Publication Detail
The publication detail shows the title, authors (with indicators showing other profiled authors), information on the publishing organization, abstract and a link to the article in PubMed. This abstract is what is used to create the fingerprint of the publication. If any grants are referenced by the publication, they will be listed here as well.
Development of biomarkers to chart all Alzheimer's disease stages: the royal road to cutting the therapeutic Gordian Knot.
Harald Hampel; Simone Lista; Zaven S Khachaturian (Profiled Author: Zaven Khachaturian)
Department of Psychiatry, University of Frankfurt, Frankfurt am Main, Germany. harald.hampel@med.uni-muenchen.de
Alzheimer's & dementia : the journal of the Alzheimer's Association 2012;8(4):312-36.
The aim of this perspective article is to stimulate radical shifts in thinking and foster further discussion on the effective discovery, development, validation, and qualification process of biological markers derived from all available technical modalities that meet the complex conceptual and pathophysiological challenges across all stages of the complex, nonlinear, dynamic, and chronically progressive sporadic Alzheimer's disease (AD). This perspective evaluates the current state of the science regarding a broad spectrum of hypothesis-driven and exploratory technologies and "markers" as candidates for all required biomarker functions, in particular, surrogate indicators of adaptive to maladaptive and compensatory to decompensatory, reversible to irreversible brain "systems failure." We stress the future importance of the systems biology (SB) paradigm (next to the neural network paradigm) for substantial progress in AD research. SB represents an integrated and deeper investigation of interacting biomolecules within cells and organisms. This approach has only recently become feasible as high-throughput technologies and mass spectrometric analyses of proteins and lipids, together with rigorous bioinformatics, have evolved. Existing high-content data derived from clinically and experimentally derived neural tissues point to convergent pathophysiological pathways during the course of AD, transcending traditional descriptive studies to reach a more integrated and comprehensive understanding of AD pathophysiology, derived systems biomarkers, and "druggable" system nodes. The discussion is continued on the premise that the lack of integration of advanced biomarker technologies and transfertilization from more mature translational research fields (e.g., oncology, immunology, cardiovascular), which satisfy regulatory requirements for an accurate, sensitive, and well-validated surrogate marker of specific pathophysiological processes and/or clinical outcomes, is a major rate-limiting factor for the successful development and approval of effective treatments for AD prevention. We consider the conceptual, scientific, and technical challenges for the discovery-development-validation-qualification process of biomarker tools and analytical algorithms for detection of the earliest pathophysiological processes in asymptomatic individuals at elevated risk during preclinical stages of AD. The most critical need for rapid translation of putative markers into validated (performance) and standardized (harmonized standard operating procedures) biomarker tools that fulfill regulatory requirements (qualify for use in treatment trials: e.g., safety, target engagement, mechanism of action, enrichment, stratification, secondary and primary outcome, surrogate outcome) is the availability of a large-scale worldwide comprehensive longitudinal database that includes the following cohorts: (a) healthy aging, (b) people at elevated risks (genetic/epigenetic/lifestyle/comorbid conditions), and (c) asymptomatic-preclinical/prodromal-mild cognitive impairment/syndromal mild, moderate, or severe AD. Our proposal, as initial strategic steps for integrating markers into future development of diagnostic and therapy trial technologies, is to work toward: (a) creating the essential research and development infrastructure as an international shared resource, (b) building the organizational structure for managing such a multinational shared resource, and (c) establishing an integrated transsectoral multidisciplinary global network of collaborating investigators to help build and use the shared research resource.
Scientific Context
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