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Salvadori N, Torrigiani EG, Paoletti FP, Chipi E, Montanucci C, Verderosa C, Siena E, Fruttini D, Parnetti L. Predictive value for cerebrospinal fluid Alzheimer's disease profile of different measures of verbal episodic memory in patients with MCI. Sci Rep 2024; 14:12235. [PMID: 38806521 PMCID: PMC11133313 DOI: 10.1038/s41598-024-62604-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 05/20/2024] [Indexed: 05/30/2024] Open
Abstract
Neuropsychological evidence of memory impairment represents the main feature of the clinical onset of typical Alzheimer's disease (AD). Rey's Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) are two tests both assessing verbal episodic memory, widely used in clinical practice. Our aim was to investigate the added value of their combined use in predicting cerebrospinal fluid (CSF) AD biomarkers positivity in a retrospective consecutive series of patients with mild cognitive impairment (MCI). 169 MCI patients were included. For all of them neuropsychological assessment and CSF analysis were available. According to CSF A/T/(N) profile, 109 were defined as MCI due to AD (A+T+), and 60 were non-AD MCI (A-T-). Logistic regression model and receiver-operating characteristic (ROC) curves were analyzed to evaluate the discriminatory power of single and combined sub-measures between AD and non-AD patients. The combination of RAVLT-del with LM could acceptably discriminate the two groups (AUC: 0.69, CI 95% 0.617-0.761, sens: 0.75, spec. 0.58, p < 0.001), while the single tests did not show sufficient discriminative performance. Our study shows that the combination of RAVLT delayed recall with LM better predicts the biological AD diagnosis (A+T+), showing a good discriminative power between MCI-AD from non-AD MCI. Since RAVLT and LM assess different components of verbal episodic memory, they should be considered as complementary, rather than interchangeable, tests.
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Affiliation(s)
- Nicola Salvadori
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Edoardo Guido Torrigiani
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Federico Paolini Paoletti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Elena Chipi
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Chiara Montanucci
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Claudio Verderosa
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Elisa Siena
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Daniela Fruttini
- Section of Endocrinology and Metabolism, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lucilla Parnetti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
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2
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Wegner P, Balabin H, Ay MC, Bauermeister S, Killin L, Gallacher J, Hofmann-Apitius M, Salimi Y. Semantic Harmonization of Alzheimer's Disease Datasets Using AD-Mapper. J Alzheimers Dis 2024; 99:1409-1423. [PMID: 38759012 PMCID: PMC11191441 DOI: 10.3233/jad-240116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/18/2024] [Indexed: 05/19/2024]
Abstract
Background Despite numerous past endeavors for the semantic harmonization of Alzheimer's disease (AD) cohort studies, an automatic tool has yet to be developed. Objective As cohort studies form the basis of data-driven analysis, harmonizing them is crucial for cross-cohort analysis. We aimed to accelerate this task by constructing an automatic harmonization tool. Methods We created a common data model (CDM) through cross-mapping data from 20 cohorts, three CDMs, and ontology terms, which was then used to fine-tune a BioBERT model. Finally, we evaluated the model using three previously unseen cohorts and compared its performance to a string-matching baseline model. Results Here, we present our AD-Mapper interface for automatic harmonization of AD cohort studies, which outperformed a string-matching baseline on previously unseen cohort studies. We showcase our CDM comprising 1218 unique variables. Conclusion AD-Mapper leverages semantic similarities in naming conventions across cohorts to improve mapping performance.
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Affiliation(s)
- Philipp Wegner
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Helena Balabin
- Department of Neurosciences, Laboratory for Cognitive Neurology, KU Leuven, Leuven, Belgium
- Department of Computer Science, Language Intelligence and Information Retrieval Lab, KU Leuven, Leuven, Belgium
| | - Mehmet Can Ay
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Sarah Bauermeister
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Lewis Killin
- SYNAPSE Research Management Partners, Barcelona, Spain
| | - John Gallacher
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Martin Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Yasamin Salimi
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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3
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Maheux E, Koval I, Ortholand J, Birkenbihl C, Archetti D, Bouteloup V, Epelbaum S, Dufouil C, Hofmann-Apitius M, Durrleman S. Forecasting individual progression trajectories in Alzheimer's disease. Nat Commun 2023; 14:761. [PMID: 36765056 PMCID: PMC9918533 DOI: 10.1038/s41467-022-35712-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 12/19/2022] [Indexed: 02/12/2023] Open
Abstract
The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical trial. We show that enriching the population with the predicted progressors decreases the required sample size by 38% to 50%, depending on trial duration, outcome, and targeted disease stage, from asymptomatic individuals at risk of AD to subjects with early and mild AD. We show that the method introduces no biases regarding sex or geographic locations and is robust to missing data. It performs best at the earliest stages of disease and is therefore highly suitable for use in prevention trials.
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Affiliation(s)
- Etienne Maheux
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Igor Koval
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Juliette Ortholand
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Colin Birkenbihl
- Department of bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115, Germany
| | - Damiano Archetti
- IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Vincent Bouteloup
- Université de Bordeaux, CNRS UMR 5293, Institut des Maladies Neurodégénératives, Bordeaux, France
- Centre Hospitalier Universitaire (CHU) de Bordeaux, pôle de neurosciences cliniques, centre mémoire de ressources et de recherche, Bordeaux, France
| | - Stéphane Epelbaum
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Institut de la mémoire et de la maladie d'Alzheimer (IM2A), center of excellence of neurodegenerative diseases (CoEN), department of Neurology, DMU Neurosciences, Paris, France
| | - Carole Dufouil
- Université de Bordeaux, CNRS UMR 5293, Institut des Maladies Neurodégénératives, Bordeaux, France
- Centre Hospitalier Universitaire (CHU) de Bordeaux, pôle de neurosciences cliniques, centre mémoire de ressources et de recherche, Bordeaux, France
| | - Martin Hofmann-Apitius
- Department of bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115, Germany
| | - Stanley Durrleman
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France.
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4
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Del Percio C, Lopez S, Noce G, Lizio R, Tucci F, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Buttinelli C, Giubilei F, Marizzoni M, Güntekin B, Yener G, Stocchi F, Vacca L, Frisoni GB, Babiloni C. What a Single Electroencephalographic (EEG) Channel Can Tell us About Alzheimer's Disease Patients With Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:21-35. [PMID: 36413420 DOI: 10.1177/15500594221125033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.
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Affiliation(s)
- Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | | | | | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Flavio Nobili
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), 27212Università di Genova, Italy
| | - Dario Arnaldi
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), 27212Università di Genova, Italy
| | - Francesco Famà
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, 9311Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, 9311Sapienza University of Rome, Rome, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, 218502Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., 218502Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir University of Economics, Faculty of Medicine, Izmir, Turkey
| | | | | | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and 27212University of Geneva, Geneva, Switzerland
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
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5
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What a single electroencephalographic (EEG) channel can tell us about patients with dementia due to Alzheimer's disease. Int J Psychophysiol 2022; 182:169-181. [DOI: 10.1016/j.ijpsycho.2022.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/20/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022]
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6
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Vallarino E, Sommariva S, Famà F, Piana M, Nobili F, Arnaldi D. Transfreq: A Python package for computing the theta-to-alpha transition frequency from resting state electroencephalographic data. Hum Brain Mapp 2022; 43:5095-5110. [PMID: 35770938 PMCID: PMC9812240 DOI: 10.1002/hbm.25995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/05/2022] [Indexed: 01/15/2023] Open
Abstract
A classic approach to estimate individual theta-to-alpha transition frequency (TF) requires two electroencephalographic (EEG) recordings, one acquired in a resting state condition and one showing alpha desynchronisation due, for example, to task execution. This translates into long recording sessions that may be cumbersome in studies involving patients. Moreover, an incomplete desynchronisation of the alpha rhythm may compromise TF estimates. Here we present transfreq, a publicly available Python library that allows TF computation from resting state data by clustering the spectral profiles associated to the EEG channels based on their content in alpha and theta bands. A detailed overview of transfreq core algorithm and software architecture is provided. Its effectiveness and robustness across different experimental setups are demonstrated on a publicly available EEG data set and on in-house recordings, including scenarios where the classic approach fails to estimate TF. We conclude with a proof of concept of the predictive power of transfreq TF as a clinical marker. Specifically, we present a scenario where transfreq TF shows a stronger correlation with the mini mental state examination score than other widely used EEG features, including individual alpha peak and median/mean frequency. The documentation of transfreq and the codes for reproducing the analysis of the article with the open-source data set are available online at https://elisabettavallarino.github.io/transfreq/. Motivated by the results showed in this article, we believe our method will provide a robust tool for discovering markers of neurodegenerative diseases.
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Affiliation(s)
| | - Sara Sommariva
- Dipartimento di Matematica (DIMA)Università degli Studi di GenovaGenoaItaly,CNR‐SPINGenoaItaly
| | - Francesco Famà
- Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno‐Infantili (DINOGMI)Università degli Studi di GenovaGenoaItaly,IRCCS Ospedale Policlinico San MartinoGenoaItaly
| | - Michele Piana
- Dipartimento di Matematica (DIMA)Università degli Studi di GenovaGenoaItaly,IRCCS Ospedale Policlinico San MartinoGenoaItaly
| | - Flavio Nobili
- Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno‐Infantili (DINOGMI)Università degli Studi di GenovaGenoaItaly,IRCCS Ospedale Policlinico San MartinoGenoaItaly
| | - Dario Arnaldi
- Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno‐Infantili (DINOGMI)Università degli Studi di GenovaGenoaItaly,IRCCS Ospedale Policlinico San MartinoGenoaItaly
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7
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Babiloni C, Noce G, Di Bonaventura C, Lizio R, Eldellaa A, Tucci F, Salamone EM, Ferri R, Soricelli A, Nobili F, Famà F, Arnaldi D, Palma E, Cifelli P, Marizzoni M, Stocchi F, Bruno G, Di Gennaro G, Frisoni GB, Del Percio C. Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment. J Alzheimers Dis 2022; 88:903-931. [PMID: 35694930 DOI: 10.3233/jad-220442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing." OBJECTIVE Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients. METHODS Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals. RESULTS EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals. CONCLUSION It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
| | | | - Carlo Di Bonaventura
- Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Ali Eldellaa
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Enrico M Salamone
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy.,Department of Neuroscience (DiNOGMI), University of Genoa, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Eleonora Palma
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Pasteur Institute-Cenci Bolognetti Foundation, Rome, Italy
| | - Pierangelo Cifelli
- IRCCS Neuromed, Pozzilli, (IS), Italy.,Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Giuseppe Bruno
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | | | - Giovanni B Frisoni
- Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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Rane Levendovszky S. Cross-Sectional and Longitudinal Hippocampal Atrophy, Not Cortical Thinning, Occurs in Amyloid-Negative, p-Tau-Positive, Older Adults With Non-Amyloid Pathology and Mild Cognitive Impairment. FRONTIERS IN NEUROIMAGING 2022; 1:828767. [PMID: 37555137 PMCID: PMC10406207 DOI: 10.3389/fnimg.2022.828767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 03/11/2022] [Indexed: 08/10/2023]
Abstract
Introduction Alzheimer's disease (AD) is a degenerative disease characterized by pathological accumulation of amyloid and phosphorylated tau. Typically, the early stage of AD, also called mild cognitive impairment (MCI), shows amyloid pathology. A small but significant number of individuals with MCI do not exhibit amyloid pathology but have elevated phosphorylated tau levels (A-T+ MCI). We used CSF amyloid and phosphorylated tau to identify the individuals with A+T+ and A-T+ MCI as well as cognitively normal (A-T-) controls. To increase the sample size, we leveraged the Global Alzheimer's Association Interactive Network and identified 137 MCI+ and 61 A-T+ MCI participants. We compared baseline and longitudinal, hippocampal, and cortical atrophy between groups. Methods We applied ComBat harmonization to minimize site-related variability and used FreeSurfer for all measurements. Results Harmonization reduced unwanted variability in cortical thickness by 3.4% and in hippocampal volume measurement by 10.3%. Cross-sectionally, widespread cortical thinning with age was seen in the A+T+ and A-T+ MCI groups (p < 0.0005). A decrease in the hippocampal volume with age was faster in both groups (p < 0.05) than in the controls. Longitudinally also, hippocampal atrophy rates were significant (p < 0.05) when compared with the controls. No longitudinal cortical thinning was observed in A-T+ MCI group. Discussion A-T+ MCI participants showed similar baseline cortical thickness patterns with aging and longitudinal hippocampal atrophy rates as participants with A+T+ MCI, but did not show longitudinal cortical atrophy signature.
