scale - Cognitive 13-item scale (ADAS13), and assessment of APOE4 allele carrier status. The study included individuals with MCI or AD who met the Mayo Clinic criteria or the National Institute of Neurological Disorders and Stroke - Alzheimer's Disease and Related Disorders Association guidelines. The levels of Aβ42, P-tau, T-tau, and α-Syn in the cerebrospinal fluid of all individuals were quantified. For data analysis, a cross-sectional analysis of the levels of α-Syn, Aβ42, P-tau, and T-tau in the cerebrospinal fluid of individuals diagnosed with MCI was performed. In addition, a hypothesis assessment was performed on individuals classified as AD according to the newly established ATN framework of the National Institute on Aging and the Alzheimer's Association.

[0055] 1.2 Magnetic Resonance Imaging (MRI) Assessment

[0056] Longitudinal hippocampal volume was measured using 3T MPRAGE MRI scans to assess neurodegeneration. Data were obtained from the ADNI imaging core (UCSF) and were based on FreeSurfer from the ADNI database (http: / / adni.loni.usc.edu / ). Median images were created for each participant by accurately registering all of their longitudinal time point images, generating a fair template specific to each participant. This template was then used to initialize subsequent algorithms, including surface reconstruction, non-linear spatial normalization to atlas space, and parcellation. This strategy ensured a consistent approach to image processing across all time points, minimizing the risk of bias related to temporal order. Prior to hippocampal volume extraction, we performed extensive preprocessing on all images. This included intensity normalization, removal of non-brain voxels, affine registration to Talairach space, and segmentation of subcortical white matter and nuclei, followed by a second intensity normalization. Subsequently, we performed surface reconstruction on all images using a series of steps, including non-linearly registering individual surface models to a spherical atlas and automated brain parcellation. A comprehensive description of the longitudinal FreeSurfer imaging pipeline used on ADNI data can be accessed online (http: / / adni.loni.usc.edu / ) as well as in previous publications.

[0057] 1.3 α-Synuclein seed amplification assay (αS SAA)

[0058] Datasets of α-Syn levels were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http: / / adni.loni.usc.edu / ). Assessment of synuclein seeds in cerebrospinal fluid was performed using the synuclein seed amplification assay provided by Amprion (https: / / ampriondx.com / ). The α-Syn seed amplification assay was conducted at the Amprion Clinical Laboratory (CLIA ID No. 05D2209417; CAP No. 8168002) and followed a validated method that met the requirements of the Clinical Laboratory Improvement Amendments (CLIA) for clinical use. Each sample was analyzed in triplicate in a 96-well plate, and the reaction mixture included 100 mM PIPES pH 6.5, 0.5 M NaCl, 0.1% sarkosyl, 10 μM ThT, 0.3 mg / mL recombinant α-Syn, and 40 μL of cerebrospinal fluid, with a final volume of 100 μL. Two silicon nitride beads were included in each well, and positive and negative assay quality control samples were included on each plate. The plates were sealed with an optically adherent film and placed in the chamber of a BMG LABTECH FLUOstar Ω microplate reader, incubated at 42°C with a 1-minute shake followed by a 14-minute rest, and fluorescence was measured (excitation wavelength 440 nm, emission 490 nm) after each shake cycle. After a total incubation time of 20 hours, the maximum fluorescence of each well was determined, and an algorithm was applied to the triplicate measurements of each sample for result classification. Patients with a negative αS SAA result were classified into the α-Syn0 group.

[0059] 1.4 α-Synuclein Protein Misfolding Cyclic Amplification (PMCA)

[0060] The PMCA result dataset of cerebrospinal fluid α-Syn was from the ADNI database (http: / / adni.loni.usc.edu / ). The α-Syn-PMCA assay was performed as previously described. Briefly, the seed-free monomeric α-Syn sample at a concentration of 1 mg / ml was placed in an environment of 100 mM PIPES, pH 6.5 and 500 mM NaCl, put into an opaque 96-well plate (Costar, REF 3916), and 5 μM ThT was added at a final volume of 200 μl. For each test, we added 40 μl of cerebrospinal fluid from patients and controls or 40 μl of brain homogenate (final concentration of 0.001%). Positive controls included a well-documented previous sample. The samples were cyclically agitated at 37°C (agitated for 1 minute at 500 rpm and then not agitated for 29 minutes). The increase in ThT fluorescence was regularly monitored using a microplate fluorometer (Gemini-EM, Molecular Devices) with an excitation wavelength of 435 nm and an emission wavelength of 485 nm. Samples with maximum fluorescence values between 2,000 and 8,000 units were identified as having aggregated α-Syn consistent with PD, and these patients were classified into the α-Syn1 group.

