Multi-proteomic analyses of 5xFAD mice reveal new molecular signatures of early-stage Alzheimer's disease

Seulah Lee, Kuk-In Jang, Hagyeong Lee,Yeon Suk Jo, Dayoung Kwon, Geuna Park,Sungwon Bae,Yang Woo Kwon, Jin-Hyeok Jang,Yong-Seok Oh, Chany Lee,Jong Hyuk Yoon

AGING CELL(2024)

引用 0|浏览4
暂无评分
摘要
An early diagnosis of Alzheimer's disease is crucial as treatment efficacy is limited to the early stages. However, the current diagnostic methods are limited to mid or later stages of disease development owing to the limitations of clinical examinations and amyloid plaque imaging. Therefore, this study aimed to identify molecular signatures including blood plasma extracellular vesicle biomarker proteins associated with Alzheimer's disease to aid early-stage diagnosis. The hippocampus, cortex, and blood plasma extracellular vesicles of 3- and 6-month-old 5xFAD mice were analyzed using quantitative proteomics. Subsequent bioinformatics and biochemical analyses were performed to compare the molecular signatures between wild type and 5xFAD mice across different brain regions and age groups to elucidate disease pathology. There was a unique signature of significantly altered proteins in the hippocampal and cortical proteomes of 3- and 6-month-old mice. The plasma extracellular vesicle proteomes exhibited distinct informatic features compared with the other proteomes. Furthermore, the regulation of several canonical pathways (including phosphatidylinositol 3-kinase/protein kinase B signaling) differed between the hippocampus and cortex. Twelve potential biomarkers for the detection of early-stage Alzheimer's disease were identified and validated using plasma extracellular vesicles from stage-divided patients. Finally, integrin alpha-IIb, creatine kinase M-type, filamin C, glutamine gamma-glutamyltransferase 2, and lysosomal alpha-mannosidase were selected as distinguishing biomarkers for healthy individuals and early-stage Alzheimer's disease patients using machine learning modeling with approximately 79% accuracy. Our study identified novel early-stage molecular signatures associated with the progression of Alzheimer's disease, thereby providing novel insights into its pathogenesis. In this study, multi-proteomic analyses revealed molecular signatures that can aid the elucidation of AD pathology. Moreover, our study identified candidate blood plasma EV biomarkers for the diagnosis of early-stage AD, which included A2M, CKM, FLNA, ITGA2B, ORM2, PLTP, HP, QSOX1, TGM2, FLNC, HSP70, and MAN2B1.image
更多
查看译文
关键词
Alzheimer's disease,biomarker,early-stage Alzheimer's disease,extracellular vesicle,machine learning,proteomics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要