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Articles by Harald Hampel
Total Records ( 4 ) for Harald Hampel
  Maria C. Carrillo , Andrew Blackwell , Harald Hampel , Johan Lindborg , Reisa Sperling , Dale Schenk , Jeffrey J. Sevigny , Steven Ferris , David A. Bennett , Suzanne Craft , Timothy Hsu and William Klunk
  The purpose of the Alzheimer's Association Research Roundtable meeting was to discuss the potential of finding diagnostic tools to determine the earliest risk factors for Alzheimer's disease (AD). Currently, drugs approved for AD address symptoms which are generally manifest after the disease is already well-established, but there is a growing pipeline of drugs that may alter the underlying pathology and therefore slow or halt progression of the disease. As these drugs become available, it will become increasingly imperative that those at risk for AD be detected and possibly treated early, especially given recent indications that the disease process may start decades before the first clinical symptoms are recognized. Early detection must go hand-in-hand with qualified tools to determine the efficacy of drugs in people who may be asymptomatic or who have only very mild symptoms of the disease. Devising strategies and screening tools to identify and monitor those at risk in order to perform ”prevention” trials is seen by many as a top public-health priority, made all the more urgent by an impending growth in the elderly population worldwide.
  Niklas Mattsson , Ulf Andreasson , Staffan Persson , Hiroyuki Arai , Sat Dev Batish , Sergio Bernardini , Luisella Bocchio- Chiavetto , Marinus A. Blankenstein , Maria C. Carrillo , Sonia Chalbot , Els Coart , Davide Chiasserini , Neal Cutler , Gunilla Dahlfors , Stefan Duller , Anne M. Fagan , Orestes Forlenza , Giovanni B. Frisoni , Douglas Galasko , Daniela Galimberti , Harald Hampel , Aase Handberg , Michael T. Heneka , Adrianna Z. Herskovits , Sanna-Kaisa Herukka , David M. Holtzman , Christian Humpel , Bradley T. Hyman , Khalid Iqbal , Khalid Iqbal , Stephan A. Kaeser , Elmar Kaiser , Elisabeth Kapaki , Daniel Kidd , Peter Klivenyi , Cindy S. Knudsen , Markus P. Kummer , James Lui , Albert Llado , Piotr Lewczuk , Qiao-Xin Li , Ralph Martins , Colin Masters , John McAuliffe , Marc Mercken , Abhay Moghekar , Jose Luis Molinuevo , Thomas J. Montine , William Nowatzke , Richard O’Brien , Markus Otto , George P. Paraskevas , Lucilla Parnetti , Ronald C. Petersen , David Prvulovic , Herman P.M. de Reus , Robert A. Rissman , Elio Scarpini , Alessandro Stefani , Hilkka Soininen , Johannes Schroder , Leslie M. Shaw , Anders Skinningsrud , Brith Skrogstad and Annette Spreer
  Background The cerebrospinal fluid (CSF) biomarkers amyloid β (Aβ)-42, total-tau (T-tau), and phosphorylated-tau (P-tau) demonstrate good diagnostic accuracy for Alzheimer‘s disease (AD). However, there are large variations in biomarker measurements between studies, and between and within laboratories. The Alzheimer‘s Association has initiated a global quality control program to estimate and monitor variability of measurements, quantify batch-to-batch assay variations, and identify sources of variability. In this article, we present the results from the first two rounds of the program. Methods The program is open for laboratories using commercially available kits for Aβ, T-tau, or P-tau. CSF samples (aliquots of pooled CSF) are sent for analysis several times a year from the Clinical Neurochemistry Laboratory at the Molndal campus of the University of Gothenburg, Sweden. Each round consists of three quality control samples. Results Forty laboratories participated. Twenty-six used INNOTEST enzyme-linked immunosorbent assay kits, 14 used Luminex xMAP with the INNO-BIA AlzBio3 kit (both measure Aβ-(1-42), P-tau(181P), and T-tau), and 5 used Meso Scale Discovery with the Aβ triplex (AβN-42, AβN-40, and AβN-38) or T-tau kits. The total coefficients of variation between the laboratories were 13% to 36%. Five laboratories analyzed the samples six times on different occasions. Within-laboratory precisions differed considerably between biomarkers within individual laboratories. Conclusions Measurements of CSF AD biomarkers show large between-laboratory variability, likely caused by factors related to analytical procedures and the analytical kits. Standardization of laboratory procedures and efforts by kit vendors to increase kit performance might lower variability, and will likely increase the usefulness of CSF AD biomarkers.
  Clifford R. Jack , Frederik Barkhof , Matt A. Bernstein , Marc Cantillon , Patricia E. Cole , Charles DeCarli , Bruno Dubois , Simon Duchesne , Nick C. Fox , Giovanni B. Frisoni , Harald Hampel , Derek L.G. Hill , Keith Johnson , Jean-Francois Mangin , Philip Scheltens , Adam J. Schwarz , Reisa Sperling , Joyce Suhy , Paul M. Thompson , Michael Weiner and Norman L. Foster
  Background The promise of Alzheimer‘s disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer‘s disease and thus represents the most rational target for an initial effort at standardization. Methods and Results The authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer‘s Disease Centers–Alzheimer‘s Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer‘s Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark. Conclusions Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.
  Harald Hampel , Simone Lista and Zaven S. Khachaturian
  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.
 
 
 
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