[0061] 1.5 Statistical analysis

[0062] Continuous baseline variables were expressed as mean (SE), and discrete variables were summarized as frequency and percentage. For the comparison of continuous variable groups, ANOVA or Kruskal Wallis, t-test or non-parametric test was appropriately used after passing the normality test and / or variance chi-square test. When appropriate, the chi-square test was used for the comparison of discrete variables. The correlation was corrected for multiple comparisons. All biomarker variables were included together with the variables in the reference model, including age, gender, years of education, and ApoE ε4 carrier status, and each variable was evaluated independently. The model performance was evaluated by estimating the area under the receiver operating characteristic (ROC) curve (AUC). The cut-off value was determined by ROC analysis, considering AUC, sensitivity, and specificity. The optimal cut-off point was the value that minimized the sum of the absolute differences between AUC and sensitivity or specificity, ensuring the minimum difference between sensitivity and specificity. The Pearson correlation test was used to establish the association between α-Syn and T-tau, p-tau, and Aβ42 in cerebrospinal fluid, considering other covariates. The Cox proportional hazards model was used for multivariate analysis, adjusting for ApoE4, age, and gender, to evaluate the risk of AD progression. The significance level of all statistical tests was P<0.05. Statistical analysis was performed using SPSS version 20 (IBM Corp., Armonk, New York, USA) and R version 4.2.1 (R Development Core Team, Vienna, Austria).

[0063] II. Results

[0064] 2.1 Baseline demographics and clinical characteristics of participants

[0065] The participants included 119 patients with mild cognitive impairment (MCI), 61 patients with Alzheimer's disease (AD), and 70 controls. The demographic characteristics, clinical characteristics, and cerebrospinal fluid (CSF) biomarker levels of all participants are shown in Table 1. There were no significant differences among the three groups in terms of age (p = 0.376), sex (p = 0.052), and years of education (p = 0.588). As expected, there were differences in the Mini-Mental State Examination (MMSE), Functional Activities Questionnaire (FAQ), CSF Aβ42, CSF p-tau, CSF T-tau, and APOE ε4 among the diagnostic groups at baseline. Similar to previous studies in the ADNI cohort, the levels of alpha-synuclein (α-Syn) were significantly increased in patients with MCI and AD ( Figure 1 A). Subsequently, the subjects were divided into α-Syn0 and α-Syn1 subgroups according to the differences in the CSF α-Syn aggregation status (the specific method is described in the Methods section).

[0066] Table 1 Baseline demographic characteristics of participants

[0067]

[0068] Abbreviations: MMSE: Mini-Mental State Examination; FAQ: Functional Activities Questionnaire; CN: cognitively normal; MCI: mild cognitive impairment; AD: Alzheimer's disease.

[0069] 2.2 Differences in the levels of CSF α-Syn with different aggregation types among diagnostic groups

[0070] After stratifying the subjects according to the α-Syn aggregation status, we found that in the α-Syn0 group, the α-Syn levels were significantly increased in patients with MCI, and the α-Syn levels were further increased in patients with AD ( Figure 1 B). However, in the α-Syn1 group, there were no significant differences in the α-Syn concentrations among different diagnostic groups at baseline ( Figure 1 B). Next, the differences in the α-Syn levels between the CSF α-Syn0 and α-Syn1 groups were analyzed in different pathological subgroups. According to the ATN framework, the participants were classified into amyloid-beta positive (A+) and amyloid-beta negative (A-) or tau positive (T+) and tau negative (T-) categories based on neuropathological findings. In the α-Syn1 group, there were no statistically significant differences in the α-Syn concentrations among the healthy control (HC), MCI, and AD subgroups ( Figure 1D). However, in the A-T+ subgroup of the α-Syn0 group, we found an increasing trend in the CSF α-Syn concentration in MCI and AD patients, and there was a significant difference between AD and HC ( Figure 1 C). These results suggest that CSF α-Syn levels may be associated with disease status and other pathological markers.

