Methods, systems, compositions, and kits for diagnosing and differentiating alzheimer's disease based on human hippocampal spatial transcriptomics

Abstract

The application is based on a method, system, composition and kit for diagnosing and differentiating Alzheimer's disease by hippocampus spatial transcriptomics, and realizes the differentiation of Alzheimer's disease by one or several of CCK, Neurogranin and PMP2 carried by plasma extracellular vesicles (EVs). The core detection technology of the application is nano-flow detection technology, which focuses on the early diagnosis and differentiation of AD cognitive impairment, and solves the clinical and scientific research problems. Through international leading spatial transcriptome and single cell sequencing and new nano-flow detection technology, the high sensitivity and high throughput detection of EVs of nervous system origin in peripheral blood is realized, and the advantages of rapidness and low cost are also possessed. The application applies the resources of human brain, innovates the EVs marker of central nervous system brain area and cell specific source, realizes the rapid and efficient early diagnosis and differentiation of AD cognitive impairment, and provides new technical means and methods for clinical AD cognitive impairment clinical application and large-scale screening related precision diagnosis work.

Description

Technical Field

[0001] This invention relates to the field of precision diagnosis technology for Alzheimer's disease, and to methods, systems, compositions, and kits for the diagnosis and differential diagnosis of Alzheimer's disease based on human hippocampal spatial transcriptomics. Specifically, it relates to methods, systems, compositions, and kits for the diagnosis and differential diagnosis of Alzheimer's disease based on research and screening of human hippocampal spatial transcriptomics / single-cell sequencing data, combined with exosome detection technology. Background Technology

[0002] Early diagnosis techniques for Alzheimer's disease (AD) are not yet mature, and the variety of related products is limited. Due to the current lack of specific and sensitive early diagnostic methods and standards in clinical practice, AD patients are often diagnosed based on clinical symptoms and imaging indicators only after extensive irreversible neuronal damage has occurred, indicating that the disease has progressed to the middle or late stages and the optimal intervention window has been missed. Furthermore, there is currently a lack of rapid and efficient diagnostic methods to differentiate AD from non-AD cognitive impairment. Because current research has not yet clarified the pathogenesis of AD, there are no effective drugs for etiological treatment of AD; only symptomatic treatment can alleviate patient symptoms.

[0003] While imaging methods have some value in the diagnosis of Alzheimer's disease (AD) in clinical practice, the cost of imaging examinations is extremely high, with only large general hospitals equipped with the necessary equipment. The examination process is complex and time-consuming, requiring highly experienced radiologists, which places a significant economic burden on patients and society. In contrast to the high cost and complexity of imaging examinations, AD biomarker testing offers advantages such as low cost and shorter processing time. Cerebrospinal fluid (CSF) biomarkers have been found to have some clinical value in assisting the diagnosis of AD. However, CSF collection requires a high level of professional skill from medical personnel, and patients have low tolerance for the invasive and risky procedure of lumbar puncture. Therefore, CSF collection faces significant challenges in clinical diagnosis, especially in clinical screening.

[0004] As mentioned earlier, early diagnosis and differential diagnosis of Alzheimer's disease (AD) cognitive impairment have always been a challenge and a research bottleneck in clinical practice and scientific research. However, the development of AD diagnostic biomarkers based on peripheral blood has significant advantages such as being minimally invasive, easy to accept, simple to operate and easy to standardize, and low in cost and easy to popularize, and has great clinical practice and public health value. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides methods, systems, compositions, and kits for the diagnosis and differential diagnosis of Alzheimer's disease based on data screening developed from human hippocampal spatial transcriptomics / single-cell sequencing.