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Affiliation(s)
- Swati Rane Levendovszky
- Department of Radiology, School of Medicine, University of Washington, Seattle, WA, United States
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9
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Salimi Y, Domingo-Fernández D, Bobis-Álvarez C, Hofmann-Apitius M, Birkenbihl C. ADataViewer: exploring semantically harmonized Alzheimer's disease cohort datasets. Alzheimers Res Ther 2022; 14:69. [PMID: 35598021 PMCID: PMC9123725 DOI: 10.1186/s13195-022-01009-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 04/27/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Currently, Alzheimer's disease (AD) cohort datasets are difficult to find and lack across-cohort interoperability, and the actual content of publicly available datasets often only becomes clear to third-party researchers once data access has been granted. These aspects severely hinder the advancement of AD research through emerging data-driven approaches such as machine learning and artificial intelligence and bias current data-driven findings towards the few commonly used, well-explored AD cohorts. To achieve robust and generalizable results, validation across multiple datasets is crucial. METHODS We accessed and systematically investigated the content of 20 major AD cohort datasets at the data level. Both, a medical professional and a data specialist, manually curated and semantically harmonized the acquired datasets. Finally, we developed a platform that displays vital information about the available datasets. RESULTS Here, we present ADataViewer, an interactive platform that facilitates the exploration of 20 cohort datasets with respect to longitudinal follow-up, demographics, ethnoracial diversity, measured modalities, and statistical properties of individual variables. It allows researchers to quickly identify AD cohorts that meet user-specified requirements for discovery and validation studies regarding available variables, sample sizes, and longitudinal follow-up. Additionally, we publish the underlying variable mapping catalog that harmonizes 1196 unique variables across the 20 cohorts and paves the way for interoperable AD datasets. CONCLUSIONS In conclusion, ADataViewer facilitates fast, robust data-driven research by transparently displaying cohort dataset content and supporting researchers in selecting datasets that are suited for their envisioned study. The platform is available at https://adata.scai.fraunhofer.de/ .
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Affiliation(s)
- Yasamin Salimi
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754, Sankt Augustin, Germany.
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115, Bonn, Germany.
| | - Daniel Domingo-Fernández
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754, Sankt Augustin, Germany
| | - Carlos Bobis-Álvarez
- University Hospital Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, 38010, Spain
| | - Martin Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754, Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115, Bonn, Germany
| | - Colin Birkenbihl
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754, Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115, Bonn, Germany
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10
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Pettigrew C, Soldan A, Brichko R, Zhu Y, Wang MC, Kutten K, Bilgel M, Mori S, Miller MI, Albert M. Computerized paired associate learning performance and imaging biomarkers in older adults without dementia. Brain Imaging Behav 2022; 16:921-929. [PMID: 34686968 PMCID: PMC9012682 DOI: 10.1007/s11682-021-00583-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2021] [Indexed: 01/21/2023]
Abstract
This cross-sectional study examined whether performance on the computerized Paired Associate Learning (PAL) task from the Cambridge Neuropsychological Test Automated Battery is associated with amyloid positivity as measured by Positron Emission Tomography, regional volume composites as measured by Magnetic Resonance Imaging, and cognitive impairment. Participants from the BIOCARD Study (N = 73, including 62 cognitively normal and 11 with mild cognitive impairment; M age = 70 years) completed the PAL task, a comprehensive clinical and neuropsychological assessment, and neuroimaging as part of their annual study visit. In linear regressions covarying age, sex, years of education and diagnosis, higher PAL error scores were associated with amyloid positivity but not with medial temporal or cortical volume composites. By comparison, standard neuropsychological measures of episodic memory and global cognition were unrelated to amyloid positivity, but better performance on the verbal episodic memory measures was associated with larger cortical volume composites. Participants with mild cognitive impairment demonstrated worse cognitive performance on all of the cognitive measures, including the PAL task. These findings suggest that this computerized visual paired associate learning task may be more sensitive to amyloid positivity than standard neuropsychological tests, and may therefore be a promising tool for detecting amyloid positivity in non-demented participants.
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Affiliation(s)
- Corinne Pettigrew
- Department of Neurology, Division of Cognitive Neuroscience, Johns Hopkins University School of Medicine, 1620 McElderry Street, Reed Hall West - 1, Baltimore, MD, 21205, USA.
| | - Anja Soldan
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Rostislav Brichko
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Yuxin Zhu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21287, USA
| | - Mei-Cheng Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21287, USA
| | - Kwame Kutten
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute On Aging, Baltimore, MD, 21224, USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Michael I Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Marilyn Albert
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
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11
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Schilling KG, Tax CM, Rheault F, Hansen C, Yang Q, Yeh FC, Cai L, Anderson AW, Landman BA. Fiber tractography bundle segmentation depends on scanner effects, vendor effects, acquisition resolution, diffusion sampling scheme, diffusion sensitization, and bundle segmentation workflow. Neuroimage 2021; 242:118451. [PMID: 34358660 PMCID: PMC9933001 DOI: 10.1016/j.neuroimage.2021.118451] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 01/08/2023] Open
Abstract
When investigating connectivity and microstructure of white matter pathways of the brain using diffusion tractography bundle segmentation, it is important to understand potential confounds and sources of variation in the process. While cross-scanner and cross-protocol effects on diffusion microstructure measures are well described (in particular fractional anisotropy and mean diffusivity), it is unknown how potential sources of variation effect bundle segmentation results, which features of the bundle are most affected, where variability occurs, nor how these sources of variation depend upon the method used to reconstruct and segment bundles. In this study, we investigate six potential sources of variation, or confounds, for bundle segmentation: variation (1) across scan repeats, (2) across scanners, (3) across vendors (4) across acquisition resolution, (5) across diffusion schemes, and (6) across diffusion sensitization. We employ four different bundle segmentation workflows on two benchmark multi-subject cross-scanner and cross-protocol databases, and investigate reproducibility and biases in volume overlap, shape geometry features of fiber pathways, and microstructure features within the pathways. We find that the effects of acquisition protocol, in particular acquisition resolution, result in the lowest reproducibility of tractography and largest variation of features, followed by vendor-effects, scanner-effects, and finally diffusion scheme and b-value effects which had similar reproducibility as scan-rescan variation. However, confounds varied both across pathways and across segmentation workflows, with some bundle segmentation workflows more (or less) robust to sources of variation. Despite variability, bundle dissection is consistently able to recover the same location of pathways in the deep white matter, with variation at the gray matter/ white matter interface. Next, we show that differences due to the choice of bundle segmentation workflows are larger than any other studied confound, with low-to-moderate overlap of the same intended pathway when segmented using different methods. Finally, quantifying microstructure features within a pathway, we show that tractography adds variability over-and-above that which exists due to noise, scanner effects, and acquisition effects. Overall, these confounds need to be considered when harmonizing diffusion datasets, interpreting or combining data across sites, and when attempting to understand the successes and limitations of different methodologies in the design and development of new tractography or bundle segmentation methods.
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Affiliation(s)
- Kurt G. Schilling
- Department of Radiology & Radiological Science, Vanderbilt University Medical Center, Nashville, TN, United States,Vanderbilt Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Chantal M.W. Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Colin Hansen
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Qi Yang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, United States
| | - Leon Cai
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Adam W. Anderson
- Department of Radiology & Radiological Science, Vanderbilt University Medical Center, Nashville, TN, United States,Vanderbilt Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Bennett A. Landman
- Department of Radiology & Radiological Science, Vanderbilt University Medical Center, Nashville, TN, United States,Vanderbilt Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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12
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Xu J, Green R, Kim M, Lord J, Ebshiana A, Westwood S, Baird AL, Nevado-Holgado AJ, Shi L, Hye A, Snowden SG, Bos I, Vos SJB, Vandenberghe R, Teunissen CE, Kate MT, Scheltens P, Gabel S, Meersmans K, Blin O, Richardson J, De Roeck EE, Engelborghs S, Sleegers K, Bordet R, Rami L, Kettunen P, Tsolaki M, Verhey FRJ, Alcolea D, Lleó A, Peyratout G, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Frisoni GB, Molinuevo JL, Wallin A, Popp J, Martinez-Lage P, Bertram L, Blennow K, Zetterberg H, Streffer J, Visser PJ, Lovestone S, Proitsi P, Legido-Quigley C. Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort. Biomedicines 2021; 9:1610. [PMID: 34829839 PMCID: PMC8615383 DOI: 10.3390/biomedicines9111610] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. METHODS We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD. RESULTS In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). CONCLUSIONS metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.
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Affiliation(s)
- Jin Xu
- Institute of Pharmaceutical Science, King’s College London, London SE1 9NH, UK; (J.X.); (A.E.); (S.G.S.)
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
| | - Rebecca Green
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London SE5 8AF, UK
| | - Min Kim
- Steno Diabetes Center, 2820 Gentofte, Denmark;
| | - Jodie Lord
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
| | - Amera Ebshiana
- Institute of Pharmaceutical Science, King’s College London, London SE1 9NH, UK; (J.X.); (A.E.); (S.G.S.)
| | - Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (S.W.); (A.L.B.); (A.J.N.-H.); (L.S.)
| | - Alison L. Baird
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (S.W.); (A.L.B.); (A.J.N.-H.); (L.S.)
| | - Alejo J. Nevado-Holgado
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (S.W.); (A.L.B.); (A.J.N.-H.); (L.S.)
| | - Liu Shi
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (S.W.); (A.L.B.); (A.J.N.-H.); (L.S.)
| | - Abdul Hye
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
| | - Stuart G. Snowden
- Institute of Pharmaceutical Science, King’s College London, London SE1 9NH, UK; (J.X.); (A.E.); (S.G.S.)
| | - Isabelle Bos
- Alzheimer Center, VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (I.B.); (R.V.); (M.T.K.); (P.S.); (P.J.V.)
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, 6211 LK Maastricht, The Netherlands; (S.J.B.V.); (F.R.J.V.)
| | - Stephanie J. B. Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, 6211 LK Maastricht, The Netherlands; (S.J.B.V.); (F.R.J.V.)
| | - Rik Vandenberghe
- Alzheimer Center, VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (I.B.); (R.V.); (M.T.K.); (P.S.); (P.J.V.)
| | - Charlotte E. Teunissen
- Department of Radiology and Nuclear Medicine, VU University Medical Center, 1081 HV Amsterdam, The Netherlands;
| | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (I.B.); (R.V.); (M.T.K.); (P.S.); (P.J.V.)