[0071] 2.3 Correlation between CSF α-Syn concentration of different aggregation types and Aβ and tau pathological levels

[0072] Using CSF Aβ42, T-tau, and p-tau levels as pathological indicators of AD. Except for the weak correlation between CSF α-Syn and Aβ42 in AD patients observed in the α-Syn0 group, there was no other significant correlation between α-Syn concentration and Aβ42 level ( Figure 2 A-B). However, in the α-Syn0 group, a strong correlation was observed between α-Syn and CSF T-tau and p-tau levels ( Figure 2 C, 2E). In the α-Syn1 group, a positive correlation was also observed between α-Syn concentration and CSF T-tau and p-tau ( Figure 2 D, 2F). These findings suggest that α-Syn may be more closely associated with tau-related AD pathology and progression than with Aβ42.

[0073] 2.4 Effect of CSF α-Syn concentration of different aggregation types on cognitive decline in AD patients

[0074] Then, the effect of different types of CSF α-Syn structural states on cognitive decline in the AD group was investigated. Cognitive changes were evaluated by the ADAS13 score, and adjusted for gender, age, education, and ApoE ε4 carrier status. Patients in the α-Syn0 group experienced significantly faster cognitive decline, while patients in the α-Syn1 group were slower ( Figure 3 A). Then, α-Syn levels were classified as below or above the cut-off value. The cut-off value was determined by the ROC curve and Youden index. The determined α-Syn cut-off value was 0.48. In the α-Syn1 group, higher α-Syn concentration was associated with a rapid increase in the ADAS13 score, which was consistent with the results observed in the overall α-Syn group but inconsistent with the results in the α-Syn0 subgroup ( Figure 3 B, Figure 4A, 4D). Due to the significant correlation between α-Syn and tau pathology, we calculated the ratio of α-Syn to tau. The ROC curve determined the cut-off values of α-Syn / T-tau and α-Syn / p-tau to be 0.0016 and 0.016, respectively. We observed that the results of the α-Syn1 subgroup were consistent with those of the overall α-Syn group. Higher α-Syn / T-tau and α-Syn / p-tau ratios were associated with a rapid increase in the ADAS13 score, suggesting more rapid cognitive decline ( Figure 3 C-D, Figure 4 B-C). In contrast, these results were not observed in the α-Syn0 subgroup ( Figure 4 E-F). In summary, patients in the α-Syn0 group experienced more rapid cognitive decline than those in the α-Syn1 group. Meanwhile, in the α-Syn1 group, high concentrations of CSF α-Syn led to more pronounced cognitive decline.

[0075] 2.5 Correlation between different types of α-Syn structural states and changes in hippocampal volume in AD patients

[0076] To evaluate the effect of α-Syn levels on the progression of cognitive decline, we analyzed the correlation between α-Syn levels and changes in hippocampal volume during follow-up visits in the AD group. All results were adjusted for gender, age, education, and ApoE ε4 carrier status. We found that AD patients in the α-Syn0 group had a faster rate of hippocampal volume decline than those in the α-Syn1 group ( Figure 5 A). α-Syn levels were dichotomized into high and low groups based on the median expression as the cut-off value. As Figure 5 shown in B-D, in the α-Syn0 group, higher α-Syn concentrations, higher α-Syn / T-tau ratios, and α-Syn / p-tau ratios were associated with a faster rate of hippocampal volume decline ( Figure 5 B-D), which was consistent with the results observed in the overall α-Syn group ( Figure 6 A-C). However, in the α-Syn1 group, no correlation was found between α-Syn concentration and changes in hippocampal volume ( Figure 6 D-F).