[0006] This application primarily utilizes human brain spatial transcriptomics / single-cell sequencing data, combined with an exosome database, to screen candidate targets and detect brain-region-specific extracellular vesicles (EVs) of nervous system origin in peripheral blood, aiming to achieve early diagnosis and differential diagnosis of Alzheimer's disease (AD). Due to its minimally invasive, easily accepted, low-cost, and readily available advantages, this invention holds promise for clinical practice and large-scale screening. The key biomarkers in this application are differentially expressed markers discovered through human brain spatial transcriptomics. Because of their disease-specific and brain-region-specific characteristics, they can more directly reflect AD-related central nervous system-specific pathological changes, thereby enabling the diagnosis and differential diagnosis of AD. This application incorporates all differentially expressed genes (A2M, ABCA2, ABI1, AC009879.3, AC091167.2, AC092143.1, AC093330.1, APOE) from human hippocampal spatial transcriptomics / single-cell sequencing data. , AC093512.2, ACADVL, ACAT2, ACTB, ACTG1, ACTR1A, ADD3, ADGRB3, ADGRG1, ADIRF, AEBP1, AHNAK, C9 orf16, AHSA1, AL049839.2, AL121594.1, AL365205.1, ANGPTL4, ANK2, AQP1, AP2M1, C3, AP2S1, APLNR , APOC1, ARL1, ARL6IP1, ARPC2, ARPC5L, CALM1, ATF4, CABP7, CADM2, ATP1A1, ATP1B1, BHLHE22, ATP2A 2. ATP5F1A, ATP5F1B, CALM3, ATP5F1D, ATP5F1E, CADM3, ATP5MC1, ATP5MC2, ATP5MC3, ATP5MF, CACYBP , ATP5MG, ATP5MPL, CALM2, ATP5PB, ATP6AP2, ATP6V0E2, ATP6V1D, ATP6V1E1, ATP6V1F, ATP6V1H, BEX4, A TP8A1, AUTS2, AUXG01000058.1, B2M, B4GAT1, BAIAP3, BCYRN1, BEX1, C1orf216, BEX2, BEX3, BRK1, C1QB , BSCL2, BTBD3, BTF3, CALY, CAMK1, CAMK2B, CAMK2N1, CAPS, CBR1, CCT5, CCT8, CD14, CD151, CD44, CD59, CD63, CD74, CEBPD, CELF4, CELSR2, CHGB, CHI3L1, CFL1, CHCHD2, CELF2, CD81, CD9, CDK2AP1, CDKN1A, CIRBP, CLSTN1,CLSTN2, CNN3, CKB, COMT, CLDN5, CLU, CNBP, CLASP2, CLDN11, CNDP2, COPA, D