- Department of Radiology and Nuclear Medicine, VU University Medical Center, 1081 HV Amsterdam, The Netherlands;
| | - Philip Scheltens
- Alzheimer Center, VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (I.B.); (R.V.); (M.T.K.); (P.S.); (P.J.V.)
| | - Silvy Gabel
- Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands;
- Department of Neurosciences, Laboratory for Cognitive Neurology, KU Leuven, 3000 Leuven, Belgium;
- University Hospital Leuven, 3000 Leuven, Belgium
| | - Karen Meersmans
- Department of Neurosciences, Laboratory for Cognitive Neurology, KU Leuven, 3000 Leuven, Belgium;
- University Hospital Leuven, 3000 Leuven, Belgium
| | - Olivier Blin
- Clinical Pharmacology & Pharmacovigilance Department, Aix-Marseille University-CNRS, 13007 Marseille, France;
| | - Jill Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage SG1 2NY, UK;
| | - Ellen Elisa De Roeck
- Center for Neurosciences, Vrije Universiteit Brussel, 1050 Brussels, Belgium;
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, 2000 Antwerp, Belgium; (S.E.); (J.S.)
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, 2000 Antwerp, Belgium; (S.E.); (J.S.)
- Department of Neurology and Center for Neurosciences (C4N), UZ Brussel and Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium
| | - Kristel Sleegers
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, University of Antwerp, 2000 Antwerp, Belgium;
- Complex Genetics of Alzheimer’s Disease Group, VIB Center for Molecular Neurology, VIB, 2000 Antwerp, Belgium
| | - Régis Bordet
- Department of Medical Pharmacology, Université de Lille, 59000 Lille, France;
| | - Lorena Rami
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic of Barcelona, August Pi Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain; (L.R.); (J.L.M.)
| | - Petronella Kettunen
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden; (P.K.); (A.W.)
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, 546 21 Thessaloniki, Greece;
| | - Frans R. J. Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, 6211 LK Maastricht, The Netherlands; (S.J.B.V.); (F.R.J.V.)
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (D.A.); (A.L.)
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (D.A.); (A.L.)
| | | | - Mikel Tainta
- Fundación CITA-Alzhéimer Fundazioa, 20009 San Sebastian, Spain;
| | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, 2100 Copenhagen, Denmark;
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Karolinska University Hospital Huddinge, 141 86 Stockholm, Sweden;
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London SE5 8AF, UK
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68167 Mannheim, Germany;
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, 23562 Lübeck, Germany; (V.D.); (L.B.)
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, 1205 Geneva, Switzerland;
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - José Luis Molinuevo
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic of Barcelona, August Pi Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain; (L.R.); (J.L.M.)
- Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, 08002 Barcelona, Spain
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden; (P.K.); (A.W.)
| | - Julius Popp
- Old Age Psychiatry, Department of Psychiatry, University Hospital Lausanne, 1011 Lausanne, Switzerland;
- Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, 8008 Zürich, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, 20009 San Sebastian, Spain;
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, 23562 Lübeck, Germany; (V.D.); (L.B.)
- Department of Psychology, University of Oslo, 0315 Oslo, Norway
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden; (K.B.); (H.Z.)
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 415 45 Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden; (K.B.); (H.Z.)
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 415 45 Mölndal, Sweden
- UK Dementia Research Institute at UCL, London WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N 3BG, UK
| | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, 2000 Antwerp, Belgium; (S.E.); (J.S.)
| | - Pieter Jelle Visser
- Alzheimer Center, VU University Medical Center, 1081 HV Amsterdam, The Netherlands; (I.B.); (R.V.); (M.T.K.); (P.S.); (P.J.V.)
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, 6211 LK Maastricht, The Netherlands; (S.J.B.V.); (F.R.J.V.)
| | - Simon Lovestone
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; (S.W.); (A.L.B.); (A.J.N.-H.); (L.S.)
- Janssen-Cilag UK Ltd., Oxford HP12 4EG, UK
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London SE5 9RT, UK; (R.G.); (J.L.); (A.H.); (S.L.)
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King’s College London, London SE1 9NH, UK; (J.X.); (A.E.); (S.G.S.)
- Steno Diabetes Center, 2820 Gentofte, Denmark;
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13
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Tsolaki M, Tsatali M, Gkioka M, Poptsi E, Tsolaki A, Papaliagkas V, Tabakis IM, Lazarou I, Makri M, Kazis D, Papagiannopoulos S, Kiryttopoulos A, Koutsouraki E, Tegos T. Memory Clinics and Day Care Centers in Thessaloniki, Northern Greece: 30 Years of Clinical Practice and Experience. Front Neurol 2021; 12:683131. [PMID: 34512506 PMCID: PMC8425245 DOI: 10.3389/fneur.2021.683131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/25/2021] [Indexed: 11/17/2022] Open
Abstract
Background: This review describes the diagnostic and interventional procedures conducted in two university memory clinics (established network of G. Papanikolaou Hospital: 1988–2017 and AHEPA hospital: 2017–today) and 2 day care centers (established network of DCCs: 2005–today) in North Greece and their contribution in the scientific field of dementia. The aims of this work are (1) to provide a diagnosis and treatment protocol established in the network of memory clinics and DCCs and (2) to present further research conducted in the aforementioned network during the last 30 years of clinical practice. Methods: The guidelines to set a protocol demand a series of actions as follows: (1) set the diagnosis criteria, neuropsychological assessment, laboratory examinations, and examination of neurophysiological, neuroimaging, cerebrospinal fluid, blood, and genetic markers; and (2) apply non-pharmacological interventions according to the needs and specialized psychosocial interventions of the patient to the caregivers of the patient. Results: In addition to the guidelines followed in memory clinics at the 1st and 3rd Department of Neurology and two DCCs, a database of patients, educational programs, and further participation in international research programs, including clinical trials, make our contribution in the dementia field strong. Conclusion: In the current paper, we provide useful guidelines on how major and minor neurocognitive disorders are being treated in Thessaloniki, Greece, describing successful practices which have been adapted in the last 30 years.
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Affiliation(s)
- Magda Tsolaki
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece.,1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI - AUTh) Balkan Center, Buildings A & B, Aristotle University of Thessaloniki, Thessaloniki, Greece.,3rd University Department of Neurology "G. Papanikolaou" Hospital, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Marianna Tsatali
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Mara Gkioka
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece.,1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Eleni Poptsi
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Anthoula Tsolaki
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece.,1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vasileios Papaliagkas
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece.,Department of Biomedical Sciences International Hellenic University, Thessaloniki, Greece
| | - Irene-Maria Tabakis
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Ioulietta Lazarou
- 1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Marina Makri
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece.,1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Dimitrios Kazis
- 3rd University Department of Neurology "G. Papanikolaou" Hospital, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Sotirios Papagiannopoulos
- 3rd University Department of Neurology "G. Papanikolaou" Hospital, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Andreas Kiryttopoulos
- 1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Efrosyni Koutsouraki
- 1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Thomas Tegos
- 1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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14
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Quattrini G, Marizzoni M, Pizzini FB, Galazzo IB, Aiello M, Didic M, Soricelli A, Albani D, Romano M, Blin O, Forloni G, Golay X, Jovicich J, Nathan PJ, Richardson JC, Salvatore M, Frisoni GB, Pievani M. Convergent and Discriminant Validity of Default Mode Network and Limbic Network Perfusion in Amnestic Mild Cognitive Impairment Patients. J Alzheimers Dis 2021; 82:1797-1808. [PMID: 34219733 DOI: 10.3233/jad-210531] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Previous studies reported default mode network (DMN) and limbic network (LIN) brain perfusion deficits in patients with amnestic mild cognitive impairment (aMCI), frequently a prodromal stage of Alzheimer's disease (AD). However, the validity of these measures as AD markers has not yet been tested using MRI arterial spin labeling (ASL). OBJECTIVE To investigate the convergent and discriminant validity of DMN and LIN perfusion in aMCI. METHODS We collected core AD markers (amyloid-β 42 [Aβ42], phosphorylated tau 181 levels in cerebrospinal fluid [CSF]), neurodegenerative (hippocampal volumes and CSF total tau), vascular (white matter hyperintensities), genetic (apolipoprotein E [APOE] status), and cognitive features (memory functioning on Paired Associate Learning test [PAL]) in 14 aMCI patients. Cerebral blood flow (CBF) was extracted from DMN and LIN using ASL and correlated with AD features to assess convergent validity. Discriminant validity was assessed carrying out the same analysis with AD-unrelated features, i.e., somatomotor and visual networks' perfusion, cerebellar volume, and processing speed. RESULTS Perfusion was reduced in the DMN (F = 5.486, p = 0.039) and LIN (F = 12.678, p = 0.004) in APOE ɛ4 carriers compared to non-carriers. LIN perfusion correlated with CSF Aβ42 levels (r = 0.678, p = 0.022) and memory impairment (PAL, number of errors, r = -0.779, p = 0.002). No significant correlation was detected with tau, neurodegeneration, and vascular features, nor with AD-unrelated features. CONCLUSION Our results support the validity of DMN and LIN ASL perfusion as AD markers in aMCI, indicating a significant correlation between CBF and amyloidosis, APOE ɛ4, and memory impairment.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Francesca B Pizzini
- Radiology, Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | | | | | - Mira Didic
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, Marseille, France.,APHM, Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Sport Sciences, University of Naples Parthenope, Naples, Italy
| | - Diego Albani
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Melissa Romano
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, DHUNE, Ap-Hm, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jorge Jovicich
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Pradeep J Nathan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | | | - Giovanni B Frisoni
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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15
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Archetti D, Young AL, Oxtoby NP, Ferreira D, Mårtensson G, Westman E, Alexander DC, Frisoni GB, Redolfi A. Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease. Front Big Data 2021; 4:661110. [PMID: 34095821 PMCID: PMC8173213 DOI: 10.3389/fdata.2021.661110] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/04/2021] [Indexed: 01/15/2023] Open
Abstract
Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.
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Affiliation(s)
- Damiano Archetti
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Alexandra L Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom
| | - Neil P Oxtoby
- Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Gustav Mårtensson
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Daniel C Alexander
- Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland.,Laboratory of Alzheimer's Neuroimaging and Epidemiology - LANE, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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16
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Hanas JS, Hocker JRS, Vannarath CA, Lerner MR, Blair SG, Lightfoot SA, Hanas RJ, Couch JR, Hershey LA. Distinguishing Alzheimer's Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis. Brain Sci 2021; 11:brainsci11050583. [PMID: 33946285 PMCID: PMC8145311 DOI: 10.3390/brainsci11050583] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 04/25/2021] [Accepted: 04/27/2021] [Indexed: 11/16/2022] Open
Abstract
It is important to develop minimally invasive biomarker platforms to help in the identification and monitoring of patients with Alzheimer's disease (AD). Assisting in the understanding of biochemical mechanisms as well as identifying potential novel biomarkers and therapeutic targets would be an added benefit of such platforms. This study utilizes a simplified and novel serum profiling platform, using mass spectrometry (MS), to help distinguish AD patient groups (mild and moderate) and controls, as well as to aid in understanding of biochemical phenotypes and possible disease development. A comparison of discriminating sera mass peaks between AD patients and control individuals was performed using leave one [serum sample] out cross validation (LOOCV) combined with a novel peak classification valuation (PCV) procedure. LOOCV/PCV was able to distinguish significant sera mass peak differences between a group of mild AD patients and control individuals with a p value of 10-13. This value became non-significant (p = 0.09) when the same sera samples were randomly allocated between the two groups and reanalyzed by LOOCV/PCV. This is indicative of physiological group differences in the original true-pathology binary group comparison. Similarities and differences between AD patients and traumatic brain injury (TBI) patients were also discernable using this novel LOOCV/PCV platform. MS/MS peptide analysis was performed on serum mass peaks comparing mild AD patients with control individuals. Bioinformatics analysis suggested that cell pathways/biochemical phenotypes affected in AD include those involving neuronal cell death, vasculature, neurogenesis, and AD/dementia/amyloidosis. Inflammation, autoimmunity, autophagy, and blood-brain barrier pathways also appear to be relevant to AD. An impaired VWF/ADAMTS13 vasculature axis with connections to F8 (factor VIII) and LRP1 and NOTCH1 was indicated and is proposed to be important in AD development.