[0077] 2.6 Correlation between α-Syn aggregation types and conversion to MCI

[0078] Since CSF α-Syn0 and α-Syn1 levels are related to tau pathology, they may predict disease progression. Among the 82 patients followed up, a total of 48 (58.5%) developed into confirmed AD (Table 2). We found no significant differences between the two groups in terms of age, gender, ApoE ε4 carrier genotype, or years of education.

[0079] Table 2: Characteristics of non-converters and converters with mild cognitive impairment (MCI) during follow-up

[0080]

[0081] In addition, we applied Cox analysis to evaluate whether each CSF biomarker level could predict conversion after adjusting for age and sex. The results showed that MCI patients with CSF α-Syn1 (HR = 2.890, P = 0.040, Table 3), CSF Aβ42 levels higher than 730.0 pg / mL (HR = 2.575, P = 0.045, Table 3), CSF p-tau levels higher than 29.0 pg / mL (HR = 4.300, P = 0.002, Table 3), and CSF T-tau levels higher than 310.0 pg / mL (HR = 3.132, P = 0.017, Table 3) were more likely to develop AD. The Kaplan-Meier curve was used to evaluate the predictive value of CSF α-Syn levels in different aggregation states during the conversion process. The mean AD-free survival of MCI patients in the α-Syn1 group was 24 months, while that of patients in the α-Syn0 group was 48 months (P = 0.0376, Figure 7 ). In addition, MCI patients with the CSF α-Syn1 aggregation type were more likely to develop AD.

[0082] Table 3: Assessments between converters and non-converters

[0083]

[0084] a: All results have been adjusted for age, education, and sex.

[0085] III. System for predicting the occurrence and progression of Alzheimer's disease

[0086] As Figure 8 shown, the prediction system 100 includes an input display module 1, a calculation module 2, an extraction and determination module 3, a storage module 4, and a control module 5.

[0087] Among them, the input display module 1 is used to input the basic personal information of the patient, the type of disease diagnosis, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, and the T-tau level, and display the determination result of the determination module; the calculation module 2 calculates the α-Syn / T-tau ratio and the α-Syn / p-tau ratio; the extraction and determination module 3 extracts the type of disease diagnosis, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, the T-tau level, the α-Syn / T-tau ratio, and the α-Syn / p-tau ratio of the patient, and predicts the conversion of patients with mild cognitive impairment to Alzheimer's disease or whether patients with Alzheimer's disease are likely to further develop based on the following pre-stored rules;

[0088] The storage module 4 pre-stores the corresponding thresholds of the α-Syn / T-tau ratio and the α-Syn / p-tau ratio and the prediction rules, and stores the basic information and diagnosis results of the detection object; the control module 5 is used to control the normal operation of the input display module, the calculation module, and the extraction and determination module.

[0089] The pre-stored rules are as follows: (a) The rules for predicting the conversion of patients with mild cognitive impairment to Alzheimer's disease are as follows: for patients with mild cognitive impairment, when the aggregated form of α-Syn is Syn1, the risk of conversion to Alzheimer's disease is increased compared with the Syn0 form;

[0090] For MCI patients with CSF α-Syn1, patients with CSF Aβ42 level higher than 730.0 pg / mL, CSF p-tau level higher than 29.0 pg / mL, and CSF T-tau level higher than 310.0 pg / mL are predicted to be more likely to develop into AD;

[0091] (b) The rules for predicting whether patients with Alzheimer's disease are likely to further develop are as follows: for patients with Alzheimer's disease, when the aggregated form of α-Syn is Syn0, the risk of further development is increased compared with the Syn1 form;

[0092] When the aggregated form of α-Syn is Syn1, patients are at risk of further development under the following conditions: for AD patients with CSF α-Syn1, patients with CSF α-Syn level higher than 0.48 ng / ml, CSF α-Syn / T-tau ratio higher than 0.0016, or CSF α-Syn / p-tau ratio higher than 0.016 are at risk of further development.