LG2, COX4I1, COX6C, COX5A, COX5B, COX6A1, COX6B1, COX7A2, COX7C, CRYAB SMD1, CSMD3, CYCS, DBI, CSRP1, CST3, CTSB, CTSD, CTXND1, CX3CL1, DGKG, DH CR24, DHCR7, DKK3, DCLK1, DDIT4, DEGS1, DNAJA1, DNAJA4, DNPH1, DSE, DTD1. DUSP1, DYNLL1, EEF1A1, EEF2, EEF1G, EFHD1, EID1, EIF4A1, EIF4A2, EIF5, E LOB, ENC1, ENO1, ENO2, FBXO2, EPDR1, EPHA4, EPHA5, ERBIN, ERC2, ERH, FABP3 FABP5, FAM107A, FAM162A, FAM3C, FAU, FBXW5, FEZ1, FHL1, FIS1, FKBP1B, F KBP2, FKBP5, FOS, FSCN1, FTH1, FTL, FTX, GALNT15, FXYD6, GABARAP, GABARAP L1, GABARAPL2, GADD45B, GAPDH, GDF1, GDI1, GLS, GLUL, GNAI2, GNAO1, GNAS GNB2, GOT1, GPM6B, GPRC5B, GRB2, GRIA1, GSN, GSTP1, GUK1, H2AFZ, H3F3B, H.S ACD3, HINT1, HLA-B, HLA-DRB1, HMGCR, HMGCS1, HNRNPC, HNRNPDL, HNRNPK OPX, HS6ST3, HSP90AA1, HSP90AB1, HSPA4, HSPA8, HSPB1, HSPB8, HSPE1, HSPH 1, HTRA1, ICAM5, ID4, IDI1, ISCU, ISG15, ITGAV, IDS, ITGB4, ITM2B, ITM2C. JUN, ITPKB, IGFBP5, IGFBP7, IRS2, JUNB, JUND, KCNIP4, KCNMB4, KIAA0408, K IF1A, KIF1B, KLF9, KLHL2, LARP6, LDHA, LDHB, LGALS1, MAPK8IP3, MIR7-3HG. MICAL2, MGST3, MAP4K4, LINC00844, MARCKSL1, MFSD6, MFSD4A, LMO4, LRP1B.LSAMP、MAL、MALAT1、MAOB、MGST1、MAP1LC3A、MDH2、MAP1LC3B、MAP2K1、MDH1、MEG3、MLLT11、MMD、MRFAP1、MRPL41、MRPL51、MRP S21, MSMO1, MT1E, MT2A, MTATP6P1, MTCH1, MT-CO2, MT-CO3, MT-CYB, MTLN, MT-ND1, MT-ND2, MT-ND4, MT-ND6, MTPN, MT-RNR1 T-RNR2、MYL12B、NDUFA11、MYL6、NDUFA13、NAA60、NDUFA4、NACA、NAP1L5、NAPB、NCAM2、NCDN、NDRG1、NDRG3、NDRG4、NDUFA1、ND UFA8、NDUFB8、NDUFAB1、NDUFS6、NDUFAF8、NDUFB4、NDUFV1、NEAT1、NECAB1、NENF、NLRP1、NME1、NME1-NME2、NOP56、NORAD、NPC2 、NPM1、NPTN、NPTXR、NRIP3、NRN1、NRXN1、NRXN3、NTRK2、NUCKS1、NUPR1、OAZ1、OLFM1、OXCT1、PREPL、PAK3、PARK7、PCDH8、PCDH 9. LLP、PRDX5、POLR2I、PPIA、PRDX1、PPP2CA、PPP2R2B、PPP3CA、PPP3R1、PPT1、PREX1、PSMA7、PRKAR1B、PRKCA、PRXL2A、PSMA4、PS AP、PSMB4、PSMB5、PSMB7、PSMC3、PSMD1、PSMD8、PTMA、PTMS、PTP4A2、PTPRD、PTTG1IP、QDPR、QKI、RAB31、RABAC1、RACK1、RPL18A 、RAMP1、RAN、RANGAP1、RASD1、RASGRP1、RBM3、RBX1、RFK、、RGMA、RGS14、RPL18、RHBDD2、RNASE1、RNASET2 、RPL10、RPL17-C18orf32、RPL10A、RPL11、RPL13、RPL13A、RPL15、RPL17-C18orf32、RPL19、RPL23、RPL21、RPL27A、RPL27、RPL28、RPL24、RPL26、RPL3、RPL30、RPL31、RPL34、RPL35、RP