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Depressive symptoms accelerate cognitive decline in amyloid-positive MCI patients

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

Late-life depression even in subsyndromal stages is strongly associated with Alzheimer’s disease (AD). Furthermore, brain amyloidosis is an early biomarker in subjects who subsequently suffer from AD and can be sensitively detected by amyloid PET. Therefore, we aimed to compare amyloid load and glucose metabolism in subsyndromally depressed subjects with mild cognitive impairment (MCI).

Methods

[18F]AV45 PET, [18F]FDG PET and MRI were performed in 371 MCI subjects from the Alzheimer’s Disease Neuroimaging Initiative Subjects were judged β-amyloid-positive (Aβ+; 206 patients) or β-amyloid-negative (Aβ−; 165 patients) according to [18F]AV45 PET. Depressive symptoms were assessed by the Neuropsychiatric Inventory Questionnaire depression item 4. Subjects with depressive symptoms (65 Aβ+, 41 Aβ−) were compared with their nondepressed counterparts. Conversion rates to AD were analysed (mean follow-up time 21.5 ± 9.1 months) with regard to coexisting depressive symptoms and brain amyloid load.

Results

Aβ+ depressed subjects showed large clusters with a higher amyloid load in the frontotemporal and insular cortices (p < 0.001) with coincident hypermetabolism (p < 0.001) in the frontal cortices than nondepressed subjects. Faster progression to AD was observed in subjects with depressive symptoms (p < 0.005) and in Aβ+ subjects (p < 0.001). Coincident depressive symptoms additionally shortened the conversion time in all Aβ+ subjects (p < 0.005) and to a greater extent in those with a high amyloid load (p < 0.001).

Conclusion

Our results clearly indicate that Aβ+ MCI subjects with depressive symptoms have an elevated amyloid load together with relative hypermetabolism of connected brain areas compared with cognitively matched nondepressed individuals. MCI subjects with high amyloid load and coexistent depressive symptoms are at high risk of faster conversion to AD.

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Acknowledgments

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; ; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; 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 Southern California. The authors acknowledge Inglewood Biomedical Editing for professional editing of the manuscript.

Conflicts of interest

Matthias Brendel reports no disclosures.

Oliver Pogarell reports no disclosures.

Guoming Xiong reports no disclosures.

Andreas Delker reports no disclosures.

Peter Bartenstein received research support from the Federal Ministry of Education and Science (BMBF).

Axel Rominger received research support from the Friedrich-Baur Foundation and SyNergy cluster.

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Authors and Affiliations

  1. Department of Nuclear Medicine, University of Munich, Munich, Germany

    Matthias Brendel, Guoming Xiong, Andreas Delker, Peter Bartenstein & Axel Rominger

  2. Department of Psychiatry, University of Munich, Munich, Germany

    Oliver Pogarell

  3. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    Peter Bartenstein & Axel Rominger

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  1. Matthias Brendel
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for the Alzheimer’s Disease Neuroimaging Initiative

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Correspondence to Axel Rominger.

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The data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The ADNI investigators 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/how_to_apply/ADNI_Acknowledgement_List.pdf

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Brendel, M., Pogarell, O., Xiong, G. et al. Depressive symptoms accelerate cognitive decline in amyloid-positive MCI patients. Eur J Nucl Med Mol Imaging 42, 716–724 (2015). https://doi.org/10.1007/s00259-014-2975-4

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  • DOI: https://doi.org/10.1007/s00259-014-2975-4

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