Biomarkers and kits for predicting the risk of developing ad in the elderly and their application
A risk and complex technology, applied in the field of risk biomarkers and kits, can solve the problems of time-consuming, labor-intensive, and expensive AD diagnostic methods, and achieve the effects of fast detection, low cost and high accuracy.
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Embodiment 1
[0046]For persons with mild cognitive impairment (MCI, MMSE=18-23), severe cognitive impairment (AD, MMSE=2-17) and age / sex matched normal cognition (MMSE=29-30) ( Ctrl group) performed a comprehensive and in-depth platelet proteomic analysis using TMT-LC-MS / MS technology. The specific process includes: first, label each protein sample with a TMT tag, then perform mass spectrometry identification, secondly perform differential protein analysis and Pearson correlation analysis to identify candidate proteins, and finally use machine learning methods based on candidate proteins to establish the best combination of markers.
[0047] The results of proteomic analysis such as figure 1 As shown in A, a total of 2994 platelet proteins were captured by proteomics, and a total of 360 differential proteins were identified in MCI and AD patients compared with normal cognitive population (Pfigure 1 B); AD patients compared with normal cognitive population, 121 differential proteins were do...
Embodiment 2
[0049] According to the results obtained in Example 1, 26 core platelet proteins were defined as candidate proteins through MMSE correlation and pathway analysis, and the correlation coefficients between the 26 platelet candidate proteins and MMSE scores were further ranked, and the candidate proteins were ranked according to the Pearson correlation coefficient. Ranking of biomarkers (p figure 2 A), where the ratio of the shaded circle to the circle indicates the magnitude of the correlation, and the relative expression abundance of the candidate biomarkers is shown in figure 2 shown in B. As can be seen from the figure, the increase or decrease of candidate proteins was very uniform, and all 26 candidate proteins showed moderate MMSE correlation (|r|=0.371-0.552). Among them, the decrease of platelet CD63 showed the strongest correlation with MMSE score (r=0.552, P=0.002). The correlation coefficients (r) of antiproliferative protein, cytochrome b-c1 complex subunit 6, plat...
Embodiment 3
[0052] To explore the dynamics of the platelet proteome during cognitive decline, we performed clustering and protein-protein interaction (PPI) network analysis in MCI, AD and cognitively normal control populations. Compared with normal cognitive controls, differential proteins and related bioinformatics analysis results in MCI and AD patients are as follows: image 3 shown. image 3 In A, according to the change trend of differential proteins in Ctrl, MCI to AD groups, the differential proteins are divided into three clusters (each row represents one protein); image 3 In B, signal pathway enrichment analysis was performed on the differential proteins of the three clusters by Metascape online analysis (overlapping proteins≥3, P image 3 C represents the protein-protein interaction modules detected in the three clusters; image 3 D represents the biological function process in which the differential proteins are significantly enriched. Among them, the circle module represents...
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