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Affiliation(s)
- Jay S. Hanas
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
- Veterans Administration Hospital, Oklahoma City, OK 73104, USA;
- Correspondence:
| | - James R. S. Hocker
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - Christian A. Vannarath
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - Megan R. Lerner
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
| | - Scott G. Blair
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
| | | | - Rushie J. Hanas
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - James R. Couch
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.C.); (L.A.H.)
| | - Linda A. Hershey
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.C.); (L.A.H.)
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17
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Babiloni C, Ferri R, Noce G, Lizio R, Lopez S, Lorenzo I, Panzavolta A, Soricelli A, Nobili F, Arnaldi D, Famà F, Orzi F, Buttinelli C, Giubilei F, Cipollini V, Marizzoni M, Güntekin B, Aktürk T, Hanoğlu L, Yener G, Özbek Y, Stocchi F, Vacca L, Frisoni GB, Del Percio C. Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment. Cereb Cortex 2021; 31:2220-2237. [PMID: 33251540 DOI: 10.1093/cercor/bhaa356] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 12/21/2022] Open
Abstract
In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino, Italy
| | | | | | | | - Susanna Lopez
- Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, Aldo Moro University of Bari, Bari, Italy
| | | | - Andrea Panzavolta
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Dario Arnaldi
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Francesco Famà
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Virginia Cipollini
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey.,Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Yağmur Özbek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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18
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Abate G, Vezzoli M, Polito L, Guaita A, Albani D, Marizzoni M, Garrafa E, Marengoni A, Forloni G, Frisoni GB, Cummings JL, Memo M, Uberti D. A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages. J Pers Med 2020; 11:14. [PMID: 33375220 PMCID: PMC7823360 DOI: 10.3390/jpm11010014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/22/2020] [Accepted: 12/24/2020] [Indexed: 12/12/2022] Open
Abstract
Early diagnosis of Alzheimer's disease (AD) is a crucial starting point in disease management. Blood-based biomarkers could represent a considerable advantage in providing AD-risk information in primary care settings. Here, we report new data for a relatively unknown blood-based biomarker that holds promise for AD diagnosis. We evaluate a p53-misfolding conformation recognized by the antibody 2D3A8, also named Unfolded p53 (U-p532D3A8+), in 375 plasma samples derived from InveCe.Ab and PharmaCog/E-ADNI longitudinal studies. A machine learning approach is used to combine U-p532D3A8+ plasma levels with Mini-Mental State Examination (MMSE) and apolipoprotein E epsilon-4 (APOEε4) and is able to predict AD likelihood risk in InveCe.Ab with an overall 86.67% agreement with clinical diagnosis. These algorithms also accurately classify (AUC = 0.92) Aβ+-amnestic Mild Cognitive Impairment (aMCI) patients who will develop AD in PharmaCog/E-ADNI, where subjects were stratified according to Cerebrospinal fluid (CSF) AD markers (Aβ42 and p-Tau). Results support U-p532D3A8+ plasma level as a promising additional candidate blood-based biomarker for AD.
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Affiliation(s)
- Giulia Abate
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy; (G.A.); (M.V.); (E.G.); (M.M.)
| | - Marika Vezzoli
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy; (G.A.); (M.V.); (E.G.); (M.M.)
| | - Letizia Polito
- GolgiCenci Foundation, 20081 Abbiategrasso, Italy; (L.P.); (A.G.)
| | - Antonio Guaita
- GolgiCenci Foundation, 20081 Abbiategrasso, Italy; (L.P.); (A.G.)
| | - Diego Albani
- Department of Neuroscience, IRCCS-Istituto di Ricerche Farmacologiche “Mario Negri”, 20156 Milan, Italy; (D.A.); (G.F.)
| | - Moira Marizzoni
- Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy;
| | - Emirena Garrafa
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy; (G.A.); (M.V.); (E.G.); (M.M.)
| | - Alessandra Marengoni
- Department of Clinical and Experimental Sciences, University of Brescia, Lombardy, 25123 Brescia, Italy;
| | - Gianluigi Forloni
- Department of Neuroscience, IRCCS-Istituto di Ricerche Farmacologiche “Mario Negri”, 20156 Milan, Italy; (D.A.); (G.F.)
| | - Giovanni B. Frisoni
- Memory Clinic, University Hospitals and University of Geneva, 1205 Geneva, Switzerland;
| | - Jeffrey L. Cummings
- Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV) and Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA;
| | - Maurizio Memo
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy; (G.A.); (M.V.); (E.G.); (M.M.)
| | - Daniela Uberti
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy; (G.A.); (M.V.); (E.G.); (M.M.)
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
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19
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Resting-state electroencephalographic delta rhythms may reflect global cortical arousal in healthy old seniors and patients with Alzheimer's disease dementia. Int J Psychophysiol 2020; 158:259-270. [DOI: 10.1016/j.ijpsycho.2020.08.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 08/25/2020] [Accepted: 08/27/2020] [Indexed: 12/23/2022]
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20
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Ribaldi F, Altomare D, Jovicich J, Ferrari C, Picco A, Pizzini FB, Soricelli A, Mega A, Ferretti A, Drevelegas A, Bosch B, Müller BW, Marra C, Cavaliere C, Bartrés-Faz D, Nobili F, Alessandrini F, Barkhof F, Gros-Dagnac H, Ranjeva JP, Wiltfang J, Kuijer J, Sein J, Hoffmann KT, Roccatagliata L, Parnetti L, Tsolaki M, Constantinidis M, Aiello M, Salvatore M, Montalti M, Caulo M, Didic M, Bargallo N, Blin O, Rossini PM, Schonknecht P, Floridi P, Payoux P, Visser PJ, Bordet R, Lopes R, Tarducci R, Bombois S, Hensch T, Fiedler U, Richardson JC, Frisoni GB, Marizzoni M. Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study. Magn Reson Imaging 2020; 76:108-115. [PMID: 33220450 DOI: 10.1016/j.mri.2020.11.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 10/02/2020] [Accepted: 11/14/2020] [Indexed: 01/18/2023]
Abstract
Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was -0.22[IQR = 0.50] for LGA-SPM8, -0.12[0.57] for LGA-SPM12, -0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.
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Affiliation(s)
- Federica Ribaldi
- Laboratory of Alzheimer's Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, Geneva University Hospitals, Geneva, Switzerland.
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Jorge Jovicich
- Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Agnese Picco
- Department of Neuroscience, Ophthalmology, Genetics and Mother-Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | | | - Anna Mega
- Laboratory of Alzheimer's Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonio Ferretti
- Department of Neuroscience Imaging and Clinical Sciences, University "G. d'Annunzio" of Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio" of Chieti, Italy
| | - Antonios Drevelegas
- Interbalkan Medical Center of Thessaloniki, Thessaloniki, Greece; Department of Radiology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Beatriz Bosch
- Department of Psychiatry and Clinical Psychobiology, Universitat de Barcelona and IDIBAPS, Barcelona, Spain
| | - Bernhard W Müller
- LVR-Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg-Essen, Essen, Germany
| | - Camillo Marra
- Center for Neuropsychological Research, Catholic University, Rome, Italy
| | | | - David Bartrés-Faz
- Department of Psychiatry and Clinical Psychobiology, Universitat de Barcelona and IDIBAPS, Barcelona, Spain
| | - Flavio Nobili
- Dept. of Neuroscience (DINOGMI), University of Genoa, Italy; IRCCS Ospedale Policlinico San Martino Genova, Italy
| | - Franco Alessandrini
- Radiology, Dept. of Diagnostic and Public Health, Verona University, Verona, Italy
| | - Frederik Barkhof
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Helene Gros-Dagnac
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France; Université Toulouse 3 Paul Sabatier, UMR 825 Imagerie Cérébrale et Handicaps Neurologiques, F-31024 Toulouse, France
| | - Jean-Philippe Ranjeva
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August University, Göttingen, Germany
| | - Joost Kuijer
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Julien Sein
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | | | - Luca Roccatagliata
- IRCCS Ospedale Policlinico San Martino Genova, Italy; Dept. of Health Sciences (DISSAL), University of Genoa, Italy
| | - Lucilla Parnetti
- Section of Neurology, Centre for Memory Disturbances, University of Perugia, Perugia, Italy
| | - Magda Tsolaki
- 1st Department of Neurology, Aristotle University of Thessaloniki, Makedonia, Greece
| | | | | | | | - Martina Montalti
- Laboratory of Alzheimer's Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Massimo Caulo
- Department of Neuroscience Imaging and Clinical Sciences, University "G. d'Annunzio" of Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio" of Chieti, Italy
| | - Mira Didic
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Núria Bargallo
- Department of Neuroradiology and Magnetic Resonance Image Core Facility, Hospital Clínic de Barcelona, IDIBAPS, Barcelona, Spain
| | - Olivier Blin
- Aix Marseille University, UMR-INSERM 1106, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Paolo M Rossini
- Dept. Neuroscience & Neurorehabilitation, IRCCS-San Raffaele-Pisana, Rome, Italy
| | - Peter Schonknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Piero Floridi
- Neuroradiology Unit, Perugia General Hospital, Perugia, Italy
| | - Pierre Payoux
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Régis Bordet
- Univ. Lille, INSERM, CHU Lille, Lille Neuroscience & Cognition - Degenerative and Vascular Cognitive Disorders-U1172. F-59000 Lille, France
| | - Renaud Lopes
- Univ. Lille, INSERM, CHU Lille, Lille Neuroscience & Cognition - Degenerative and Vascular Cognitive Disorders-U1172. F-59000 Lille, France
| | | | - Stephanie Bombois
- Univ. Lille, INSERM, CHU Lille, Lille Neuroscience & Cognition - Degenerative and Vascular Cognitive Disorders-U1172. F-59000 Lille, France
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Ute Fiedler
- LVR-Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg-Essen, Essen, Germany
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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21
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Del Percio C, Drinkenburg W, Lopez S, Pascarelli MT, Lizio R, Noce G, Ferri R, Bastlund JF, Laursen B, Christensen DZ, Pedersen JT, Forloni G, Frasca A, Noè FM, Fabene PF, Bertini G, Colavito V, Bentivoglio M, Kelley J, Dix S, Infarinato F, Soricelli A, Stocchi F, Richardson JC, Babiloni C. Ongoing Electroencephalographic Rhythms Related to Exploratory Movements in Transgenic TASTPM Mice. J Alzheimers Dis 2020; 78:291-308. [PMID: 32955458 DOI: 10.3233/jad-190351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The European PharmaCog study (http://www.pharmacog.org) has reported a reduction in delta (1-6 Hz) electroencephalographic (EEG) power (density) during cage exploration (active condition) compared with quiet wakefulness (passive condition) in PDAPP mice (hAPP Indiana V717F mutation) modeling Alzheimer's disease (AD) amyloidosis and cognitive deficits. OBJECTIVE Here, we tested the reproducibility of that evidence in TASTPM mice (double mutation in APP KM670/671NL and PSEN1 M146V), which develop brain amyloidosis and cognitive deficits over aging. The reliability of that evidence was examined in four research centers of the PharmaCog study. METHODS Ongoing EEG rhythms were recorded from a frontoparietal bipolar channel in 29 TASTPM and 58 matched "wild type" C57 mice (range of age: 12-24 months). Normalized EEG power was calculated. Frequency and amplitude of individual delta and theta frequency (IDF and ITF) peaks were considered during the passive and active conditions. RESULTS Compared with the "wild type" group, the TASTPM group showed a significantly lower reduction in IDF power during the active over the passive condition (p < 0.05). This effect was observed in 3 out of 4 EEG recording units. CONCLUSION TASTPM mice were characterized by "poor reactivity" of delta EEG rhythms during the cage exploration in line with previous evidence in PDAPP mice. The reliability of that result across the centers was moderate, thus unveiling pros and cons of multicenter preclinical EEG trials in TASTPM mice useful for planning future studies.