L35A、RPL36、RPL37A、RPL38、RPL4、RPL41、RPL5、RPL8、RPL9、RPLP0、RPLP1、R PS10、RPS11、RPS12、RPS13、RPS14、RPS15、RPS15A、RPS16、RPS19、RPS2、RPS 20、RPS21、RPS23、RPS27、RPS27A、RPS29、RPS3、RPS3A、RPS4X、RPS6、RPS7、RP S8、RPSA、RTN3、RTN4、RYR2、S100A10、S100A6、SAP18、SAT1、SCAMP5、SCD、SC G3、SCGN、SCOC、SCRG1、SDHA、SEC61B、SELENOP、SELENOW、SEM1、SEMA3B、SEMA 5A, SERF2, SERINC1, SHTN1, SIK3, SKP1, SLC22A17, SLC24A3, SLC25A3, SLC25A4, SLC2A3, SLC38A2, SLC44A1, SLC7A11, SLIT1, SNRPN, SOD1, SOD2, SORBS1 、SPARC、SPARCL1、SPOCK1、SPP1、STXBP1、SUB1、SUMO2、SUN2、SUSD4、SYNE1、 SYNM、SYS1-DBNDD2、SYT11、SYT13、TAGLN3、TALDO1、TBCA、TCEAL2、TCEAL3、T CEAL4、TCEAL5、TCF4、TCP1、TENM2、TF、THY1、TIMP2、TIMP3、TKT、TM2D3、TM9 SF2、TMA7、TMBIM1、TMEM130、TMEM35A、TMSB10、TMSB4X、TMTC1、TNRC6C、TOLL IP、TOMM34、TOMM7、TPI1、TPPP、TPT1、TRIM2、TRMT112、TSC22D1、TSPAN7、TS PYL4、TUBA1A、TUBA4A、TUBB2A、TXN、TXNIP、TXNL1、UBB、UBC、UBE2N、UBL5、UB QLN1、UCHL1、UQCR10、UQCR11、UQCRB、UQCRH、UQCRQ、USP11、USP22、VAMP2、V APA、VDAC2、VIM、VSTM2L、WBP2、XRCC6、YJEFN3、YWHAB、YWHAG、YWHAH、YWHAQ、YWHAZ, ZCCHC12, ZCCHC24, ZFAND5, ZFP36, ZFP36L1, ZFP36L2, ZMAT2) and exosome databases were used for screening, and the following genes that showed significant changes during the development of Alzheimer's disease (AD) were identified: AK5, ALDOC, AMER, APC2, APOD, ATP1A3, BAALC, BCAN, C1orf61, CABP1, CACNG3, CACNG8, CAMKV, CCK, CHN1, CNKSR2, CHN1, CNDP1, CNTNAP4, CREG2, CTXN1, DLGAP1, DNAJC6, ENHO, GABRA5, GAD1, GAP43, GFAP, GNG3, GPM6A, GRIK2, GRIN1, GRIN2A, GRIN2B, HEPACAM, HPCA, KCNJ10, KCNQ3, KCTD16, KIF 5C, LAMP5, MAP2, MBP, MOBP, MTURN, MLC1, MT3, MTURN, NEFL, NEFM, NEUROD2, NKX6-2, OMG, NPTX1, NRGN, OLIG1, OPALIN, PAQR6, PDYN, PHYHIP, PIANP, PLANP, PLEKHB1, PLP1, PMP2, PMP22, PNMA2, POLR2F, PP KCG, PTPRZ1, RAB3A, RGS4, RTN1, S100B, SCN2B, SEZ6L, SLC1A2, SLC17A7, SLC1A3, SLC24A2, SLC2A1, SLC4A10, SLC6A7, SNAP25, SNCB, STMN4, STMN2, SULT4A1, SYN2, SYNPR, SYT1, TTC9B, TUBB2B, TUBB4A). This data is reliable and can further improve the reliability of diagnosis and differential diagnosis.

