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April 12, 2016; 86 (15) Article

Amyloid negativity in patients with clinically diagnosed Alzheimer disease and MCI

Susan M. Landau, Andy Horng, Allison Fero, William J. Jagust, For the Alzheimer's Disease Neuroimaging Initiative
First published March 11, 2016, DOI: https://doi.org/10.1212/WNL.0000000000002576
Susan M. Landau
From Helen Wills Neuroscience Institute (S.M.L., A.H., W.J.J.), University of California, Berkeley; and Life Sciences Division (S.M.L., A.F., W.J.J.), Lawrence Berkeley National Laboratory, CA.
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Andy Horng
From Helen Wills Neuroscience Institute (S.M.L., A.H., W.J.J.), University of California, Berkeley; and Life Sciences Division (S.M.L., A.F., W.J.J.), Lawrence Berkeley National Laboratory, CA.
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Allison Fero
From Helen Wills Neuroscience Institute (S.M.L., A.H., W.J.J.), University of California, Berkeley; and Life Sciences Division (S.M.L., A.F., W.J.J.), Lawrence Berkeley National Laboratory, CA.
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William J. Jagust
From Helen Wills Neuroscience Institute (S.M.L., A.H., W.J.J.), University of California, Berkeley; and Life Sciences Division (S.M.L., A.F., W.J.J.), Lawrence Berkeley National Laboratory, CA.
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From Helen Wills Neuroscience Institute (S.M.L., A.H., W.J.J.), University of California, Berkeley; and Life Sciences Division (S.M.L., A.F., W.J.J.), Lawrence Berkeley National Laboratory, CA.
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Amyloid negativity in patients with clinically diagnosed Alzheimer disease and MCI
Susan M. Landau, Andy Horng, Allison Fero, William J. Jagust, For the Alzheimer's Disease Neuroimaging Initiative
Neurology Apr 2016, 86 (15) 1377-1385; DOI: 10.1212/WNL.0000000000002576

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Abstract

Objective: To examine the clinical and biomarker characteristics of patients with amyloid-negative Alzheimer disease (AD) and mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a prospective cohort study.

Methods: We first investigated the reliability of florbetapir− PET in patients with AD and patients with MCI using CSF-Aβ1–42 as a comparison amyloid measurement. We then compared florbetapir− vs florbetapir+ patients with respect to several AD-specific biomarkers, baseline and longitudinal cognitive measurements, and demographic and clinician report data.

Results: Florbetapir and CSF-Aβ1–42 +/− status agreed for 98% of ADs (89% of MCIs), indicating that most florbetapir− scans were a reliable representation of amyloid status. Florbetapir− AD (n = 27/177; 15%) and MCI (n = 74/217, 34%) were more likely to be APOE4-negative (MCI 83%, AD 96%) than their florbetapir+ counterparts (MCI 30%, AD 24%). Florbetapir− patients also had less AD-specific hypometabolism, lower CSF p-tau and t-tau, and better longitudinal cognitive performance, and were more likely to be taking medication for depression. In MCI only, florbetapir− participants had less hippocampal atrophy and hypometabolism and lower functional activity questionnaire scores compared to florbetapir+ participants.

Conclusions: Overall, image analysis problems do not appear to be a primary explanation of amyloid negativity. Florbetapir− ADNI patients have a variety of clinical and biomarker features that differ from their florbetapir+ counterparts, suggesting that one or more non-AD etiologies (which may include vascular disease and depression) account for their AD-like phenotype.

GLOSSARY

Aβ=
β-amyloid;
AD=
Alzheimer disease;
ADAS-cog=
Alzheimer's Disease Assessment Scale–cognitive subscale;
ADNI=
Alzheimer's Disease Neuroimaging Initiative;
AGD=
argyrophilic grain disease;
MCI=
mild cognitive impairment;
metaROI=
previously validated region of interest;
MMSE=
Mini-Mental State Examination;
MPRAGE=
magnetization-prepared rapid gradient echo;
RAVLT=
Rey Auditory Verbal Learning Test;
SUVR=
standardized uptake value ratio;
TBM-SyN=
tensor-based morphometry-symmetric diffeomorphic image normalization method;
VBM=
voxel-based morphometry;
WM=
white matter

Footnotes

  • Coinvestigators are listed on the Neurology® Web site at Neurology.org.

  • Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

  • Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

  • Supplemental data at Neurology.org

  • Received October 26, 2015.
  • Accepted in final form January 5, 2016.
  • © 2016 American Academy of Neurology
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