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Affiliation(s)
- Claudio Del Percio
- Department of Physiology and Pharmacology "V Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Susanna Lopez
- Department of Physiology and Pharmacology "V Erspamer", Sapienza University of Rome, Rome, Italy.,Department of Emergency and Organ Transplantation - Nephrology, Dialysis and Transplantation Unit, Aldo Moro University of Bari, Bari, Italy
| | | | | | | | | | | | | | | | | | - Gianluigi Forloni
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Angelisa Frasca
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Francesco M Noè
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Paolo Francesco Fabene
- Department of Neurological Biomedical and Movement Sciences, University of Verona, Verona, Italy
| | - Giuseppe Bertini
- Department of Neurological Biomedical and Movement Sciences, University of Verona, Verona, Italy
| | - Valeria Colavito
- Department of Neurological Biomedical and Movement Sciences, University of Verona, Verona, Italy
| | - Marina Bentivoglio
- Department of Neurological Biomedical and Movement Sciences, University of Verona, Verona, Italy
| | - Jonathan Kelley
- Janssen Research and Development, Pharmaceutical Companies of J&J, Beerse, Belgium
| | - Sophie Dix
- Eli Lilly, Erl Wood Manor, Windlesham, Surrey, UK
| | | | - Andrea Soricelli
- IRCCS SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Roma, Italy
| | - Jill C Richardson
- GlaxoSmithKline R&D Neurotherapeutics Area UK, Gunnels Wood Road, Stevenage, Hertfordshire, UK
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele Cassino, Cassino (FR), Italy
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22
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Albani D, Marizzoni M, Ferrari C, Fusco F, Boeri L, Raimondi I, Jovicich J, Babiloni C, Soricelli A, Lizio R, Galluzzi S, Cavaliere L, Didic M, Schönknecht P, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Bocchio L, Salvatore M, Rossini PM, Tsolaki M, Visser PJ, Richardson JC, Wiltfang J, Bordet R, Blin O, Forloni G, Frisoni GB. Plasma Aβ42 as a Biomarker of Prodromal Alzheimer's Disease Progression in Patients with Amnestic Mild Cognitive Impairment: Evidence from the PharmaCog/E-ADNI Study. J Alzheimers Dis 2020; 69:37-48. [PMID: 30149449 DOI: 10.3233/jad-180321] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.
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Affiliation(s)
- Diego Albani
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Federica Fusco
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Lucia Boeri
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Ilaria Raimondi
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Jorge Jovicich
- MR Lab Head, Center for Mind/Brain Sciences, University of Trento, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy.,Department of Neuroscience, IRCCS San Raffaele Pisana of Rome and Cassino, Rome and Cassino, Italy
| | - Andrea Soricelli
- IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | - Roberta Lizio
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, INSERM, INS UMR_S 1106, Marseille, France.,APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany, Germany
| | - José Luis Molinuevo
- Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM, Imagerie cérébrale et handicaps neurologiques UMR 825, Toulouse, France
| | - Luisella Bocchio
- Genetic Unit, IRCCS Centro Giovanni di Dio, Fatebenefratelli, Brescia, Italy; Faculty of Psychology, University eCampus, Novedrate (Como), Italy
| | - Marco Salvatore
- IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | - Paolo Maria Rossini
- Department of Gerontology, Neurosciences and Orthopedics, Catholic University, Rome, Italy.,Policlinic A. Gemelli Foundation
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | - Jens Wiltfang
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany.,iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Gianluigi Forloni
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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23
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Cocco S, Rinaudo M, Fusco S, Longo V, Gironi K, Renna P, Aceto G, Mastrodonato A, Li Puma DD, Podda MV, Grassi C. Plasma BDNF Levels Following Transcranial Direct Current Stimulation Allow Prediction of Synaptic Plasticity and Memory Deficits in 3×Tg-AD Mice. Front Cell Dev Biol 2020; 8:541. [PMID: 32719795 PMCID: PMC7349675 DOI: 10.3389/fcell.2020.00541] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 06/09/2020] [Indexed: 12/12/2022] Open
Abstract
Early diagnosis of Alzheimer’s disease (AD) supposedly increases the effectiveness of therapeutic interventions. However, presently available diagnostic procedures are either invasive or require complex and expensive technologies, which cannot be applied at a larger scale to screen populations at risk of AD. We were looking for a biomarker allowing to unveil a dysfunction of molecular mechanisms, which underly synaptic plasticity and memory, before the AD phenotype is manifested and investigated the effects of transcranial direct current stimulation (tDCS) in 3×Tg-AD mice, an experimental model of AD which does not exhibit any long-term potentiation (LTP) and memory deficits at the age of 3 months (3×Tg-AD-3M). Our results demonstrated that tDCS differentially affected 3×Tg-AD-3M and age-matched wild-type (WT) mice. While tDCS increased LTP at CA3-CA1 synapses and memory in WT mice, it failed to elicit these effects in 3×Tg-AD-3M mice. Remarkably, 3×Tg-AD-3M mice did not show the tDCS-dependent increases in pCREBSer133 and pCaMKIIThr286, which were found in WT mice. Of relevance, tDCS induced a significant increase of plasma BDNF levels in WT mice, which was not found in 3×Tg-AD-3M mice. Collectively, our results showed that plasticity mechanisms are resistant to tDCS effects in the pre-AD stage. In particular, the lack of BDNF responsiveness to tDCS in 3×Tg-AD-3M mice suggests that combining tDCS with dosages of plasma BDNF levels may provide an easy-to-detect and low-cost biomarker of covert impairment of synaptic plasticity mechanisms underlying memory, which could be clinically applicable. Testing proposed here might be useful to identify AD in its preclinical stage, allowing timely and, hopefully, more effective disease-modifying interventions.
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Affiliation(s)
- Sara Cocco
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Marco Rinaudo
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Salvatore Fusco
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Valentina Longo
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Katia Gironi
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Pietro Renna
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Giuseppe Aceto
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy
| | | | - Domenica Donatella Li Puma
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Maria Vittoria Podda
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Claudio Grassi
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
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24
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Babiloni C, Lopez S, Del Percio C, Noce G, Pascarelli MT, Lizio R, Teipel SJ, González-Escamilla G, Bakardjian H, George N, Cavedo E, Lista S, Chiesa PA, Vergallo A, Lemercier P, Spinelli G, Grothe MJ, Potier MC, Stocchi F, Ferri R, Habert MO, Fraga FJ, Dubois B, Hampel H. Resting-state posterior alpha rhythms are abnormal in subjective memory complaint seniors with preclinical Alzheimer's neuropathology and high education level: the INSIGHT-preAD study. Neurobiol Aging 2020; 90:43-59. [DOI: 10.1016/j.neurobiolaging.2020.01.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 01/24/2020] [Accepted: 01/26/2020] [Indexed: 01/05/2023]
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25
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Rolandi E, Dodich A, Galluzzi S, Ferrari C, Mandelli S, Ribaldi F, Munaretto G, Ambrosi C, Gasparotti R, Violi D, Canessa N, Iannaccone S, Marcone A, Falini A, Hampel H, Frisoni GB, Cerami C, Cavedo E. Randomized controlled trial on the efficacy of a multilevel non-pharmacologic intervention in older adults with subjective memory decline: design and baseline findings of the E.Mu.N.I. study. Aging Clin Exp Res 2020; 32:817-826. [PMID: 31749018 DOI: 10.1007/s40520-019-01403-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 10/30/2019] [Indexed: 01/19/2023]
Abstract
BACKGROUND Alzheimer's Disease (AD) is a multifactorial disorder driven by genetic and modifiable lifestyle risk factors. Lifestyle primary prevention initiatives may reduce the prevalence and incidence of dementia in older adults. OBJECTIVES The E.Mu.N.I study is a randomized controlled trial investigating the effect of multilevel non-pharmacologic interventions on cognitive performances (primary outcome) and structural and vascular brain MRI markers (secondary outcome), as well as markers of brain functional connectivity change (exploratory outcome), in older adults with subjective memory decline (SMD). Here, we present the study design and the baseline features of the sample. METHODS Cognitively intact older adults with SMD, enrolled between February 2016 and June 2017, were randomly assigned to one of the 3 interventions for 1 year: Active Control Intervention (ACI), i.e., educational lessons; Partial Intervention (PI), i.e., homotaurine administration (100 mg/die) and lessons on the Mediterranean diet; Multilevel Intervention (MI), i.e., PI plus computerized cognitive training and physical exercise training. RESULTS One-hundred and twenty-eight eligible participants were enrolled (66% female; age: 68 ± 5 years). Eighty-two percent of the sample was composed of volunteers with SMD from the community. Participants were randomly allocated to the interventions as follows: ACI (N = 40), PI (N = 44), MI (N = 44). No significant differences among groups emerged on socio-demographic, clinical-neuropsychological variables and MRI markers at baseline. CONCLUSIONS The outcomes obtained from the E.Mu.N.I. study will clarify the efficacy of multilevel non-pharmacologic interventions on cognitive and neuroimaging markers in SMD individuals. This is a crucial step forward for the development of cost-effective non-pharmacologic primary prevention initiatives for AD.
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Affiliation(s)
- Elena Rolandi
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Alessandra Dodich
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
| | - Samantha Galluzzi
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Clarissa Ferrari
- Statistics Service, IRCCS Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Sara Mandelli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Federica Ribaldi
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Ageing, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giulio Munaretto
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Department of Life Sciences, University of Trieste, Trieste, Italy
| | - Claudia Ambrosi
- Department of Diagnostic Imaging, Neuroradiology Unit, University of Brescia, Brescia, Italy
| | - Roberto Gasparotti
- Department of Diagnostic Imaging, Neuroradiology Unit, University of Brescia, Brescia, Italy
| | - Davide Violi
- Millennium Sport and Fitness, 25124, Brescia, Italy
| | - Nicola Canessa
- NEtS Center, Scuola Universitaria Superiore IUSS Pavia, 27100, Pavia, Italy
- Cognitive Neuroscience Laboratory, IRCCS ICS Maugeri, 27100, Pavia, Italy
| | - Sandro Iannaccone
- Department of Clinical Neuroscience, San Raffaele Turro Hospital, 20132, Milan, Italy
| | - Alessandra Marcone
- Department of Clinical Neuroscience, San Raffaele Turro Hospital, 20132, Milan, Italy
| | - Andrea Falini
- Division of Neuroscience, Department of Neuroradiology and CERMAC, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Harald Hampel
- Alzheimer Precision Medicine (APM), Établissements Publics à Caractère Scientifique et Technologique (E.P.S.T.), AP-HP, Pitié-Salpêtrière Hospital, Sorbonne University Clinical Research Group (GRC n°21), Boulevard de l'hôpital, 75013, Paris, France
- Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, 75013, Paris, France
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Institute of Memory and Alzheimer's Disease (IM2A), François Lhermitte Building, 47 Boulevard de l'hôpital, 75013, Paris Cedex 13, France
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Ageing, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Chiara Cerami
- Cognitive Neuroscience Laboratory, IRCCS ICS Maugeri, 27100, Pavia, Italy
| | - Enrica Cavedo
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
- Alzheimer Precision Medicine (APM), Établissements Publics à Caractère Scientifique et Technologique (E.P.S.T.), AP-HP, Pitié-Salpêtrière Hospital, Sorbonne University Clinical Research Group (GRC n°21), Boulevard de l'hôpital, 75013, Paris, France.
- Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, 75013, Paris, France.
