What amyloid ligands can tell us about molecular polymorphism and disease

• Type of Material: Article
• Authors: Lary Walker, Emory University; Harry LeVine III, University of Kentucky
• Language: English
• Date: 2016-03-23
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2017 Elsevier Inc. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.neurobiolaging.2016.03.019
• Title of Journal or Parent Work: Neurobiology of Aging
• ISSN: 0197-4580
• Volume: 42
• Start Page: 205
• End Page: 212
• Grant/Funding Information: This work was supported by NIH grant R21 NS080576-01A1 (to H.L.), NIH Center Core grant P30AG028383 (University of Kentucky Alzheimer’s Disease Center), NIH grants P50AG025688 (Emory University Alzheimer’s Disease Research Center), RR000165 and OD1113 (Yerkes National Primate Research Center), the CART Foundation (to H.L. and L.W.), and the MetLife Foundation (to L.W.).
• Keywords: tau; strains; Alzheimer; Abeta; plaques; lipids; proteopathy; tangles
• Research Categories: Biology, Molecular; Biology, Neuroscience

Abstract

Brain-penetrant PET imaging ligands selective for amyloid pathology in living subjects have sparked a revolution in presymptomatic biomarkers for Alzheimer’s disease progression. As additional chemical structures were investigated, the heterogeneity of ligand binding sites became apparent, as did discrepancies in binding of some ligands between human disease and animal models. These differences and their implications have received little attention. This review discusses the impact of different ligand binding sites and misfolded protein conformational polymorphism on the interpretation of imaging data acquired with different ligands. Investigation of the differences in binding in animal models may identify pathological processes informing improvements to these models for more faithful recapitulation of this uniquely human disease. The differential selectivity for binding of particular ligands to different conformational states could potentially be harnessed to better define disease progression and improve the prediction of clinical outcomes.