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Beta amyloid, tau, neuroimaging, and cognition: sequence modeling of biomarkers for Alzheimer’s Disease

  • ADNI: Friday Harbor 2011 Workshop SPECIAL ISSUE
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Abstract

Alzheimer’s disease (AD) is associated with a cascade of pathological events involving formation of amyloid-based neuritic plaques and tau-based neurofibrillary tangles, changes in brain structure and function, and eventually, cognitive impairment and functional disability. The precise sequence of when each of these disease markers becomes abnormal is not yet clearly understood. The present study systematically tested the relationship between classes of biomarkers according to a proposed model of temporal sequence by Jack et al. (Lancet Neurology 9:119–128, 2010). We examined temporal relations among four classes of biomarkers: CSF Aβ, CSF tau, neuroimaging variables (hippocampal volume, ventricular volume, FDG PET), and cognitive variables (memory and executive function). Random effects modeling of longitudinal data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used to test hypotheses that putative earlier markers of AD predicted change in later markers, and that intervening markers reduced effects of earlier on later markers. Specifically, we hypothesized that CSF tau would explain CSF Aβ’s relation to neuroimaging and cognitive variables, and neuroimaging variables would explain tau’s relation to cognitive variables. Consistent with hypotheses, results indicated that CSF Aβ effects on cognition change were substantially attenuated by CSF tau and measures of brain structure and function, and CSF tau effects on cognitive change were attenuated by neuroimaging variables. Contrary to hypotheses, CSF Aβ and CSF tau were observed to have independent effects on neuroimaging and CSF tau had a direct effect on baseline cognition independent of brain structure and function. These results have implications for clarifying the temporal sequence of AD changes and corresponding biomarkers.

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Acknowledgments

This manuscript was a collaborative effort from the 2011 Friday Harbor Advanced Psychometrics Workshop (R13 AG030995), and used with gracious permission data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) downloaded on 6/1/11. Data collection and sharing for this project was funded by ADNI (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Amorfix Life Sciences Ltd.; AstraZeneca; Bayer HealthCare; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129, K01 AG030514, and the Dana Foundation.

Disclosures

There were no actual or potential conflicts of interest for any of the authors.

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Authors and Affiliations

  1. Department of Behavioral Sciences, Rush University Medical Center, 600 S. Paulina St., 1022, Chicago, IL, 60612, USA

    S. Duke Han

  2. Rush Alzheimer’s Disease Center, Rush University Medical Center, 600 S. Paulina St., 1022, Chicago, IL, 60612, USA

    S. Duke Han

  3. Department of Statistics, University of Washington, Seattle, WA, USA

    Jonathan Gruhl

  4. Department of Public Health Sciences, University of California Davis, Davis, CA, USA

    Laurel Beckett

  5. Department of Neurology, Oregon Health and Sciences University, Portland, OR, USA

    Hiroko H. Dodge

  6. Psychology Service, VA Boston Healthcare System, Boston, MA, USA

    Nikki H. Stricker

  7. Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA

    Nikki H. Stricker

  8. Department of Neurology, University of California Davis, Davis, CA, USA

    Sarah Farias & Dan Mungas

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Correspondence to S. Duke Han.

Additional information

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.ucla.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: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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Han, S.D., Gruhl, J., Beckett, L. et al. Beta amyloid, tau, neuroimaging, and cognition: sequence modeling of biomarkers for Alzheimer’s Disease. Brain Imaging and Behavior 6, 610–620 (2012). https://doi.org/10.1007/s11682-012-9177-0

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