[0093] The method for predicting the occurrence and progression of Alzheimer's disease using this system includes the following steps:

[0094] (1) Input the basic information of the patient, the disease diagnosis type of the patient, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, and the T-tau level in the input display module;

[0095] (2) The calculation module calculates the α-Syn / T-tau ratio and the α-Syn / p-tau ratio;

[0096] (3) The extraction and determination module extracts the disease diagnosis type of the patient, the aggregated form of α-Syn, the α-Syn level, the Aβ42 level, the p-tau level, the T-tau level, the α-Syn / T-tau ratio, and the α-Syn / p-tau ratio, and predicts the conversion of patients with mild cognitive impairment to Alzheimer's disease or predicts whether patients with Alzheimer's disease are likely to develop further based on the above pre-stored rules.

[0097] (4) Display the determination result of the determination module in the input display module.

[0098] The above prediction system can be programmatically integrated into a computer-readable storage medium, which has executable code embedded therein; the code, when executed, implements the steps in the prediction method as described above. The computer-readable storage medium can be an APP, a mini-program, etc., and is installed in electronic devices such as computers, mobile phones, and pads.

[0099] IV. Discussion

[0100] Previous studies have shown conflicting results regarding the potential role of cerebrospinal fluid (CSF) α-synuclein (α-Syn) in Alzheimer's disease (AD) and its impact on cognitive performance, which may be related to the structural heterogeneity of α-Syn. Therefore, in this study, we stratified subjects for the first time according to the aggregation state of CSF α-Syn (α-Syn0: no α-Syn aggregation detected, α-Syn1: α-Syn aggregation detected, with aggregation characteristics consistent with Parkinson's disease (PD)), and compared α-Syn levels and their correlation with AD pathology, including AD, mild cognitive impairment (MCI), and healthy control groups. In addition, we also analyzed the correlation between α-Syn levels and AD clinical phenotypes, including cognitive decline and hippocampal atrophy. Furthermore, we analyzed and compared for the first time the predictive ability and differences of CSF α-Syn with different aggregation types during the transition from MCI to AD. We found that α-Syn levels were significantly increased in MCI and AD patients compared with the cognitively normal (CN) group. However, in the α-Syn0 group, α-Syn levels were significantly increased in MCI patients compared with the control group, and further increased in AD patients, while in the α-Syn1 group, there were no significant differences in α-Syn levels among different diagnostic groups. This partly explains the inconsistent correlation between CSF α-Syn and AD in some studies, and we will discuss the clinical implications of these results later. This also indicates the necessity to explore the role of different aggregation types of α-Syn in AD.

[0101] Abnormal tau protein aggregation is one of the core pathological features of AD. Although the accumulation of Aβ plaques is also associated with AD, no significant correlation with α-Syn levels was shown in this study. We found that in the α-Syn0 and α-Syn1 groups, α-Syn levels were correlated with T-tau and p-tau levels in CSF, but not significantly associated with Aβ levels. We speculate that α-Syn may be closely related to tau pathology in AD, while its relationship with Aβ is relatively limited. Nuclear magnetic resonance imaging (NMR) showed that monomeric tau selectively interacted with the C-terminal region of α-Syn monomers and accelerated the oligomerization of α-Syn and subsequent fiber formation. In addition, tau phosphorylation was demonstrated to be dependent on the presence of α-Syn in α-Syn-deficient cell and mouse models, indicating that α-Syn monomers and fibers promoted tau aggregation. These evidences suggest that α-Syn may affect tau pathology through interaction with tau protein. In addition, recent studies have found that CSF α-Syn positive conversion is associated with CSF Aβ42 positivity, highlighting the interaction between Aβ and α-Syn. The current findings suggest that α-Syn may play a key role in the tau pathology of AD, while its involvement in Aβ pathology is relatively limited. This differential association provides important insights into the different pathological mechanisms of AD.

