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024 | 7 | _ | |a pmc:PMC9214531 |2 pmc |
024 | 7 | _ | |a 10.1073/pnas.2119804119 |2 doi |
024 | 7 | _ | |a 0027-8424 |2 ISSN |
024 | 7 | _ | |a 1091-6490 |2 ISSN |
024 | 7 | _ | |a altmetric:129361312 |2 altmetric |
024 | 7 | _ | |a pmid:35666874 |2 pmid |
037 | _ | _ | |a DZNE-2022-01184 |
082 | _ | _ | |a 500 |
100 | 1 | _ | |a Eninger, Timo |0 P:(DE-2719)2811141 |b 0 |e First author |
245 | _ | _ | |a Signatures of glial activity can be detected in the CSF proteome |
260 | _ | _ | |a Washington, DC |c 2022 |b National Acad. of Sciences |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1709304208_5354 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a Single-cell transcriptomics has revealed specific glial activation states associated with the pathogenesis of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease. While these findings may eventually lead to new therapeutic opportunities, little is known about how these glial responses are reflected by biomarker changes in bodily fluids. Such knowledge, however, appears crucial for patient stratification, as well as monitoring disease progression and treatment responses in clinical trials. Here, we took advantage of well-described mouse models of β-amyloidosis and α-synucleinopathy to explore cerebrospinal fluid (CSF) proteome changes related to their respective proteopathic lesions. Nontargeted liquid chromatography-mass spectrometry revealed that the majority of proteins that undergo age-related changes in CSF of either mouse model were linked to microglia and astrocytes. Specifically, we identified a panel of more than 20 glial-derived proteins that were increased in CSF of aged β-amyloid precursor protein- and α-synuclein-transgenic mice and largely overlap with previously described disease-associated glial genes identified by single-cell transcriptomics. Our results also show that enhanced shedding is responsible for the increase of several of the identified glial CSF proteins as exemplified for TREM2. Notably, the vast majority of these proteins can also be quantified in human CSF and reveal changes in Alzheimer’s disease cohorts. The finding that cellular transcriptome changes translate into corresponding changes of CSF proteins is of clinical relevance, supporting efforts to identify fluid biomarkers that reflect the various functional states of glial responses in cerebral proteopathies, such as Alzheimer’s and Parkinson’s disease. |
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650 | _ | 2 | |a Alzheimer Disease: cerebrospinal fluid |2 MeSH |
650 | _ | 2 | |a Alzheimer Disease: metabolism |2 MeSH |
650 | _ | 2 | |a Animals |2 MeSH |
650 | _ | 2 | |a Biomarkers: cerebrospinal fluid |2 MeSH |
650 | _ | 2 | |a Cerebrospinal Fluid: metabolism |2 MeSH |
650 | _ | 2 | |a Gene Expression Profiling |2 MeSH |
650 | _ | 2 | |a Humans |2 MeSH |
650 | _ | 2 | |a Mice |2 MeSH |
650 | _ | 2 | |a Neuroglia: metabolism |2 MeSH |
650 | _ | 2 | |a Parkinson Disease: cerebrospinal fluid |2 MeSH |
650 | _ | 2 | |a Parkinson Disease: metabolism |2 MeSH |
650 | _ | 2 | |a Proteome: metabolism |2 MeSH |
650 | _ | 2 | |a Single-Cell Analysis |2 MeSH |
650 | _ | 2 | |a tau Proteins |2 MeSH |
700 | 1 | _ | |a Müller, Stephan A. |0 P:(DE-2719)2810938 |b 1 |
700 | 1 | _ | |a Bacioglu, Mehtap |0 P:(DE-2719)2810940 |b 2 |
700 | 1 | _ | |a Schweighauser, Manuel |0 P:(DE-2719)9000294 |b 3 |
700 | 1 | _ | |a Lambert, Marius |0 P:(DE-2719)2810762 |b 4 |
700 | 1 | _ | |a Maia, Luis F. |0 P:(DE-2719)9000196 |b 5 |
700 | 1 | _ | |a Neher, Jonas |0 P:(DE-2719)2811021 |b 6 |
700 | 1 | _ | |a Hornfeck, Sarah M |0 P:(DE-2719)9002482 |b 7 |u dzne |
700 | 1 | _ | |a Obermüller, Ulrike |0 P:(DE-2719)2814201 |b 8 |
700 | 1 | _ | |a Kleinberger, Gernot |0 P:(DE-2719)9000907 |b 9 |
700 | 1 | _ | |a Haass, Christian |0 P:(DE-2719)2202037 |b 10 |
700 | 1 | _ | |a Kahle, Philipp |0 P:(DE-2719)2810803 |b 11 |
700 | 1 | _ | |a Staufenbiel, Matthias |0 P:(DE-2719)9000301 |b 12 |
700 | 1 | _ | |a Ping, Lingyan |b 13 |
700 | 1 | _ | |a Duong, Duc M. |b 14 |
700 | 1 | _ | |a Levey, Allan I. |0 0000-0002-3153-502X |b 15 |
700 | 1 | _ | |a Seyfried, Nicholas T. |b 16 |
700 | 1 | _ | |a Lichtenthaler, Stefan |0 P:(DE-2719)2181459 |b 17 |
700 | 1 | _ | |a Jucker, Mathias |0 P:(DE-2719)2000010 |b 18 |
700 | 1 | _ | |a Kaeser, Stephan A. |0 P:(DE-2719)9000387 |b 19 |e Last author |
773 | _ | _ | |a 10.1073/pnas.2119804119 |g Vol. 119, no. 24, p. e2119804119 |0 PERI:(DE-600)1461794-8 |n 24 |p e2119804119 |t Proceedings of the National Academy of Sciences of the United States of America |v 119 |y 2022 |x 0027-8424 |
856 | 4 | _ | |u https://pub.dzne.de/record/164654/files/DZNE-2022-01184.pdf |y OpenAccess |
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