[0007] To achieve the above objectives, the present invention provides a composition for the diagnosis and differential diagnosis of Alzheimer's disease based on human hippocampal spatial transcriptomics / single-cell sequencing, which is one or more of CCK, Neurogranin (NRGN) and PMP2 carried by plasma extracellular vesicles (EVs).

[0008] Preferably, the CCK, Neurogranin, and PMP2 carried by the plasma extracellular vesicles (EVs) are enriched by PEG8000 sedimentation.

[0009] This invention provides a detection kit comprising Zenon reagent labeled with antibodies. TM Alexa Fluor TM647Rabbit IgG Labeling Kit, lipid probes, and antibodies;

[0010] The lipid probe has the sequence SEQ ID NO: 1 as TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT, with 5' end modified with CY3 and 3' end modified with Cholesteryl; the antibody includes one or more of CCK, Neurogranin, and PMP2 antibodies.

[0011] This invention provides an application of CCK protein in the differential diagnosis of Alzheimer's disease and non-AD-dementia.

[0012] This invention provides a method for detecting CCK, Neurogranin, and PMP2 positive proteins, comprising the following steps:

[0013] CCK, Neurogranin, and PMP2 antibodies were labeled using the Alexa Fluro fluorescent labeling kit. The labeled antibodies were mixed with the blocked exosomes and incubated overnight at 4°C in the dark. Then, lipid probes were added and incubated at 4°C in the dark.

[0014] Add PFA to the labeled sample, mix well, and incubate at room temperature in the dark.

[0015] Dilute to the appropriate concentration with PBS and run on the instrument. Detect using CytoFLEX or similar nanoflow cytometry techniques. The number of particles per second is less than 10,000.

[0016] When detecting positive lipid probes using CytoFLEX or similar nanoflow cytometry in VSSC mode, the positive rate of protein labeling can be obtained.

[0017] Preferably, the method is used for identification purposes other than disease diagnosis and treatment.

[0018] The beneficial effects of this invention are as follows:

[0019] The core detection technology employed in this application is nanoflow cytometry, which enables highly sensitive and high-throughput detection of extracorporeal endothelial cells (EVs) originating from the central nervous system in peripheral blood. This technology also offers advantages in speed and low cost, providing technical support for clinical applications and large-scale screening. This application focuses on the clinical and research challenge of early diagnosis and differential diagnosis of Alzheimer's disease (AD). Through internationally leading spatial transcription and single-cell sequencing, along with novel nanoflow cytometry technology, and by utilizing the resources of the Chinese brain, it innovatively discovers EV biomarkers specific to brain regions and cells within the central nervous system, achieving rapid and efficient early diagnosis and differential diagnosis of AD, thus providing new technical means and methods for clinical AD diagnosis. Attached Figure Description

[0020] Figure 1 The image shows the plasma EVs extracted in Example 1 of this invention. Transmission electron microscopy revealed that the EVs have a bilayer membrane structure and their size is within the particle size range of EVs.

[0021] Figure 2 The results of particle size distribution and concentration analysis of EVs enriched by PEG8000 in Example 1 of this invention are shown, where the horizontal axis represents particle size distribution and the vertical axis represents EV concentration.

[0022] Figure 3 The present invention presents the specificity and stability results of nanoflow cytometry detection of plasma EVs extracted in Example 1. In A, it can be seen that the percentage of EVs containing CCK, Neurogranin, and PMP2 in peripheral plasma is significantly higher than that in the isotype IgG control group; B and C show that the percentage of EVs labeled by CCK, Neurogranin, and PMP2 antibodies remains stable under different dilution factors (B) and different incubation times (C), respectively.

[0023] Figure 4 For the purpose of screening the diagnostic capabilities of some potential biomarkers in this invention, AB represents the statistical analysis and ROC results of CCK protein detection, CD represents the statistical analysis and ROC results of Neurogranin protein detection, EF represents the statistical analysis and ROC results of PMP2 protein detection, GH represents the statistical analysis and ROC results of CREG2 protein detection, IJ represents the statistical analysis and ROC results of CPLX2 protein detection, KL represents the statistical analysis and ROC results of NEFM protein detection, MN represents the statistical analysis and ROC results of STMN4 protein detection, and OP represents the statistical analysis and ROC results of STMN protein detection.

