Volume 11, Issue 7 p. 823-831
Review

The Alzheimer's Disease Neuroimaging Initiative phase 2: Increasing the length, breadth, and depth of our understanding

Laurel A. Beckett

Corresponding Author

Laurel A. Beckett

Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA

Corresponding author. Tel.: +1-530-754-7161; Fax: +1-530-752-3239.

E-mail address: [email protected]

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Michael C. Donohue

Michael C. Donohue

Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California, San Diego, CA, USA

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Cathy Wang

Cathy Wang

Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA

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Paul Aisen

Paul Aisen

Department of Neurosciences, University of California, San Diego, CA, USA

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Danielle J. Harvey

Danielle J. Harvey

Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA

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Naomi Saito

Naomi Saito

Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA

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Alzheimer's Disease Neuroimaging Initiative

Alzheimer's Disease Neuroimaging Initiative

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 the analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/howtoapply/ADNIAcknowledgementList.pdf.

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First published: 01 July 2015
Citations: 50

Abstract

Introduction

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a multisite study designed to characterize the trajectories of biomarkers across the aging process. We present ADNI Biostatistics Core analyses that integrate data over the length, breadth, and depth of ADNI.

Methods

Relative progression of key imaging, fluid, and clinical measures was assessed. Individuals with subjective memory complaints (SMC) and early mild cognitive impairment (eMCI) were compared with normal controls (NC), MCI, and individuals with Alzheimer's disease. Amyloid imaging and magnetic resonance imaging (MRI) summaries were assessed as predictors of disease progression.

Results

Relative progression of markers supports parts of the amyloid cascade hypothesis, although evidence of earlier occurrence of cognitive change exists. SMC are similar to NC, whereas eMCI fall between the cognitively normal and MCI groups. Amyloid leads to faster conversion and increased cognitive impairment.

Discussion

Analyses support features of the amyloid hypothesis, but also illustrate the considerable heterogeneity in the aging process.