Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2019Plasma biomarkers for amyloid, tau, and cytokines in Down syndrome and sporadic Alzheimer's disease71citations
  • 2017Lessons Learned from Large-Diameter Pipe Failure Case Studies9citations

Places of action

Chart of shared publication
Strydom, Andre
1 / 3 shared
Hamburg, Sarah
1 / 1 shared
Hithersay, Rosalyn Jane
1 / 1 shared
Ashton, Nicholas J.
1 / 1 shared
Wiseman, Frances K.
1 / 1 shared
Mok, Kin Y.
1 / 1 shared
Startin, Carla
1 / 1 shared
Hardy, John
1 / 7 shared
Tybulewicz, Victor
1 / 1 shared
Karmiloff-Smith, Annette
1 / 1 shared
Zetterberg, Henrik
1 / 4 shared
Al-Janabi, Tamara
1 / 1 shared
Lovestone, Simon
1 / 1 shared
Lleó, Alberto
1 / 1 shared
Hye, Abdul
1 / 1 shared
Parnetti, Lucilla
1 / 1 shared
Fisher, Elizabeth
1 / 1 shared
Nizetic, Dean
1 / 1 shared
Zhang, Jian
1 / 13 shared
Blaha, Frank
1 / 1 shared
Crawly, Craig
1 / 1 shared
Chart of publication period
2019
2017

Co-Authors (by relevance)

  • Strydom, Andre
  • Hamburg, Sarah
  • Hithersay, Rosalyn Jane
  • Ashton, Nicholas J.
  • Wiseman, Frances K.
  • Mok, Kin Y.
  • Startin, Carla
  • Hardy, John
  • Tybulewicz, Victor
  • Karmiloff-Smith, Annette
  • Zetterberg, Henrik
  • Al-Janabi, Tamara
  • Lovestone, Simon
  • Lleó, Alberto
  • Hye, Abdul
  • Parnetti, Lucilla
  • Fisher, Elizabeth
  • Nizetic, Dean
  • Zhang, Jian
  • Blaha, Frank
  • Crawly, Craig
OrganizationsLocationPeople

article

Plasma biomarkers for amyloid, tau, and cytokines in Down syndrome and sporadic Alzheimer's disease

  • Strydom, Andre
  • Hamburg, Sarah
  • Hithersay, Rosalyn Jane
  • Ashton, Nicholas J.
  • Wiseman, Frances K.
  • Mok, Kin Y.
  • Startin, Carla
  • Hardy, John
  • Tybulewicz, Victor
  • Karmiloff-Smith, Annette
  • Zetterberg, Henrik
  • Al-Janabi, Tamara
  • Zhang, David
  • Lovestone, Simon
  • Lleó, Alberto
  • Hye, Abdul
  • Parnetti, Lucilla
  • Fisher, Elizabeth
  • Nizetic, Dean
Abstract

Background: Down syndrome (DS), caused by chromosome 21 trisomy, is associated with an ultra-high risk of dementia due to Alzheimer’s disease (AD), driven by amyloid precursor protein (APP) gene triplication. Understanding relevant molecular differences between those with DS, those with sporadic AD (sAD) without DS, and controls will aid in understanding AD development in DS. We explored group differences in plasma concentrations of amyloid-β peptides and tau (as their accumulation is a characteristic feature of AD) and cytokines (as the inflammatory response has been implicated in AD development, and immune dysfunction is common in DS).<br/><br/>Methods: We used ultrasensitive assays to compare plasma concentrations of the amyloid-β peptides Aβ40 and Aβ42, total tau (t-tau), and the cytokines IL1β, IL10, IL6, and TNFα between adults with DS (n=31), adults with sAD (n=27), and controls age-matched to the group with DS (n=27), and explored relationships between molecular concentrations and with age within each group. In the group with DS, we also explored relationships with neurofilament light (NfL) concentration, due to its potential use as a biomarker for AD in DS.<br/><br/>Results: Aβ40, Aβ42, and IL1β concentrations were higher in DS, with a higher Aβ42/Aβ40 ratio in controls. The group with DS showed moderate positive associations between concentrations of t-tau and both Aβ42 and IL1β. Only NfL concentration in the group with DS showed a significant positive association with age.<br/><br/>Conclusions: Concentrations of Aβ40 and Aβ42 were much higher in adults with DS than in other groups, reflecting APP gene triplication, while no difference in the Aβ42/Aβ40 ratio between those with DS and sAD may indicate similar processing and deposition of Aβ40 and Aβ42 in these groups. Higher concentrations of IL1β in DS may reflect an increased vulnerability to infections and/or an increased prevalence of autoimmune disorders, while the positive association between IL1β and t-tau in DS may indicate IL1β is associated with neurodegeneration. Finally, NfL concentration may be the most suitable biomarker for dementia progression in DS. The identification of such a biomarker is important to improve the detection of dementia and monitor its progression, and for designing clinical intervention studies.

Topics
  • Deposition
  • impedance spectroscopy