[0102] In addition, we deeply analyzed the correlation between CSF α-Syn levels in different aggregation states and cognitive decline and hippocampal atrophy. Our results showed that the rate of cognitive impairment and hippocampal atrophy was faster in CSF α-Syn0-AD patients than in α-Syn1-AD patients. Interestingly, in the α-Syn1 subgroup, we found that high levels of α-Syn led to faster cognitive decline, but were not correlated with hippocampal atrophy. In contrast, in the α-Syn0 group, high levels of α-Syn led to faster changes in hippocampal atrophy, but no detectable correlation with changes in cognitive impairment. Considering the high correlation between tau and α-Syn levels, the subsequent disruption of abnormal neuronal synaptic function may increase the amount of α-Syn released into the cerebrospinal fluid, similar to the release of tau from neuronal death. Therefore, CSF α-Syn levels were significantly elevated in all AD patients positive for the three CSF markers (Aβ42, total tau, and phosphorylated tau). Therefore, we speculate that the dysregulation of CSF α-Syn levels in the α-Syn0 group may represent a key neurobiological event related to the disruption of synaptic function in the pathophysiological process of AD. The increase in CSF α-Syn levels in the α-Syn0 group may predict the rapid progression of AD, as the α-Syn levels in α-Syn0-AD patients were significantly higher at baseline, which requires further validation and discussion.

[0103] Numerous studies have reported that approximately 50 - 60% of autopsy-proven AD patients have α-Syn pathology. Patients with mixed pathology and animal models expressing both AD and α-Syn pathology tend to exhibit earlier cognitive impairment. Conversely, approximately 50% of patients with dementia with Parkinson's disease (PD) develop sufficient Aβ and tau pathology to receive a secondary pathological diagnosis of AD. The results of these studies suggest that α-Syn pathology may be involved in the early stages of AD pathogenesis and is associated with the progression of cognitive dysfunction. Patients with CSF α-Syn1 are more likely to develop Lewy body pathology. The correlation between high CSF α-Syn levels and increased ADAS13 scores in the α-Syn1 group supports this speculation. We further hypothesized that α-Syn levels may be crucial in the early diagnosis and identification of preclinical AD to optimize outcomes in patients in the α-Syn1 group. Therefore, we analyzed and compared the role of different CSF α-Syn aggregation states in the transition from MCI to AD. We found that the mean AD-free survival in α-Syn1-MCI patients was 24 months, while that in α-Syn0-MCI patients was 48 months. These results provide evidence for the predictive value of CSF α-Syn1 aggregation state in the transition from MCI to AD and suggest that CSF α-Syn1 aggregation state may be involved in the pathophysiological mechanisms of the early preclinical onset of AD, warranting further exploration. Interestingly, CSF α-Syn levels did not increase significantly at baseline in CSF α-Syn1-AD patients, which may confirm that AD mainly involves tau or Aβ pathology rather than synucleinopathy. Previous studies have shown that α-Syn is involved in the early generation of Aβ and tau pathology and co-precipitates with them, which may explain the faster AD transition in α-Syn1-MCI. Therefore, we speculate that the degree of α-Syn1 aggregation state may be associated with the development of AD, which requires further experimental exploration.

[0104] In summary, we found that CSF α-Syn is associated with tau pathology in AD. Different aggregation states of CSF α-Syn are associated with different AD clinical phenotypes and early transitions. In the α-Syn0 group, high concentrations of CSF α-Syn imply faster cognitive impairment and hippocampal atrophy, while the CSF α-Syn1 aggregation state is associated with a more rapid transition from MCI to AD. These results suggest that the α-Syn0 and α-Syn1 aggregation states may be biomarkers for the rapid progression of AD and the risk of transition from MCI to AD, respectively, associated with different pathophysiological mechanisms. Regarding the correlation between CSF α-Syn and AD, further in-depth studies are still needed to provide more accurate insights into AD and may open up new avenues for disease prevention and treatment.

[0105] The parts not described in this invention are the same as or implemented by the prior art. The applicant declares that this invention illustrates the detailed method of this invention through the above embodiments, but this invention is not limited to the above detailed method, that is, it does not mean that this invention must rely on the above detailed method to be implemented. Those skilled in the art should understand that any improvement to this invention, the equivalent substitution of each raw material of the products of this invention, the addition of auxiliary components, the selection of specific methods, etc., all fall within the protection scope and the disclosure scope of this invention.

Claims

1. Application of α-Syn aggregate form as a marker in the preparation of a system for predicting the occurrence and progression of Alzheimer's disease.

2. The use according to claim 1, characterized in that: The aggregated forms of α-Syn are divided into the Syn1 form, in which α-Syn aggregates can be detected in the cerebrospinal fluid (CSF), and the Syn0 form, in which no α-Syn aggregates are detected in the CSF.