[0024] Figure 5 This is an analysis diagram of the verification queue results in Embodiment 3 of the present invention, wherein... Figure 5As shown in Figure 5A, compared with the NC group, the ratio of CCK protein-positive EVs to total EVs in plasma was significantly lower in the AD group (****, p<0.000), and compared with the NAD group, the ratio of CCK protein-positive EVs to total EVs in plasma was also significantly lower in the AD group (***, p<0.001); compared with the NC group, the ratio of CCK protein-positive EVs to total EVs in plasma was also significantly lower in the NAD group (**, p<0.01). In Figure 5B, compared with the NC group, the ratio of Neurogranin protein-positive EVs to total EVs in plasma was significantly lower in the AD group (****, p<0.0001), and compared with the NC group, the ratio of Neurogranin protein-positive EVs to total EVs in plasma was also significantly lower in the NAD group (***, p<0.001). In Figure 5C, compared with the NC group, the ratio of PMP2 protein-positive EVs in plasma was significantly lower in the AD group. The proportion of PMP2-positive EVs in the total number of EVs was significantly lower in the NAD group (****, p<0.0001). Compared with the NC group, the proportion of PMP2-positive EVs in the total number of EVs in the plasma of the NAD group was also significantly lower (**, p<0.01). Figure 5 In Figure 5D, the Logistic Regression Analysis Enter method was used to include CCK, Neurogranin, and PMP2 data, with an AUC of 0.92 (NCVS AD). In Figure 5E, the Logistic Regression Analysis Enter method was used to include CCK, Neurogranin, and PMP2 data, with an AUC of 0.83 (ADVS NAD). Detailed Implementation

[0025] To better illustrate the purpose, technical solution, and advantages of this invention, the following will provide further explanation of this application in conjunction with specific embodiments.

[0026] Example 1

[0027] PEG8000 sedimentation enrichment of EVs

[0028] 1. Plasma from the subjects was rapidly thawed at 37°C (within 2 minutes) and vortexed to mix;

[0029] 2. Centrifuge plasma samples (>300 μL) at 4℃ and 2,000 × g for 15 min, and collect the supernatant;

[0030] 3. Next, centrifuge at 4℃ and 12,000×g for 30 min, and collect the supernatant;

[0031] 4. Transfer 10 μL of centrifuged plasma to a 1.5 mL centrifuge tube, add 70 μL of PBS and 20 μL of 40% PEG8000, mix thoroughly by pipetting, and let stand at room temperature for 30 min.

[0032] 5. Centrifuge at 12000g, 4℃ for 20 minutes;

[0033] 6. Discard the supernatant, add 100 μL of PBS to resuspend, mix well by pipetting, dispense 10 μL / tube, and store at -80℃ for later use.

[0034] Example 2

[0035] 1. Sample sealing

[0036] (1) Take 10 μL of EVs (Example 1) enriched by PEG8000 sedimentation using the above method and transfer it to a 0.6 mL centrifuge tube;

[0037] (2) Add 10 μL of 2% BSA solution (filtered through a 0.22 μm membrane) and mix well;

[0038] (3) Indoor closure at room temperature (25-26℃) for 1 hour to remove non-specific binding;

[0039] (4) Add 10 μL of PBS (filtered through a 0.22 μm membrane) to dilute and terminate the blocking.

[0040] 2. Sample labeling

[0041] Antibodies for detecting biomarkers were labeled using a labeling method. Reagents used: The Alexa Fluro fluorescent labeling kit was used to label CCK, Neurogranin, and PMP2 antibodies. The labeling reagent for the antibodies was Zenon. TM Alexa Fluor TM The 647 Rabbit IgG Labeling Kit, purchased from Thermo Fisher Scientific, contains a lipid-labeling probe with the sequence SEQ ID NO: 1: TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT, 5' end modified with CY3, and 3' end modified with Cholesteryl.

[0042] (1) Take 1 μg of antibody for the corresponding marker and dilute it to 5 μL (0.2 μg / μL) with PBS (filtered through a 0.22 μm membrane);

[0043] (2) Add 5 μL Zenon TM Alexa FluorTM Mix the 647 Rabbit IgG Labeling Kit A solution thoroughly and incubate at room temperature (25-26℃) in the dark for 20 minutes.

