Daniel S Spellman1, Kristin R Wildsmith2, Lee A Honigberg2, Marianne Tuefferd3, David Baker4, Nandini Raghavan4, Angus C Nairn5, Pascal Croteau6, Michael Schirm6, Rene Allard6, Julie Lamontagne6, Daniel Chelsky6, Steven Hoffmann7, William Z Potter8. 1. Department of Pharmacokinetics, Pharmacodynamics and Drug Metabolism, Merck Research Laboratories, Pennsylvania, PA, USA. 2. Department of Pharmacodynamic Biomarkers within Development Sciences, Genentech, Inc (a member of the Roche Group), South San Francisco, CA, USA. 3. Discovery Sciences, Janssen Research & Development LLC, Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium. 4. Janssen Research & Development LLC, Titusville, NJ, USA. 5. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA. 6. Caprion Pharmaceuticals, Montreal, QC, Canada. 7. Foundation for the National Institutes of Health, Inc, Bethesda, MD, USA. 8. National Institute of Mental Health, Bethesda, MD, USA.
Abstract
PURPOSE: We describe the outcome of the Biomarkers Consortium CSF Proteomics Project (where CSF is cerebral spinal fluid), a public-private partnership of government, academia, nonprofit, and industry. The goal of this study was to evaluate a multiplexed MS-based approach for the qualification of candidate Alzheimer's disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative. EXPERIMENTAL DESIGN: Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (mild cognitive impairment (MCI), AD) versus healthy controls or associated with progression for MCI patients, and included (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis. RESULTS: A robust targeted MS-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from hemoglobin A, hemoglobin B, and superoxide dismutase) or predicting (including peptides from neuronal pentraxin-2, neurosecretory protein VGF (VGF), and secretogranin-2) progression versus nonprogression from MCI to AD. CONCLUSIONS AND CLINICAL RELEVANCE: These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis.
PURPOSE: We describe the outcome of the Biomarkers Consortium CSF Proteomics Project (where CSF is cerebral spinal fluid), a public-private partnership of government, academia, nonprofit, and industry. The goal of this study was to evaluate a multiplexed MS-based approach for the qualification of candidate Alzheimer's disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative. EXPERIMENTAL DESIGN: Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (mild cognitive impairment (MCI), AD) versus healthy controls or associated with progression for MCI patients, and included (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis. RESULTS: A robust targeted MS-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from hemoglobin A, hemoglobin B, and superoxide dismutase) or predicting (including peptides from neuronal pentraxin-2, neurosecretory protein VGF (VGF), and secretogranin-2) progression versus nonprogression from MCI to AD. CONCLUSIONS AND CLINICAL RELEVANCE: These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis.
Authors: Barbara J Snider; Anne M Fagan; Catherine Roe; Aarti R Shah; Elizabeth A Grant; Chengjie Xiong; John C Morris; David M Holtzman Journal: Arch Neurol Date: 2009-05
Authors: Terri A Addona; Susan E Abbatiello; Birgit Schilling; Steven J Skates; D R Mani; David M Bunk; Clifford H Spiegelman; Lisa J Zimmerman; Amy-Joan L Ham; Hasmik Keshishian; Steven C Hall; Simon Allen; Ronald K Blackman; Christoph H Borchers; Charles Buck; Helene L Cardasis; Michael P Cusack; Nathan G Dodder; Bradford W Gibson; Jason M Held; Tara Hiltke; Angela Jackson; Eric B Johansen; Christopher R Kinsinger; Jing Li; Mehdi Mesri; Thomas A Neubert; Richard K Niles; Trenton C Pulsipher; David Ransohoff; Henry Rodriguez; Paul A Rudnick; Derek Smith; David L Tabb; Tony J Tegeler; Asokan M Variyath; Lorenzo J Vega-Montoto; Asa Wahlander; Sofia Waldemarson; Mu Wang; Jeffrey R Whiteaker; Lei Zhao; N Leigh Anderson; Susan J Fisher; Daniel C Liebler; Amanda G Paulovich; Fred E Regnier; Paul Tempst; Steven A Carr Journal: Nat Biotechnol Date: 2009-06-28 Impact factor: 54.908
Authors: Trey Sunderland; Gary Linker; Nadeem Mirza; Karen T Putnam; David L Friedman; Lida H Kimmel; Judy Bergeson; Guy J Manetti; Matthew Zimmermann; Brian Tang; John J Bartko; Robert M Cohen Journal: JAMA Date: 2003 Apr 23-30 Impact factor: 56.272
Authors: Nelleke Tolboom; Wiesje M van der Flier; Maqsood Yaqub; Ronald Boellaard; Nicolaas A Verwey; Marinus A Blankenstein; Albert D Windhorst; Philip Scheltens; Adriaan A Lammertsma; Bart N M van Berckel Journal: J Nucl Med Date: 2009-08-18 Impact factor: 10.057
Authors: Karl T Hansson; Tobias Skillbäck; Elin Pernevik; Jessica Holmén-Larsson; Gunnar Brinkmalm; Kaj Blennow; Henrik Zetterberg; Johan Gobom Journal: J Vis Exp Date: 2017-12-04 Impact factor: 1.355