Bai, Bing, Wang, Xusheng, Li, Yuxin, Chen, Ping-Chung, Yu, Kaiwen, Dey, Kaushik Kumar, Yarbro, Jay M., Han, Xian, Lutz, Brianna M., Rao, Shuquan, Jiao, Yun, Sifford, Jeffrey M., Han, Jonghee, Wang, Minghui, Tan, Haiyan, Shaw, Timothy I., Cho, Ji-Hoon, Zhou, Suiping, Wang, Hong, and Niu, Mingming
Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression. • Deep profiling of proteome and phosphoproteome in AD progression • Validation of protein alterations in two independent AD cohorts • Identification of Aβ-induced protein changes in AD and the 5xFAD mouse model • Prioritization of proteins and pathways in AD by multi-omics integration By mass spectrometry-based proteomics and integrated multi-omics, Bai et al. reveal novel proteins and molecular networks during Alzheimer's disease progression and validate the proteins in 5xFAD mice. Further comparisons of brain tissue and cerebrospinal fluid proteomes identify biomarker candidates. [ABSTRACT FROM AUTHOR]