To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

Inflammatory biomarkers i… - University of Gothenburg, Sweden Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

Inflammatory biomarkers in Alzheimer's disease plasma.

Journal article
Authors Angharad R Morgan
Samuel Touchard
Claire Leckey
Caroline O'Hagan
Alejo J Nevado-Holgado
Frederik Barkhof
Lars Bertram
Olivier Blin
Isabelle Bos
Valerija Dobricic
Sebastiaan Engelborghs
Giovanni Frisoni
Lutz Frölich
Silvey Gabel
Peter Johannsen
Petronella Kettunen
Iwona Kłoszewska
Cristina Legido-Quigley
Alberto Lleó
Pablo Martinez-Lage
Patrizia Mecocci
Karen Meersmans
José Luis Molinuevo
Gwendoline Peyratout
Julius Popp
Jill Richardson
Isabel Sala
Philip Scheltens
Johannes Streffer
Hikka Soininen
Mikel Tainta-Cuezva
Charlotte Teunissen
Magda Tsolaki
Rik Vandenberghe
Pieter Jelle Visser
Stephanie Vos
Lars-Olof Wahlund
Anders Wallin
Sarah Westwood
Henrik Zetterberg
Simon Lovestone
B Paul Morgan
Published in Alzheimer's & dementia : the journal of the Alzheimer's Association
Volume 15
Issue 6
Pages 776-787
ISSN 1552-5279
Publication year 2019
Published at Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry
Pages 776-787
Language en
Links dx.doi.org/10.1016/j.jalz.2019.03.0...
www.ncbi.nlm.nih.gov/entrez/query.f...
Subject categories Clinical Medicine

Abstract

Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers.A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.

Page Manager: Webmaster|Last update: 9/11/2012
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?