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Institute of Memory and Alzheimer's Disease (IM2A), François Lhermitte Building, 47 Boulevard de l'hôpital, 75013, Paris Cedex 13, France.
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26
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Iacono D, Feltis GC. Impact of Apolipoprotein E gene polymorphism during normal and pathological conditions of the brain across the lifespan. Aging (Albany NY) 2020; 11:787-816. [PMID: 30677746 PMCID: PMC6366964 DOI: 10.18632/aging.101757] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 01/05/2019] [Indexed: 12/12/2022]
Abstract
The central nervous system (CNS) is the cellular substrate for the integration of complex, dynamic, constant, and simultaneous interactions among endogenous and exogenous stimuli across the entire human lifespan. Numerous studies on aging-related brain diseases show that some genes identified as risk factors for some of the most common neurodegenerative diseases - such as the allele 4 of APOE gene (APOE4) for Alzheimer's disease (AD) - have a much earlier neuro-anatomical and neuro-physiological impact. The impact of APOE polymorphism appears in fact to start as early as youth and early-adult life. Intriguingly, though, those same genes associated with aging-related brain diseases seem to influence different aspects of the brain functioning much earlier actually, that is, even from the neonatal periods and earlier. The APOE4, an allele classically associated with later-life neurodegenerative disorders as AD, seems in fact to exert a series of very early effects on phenomena of neuroplasticity and synaptogenesis that begin from the earliest periods of life such as the fetal ones.We reviewed some of the findings supporting the hypothesis that APOE polymorphism is an early modifier of various neurobiological aspects across the entire human lifespan - from the in-utero to the centenarian life - during both normal and pathological conditions of the brain.
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Affiliation(s)
- Diego Iacono
- Neuropathology Research, Biomedical Research Institute of New Jersey (BRInj), Cedar Knolls, NJ 07927, USA.,MidAtlantic Neonatology Associates (MANA), Morristown, NJ 07960, USA.,Atlantic Neuroscience Institute, Atlantic Health System (AHS), Overlook Medical Center, Summit, NJ 07901, USA
| | - Gloria C Feltis
- Neuropathology Research, Biomedical Research Institute of New Jersey (BRInj), Cedar Knolls, NJ 07927, USA
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27
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Luque Laguna PA, Combes AJE, Streffer J, Einstein S, Timmers M, Williams SCR, Dell'Acqua F. Reproducibility, reliability and variability of FA and MD in the older healthy population: A test-retest multiparametric analysis. NEUROIMAGE-CLINICAL 2020; 26:102168. [PMID: 32035272 PMCID: PMC7011084 DOI: 10.1016/j.nicl.2020.102168] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 01/10/2020] [Accepted: 01/10/2020] [Indexed: 12/13/2022]
Abstract
In older healthy subjects, FA and MD show overall good test-retest reliability & reproducibility. MD is sistematically more reproducible than FA across the entire brain anatomy. FA is more reliable than MD in subcortical white matter regions. In high reliability & low reproducibility regions, variability between subjects is high and statistical power is low. In low reliability & high reproducibility regions, variability between subjects is low and statistical power is high.
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Affiliation(s)
- Pedro A Luque Laguna
- Department 5 of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Natbrainlab, Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK; Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.
| | - Anna J E Combes
- Department 5 of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Johannes Streffer
- UCB Biopharma SPRL, Chemin du Foriest B-1420 Braine-l'Alleud, Belgium; Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Steven Einstein
- Janssen Research and Development LLC, Titusville, NJ, US; UCB Biopharma SPRL, Chemin du Foriest B-1420 Braine-l'Alleud, Belgium
| | - Maarten Timmers
- Janssen Research and Development, a division of Janssen Pharmaceutica NV, Beerse, Belgium; Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Steve C R Williams
- Department 5 of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Flavio Dell'Acqua
- Natbrainlab, Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK; Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.
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28
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Westwood S, Baird AL, Anand SN, Nevado-Holgado AJ, Kormilitzin A, Shi L, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJ, Baker S, Buckley NJ, Ten Kate M, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Bertram L, Barkhof F, Zetterberg H, Morgan BP, Streffer J, Visser PJ, Lovestone S. Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort. J Alzheimers Dis 2020; 74:213-225. [PMID: 31985466 PMCID: PMC7175945 DOI: 10.3233/jad-190434] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.
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Affiliation(s)
| | | | | | | | | | - Liu Shi
- Department of Psychiatry, University of Oxford, UK
| | - Abdul Hye
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Nicholas J. Ashton
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular & Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | | | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J.B. Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | | | | | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | | | | | - Silvy Gabel
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium
| | - Karen Meersmans
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium
| | - Sebastiaan Engelborghs
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, University of Antwerp, Antwerp, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Ellen E. De Roeck
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, University of Antwerp, Antwerp, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Kristel Sleegers
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Belgium
| | - Giovanni B. Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- AIX Marseille University, INS, Ap-Hm, Marseille, France
| | | | | | - José L. Molinuevo
- Alzheimer’s Disease & Other Cognitive Disorders Unit, Hopsital Clínic-IDIBAPS, Barcelona, Spain
- Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, Barcelona, Spain
| | - Lorena Rami
- Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, Barcelona, Spain
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Petronella Kettunen
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Makedonia, Thessaloniki, Greece
| | - Frans Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Alberto Lléo
- Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Isabel Sala
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Julius Popp
- University Hospital of Lausanne, Lausanne, Switzerland
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | | | - Pablo Martinez-Lage
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | | | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, and Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of Heidelberg, Mannheim, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Cristina Legido-Quigley
- Kings College London, London, UK
- The Systems Medicine Group, Steno Diabetes Center, Gentofte, Denmark
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherland
- UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - B. Paul Morgan
- Dementia Research Institute Cardiff, Cardiff University, Cardiff, UK
| | - Johannes Streffer
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- UCB, Braine-l’Alleud, Belgium, formerly Janssen R&D, LLC. Beerse, Belgium at the Time of Study Conduct
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, UK
- Janssen R&D, UK formerly affiliation (1) at the Time of the Study Conduct
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Marizzoni M, Ferrari C, Babiloni C, Albani D, Barkhof F, Cavaliere L, Didic M, Forloni G, Fusco F, Galluzzi S, Hensch T, Jovicich J, Marra C, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Ranjeva JP, Ribaldi F, Rolandi E, Rossini PM, Salvatore M, Soricelli A, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. CSF cutoffs for MCI due to AD depend on APOEε4 carrier status. Neurobiol Aging 2019; 89:55-62. [PMID: 32029236 DOI: 10.1016/j.neurobiolaging.2019.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 12/20/2019] [Accepted: 12/21/2019] [Indexed: 12/14/2022]
Abstract
Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aβ42 and Aβ42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis.
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Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino (FR), Cassino, Italy
| | - Diego Albani
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Federica Fusco
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Camillo Marra
- Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Rome, Italy
| | - José Luis Molinuevo
- Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Dept. of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, INSERM, Marseille, France; Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Federica Ribaldi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Elena Rolandi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Marco Salvatore
- SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | | | - Magda Tsolaki
- 1st University Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, the Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany; Medical Sciences Department, iBiMED, University of Aveiro, Aveiro, Portugal
| | | | - Régis Bordet
- University of Lille, Inserm, CHU, Lille, France; U1171 - Degenerative and Vascular Cognitive Disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-INSERM 1106, Service de Pharmacologie Clinique, APHM, Marseille, France
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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30
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The Role of Physical Fitness in Cognitive-Related Biomarkers in Persons at Genetic Risk of Familial Alzheimer's Disease. J Clin Med 2019; 8:jcm8101639. [PMID: 31591322 PMCID: PMC6832576 DOI: 10.3390/jcm8101639] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 10/01/2019] [Accepted: 10/03/2019] [Indexed: 12/28/2022] Open
Abstract
Introduction: Nondemented people with a family history of Alzheimer’s disease (ADFH) and the ApoE-4 allele have been demonstrated to show a trend for a higher probability of cognitive decline and aberrant levels of cognitive-related biomarkers. However, the potential interactive effects on physical fitness have not been investigated. Purpose: The primary purpose of this study was to determine whether ADFH individuals with the ApoE-4 genotype show deviant brain event-related neural oscillatory performance and cognitively-related molecular indices. A secondary purpose was to examine the interactive effects on physical fitness. Methods: Blood samples were provided from 110 individuals with ADFH to assess molecular biomarkers and the ApoE genotype for the purpose of dividing them into an ApoE-4 group (n = 16) and a non-ApoE-4 group (n = 16) in order for them to complete a visuospatial working memory task while simultaneously recording electroencephalographic signals. They also performed a senior functional physical fitness (SFPF) test. Results: While performing the cognitive task, the ApoE-4 relative to non-ApoE-4 group showed worse accuracy rates (ARs) and brain neural oscillatory performance. There were no significant between-group differences with regard to any molecular biomarkers (e.g., IL-1β, IL-6, IL-8, BDNF, Aβ1-40, Aβ1-42). VO2max was significantly correlated with the neuropsychological performance (i.e., ARs and RTs) in the 2-item and 4-item conditions in the ApoE-4 group and across the two groups. However, the electroencephalogram (EEG) oscillations during visuospatial working memory processing in the two conditions were not correlated with any SFPF scores or cardiorespiratory tests in the two groups. Conclusions: ADFH individuals with the ApoE-4 genotype only showed deviant neuropsychological (e.g., ARs) and neural oscillatory performance when performing the cognitive task with a higher visuospatial working memory load. Cardiorespiratory fitness potentially played an important role in neuropsychological impairment in this group.
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31
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Dumont M, Roy M, Jodoin PM, Morency FC, Houde JC, Xie Z, Bauer C, Samad TA, Van Dijk KRA, Goodman JA, Descoteaux M. Free Water in White Matter Differentiates MCI and AD From Control Subjects. Front Aging Neurosci 2019; 11:270. [PMID: 31632265 PMCID: PMC6783505 DOI: 10.3389/fnagi.2019.00270] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 09/18/2019] [Indexed: 01/18/2023] Open
Abstract
Recent evidence shows that neuroinflammation plays a role in many neurological diseases including mild cognitive impairment (MCI) and Alzheimer's disease (AD), and that free water (FW) modeling from clinically acquired diffusion MRI (DTI-like acquisitions) can be sensitive to this phenomenon. This FW index measures the fraction of the diffusion signal explained by isotropically unconstrained water, as estimated from a bi-tensor model. In this study, we developed a simple but powerful whole-brain FW measure designed for easy translation to clinical settings and potential use as a priori outcome measure in clinical trials. These simple FW measures use a "safe" white matter (WM) mask without gray matter (GM)/CSF partial volume contamination (WM safe) near ventricles and sulci. We investigated if FW inside the WM safe mask, including and excluding areas of white matter damage such as white matter hyperintensities (WMHs) as shown on T2 FLAIR, computed across the whole white matter could be indicative of diagnostic grouping along the AD continuum. After careful quality control, 81 cognitively normal controls (NC), 103 subjects with MCI and 42 with AD were selected from the ADNIGO and ADNI2 databases. We show that MCI and AD have significantly higher FW measures even after removing all partial volume contamination. We also show, for the first time, that when WMHs are removed from the masks, the significant results are maintained, which demonstrates that the FW measures are not just a byproduct of WMHs. Our new and simple FW measures can be used to increase our understanding of the role of inflammation-associated edema in AD and may aid in the differentiation of healthy subjects from MCI and AD patients.
