Home > Publications database > Quantitative detection of α-Synuclein and Tau oligomers and other aggregates by digital single particle counting > print

001     909074
005     20230307160125.0
024 7 _ |a 10.1038/s41531-022-00330-x
|2 doi
024 7 _ |a 2128/31662
|2 Handle
024 7 _ |a 35655068
|2 pmid
024 7 _ |a WOS:000805184000001
|2 WOS
037 _ _ |a FZJ-2022-02992
082 _ _ |a 610
100 1 _ |a Blömeke, Lara
|0 P:(DE-Juel1)177730
|b 0
245 _ _ |a Quantitative detection of α-Synuclein and Tau oligomers and other aggregates by digital single particle counting
260 _ _ |a London [u.a.]
|c 2022
|b Nature Publ. Group
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 1661167779_2169
|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 The pathological hallmark of neurodegenerative diseases is the formation of toxic oligomers by proteins such as alpha-synuclein (aSyn) or microtubule-associated protein tau (Tau). Consequently, such oligomers are promising biomarker candidates for diagnostics as well as drug development. However, measuring oligomers and other aggregates in human biofluids is still challenging as extreme sensitivity and specificity are required. We previously developed surface-based fluorescence intensity distribution analysis (sFIDA) featuring single-particle sensitivity and absolute specificity for aggregates. In this work, we measured aSyn and Tau aggregate concentrations of 237 cerebrospinal fluid (CSF) samples from five cohorts: Parkinson's disease (PD), dementia with Lewy bodies (DLB), Alzheimer's disease (AD), progressive supranuclear palsy (PSP), and a neurologically-normal control group. aSyn aggregate concentration discriminates PD and DLB patients from normal controls (sensitivity 73%, specificity 65%, area under the receiver operating curve (AUC) 0.68). Tau aggregates were significantly elevated in PSP patients compared to all other groups (sensitivity 87%, specificity 70%, AUC 0.76). Further, we found a tight correlation between aSyn and Tau aggregate titers among all patient cohorts (Pearson coefficient of correlation r = 0.81). Our results demonstrate that aSyn and Tau aggregate concentrations measured by sFIDA differentiate neurodegenerative disease diagnostic groups. Moreover, sFIDA-based Tau aggregate measurements might be particularly useful in distinguishing PSP from other parkinsonisms. Finally, our findings suggest that sFIDA can improve pre-clinical and clinical studies by identifying those individuals that will most likely respond to compounds designed to eliminate specific oligomers or to prevent their formation.
536 _ _ |a 5244 - Information Processing in Neuronal Networks (POF4-524)
|0 G:(DE-HGF)POF4-5244
|c POF4-524
|f POF IV
|x 0
536 _ _ |a 520 - Natural, Artificial and Cognitive Information Processing (POF4-500)
|0 G:(DE-HGF)POF4-520
|c POF4-500
|f POF IV
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Pils, Marlene
|0 P:(DE-Juel1)171619
|b 1
700 1 _ |a Kraemer-Schulien, Victoria
|0 P:(DE-Juel1)172001
|b 2
700 1 _ |a Dybala, Alexandra
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Schaffrath, Anja
|0 P:(DE-Juel1)176527
|b 4
700 1 _ |a Kulawik, Andreas
|0 P:(DE-Juel1)162310
|b 5
700 1 _ |a Rehn, Fabian
|0 P:(DE-Juel1)190725
|b 6
700 1 _ |a Cousin, Anneliese
|0 P:(DE-Juel1)139572
|b 7
700 1 _ |a Nischwitz, Volker
|0 P:(DE-Juel1)157638
|b 8
700 1 _ |a Willbold, Johannes
|0 P:(DE-Juel1)159192
|b 9
700 1 _ |a Zack, Rebecca
|0 P:(DE-HGF)0
|b 10
700 1 _ |a Tropea, Thomas F.
|0 P:(DE-HGF)0
|b 11
700 1 _ |a Bujnicki, Tuyen
|0 P:(DE-Juel1)162212
|b 12
700 1 _ |a Tamgüney, Gültekin
|0 P:(DE-Juel1)177986
|b 13
700 1 _ |a Weintraub, Daniel
|0 P:(DE-HGF)0
|b 14
700 1 _ |a Irwin, David
|0 P:(DE-HGF)0
|b 15
700 1 _ |a Grossman, Murray
|0 P:(DE-HGF)0
|b 16
700 1 _ |a Wolk, David A.
|0 P:(DE-HGF)0
|b 17
700 1 _ |a Trojanowski, John Q.
|0 P:(DE-HGF)0
|b 18
700 1 _ |a Bannach, Oliver
|0 P:(DE-Juel1)157832
|b 19
700 1 _ |a Chen-Plotkin, Alice
|0 P:(DE-HGF)0
|b 20
700 1 _ |a Willbold, Dieter
|0 P:(DE-Juel1)132029
|b 21
|e Corresponding author
773 _ _ |a 10.1038/s41531-022-00330-x
|g Vol. 8, no. 1, p. 68
|0 PERI:(DE-600)2819218-7
|n 1
|p 68
|t npj Parkinson's Disease
|v 8
|y 2022
|x 2373-8057
856 4 _ |u https://juser.fz-juelich.de/record/909074/files/s41531-022-00330-x.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:909074
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)177730
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)171619
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)172001
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)176527
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)190725
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)139572
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 8
|6 P:(DE-Juel1)157638
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 12
|6 P:(DE-Juel1)162212
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 13
|6 P:(DE-Juel1)177986
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 19
|6 P:(DE-Juel1)157832
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 21
|6 P:(DE-Juel1)132029
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-524
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Molecular and Cellular Information Processing
|9 G:(DE-HGF)POF4-5244
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|x 1
914 1 _ |y 2022
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-09-03
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2020-09-03
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2020-09-03
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2021-10-13T14:34:28Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2021-10-13T14:34:28Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2021-10-13T14:34:28Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2022-11-11
915 p c |a Local Funding
|2 APC
|0 PC:(DE-HGF)0001
915 p c |a DFG OA Publikationskosten
|2 APC
|0 PC:(DE-HGF)0002
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IBI-7-20200312
|k IBI-7
|l Strukturbiochemie
|x 0
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IBI-7-20200312
980 _ _ |a APC

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21