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Prognostic value of Alzheimer’s biomarkers in mild cognitive impairment: the effect of age at onset

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Abstract

Objective

The aim of this study is to assess the impact of age at onset on the prognostic value of Alzheimer’s biomarkers in a large sample of patients with mild cognitive impairment (MCI).

Methods

We measured Aβ42, t-tau, hippocampal volume on magnetic resonance imaging (MRI) and cortical metabolism on fluorodeoxyglucose–positron emission tomography (FDG-PET) in 188 MCI patients followed for at least 1 year. We categorised patients into earlier and later onset (EO/LO). Receiver operating characteristic curves and corresponding areas under the curve (AUCs) were performed to assess and compar the biomarker prognostic performances in EO and LO groups. Linear Model was adopted for estimating the time-to-progression in relation with earlier/later onset MCI groups and biomarkers.

Results

In earlier onset patients, all the assessed biomarkers were able to predict cognitive decline (p < 0.05), with FDG-PET showing the best performance. In later onset patients, all biomarkers but t-tau predicted cognitive decline (p < 0.05). Moreover, FDG-PET alone in earlier onset patients showed a higher prognostic value than the one resulting from the combination of all the biomarkers in later onset patients (earlier onset AUC 0.935 vs later onset AUC 0.753, p < 0.001). Finally, FDG-PET showed a different prognostic value between earlier and later onset patients (p = 0.040) in time-to-progression allowing an estimate of the time free from disease.

Discussion

FDG-PET may represent the most universal tool for the establishment of a prognosis in MCI patients and may be used for obtaining an onset-related estimate of the time free from disease.

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Acknowledgements

Data used in this article were partially collected by Translational Outpatient Memory Clinic—TOMC—working group at IRCCS Centro San Giovanni di Dio Fatebenefratelli in Brescia, Italy. Contributors to the TOMC, involved in data collection, are: G Amicucci, S Archetti, L Benussi, G Binetti, L Bocchio-Chiavetto, C Bonvicini, E Canu, F Caobelli, E Cavedo, E Chittò, M Cotelli, M Gennarelli, S Galluzzi, C Geroldi, R Ghidoni, R Giubbini, UP Guerra, G Kuffenschin, G Lussignoli, D Moretti, B Paghera, M Parapini, C Porteri, M Romano, S Rosini, I Villa, R Zanardini, O Zanetti. FB is supported by the NIHR UCLH biomedical research centre. Part of the data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://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: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

Funding

EU data collection and sharing: The work was supported by the Swedish Research Council (project 05817), the Strategic Research Program in Neuroscience at Karolinska Institutet, the Swedish Brain Power. This work was also supported by the grants: sottoprogetto finalizzato Strategico 2006: “Strumenti e procedure diagnostiche per le demenze utilizzabili nella clinica ai fini della diagnosi precoce e differenziale, della individuazione delle forme a rapida o lenta progressione e delle forme con risposta ottimale alle attuali terapie”; Programma Strategico 2006, Convenzione 71; Programma Strategico 2007, Convenzione PS39, Ricerca Corrente Italian Ministry of Health. Some of the costs related to patient assessment and imaging and biomarker detection were funded thanks to an ad hoc grant from the Fitness e Solidarieta‘2006 and 2007 campaigns. The analyses of MRI data presented in the paper have been performed thanks to the neuGRID platform, which has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 283562. Alzheimer’s Disease Neuroimaging Initiative (ADNI) data: 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; 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.; 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; 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 (http://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.

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Author notes

  1. Daniele Altomare and Clarissa Ferrari contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland

    Daniele Altomare & Giovanni B. Frisoni

  2. Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy

    Clarissa Ferrari

  3. Medical Imaging Unit, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy

    Anna Caroli

  4. Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy

    Samantha Galluzzi, Annapaola Prestia, Alberto Redolfi & Giovanni B. Frisoni

  5. Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands

    Wiesje M. van der Flier, Rik Ossenkoppele, Bart Van Berckel & Philip Scheltens

  6. Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands

    Wiesje M. van der Flier

  7. Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands

    Rik Ossenkoppele, Bart Van Berckel & Frederik Barkhof

  8. Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden

    Rik Ossenkoppele & Michael Schöll

  9. Institute of Neurology, UCL, London, UK

    Frederik Barkhof

  10. Institute of Healthcare Engineering, UCL, London, UK

    Frederik Barkhof

  11. Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands

    Charlotte E. Teunissen

  12. Section of Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden

    Anders Wall

  13. Alzheimer Neurobiology Center, Karolinska Institutet, Stockholm, Sweden

    Stephen F. Carter & IL Han Choo

  14. Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK

    Stephen F. Carter

  15. Department of Neuropsychiatry, School of Medicine, Chosun University, Gwangju, Republic of Korea

    IL Han Choo

  16. Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technische Universität München, Munich, Germany

    Timo Grimmer

  17. Center for Alzheimer Research, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden

    Agneta Nordberg

  18. Aging Theme, Karolinska University Hospital, Stockholm, Sweden

    Agneta Nordberg

  19. Department of Nuclear Medicine, University of Cologne, Cologne, Germany

    Alexander Drzezga

  20. Memory Clinic, University Hospital of Geneva, Geneva, Switzerland

    Daniele Altomare & Giovanni B. Frisoni

  21. Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden

    Michael Schöll

  22. Dementia Research Centre, Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK

    Michael Schöll

Authors
  1. Daniele Altomare
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  2. Clarissa Ferrari
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  3. Anna Caroli
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Correspondence to Clarissa Ferrari.

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This study was approved by the ethics committee of each participating center and all participants were enrolled after written informed consent was obtained.

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Altomare, D., Ferrari, C., Caroli, A. et al. Prognostic value of Alzheimer’s biomarkers in mild cognitive impairment: the effect of age at onset. J Neurol 266, 2535–2545 (2019). https://doi.org/10.1007/s00415-019-09441-7

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