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Affiliation(s)
| | - Maggie Roy
- Imeka Solutions, Inc., Sherbrooke, QC, Canada
- Sherbrooke Connectivity Imaging Lab, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Pierre-Marc Jodoin
- Imeka Solutions, Inc., Sherbrooke, QC, Canada
- VITAlab, University of Sherbrooke, Sherbrooke, QC, Canada
| | | | - Jean-Christophe Houde
- Imeka Solutions, Inc., Sherbrooke, QC, Canada
- Sherbrooke Connectivity Imaging Lab, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Zhiyong Xie
- Digital Medicine & Translational Imaging, Early Clinical Development, Pfizer Inc., Cambridge, MA, United States
| | - Cici Bauer
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Tarek A. Samad
- Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States
| | - Koene R. A. Van Dijk
- Digital Medicine & Translational Imaging, Early Clinical Development, Pfizer Inc., Cambridge, MA, United States
| | - James A. Goodman
- Digital Medicine & Translational Imaging, Early Clinical Development, Pfizer Inc., Cambridge, MA, United States
| | - Maxime Descoteaux
- Imeka Solutions, Inc., Sherbrooke, QC, Canada
- Sherbrooke Connectivity Imaging Lab, University of Sherbrooke, Sherbrooke, QC, Canada
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32
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Archetti D, Ingala S, Venkatraghavan V, Wottschel V, Young AL, Bellio M, Bron EE, Klein S, Barkhof F, Alexander DC, Oxtoby NP, Frisoni GB, Redolfi A. Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease. NEUROIMAGE-CLINICAL 2019; 24:101954. [PMID: 31362149 PMCID: PMC6675943 DOI: 10.1016/j.nicl.2019.101954] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 06/24/2019] [Accepted: 07/19/2019] [Indexed: 11/18/2022]
Abstract
Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols. Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used. Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R2EBM = 0.866; R2DEBM = 0.906). In discriminant analyses, significant differences (p-value ≤ 0.05) between the staging of subjects from training and test sets were observed in both models. No significant difference between the staging of subjects from the training and test was observed (p-value > 0.05) when considering a subset composed by 562 subjects for which all biomarker families (cognitive, imaging and CSF) are available. Event sequence obtained with DEBM recapitulates the heuristic models in a data-driven fashion and is clinically plausible. We demonstrated inter-cohort transferability of two disease progression models and their robustness in detecting AD phases. This is an important step towards the adoption of data-driven statistical models into clinical domain. Data-driven event sequences describe evolution of relevant biomarkers in AD. Agreement between event sequences and heuristic AD progression models Accuracy in classifying subjects from clinical cohorts up to 91% Staging of subjects and MMSE scores of individuals show linear relation. Transferability of AD progression models based on research data to clinical cohorts
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Affiliation(s)
- Damiano Archetti
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Vikram Venkatraghavan
- Biomedical Imaging Group Rotterdam, Depts. of Medical Informatics & Radiology, Erasmus MC, The Netherlands.
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK.
| | - Maura Bellio
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK.
| | - Esther E Bron
- Biomedical Imaging Group Rotterdam, Depts. of Medical Informatics & Radiology, Erasmus MC, The Netherlands.
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Depts. of Medical Informatics & Radiology, Erasmus MC, The Netherlands.
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK.
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK.
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK.
| | - Giovanni B Frisoni
- University of Geneva, Geneva, Switzerland; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Alberto Redolfi
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
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Del Percio C, Derambure P, Noce G, Lizio R, Bartrés-Faz D, Blin O, Payoux P, Deplanque D, Méligne D, Chauveau N, Bourriez JL, Casse-Perrot C, Lanteaume L, Thalamas C, Dukart J, Ferri R, Pascarelli MT, Richardson JC, Bordet R, Babiloni C. Sleep deprivation and Modafinil affect cortical sources of resting state electroencephalographic rhythms in healthy young adults. Clin Neurophysiol 2019; 130:1488-1498. [PMID: 31295717 DOI: 10.1016/j.clinph.2019.06.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 05/06/2019] [Accepted: 06/03/2019] [Indexed: 11/28/2022]
Abstract
OBJECTIVE It has been reported that sleep deprivation affects the neurophysiological mechanisms underpinning the vigilance. Here, we tested the following hypotheses in the PharmaCog project (www.pharmacog.org): (i) sleep deprivation may alter posterior cortical delta and alpha sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms in healthy young adults; (ii) after the sleep deprivation, a vigilance enhancer may recover those rsEEG source markers. METHODS rsEEG data were recorded in 36 healthy young adults before (Pre-sleep deprivation) and after (Post-sleep deprivation) one night of sleep deprivation. In the Post-sleep deprivation, these data were collected after a single dose of PLACEBO or MODAFINIL. rsEEG cortical sources were estimated by eLORETA freeware. RESULTS In the PLACEBO condition, the sleep deprivation induced an increase and a decrease in posterior delta (2-4 Hz) and alpha (8-13 Hz) source activities, respectively. In the MODAFINIL condition, the vigilance enhancer partially recovered those source activities. CONCLUSIONS The present results suggest that posterior delta and alpha source activities may be both related to the regulation of human brain arousal and vigilance in quiet wakefulness. SIGNIFICANCE Future research in healthy young adults may use this methodology to preselect new symptomatic drug candidates designed to normalize brain arousal and vigilance in seniors with dementia.
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Affiliation(s)
- Claudio Del Percio
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy
| | - Philippe Derambure
- Univ Lille, Inserm, CHU Lille, UMR_S 1171 - Degenerative and Vascular Cognitive Disorders, F59000 Lille, France
| | | | | | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Healthy Sciences, University of Barcelona; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Pierre Payoux
- INSERM, Imagerie Cérébrale et Handicaps Neurologiques, Toulouse, France
| | - Dominique Deplanque
- Univ Lille, Inserm, CHU Lille, CIC1403 & UMR_S 1171 - Degenerative and Vascular Cognitive Disorders, F59000 Lille, France
| | - Déborah Méligne
- INSERM UMR 825 Brain Imaging and Neurological Dysfunctions, Toulouse, France
| | - Nicolas Chauveau
- INSERM UMR 825 Brain Imaging and Neurological Dysfunctions, Toulouse, France
| | - Jean Louis Bourriez
- Univ Lille, Inserm, CHU Lille, UMR_S 1171 - Degenerative and Vascular Cognitive Disorders, F59000 Lille, France
| | - Catherine Casse-Perrot
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Laura Lanteaume
- Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Claire Thalamas
- Department of Medical Pharmacology, INSERM CIC 1436, Toulouse University Medical Center, Toulouse, France
| | - Juergen Dukart
- F. Hoffmann-La Roche, Pharma Research Early Development, Roche Innovation Centre Basel, Basel, Switzerland
| | | | | | | | - Regis Bordet
- Univ Lille, Inserm, CHU Lille, UMR_S 1171 - Degenerative and Vascular Cognitive Disorders, F59000 Lille, France
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino, Cassino, FR, Italy.
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34
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Magni LR, Carcione A, Ferrari C, Semerari A, Riccardi I, Nicolo’ G, Lanfredi M, Pedrini L, Cotelli M, Bocchio L, Pievani M, Gasparotti R, Rossi R. Neurobiological and clinical effect of metacognitive interpersonal therapy vs structured clinical model: study protocol for a randomized controlled trial. BMC Psychiatry 2019; 19:195. [PMID: 31234864 PMCID: PMC6591903 DOI: 10.1186/s12888-019-2127-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 04/26/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Borderline Personality Disorder (BPD) is a complex and debilitating disorder, characterized by deficits in metacognition and emotion dysregulation. The "gold standard" treatment for this disorder is psychotherapy with pharmacotherapy as an adjunctive treatment to target state symptoms. The present randomized clinical trial aims to assess the clinical and neurobiological changes following Metacognitive Interpersonal Therapy (MIT) compared with Structured Clinical Management (SCM) derived from specific recommendations in APA (American Psychiatric Association) guidelines for BPD. METHODS The study design is a randomized parallel controlled clinical trial and will include 80 BPD outpatients, aged 18-45 enrolled at 2 recruitment centers. Primary outcome will be the clinical change in emotion regulation capacities assessed with the Difficulties in Emotion Regulation Scale (DERS). We will also investigated the effect of psychotherapy on metacognitive abilities and several clinical features such as BPD symptomatology, general psychopathology, depression, personal functioning, and trait dimensions (anger, impulsivity, alexithymia). We will evaluate changes in brain connectivity patterns and during the view of emotional pictures. A multidimensional assessment will be performed at the baseline, at 6, 12, 18 months. We will obtain structural and functional Magnetic Resonance Images (MRIs) in MIT-Treated BPD (N = 30) and SCM-treated BPD (N = 30) at baseline and after treatment, as well as in a group of 30 healthy and unrelated volunteers that will be scanned once for comparison. DISCUSSION The present study could contribute to elucidate the neurobiological mechanisms underlying psychotherapy efficacy. The inclusion of a multidisciplinary study protocol will allow to study BPD considering different features that can affect the treatment response and their reciprocal relationships. TRIAL REGISTRATION NCT02370316 . Registered 02/24/2015.
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Affiliation(s)
- Laura Rosa Magni
- grid.419422.8Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonino Carcione
- Third Centre of Cognitive Psychotherapy, Rome, Italy ,Italian School of Cognitive Psychotherapy (SICC), Rome, Italy
| | - Clarissa Ferrari
- grid.419422.8Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonio Semerari
- Third Centre of Cognitive Psychotherapy, Rome, Italy ,Italian School of Cognitive Psychotherapy (SICC), Rome, Italy
| | - Ilaria Riccardi
- Third Centre of Cognitive Psychotherapy, Rome, Italy ,Italian School of Cognitive Psychotherapy (SICC), Rome, Italy
| | - Giuseppe Nicolo’
- Third Centre of Cognitive Psychotherapy, Rome, Italy ,Italian School of Cognitive Psychotherapy (SICC), Rome, Italy ,Dipartimento Salute Mentale Roma 5, Rome, Italy
| | - Mariangela Lanfredi
- grid.419422.8Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Laura Pedrini
- grid.419422.8Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Maria Cotelli
- grid.419422.8Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Luisella Bocchio
- grid.425670.2IRCCS Istituto Centro S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy
| | - Michela Pievani
- grid.419422.8Laboratory Alzheimer’s Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Roberto Gasparotti
- 0000000417571846grid.7637.5Neuroradiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy
| | - Roberta Rossi
- Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
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35
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Ansari A, Maffioletti E, Milanesi E, Marizzoni M, Frisoni GB, Blin O, Richardson JC, Bordet R, Forloni G, Gennarelli M, Bocchio-Chiavetto L. miR-146a and miR-181a are involved in the progression of mild cognitive impairment to Alzheimer's disease. Neurobiol Aging 2019; 82:102-109. [PMID: 31437718 DOI: 10.1016/j.neurobiolaging.2019.06.005] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 06/12/2019] [Accepted: 06/12/2019] [Indexed: 12/22/2022]
Abstract
The identification of mechanisms associated with Alzheimer's disease (AD) development in mild cognitive impairment (MCI) would be of great usefulness to clarify AD pathogenesis and to develop preventive and therapeutic strategies. In this study, blood levels of the candidate microRNAs (small noncoding RNAs that play a pivotal role in gene expression) miR-146a, miR-181a, miR-181b, miR-24-3p, miR-186a, miR-101, miR-339, miR-590, and miR-22 have been investigated for association to AD conversion within 2 years in a group of 45 patients with MCI. Baseline miR-146a (p = 0.036) and miR-181a (p = 0.026) showed a significant upregulation in patients with MCI who later converted to AD. These alterations were related to AD hallmarks: a significant negative correlation was found with amyloid beta cerebrospinal fluid concentration for miR-146a (p = 0.006) and miR-181a (p = 0.001). Moreover, higher levels of miR-146a were associated to apolipoprotein E ε4 allele presence, smaller volume of the hippocampus (p = 0.045) and of the CA1 (p = 0.013) and the subiculum (p = 0.027) subfields. Increased levels of miR-146a (p = 0.031) and miR-181a (p = 0.002) were also linked with diffusivity alterations in the cingulum. These data support a role for miR-146a and miR-181a in the mechanisms of AD progression.
