Literature DB >> 21282074

Transforming cerebrospinal fluid Aβ42 measures into calculated Pittsburgh Compound B units of brain Aβ amyloid.

Stephen D Weigand1, Prashanthi Vemuri, Heather J Wiste, Matthew L Senjem, Vernon S Pankratz, Paul S Aisen, Michael W Weiner, Ronald C Petersen, Leslie M Shaw, John Q Trojanowski, David S Knopman, Clifford R Jack.   

Abstract

BACKGROUND: Positron-emission tomography (PET) imaging of amyloid with Pittsburgh Compound B (PIB) and Aβ42 levels in the cerebrospinal fluid (CSF Aβ42) demonstrate a highly significant inverse correlation. Both these techniques are presumed to measure brain Aβ amyloid load. The objectives of this study were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects.
METHODS: In all, 41 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the "training" sample (nine cognitively normal subjects, 22 subjects with mild cognitive impairment, and 10 subjects with Alzheimer's disease), was used to develop a regression model by which CSF Aβ42 (with apolipoprotein E ɛ4 carrier status as a covariate) was transformed into units of PIB PET (PIBcalc). An independent "supporting" sample of 362 ADNI subjects (105 cognitively normal subjects, 164 subjects with mild cognitive impairment, and 93 subjects with Alzheimer's disease) who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared with the overall PIB PET distribution found in the ADNI subjects (n=102).
RESULTS: A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R(2)=0.77, P<.001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrate group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies.
CONCLUSION: Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into PIBcalc measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based PIBcalc value.
Copyright © 2011 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21282074      PMCID: PMC3060961          DOI: 10.1016/j.jalz.2010.08.230

Source DB:  PubMed          Journal:  Alzheimers Dement        ISSN: 1552-5260            Impact factor:   21.566


  37 in total

1.  Pittsburgh compound-B and Alzheimer's disease biomarkers in CSF, plasma and urine: An exploratory study.

Authors:  M Degerman Gunnarsson; M Lindau; A Wall; K Blennow; T Darreh-Shori; S Basu; A Nordberg; A Larsson; L Lannfelt; H Basun; L Kilander
Journal:  Dement Geriatr Cogn Disord       Date:  2010-03-20       Impact factor: 2.959

2.  Serial MRI and CSF biomarkers in normal aging, MCI, and AD.

Authors:  P Vemuri; H J Wiste; S D Weigand; D S Knopman; J Q Trojanowski; L M Shaw; M A Bernstein; P S Aisen; M Weiner; R C Petersen; C R Jack
Journal:  Neurology       Date:  2010-07-13       Impact factor: 9.910

3.  11C-PiB PET assessment of change in fibrillar amyloid-beta load in patients with Alzheimer's disease treated with bapineuzumab: a phase 2, double-blind, placebo-controlled, ascending-dose study.

Authors:  Juha O Rinne; David J Brooks; Martin N Rossor; Nick C Fox; Roger Bullock; William E Klunk; Chester A Mathis; Kaj Blennow; Jerome Barakos; Aren A Okello; Sofia Rodriguez Martinez de Liano; Enchi Liu; Martin Koller; Keith M Gregg; Dale Schenk; Ronald Black; Michael Grundman
Journal:  Lancet Neurol       Date:  2010-02-26       Impact factor: 44.182

4.  Absence of Pittsburgh compound B detection of cerebral amyloid beta in a patient with clinical, cognitive, and cerebrospinal fluid markers of Alzheimer disease: a case report.

Authors:  Nigel J Cairns; Milos D Ikonomovic; Tammie Benzinger; Martha Storandt; Anne M Fagan; Aarti R Shah; Lisa Taylor Reinwald; Deborah Carter; Angela Felton; David M Holtzman; Mark A Mintun; William E Klunk; John C Morris
Journal:  Arch Neurol       Date:  2009-12

5.  Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease.

Authors:  John C Morris; Catherine M Roe; Elizabeth A Grant; Denise Head; Martha Storandt; Alison M Goate; Anne M Fagan; David M Holtzman; Mark A Mintun
Journal:  Arch Neurol       Date:  2009-12

6.  Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade.

Authors:  Clifford R Jack; David S Knopman; William J Jagust; Leslie M Shaw; Paul S Aisen; Michael W Weiner; Ronald C Petersen; John Q Trojanowski
Journal:  Lancet Neurol       Date:  2010-01       Impact factor: 44.182

7.  Relationship of cerebrospinal fluid markers to 11C-PiB and 18F-FDDNP binding.

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

8.  Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization.

