Background Alzheimer’s disease (AD) early diagnosis remains difficult due to limitations in clinical exams and amyloid plaque imaging. Methods In the present study, the hippocampus, cortex, and blood plasma extracellular vesicles (EVs) from 3- and 6-month-old 5xFAD mice were analysed by reliable quantitative proteomics approach. Results The 3- and 6-month-old hippocampus and cortex proteome in both the age groups showed similar features in functional annotation and canonical pathway analysis, but the significantly changed proteins were rarely overlapped. Furthermore, the plasma EVs proteome showed significantly different informatic features compared with other proteomes. Depending on the AD stage, proteomic profiles undergo drastic changes in brain subregion- and in tissue-specific manners. Notably, regulations of several canonical pathways, including PI3K/Akt signalling, were differing between the hippocampus and cortex. Furthermore, we identified eight potential biomarkers that can detect early-stage AD (integrin alpha-IIb (ITGA2B), sulfhydryl oxidase 1, phospholipid transfer protein, talin (TLN), heat shock 70 kDa protein 1 (HSPA1L), alpha-2 macroglobulin (A2M), platelet factor 4, and filamin A (FLNA)) and validated them, using plasma EVs of stage-divided patients with AD. Conclusion ITGA2B, TLN, HSPA1L, and A2M were finally selected by machine learning modelling as distinguishing biomarkers for normal and early-stage AD with 85% accuracy. The present study provides insights into AD pathogenesis and identifies novel early-stage AD biomarkers.