3. The use according to claim 2, characterized in that: The system for predicting the occurrence and progression of Alzheimer's disease is used to predict the transformation of mild cognitive impairment (MCI) patients to Alzheimer's disease (AD), or to predict whether Alzheimer's disease patients are prone to further development.

4. The use according to claim 3, characterized in that: The system for predicting the occurrence and progression of Alzheimer's disease is predicted by the following method: For patients with mild cognitive impairment (MCI), when α-Syn aggregates into Syn1, the risk of conversion to Alzheimer's disease increases; For Alzheimer's disease patients, when the α-Syn aggregation form is Syn0, the risk of further development increases compared to the Syn1 aggregation form; when the α-Syn aggregation form is Syn1, the patient has the risk of further development under certain conditions.

5. The use according to claim 4, characterized in that: The system for predicting the occurrence and progression of Alzheimer's disease is predicted by the following method: Among them, for MCI patients with CSF α-Syn1, patients with CSF Aβ42 levels higher than 730.0 pg / mL, CSF p-tau levels higher than 29.0 pg / mL, and CSF T-tau levels higher than 310.0 pg / mL were predicted to be more likely to develop AD; For AD patients with CSF α-Syn1, patients with CSF α-Syn level higher than 0.48 ng / ml, CSF α-Syn / T-tau ratio higher than 0.0016, or CSF α-Syn / p-tau ratio higher than 0.016 were at risk of further progression.

6. A system for predicting the occurrence and progression of Alzheimer's disease, characterized in that: It includes input display module, calculation module and extraction and judgment module. The input display module is at least used to input the patient's disease diagnosis type, α-Syn aggregation form, α-Syn level, Aβ42 level, p-tau level and T-tau level, and display the determination result of the determination module; The calculation module calculates the α-Syn / T-tau ratio and the α-Syn / p-tau ratio; The extraction and determination module extracts the patient's disease diagnosis type, α-Syn aggregation form, α-Syn level, Aβ42 level, p-tau level, T-tau level, α-Syn / T-tau ratio, and α-Syn / p-tau ratio, and predicts the transformation of mild cognitive impairment patients to Alzheimer's disease based on pre-stored rules, or predicts whether Alzheimer's disease patients are prone to further development.

7. The system for predicting the occurrence and progression of Alzheimer's disease according to claim 6, characterized in that: (a) The rule for predicting the transformation of patients with mild cognitive impairment to Alzheimer's disease is as follows: For patients with mild cognitive impairment, when the α-Syn aggregate form is Syn1, the risk of transformation to Alzheimer's disease is increased compared to the Syn0 form. For MCI patients with CSF α-Syn1, patients with CSF Aβ42 levels higher than 730.0 pg / mL, CSF p-tau levels higher than 29.0 pg / mL, and CSF T-tau levels higher than 310.0 pg / mL were predicted to be more likely to develop AD; (b) The rule for predicting whether an Alzheimer's disease patient is prone to further development is as follows: For Alzheimer's disease patients, when the α-Syn aggregate form is Syn0, the risk of further development increases compared to the Syn1 form; When the aggregated form of α-Syn is Syn1, the patient is at risk of further progression under the following conditions: For AD patients with CSF α-Syn1, patients with CSF α-Syn levels higher than 0.48 ng / ml, CSF α-Syn / T-tau ratio higher than 0.0016, or CSF α-Syn / p-tau ratio higher than 0.016 are at risk of further progression.

8. The system for predicting the occurrence and progression of Alzheimer's disease according to claim 7, characterized in that: It also includes a storage module and a control module. The storage module pre-stores corresponding thresholds of the α-Syn / T-tau ratio and the α-Syn / p-tau ratio and the prediction rule, and stores basic information and diagnostic results of the test object; The control module is used to control the normal operation of the input display module, the calculation module and the extraction and determination module.

9. A computer-readable storage medium, wherein: The computer-readable medium has executable code embedded therein; when the code is executed, the steps in the system for predicting the occurrence and progression of Alzheimer's disease as claimed in claim 6 or 7 are implemented.

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