[0044] (3) Add 3 μL (3 μg) Zenon to the solution from step (2). TM Alexa Fluor TM 647 RabbitIgG Labeling Kit Solution B (Solution B diluted to 1 μg / μL), mix well and incubate at room temperature (25℃) in the dark for 10 min to quench unbound free fluorescein;

[0045] (4) Add PBS (filtered through a 0.22 μm membrane) and dilute to a total volume of 50 μL;

[0046] (5) Take 3 μL of Zenon TM Alexa Fluor TM The antibody labeled with the 647 Rabbit IgG Labeling Kit was mixed with the blocked sample from step 1 and incubated overnight at 4°C in the dark.

[0047] 3. Reagents used for probe incubation: A synthetic DNA anchor with the sequence TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT (SEQ ID NO: 1); 5' end modified with CY3; 3' end modified with Cholesteryl. This lipid probe can bind to the EV membrane, and probe-labeled positive particles are considered true EVs; this method further improves the scientific validity and accuracy of EV labeling.

[0048] (1) The next day, add 62 μL PBS + 5 μL lipid probe (lipid probe working solution concentration 10 μM) (reaction volume 100 μL, probe final concentration 500 nM), and incubate at 4°C in the dark for 1 h.

[0049] (2) Add 100 μL of 4% PFA (filtered through a 0.22 μm filter membrane) to the labeled sample, mix well, and incubate at room temperature (25-26℃) in the dark for 20 min;

[0050] (3) Dilute with PBS to a suitable concentration for testing. Standard: Detection with CytoFLEX, less than 10,000 particles per second. Collect 50,000 particles under the lipid probe gate (in this case, the total number of particles is approximately 100,000; in other words, the particles obtained from the example are screened using the lipid probe, of which the actual EVs are approximately 50%).

[0051] 4. Testing

[0052] The positive rate of related protein markers was detected using CytoFLEX's VSSC mode when lipid probes were positive.

[0053] Example 3

[0054] Screening for differential diagnostic capabilities of some of the above biomarkers in a small cohort.

[0055] Plasma samples were obtained from 15 age- and sex-matched healthy controls (NC group), 15 Alzheimer's disease subjects (AD group), and 15 non-AD dementia subjects (NAD group), and experiments were conducted using the methods described in Examples 1 and 2 above.

[0056] The number of single fluorescently labeled extracellular molecules (EVs) of CCK, Neurogranin, PMP2, CREG2, CPLX2, NEFM, STMN4, and STMN2 was detected using the VSSC mode of CytoFLEX, and the proportion of each EV to the number of lipid probe-labeled EVs was calculated to determine its ability to distinguish between non-nucleotide (NC), adenosine monoclonal antibody (AD), and non-alcoholic angioplasm (NAD). The results are as follows: Figure 4 As shown,

[0057] Compared with the NC group, the proportion of CCK protein-positive EVs in plasma was significantly lower in the AD group (****, p<0.0001), and the proportion of CCK protein-positive EVs in plasma was significantly lower in the NAD group (****, p<0.0001) (4A), ROC=0.86 (4B);

[0058] Compared with the NC group, the proportion of Neurogranin-positive EVs in plasma was significantly lower in the AD group (****, p<0.0001), and the proportion of Neurogranin-positive EVs in plasma was significantly lower in the NAD group (**, p<0.01) (4C), ROC=0.84 (4D);

[0059] Compared with the NC group, the proportion of PMP2 protein-positive EVs in plasma was significantly lower in the AD group (***, p<0.001), and the proportion of PMP2 protein-positive EVs in plasma was significantly lower in the NAD group (**, p<0.01) (4E), ROC=0.80 (4F);

[0060] Compared with the NC group, the proportion of CREG-2 protein-positive EVs in plasma was significantly lower in the AD group (**, p<0.01) (4G), ROC=0.76 (4H);

[0061] Compared with the NC group, the proportion of CPLX2 protein-positive EVs in plasma of the AD group was significantly lower (****, p<0.0001), and compared with the NC group, the proportion of CPLX2 protein-positive EVs in plasma of the NAD group was significantly lower (****, p<0.0001) (4I), ROC=0.79 (4J);

[0062] Compared with the NC group, there was no significant difference in the proportion of NEFM protein-positive EVs in the plasma of the AD group and the NAD group (4K), ROC=0.79 (4L);

[0063] Compared with the NC group, there was no significant difference in the proportion of STMN4 protein-positive EVs in the plasma of the AD group and the NAD group (4M), ROC=0.69 (4N);

[0064] Compared with the NC group, there was no significant difference in the proportion of STMN2 protein-positive EVs in the plasma of the AD group and the NAD group (4O), ROC=0.64 (4P).

