| Literature DB >> 32284590 |
Erik C B Johnson1,2, Eric B Dammer3,4, Duc M Duong3,4, Lingyan Ping3,5,4, Maotian Zhou3,5,4, Luming Yin4, Lenora A Higginbotham5, Andrew Guajardo6, Bartholomew White6, Juan C Troncoso6, Madhav Thambisetty7, Thomas J Montine8, Edward B Lee9, John Q Trojanowski9, Thomas G Beach10, Eric M Reiman11, Vahram Haroutunian12,13, Minghui Wang14, Eric Schadt14, Bin Zhang14, Dennis W Dickson15, Nilüfer Ertekin-Taner15,16, Todd E Golde17, Vladislav A Petyuk18, Philip L De Jager19, David A Bennett20, Thomas S Wingo3,5,21, Srikant Rangaraju5, Ihab Hajjar5, Joshua M Shulman22,23, James J Lah3,5, Allan I Levey24,25, Nicholas T Seyfried26,27,28.
Abstract
Our understanding of Alzheimer's disease (AD) pathophysiology remains incomplete. Here we used quantitative mass spectrometry and coexpression network analysis to conduct the largest proteomic study thus far on AD. A protein network module linked to sugar metabolism emerged as one of the modules most significantly associated with AD pathology and cognitive impairment. This module was enriched in AD genetic risk factors and in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from this module were elevated in cerebrospinal fluid in early stages of the disease. In this study of >2,000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brains that may serve as therapeutic targets and fluid biomarkers for the disease.Entities:
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Year: 2020 PMID： 32284590 PMCID： PMC7405761 DOI： 10.1038/s41591-020-0815-6
Source DB: PubMed Journal: Nat Med ISSN： 1078-8956 Impact factor: 53.440