Elsevier

Alzheimer's & Dementia

Volume 7, Issue 2, March 2011, Pages 133-141
Alzheimer's & Dementia

Featured Article
Transforming cerebrospinal fluid Aβ42 measures into calculated Pittsburgh compound B units of brain Aβ amyloid

https://doi.org/10.1016/j.jalz.2010.08.230Get rights and content

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 (R2 = 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.

Introduction

Aβ42 in the cerebrospinal fluid (CSF Aβ42) and positron-emission tomography (PET) imaging of amyloid with Pittsburgh Compound B (PIB) demonstrate a highly significant inverse correlation which has been faithfully replicated in each independent sample in which this correlation has been assessed [1], [2], [3], [4], [5], [6], [7]. Both these techniques are presumed to measure brain Aβ amyloid load [8], [9], [10], [11], [12], [13], [14] (referred to from here on as Aβ load), which is an important disease feature that must be ascertained in individual subjects for many therapeutic and observational studies. However, in some circumstances it may not be possible to measure Aβ load in all subjects in a study by a single method. Our objective was to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ load, to partially validate the method in an independent sample of subjects, and illustrate how PIB PET and PIBcalc measures could be pooled in a statistical analysis.

Section snippets

Subjects

Criteria and methods to characterize subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) into diagnostic groups can be found in the report by Petersen et al [15]. A total of 102 ADNI subjects had usable PIB PET imaging data, and a subset of 41 of these subjects underwent both PIB PET and lumbar puncture (LP) at their 12-month visit. This subset, referred to as the “training” sample, consisted of individuals with the following clinical diagnoses: nine subjects were cognitively

Results

Table 1 summarizes the characteristics of the subjects in the training sample. Figure 2A shows the relationship between PIB PET on the y-axis versus CSF Aβ42 on the x-axis in the training sample (n = 41). The data illustrate the expected nonlinear inverse relationship which becomes approximately linear when plotted on the log2 scale (Fig. 2B). The covariates age (P = .32), gender (P = .68), and years of education (P = .66) did not account for a significant amount of variability in PIB PET on

Discussion

Brain Aβ load can be measured either by CSF Aβ42 or PET amyloid imaging. It is increasingly evident that obtaining estimates of brain Aβ load is necessary for many types of research studies in aging and dementia. For example, some would argue that brain Aβ load must be established in all subjects for inclusion in antiamyloid therapeutic trials. In addition, establishing the presence of Aβ amyloid will likely be an important feature of future revised criteria for AD at all clinical stages.

Acknowledgments

The authors acknowledge the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Foundation, U.S.A, and the Robert H. and Clarice Smith and Abigail Van Buren Alzheimer’s Disease Research Program of the Mayo Foundation, U.S.A. The authors thank Denise Reyes and Samantha Wille for Manuscript preparation. This work was supported by the National Institute on Aging (P50 AG16574, U01 AG06786, R01 AG11378, and AG024904) and National Institute of Health Construction Grant (NIH C06

References (41)

  • W.E. Klunk et al.

    Imaging brain amyloid in Alzheimer’s disease with Pittsburgh compound-B

    Ann Neurol

    (2004)
  • M.D. Ikonomovic et al.

    Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease

    Brain

    (2008)
  • V. Leinonen et al.

    Assessment of beta-amyloid in a frontal cortical brain biopsy specimen and by positron emission tomography with carbon 11-labeled Pittsburgh compound B

    Arch Neurol

    (2008)
  • C.C. Rowe et al.

    Imaging beta-amyloid burden in aging and dementia

    Neurology

    (2007)
  • C.M. Clark et al.

    Cerebrospinal fluid tau and beta-amyloid: how well do these biomarkers reflect autopsy-confirmed dementia diagnoses?

    Arch Neurol

    (2003)
  • D. Strozyk et al.

    CSF Abeta 42 levels correlate with amyloid-neuropathology in a population-based autopsy study

    Neurology

    (2003)
  • T. Tapiola et al.

    Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain

    Arch Neurol

    (2009)
  • R.C. Petersen et al.

    Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization

    Neurology

    (2010)
  • C.A. Mathis et al.

    Synthesis and evaluation of 11C-labeled 6-substituted 2-arylbenzothiazoles as amyloid imaging agents

    J Med Chem

    (2003)
  • Senjem ML, Lowe V, Kemp B, Weigand SD, Knopman D, Boeve B, et al. Automated ROI analysis of 11C Pittsburgh compound B...
  • Cited by (85)

    • Exposure to surgery with general anaesthesia during adult life is not associated with increased brain amyloid deposition in older adults

      2020, British Journal of Anaesthesia
      Citation Excerpt :

      Continuous outcomes were analysed using multivariable linear regression, and binary outcomes were analysed using multivariable logistic regression. Log transformations of PiB PET values were performed to satisfy distributional assumptions.58 The multivariable models adjusted for ‘risk factors’ are age; sex; education; marital status; smoking status; apolipoprotein E ε-4 genotype; and midlife diabetes mellitus, hypertension, and dyslipidaemia (midlife defined as before age 65 yr).

    • Challenges associated with biomarker-based classification systems for Alzheimer's disease

      2018, Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
    • A randomized, exploratory molecular imaging study targeting amyloid β with a novel 8-OH quinoline in Alzheimer's disease: The PBT2-204 IMAGINE study

      2017, Alzheimer's and Dementia: Translational Research and Clinical Interventions
      Citation Excerpt :

      The recently reported aducanumab phase 1 study had intake criteria of PiB-equivalent of ∼1.9-2.1 [25] (see also Fig. 8), and the AZD 3293 trial of a BACE 1 inhibitor has intake criteria of PiB-equivalent ∼1.6-2.0 [38]. Based on Aβ-CSF levels, we infer that the intake PiB SUVR of the PBT2 Euro study was ∼2.15 [39]. Taken together, these observations suggest that the IMAGINE PiB baseline was exceptionally high, and that future studies should aim for intake PiB SUVR between 1.5 and 2.0, a value which is well-within the linear rates of change as seen in AIBL and other longitudinal studies [9,10].

    • Amyloid status imputed from a multimodal classifier including structural MRI distinguishes progressors from nonprogressors in a mild Alzheimer's disease clinical trial cohort

      2016, Alzheimer's and Dementia
      Citation Excerpt :

      Both positron emission tomography (PET) imaging, using Aβ-specific radiotracers such as [11C]-PIB or [18F]-florbetapir, and measurement of Aβ proteins from cerebral spinal fluid (CSF) samples, are widely used in the research setting to quantify brain Aβ plaque load. Cut points for positivity have been defined for each of these modalities, yielding highly convergent results [2,3]. Analysis of Aβ biomarker subgroups in phase 3 clinical trials from two independent drug development programs revealed that approximately 27% of subjects meeting clinical inclusion criteria for mild-AD were Aβ-negative [4,5].

    View all citing articles on Scopus

    ADNI investigators include (complete listing available at: www.loni.ucla.edu\ADNI\Collaboration\ADNI_Manuscript_Citations.pdf).

    View full text