[0065] Example 4

[0066] The differential diagnostic ability of the above biomarkers was tested in a standardized clinical cohort.

[0067] Plasma samples were obtained from 66 age- and sex-matched healthy controls (NC group), 45 Alzheimer's disease subjects (AD group), and 45 non-AD dementia subjects (NAD group), and experiments were conducted using the methods described in Examples 1 and 2 above.

[0068] The number of single fluorescently labeled EVs (CCK, Neurogranin, and PMP2) were detected using the VSSC mode of CytoFLEX, and the proportion of each labeled EV to the number of lipid probe-positive EVs was calculated. The ability to distinguish between NC, AD, and NAD was also assessed. Results are as follows: Figure 5 show,

[0069] Compared with the NC group, the proportion of CCK protein-positive EVs in plasma of the AD group was significantly lower (****, p<0.0001), and compared with the NAD group, the proportion of CCK protein-positive EVs in plasma of the AD group was also significantly lower (**, p<0.01), both of which showed significant differences (Figure 5A).

[0070] Compared with the NC group, the proportion of Neurogranin-positive EVs in plasma was significantly lower in the AD group (****, p<0.0001) (Figure 5B); compared with the NC group, the proportion of PMP2-positive EVs in plasma was significantly lower in the AD group (****, p<0.0001) (Figure 5C).

[0071] Logistic regression analysis was used to include CCK, Neurogranin, and PMP2 data. The AUC was 0.92 (NC vs. AD) (Figure 5D); and AUC was 0.83 (AD vs. NAD) (Figure 5E). Analysis showed that relying on the proportion of single-label positive EVs for CCK, Neurogranin, and PMP2 to the total number of EVs not only effectively distinguishes between NC and AD patients but also provides a good differential diagnosis between AD and NAD.

[0072] The above description is merely a preferred embodiment of this application and is not intended to limit the application in any other way. Any person skilled in the art may use the disclosed technical content and targets to make changes or modifications to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the protection scope of this application.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. The use of a composition in the preparation of a kit for the auxiliary differential diagnosis of Alzheimer's disease, characterized in that: The composition is a combination of CCK, Neurogranin, and PMP2 proteins carried by extracellular plasma vesicles (EVs). The plasma extracellular vesicles (EVs) carrying CCK, Neurogranin, and PMP2 were enriched by PEG8000 sedimentation. The detection reagents include Zenon reagents labeled with antibodies. TM Alexa Fluor TM 647 Rabbit IgG Labeling Kit, lipid probes, and antibodies; The lipid probe has the sequence SEQ ID NO: 1 as TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT, with 5' end modified with CY3 and 3' end modified with Cholesteryl. The antibodies include antibodies against CCK, Neurogranin, and PMP2.

2. The use of the composition according to claim 1 in the preparation of a kit for the auxiliary differential diagnosis of Alzheimer's disease, characterized in that: Includes the following steps, CCK, Neurogranin, and PMP2 antibodies were labeled using the Alexa Fluro fluorescent labeling kit. The labeled antibodies were mixed with the blocked exosomes and incubated overnight at 4°C in the dark. Lipid probes were then added and incubated at 4°C in the dark. Add PFA to the labeled sample, mix well, and incubate at room temperature in the dark. Dilute with PBS to the appropriate concentration and run on the instrument. Detect using CytoFLEX; the number of particles per second is less than 10,000. When detecting positive lipid probes using CytoFLEX's VSSC mode, the positive rate of protein labeling can be obtained.

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