| Literature DB >> 31926610 |
Bing Bai1, Xusheng Wang2, Yuxin Li3, Ping-Chung Chen1, Kaiwen Yu1, Kaushik Kumar Dey1, Jay M Yarbro4, Xian Han4, Brianna M Lutz1, Shuquan Rao1, Yun Jiao1, Jeffrey M Sifford1, Jonghee Han5, Minghui Wang6, Haiyan Tan7, Timothy I Shaw8, Ji-Hoon Cho7, Suiping Zhou7, Hong Wang4, Mingming Niu1, Ariana Mancieri1, Kaitlynn A Messler1, Xiaojun Sun1, Zhiping Wu1, Vishwajeeth Pagala7, Anthony A High7, Wenjian Bi9, Hui Zhang9, Hongbo Chi10, Vahram Haroutunian6, Bin Zhang11, Thomas G Beach12, Gang Yu5, Junmin Peng13.
Abstract
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.Entities:
Keywords: Alzheimer’s disease; biomarker; cerebrospinal fluid; genomics; mass spectrometry; multi-omics; phosphoproteome; proteome; proteomics; systems biology
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Year: 2020 PMID: 31926610 PMCID: PMC7318843 DOI: 10.1016/j.neuron.2019.12.015
Source DB: PubMed Journal: Neuron ISSN: 0896-6273 Impact factor: 17.173