Daniele Altomare1,2, Clarissa Ferrari3, Anna Caroli4, Samantha Galluzzi5, Annapaola Prestia5, Wiesje M van der Flier6,7, Rik Ossenkoppele6,8,9, Bart Van Berckel6,8, Frederik Barkhof8,10,11, Charlotte E Teunissen12, Anders Wall13, Stephen F Carter14,15, Michael Schöll9,16,17, I L Han Choo14,18, Timo Grimmer19, Alberto Redolfi5, Agneta Nordberg20,21, Philip Scheltens6, Alexander Drzezga22, Giovanni B Frisoni1,5,2. 1. Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland. 2. Memory Clinic, University Hospital of Geneva, Geneva, Switzerland. 3. Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy. cferrari@fatebenefratelli.eu. 4. Medical Imaging Unit, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy. 5. Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. 6. Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 7. Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 8. Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 9. Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden. 10. Institute of Neurology, UCL, London, UK. 11. Institute of Healthcare Engineering, UCL, London, UK. 12. Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 13. Section of Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. 14. Alzheimer Neurobiology Center, Karolinska Institutet, Stockholm, Sweden. 15. Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK. 16. Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden. 17. Dementia Research Centre, Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK. 18. Department of Neuropsychiatry, School of Medicine, Chosun University, Gwangju, Republic of Korea. 19. Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. 20. Center for Alzheimer Research, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. 21. Aging Theme, Karolinska University Hospital, Stockholm, Sweden. 22. Department of Nuclear Medicine, University of Cologne, Cologne, Germany.
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.
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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