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.
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.
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
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
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
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
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
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
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: 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
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
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
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
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
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
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
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
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
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
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
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