Authors:  R C Petersen; P S Aisen; L A Beckett; M C Donohue; A C Gamst; D J Harvey; C R Jack; W J Jagust; L M Shaw; A W Toga; J Q Trojanowski; M W Weiner
Journal:  Neurology       Date:  2009-12-30       Impact factor: 9.910

9.  Follow-up of [11C]PIB uptake and brain volume in patients with Alzheimer disease and controls.

Authors:  N M Scheinin; S Aalto; J Koikkalainen; J Lötjönen; M Karrasch; N Kemppainen; M Viitanen; K Någren; S Helin; M Scheinin; J O Rinne
Journal:  Neurology       Date:  2009-09-02       Impact factor: 9.910

10.  Cerebrospinal fluid tau and ptau(181) increase with cortical amyloid deposition in cognitively normal individuals: implications for future clinical trials of Alzheimer's disease.

Authors:  Anne M Fagan; Mark A Mintun; Aarti R Shah; Patricia Aldea; Catherine M Roe; Robert H Mach; Daniel Marcus; John C Morris; David M Holtzman
Journal:  EMBO Mol Med       Date:  2009-11       Impact factor: 12.137

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  50 in total

1.  Shapes of the trajectories of 5 major biomarkers of Alzheimer disease.

Authors:  Clifford R Jack; Prashanthi Vemuri; Heather J Wiste; Stephen D Weigand; Timothy G Lesnick; Val Lowe; Kejal Kantarci; Matt A Bernstein; Matthew L Senjem; Jeffrey L Gunter; Bradley F Boeve; John Q Trojanowski; Leslie M Shaw; Paul S Aisen; Michael W Weiner; Ronald C Petersen; David S Knopman
Journal:  Arch Neurol       Date:  2012-07

Review 2.  The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Enchi Liu; John C Morris; Ronald C Petersen; Andrew J Saykin; Mark E Schmidt; Leslie Shaw; Judith A Siuciak; Holly Soares; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2011-11-02       Impact factor: 21.566

3.  Factors affecting Aβ plasma levels and their utility as biomarkers in ADNI.

Authors:  Jon B Toledo; Hugo Vanderstichele; Michal Figurski; Paul S Aisen; Ronald C Petersen; Michael W Weiner; Clifford R Jack; William Jagust; Charles Decarli; Arthur W Toga; Estefanía Toledo; Sharon X Xie; Virginia M-Y Lee; John Q Trojanowski; Leslie M Shaw
Journal:  Acta Neuropathol       Date:  2011-07-30       Impact factor: 17.088

4.  A blood-based predictor for neocortical Aβ burden in Alzheimer's disease: results from the AIBL study.

Authors:  S C Burnham; N G Faux; W Wilson; S M Laws; D Ames; J Bedo; A I Bush; J D Doecke; K A Ellis; R Head; G Jones; H Kiiveri; R N Martins; A Rembach; C C Rowe; O Salvado; S L Macaulay; C L Masters; V L Villemagne
Journal:  Mol Psychiatry       Date:  2013-04-30       Impact factor: 15.992

5.  Emerging β-amyloid pathology and accelerated cortical atrophy.

Authors:  Niklas Mattsson; Philip S Insel; Rachel Nosheny; Duygu Tosun; John Q Trojanowski; Leslie M Shaw; Clifford R Jack; Michael C Donohue; Michael W Weiner
Journal:  JAMA Neurol       Date:  2014-06       Impact factor: 18.302

6.  Nonlinear Association Between Cerebrospinal Fluid and Florbetapir F-18 β-Amyloid Measures Across the Spectrum of Alzheimer Disease.

Authors:  Jon B Toledo; Maria Bjerke; Xiao Da; Susan M Landau; Norman L Foster; William Jagust; Clifford Jack; Michael Weiner; Christos Davatzikos; Leslie M Shaw; John Q Trojanowski
Journal:  JAMA Neurol       Date:  2015-05       Impact factor: 18.302

Review 7.  Biomarker modelling of early molecular changes in Alzheimer's disease.

Authors:  Ross W Paterson; Jamie Toombs; Catherine F Slattery; Jonathan M Schott; Henrik Zetterberg
Journal:  Mol Diagn Ther       Date:  2014-04       Impact factor: 4.074

8.  Effects of cerebrospinal fluid proteins on brain atrophy rates in cognitively healthy older adults.

Authors:  Niklas Mattsson; Philip Insel; Rachel Nosheny; John Q Trojanowski; Leslie M Shaw; Clifford R Jack; Duygu Tosun; Michael Weiner
Journal:  Neurobiol Aging       Date:  2013-10-01       Impact factor: 4.673

9.  β-amyloid dynamics in human plasma.

Authors:  Yafei Huang; Rachel Potter; Wendy Sigurdson; Tom Kasten; Rose Connors; John C Morris; Tammie Benzinger; Mark Mintun; Tim Ashwood; Mats Ferm; Samantha L Budd; Randall J Bateman
Journal:  Arch Neurol       Date:  2012-12

10.  Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid.

Authors:  Susan M Landau; Ming Lu; Abhinay D Joshi; Michael Pontecorvo; Mark A Mintun; John Q Trojanowski; Leslie M Shaw; William J Jagust
Journal:  Ann Neurol       Date:  2013-12       Impact factor: 10.422

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