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Longitudinal change in neuropsychological performance using latent growth models: a study of mild cognitive impairment

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Abstract

The goal of the current study was to examine cognitive change in both healthy controls (n = 229) and individuals with mild cognitive impairment (MCI) (n = 397) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We applied latent growth modeling to examine baseline and longitudinal change over 36 months in five cognitive factors derived from the ADNI neuropsychological test battery (memory, executive function/processing speed, language, attention and visuospatial). At baseline, MCI patients demonstrated lower performance on all of the five cognitive factors when compared to controls. Both controls and MCI patients declined on memory over 36 months; however, the MCI patients declined at a significantly faster rate than controls. The MCI patients also declined over 36 months on the remaining four cognitive factors. In contrast, the controls did not exhibit significant change over 36 months on the non-memory cognitive factors. Within the MCI group, executive function declined faster than memory, while the other factor scores changed slower than memory over time. These findings suggest different patterns of cognitive change in healthy older adults and MCI patients. The findings also suggest that, when compared with memory, executive function declines faster than other cognitive factors in patients with MCI. Thus, decline in non-memory domains may be an important feature for distinguishing healthy older adults and persons with MCI.

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Acknowledgements

We gratefully acknowledge a conference grant from the National Institute on Aging (NIA) (R13 AG030995, PI: Mungas) that facilitated data analysis for this project.

Dr. Johnson was supported by NIA grant R01 AG022538 (PI: Johnson). Dr. Gross was supported by a National Institutes of Health Translational Research in Aging fellowship (T32AG023480-07) and NIA grant P01 AG031720 (PI: Inouye). Dr. McLaren was supported by NIA grants P01 AG036694 (PI: Sperling) and K23 AG027171 (PI: Atri). Dr. Pa was supported by NIA grant K01 AG034175 (PI: Pa). Dr. Park was supported by NIA grant R01 AG031252 (PI: Farias). Dr. Manly was supported by NIA grants R01 AG028786 (PI: Manly) and R01 AG037212 (PI: Mayeux).

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (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.

The contents do not represent the views of the Dept. of Veterans Affairs, the United States Government, or any other funding entities.

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Authors and Affiliations

  1. Institute for Health and Aging; Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA

    Julene K. Johnson

  2. Department of Neurology, University of California, San Francisco, CA, USA

    Julene K. Johnson & Judy Pa

  3. Institute for Aging Research, Harvard Medical School and Division of Gerontology, Beth Israel Deaconess Medical Center, Boston, MA, USA

    Alden L. Gross

  4. Geriatric Research Education and Clinical Center, ENRM Veterans Hospital, Boston, MA, USA

    Donald G. McLaren

  5. Department of Neurology, Massachusetts General Hospital, Boston, MA, USA

    Donald G. McLaren

  6. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA

    Donald G. McLaren

  7. Harvard Medical School, Boston, MA, USA

    Donald G. McLaren

  8. Alzheimer’s Disease Center, Department of Neurology, University of California, Davis, Davis, CA, USA

    Lovingly Quitania Park

  9. Taub Institute for Research on Alzheimer’s Disease and the Aging Brain; Department of Neurology, Columbia University Medical Center, New York, NY, USA

    Jennifer J. Manly

  10. Institute for Health and Aging, University of California, San Francisco, 3333 California St., Suite 340, San Francisco, CA, 94118, USA

    Julene K. Johnson

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  1. Julene K. Johnson
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  2. Alden L. Gross
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for the Alzheimer’s Disease Neuroimaging Initiative

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Correspondence to Julene K. Johnson.

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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 with 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.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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Johnson, J.K., Gross, A.L., Pa, J. et al. Longitudinal change in neuropsychological performance using latent growth models: a study of mild cognitive impairment. Brain Imaging and Behavior 6, 540–550 (2012). https://doi.org/10.1007/s11682-012-9161-8

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