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Affiliation(s)
- Abulaish Ansari
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Elisabetta Maffioletti
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Elena Milanesi
- Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Cellular and Molecular Medicine, 'Victor Babes' National Institute of Pathology, Bucharest, Romania
| | - Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneve, Geneve, Switzerland
| | - Oliver Blin
- AP-HM, CHU Timone, CIC CPCET, Service de Pharmacologie Clinique et Pharmacovigilance, Marseille, France
| | - Jill C Richardson
- Neurosciences Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage, UK; MRL UK, MSD, 2 Royal College Street, London, UK
| | - Regis Bordet
- U1171 Inserm, CHU Lille, Degenerative and Vascular Cognitive Disorders, University of Lille, Lille, France
| | - Gianluigi Forloni
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Massimo Gennarelli
- Division of Biology and Genetics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Luisella Bocchio-Chiavetto
- Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Faculty of Psychology, eCampus University, Novedrate (Como), Italy
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36
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Jovicich J, Babiloni C, Ferrari C, Marizzoni M, Moretti DV, Del Percio C, Lizio R, Lopez S, Galluzzi S, Albani D, Cavaliere L, Minati L, Didic M, Fiedler U, Forloni G, Hensch T, Molinuevo JL, Bartrés Faz D, Nobili F, Orlandi D, Parnetti L, Farotti L, Costa C, Payoux P, Rossini PM, Marra C, Schönknecht P, Soricelli A, Noce G, Salvatore M, Tsolaki M, Visser PJ, Richardson JC, Wiltfang J, Bordet R, Blin O, Frisoniand GB. Two-Year Longitudinal Monitoring of Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer’s Disease Using Topographical Biomarkers Derived from Functional Magnetic Resonance Imaging and Electroencephalographic Activity. J Alzheimers Dis 2019; 69:15-35. [DOI: 10.3233/jad-180158] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- Department of Neuroscience, IRCCS-Hospital San Raffaele Pisana of Rome and Cassino, Rome and Cassino, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Moira Marizzoni
- Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Davide V. Moretti
- Alzheimer’s Epidemiology and Rehabilitation in Alzheimer’s disease Operative Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
| | - Samantha Galluzzi
- Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Diego Albani
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Libera Cavaliere
- Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Mira Didic
- Aix-Marseille Université, INSERM, INS UMR_S 1106, Marseille, France; Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Ute Fiedler
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
| | - Gianluigi Forloni
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - José Luis Molinuevo
- Alzheimer’s disease and other cognitive disorders unit, Neurology Service, ICN Hospital Clinic i Universitari and Pasqual Maragall Foundation Barcelona, Spain
| | - David Bartrés Faz
- Department of Medicine, Medical Psychology Unit, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Flavio Nobili
- Department of Neuroscience (DINOGMI), Neurology Clinic, University of Genoa, Italy
- U.O. Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Daniele Orlandi
- Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Lucia Farotti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Cinzia Costa
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Paolo Maria Rossini
- Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation-IRCCS, Rome, Italy
| | - Camillo Marra
- Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation-IRCCS, Rome, Italy
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | | | | | | | - Magda Tsolaki
- 1st University Department of Neurology, AHEPA Hospital, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jill C. Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, UK
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Giovanni B. Frisoniand
- Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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37
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Marizzoni M, Ferrari C, Macis A, Jovicich J, Albani D, Babiloni C, Cavaliere L, Didic M, Forloni G, Galluzzi S, Hoffmann KT, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Pizzini F, Rossini PM, Salvatore M, Schönknecht P, Soricelli A, Del Percio C, Hensch T, Hegerl U, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. Biomarker Matrix to Track Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer’s Disease. J Alzheimers Dis 2019; 69:49-58. [DOI: 10.3233/jad-181016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Ambra Macis
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Italy
| | - Diego Albani
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- Hospital San Raffaele Cassino, Cassino (FR), Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - José Luis Molinuevo
- Alzheimer’s Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM; Imagerie cérébrale et handicaps neurologiques UMR 825, Toulouse, France
| | - Francesca Pizzini
- Department of Diagnostics and Pathology, Neuroradiology, Verona University Hospital, Italy
| | - Paolo Maria Rossini
- Department of Gerontology, Area of Neuroscience, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation Rome, Italy
| | | | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | | | | | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jill C. Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, UK
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171-Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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38
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Marizzoni M, Ferrari C, Jovicich J, Albani D, Babiloni C, Cavaliere L, Didic M, Forloni G, Galluzzi S, Hoffmann KT, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Ribaldi F, Rossini PM, Schönknecht P, Salvatore M, Soricelli A, Hensch T, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. Predicting and Tracking Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer’s Disease: Structural Brain Biomarkers. J Alzheimers Dis 2019; 69:3-14. [DOI: 10.3233/jad-180152] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Italy
| | - Diego Albani
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- IRCCS San Raffaele Pisana of Rome, Rome, Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | | | - José Luis Molinuevo
- Alzheimer’s Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d’Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU SanMartino-IST, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Mariadella Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM; Imagerie cérébrale et handicapsneurologiques UMR 825, Toulouse, France
| | - Federica Ribaldi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Paolo Maria Rossini
- Area of Neuroscience, Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation Rome, Italy
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Marco Salvatore
- SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | | | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jens Wiltfang
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jill C. Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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Frisoni GB, Blin O, Bordet R. One Step Forward Toward a Surrogate Endpoint for Clinical Trials of Alzheimer's Disease Drugs: The Results of PharmaCog WP5 (European ADNI). J Alzheimers Dis 2019; 69:1-2. [PMID: 30958385 DOI: 10.3233/jad-190267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
| | - Olivier Blin
- System Neurosciences Institute (INS), Aix Marseille University, Marseille, France
| | - Regis Bordet
- University of Lille, Inserm, CHU Lille, Lille, France
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Bos I, Vos S, Verhey F, Scheltens P, Teunissen C, Engelborghs S, Sleegers K, Frisoni G, Blin O, Richardson JC, Bordet R, Tsolaki M, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Lleó A, Johannsen P, Freund-Levi Y, Frölich L, Vandenberghe R, Westwood S, Dobricic V, Barkhof F, Legido-Quigley C, Bertram L, Lovestone S, Streffer J, Andreasson U, Blennow K, Zetterberg H, Visser PJ. Cerebrospinal fluid biomarkers of neurodegeneration, synaptic integrity, and astroglial activation across the clinical Alzheimer's disease spectrum. Alzheimers Dement 2019; 15:644-654. [PMID: 30853464 DOI: 10.1016/j.jalz.2019.01.004] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 11/26/2018] [Accepted: 01/02/2019] [Indexed: 12/20/2022]
Abstract
INTRODUCTION We investigated relations between amyloid-β (Aβ) status, apolipoprotein E (APOE) ε4, and cognition, with cerebrospinal fluid markers of neurogranin (Ng), neurofilament light (NFL), YKL-40, and total tau (T-tau). METHODS We included 770 individuals with normal cognition, mild cognitive impairment, and Alzheimer's disease (AD)-type dementia from the EMIF-AD Multimodal Biomarker Discovery study. We tested the association of Ng, NFL, YKL-40, and T-tau with Aβ status (Aβ- vs. Aβ+), clinical diagnosis APOE ε4 carriership, baseline cognition, and change in cognition. RESULTS Ng and T-tau distinguished between Aβ+ from Aβ- individuals in each clinical group, whereas NFL and YKL-40 were associated with Aβ+ in nondemented individuals only. APOE ε4 carriership did not influence NFL, Ng, and YKL-40 in Aβ+ individuals. NFL was the best predictor of cognitive decline in Aβ+ individuals across the cognitive spectrum. DISCUSSION Axonal degeneration, synaptic dysfunction, astroglial activation, and altered tau metabolism are involved already in preclinical AD. NFL may be a useful prognostic marker.
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Affiliation(s)
- Isabelle Bos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Frans Verhey
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Charlotte Teunissen
- Neurochemistry Lab and Biobank, Department of Clinical Chemistry, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium; Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Kristel Sleegers
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Giovanni Frisoni
- University of Geneva, Geneva, Switzerland; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- Mediterranean Institute of Cognitive Neuroscience, Aix Marseille University, Marseille, France
| | | | - Régis Bordet
- University of Lille, Inserm, CHU Lille, Lille, France
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Makedonia, Thessaloniki, Greece
| | - Julius Popp
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland; Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Alberto Lleó
- Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden; Department of Psychiatry Norrtälje Hospital Tiohundra, Norrtäije, Sweden
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of Heidelberg, Mannheim, Germany
| | | | | | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | | | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany; School of Public Health, Imperial College London, London, UK; Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium; Early Clinial Neurology, UCB Biopharma SPRL, Braine-l'Alleud, Belgium
| | - Ulf Andreasson
- Clinical Neurochemistry Lab, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, University of Gothenburg, Institute of Neuroscience and Physiology, Mölndal, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Lab, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, University of Gothenburg, Institute of Neuroscience and Physiology, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Lab, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, University of Gothenburg, Institute of Neuroscience and Physiology, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK; UK Dementia Research Institute, London, UK
| | - Pieter Jelle Visser
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands; Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
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Alm KH, Bakker A. Relationships Between Diffusion Tensor Imaging and Cerebrospinal Fluid Metrics in Early Stages of the Alzheimer's Disease Continuum. J Alzheimers Dis 2019; 70:965-981. [PMID: 31306117 PMCID: PMC6860011 DOI: 10.3233/jad-181210] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Recently, the field of Alzheimer's disease (AD) research has adopted a new framework that places the progression of AD along a continuum consisting of a preclinical stage, followed by conversion to mild cognitive impairment, and ultimately dementia. Important neuropathological changes occur in the preclinical phase, necessitating the identification of metrics that can detect such early changes. While cerebrospinal fluid (CSF) measures of amyloid and tau are generally accepted as biomarkers of AD pathology, neuroimaging measures used to index white matter alterations throughout the brain remain less widely endorsed as candidate biomarkers. To explore the relationship between white matter alterations and AD pathology, we review the literature on multimodal studies that assessed both CSF markers and white matter indices, derived from diffusion tensor imaging (DTI) methods, across cohorts primarily in the early phases of AD. Our review indicates that abnormal CSF measures of Aβ42 and tau are associated with widespread alterations in white matter microstructure throughout the brain. Furthermore, white matter variability is related to individual differences in behavior and can aid in tracking longitudinal changes in cognition. Our review advocates for the utilization of DTI metrics in investigations of early AD and suggests that the combined use of DTI and CSF markers may better explain individual differences in cognition and disease progression. However, further research is needed to resolve certain mixed findings.
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Affiliation(s)
- Kylie H. Alm
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Cassani R, Estarellas M, San-Martin R, Fraga FJ, Falk TH. Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment. DISEASE MARKERS 2018; 2018:5174815. [PMID: 30405860 PMCID: PMC6200063 DOI: 10.1155/2018/5174815] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 07/12/2018] [Accepted: 07/29/2018] [Indexed: 12/17/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.
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Affiliation(s)
- Raymundo Cassani
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
| | - Mar Estarellas
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
- Department of Bioengineering, Imperial College London, London, UK
| | - Rodrigo San-Martin
- Center for Mathematics, Computation and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Brazil
| | - Francisco J. Fraga
- Engineering, Modeling and Applied Social Sciences Center, Universidade Federal do ABC, São Bernardo do Campo, Brazil
| | - Tiago H. Falk
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
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ten Kate M, Redolfi A, Peira E, Bos I, Vos SJ, Vandenberghe R, Gabel S, Schaeverbeke J, Scheltens P, Blin O, Richardson JC, Bordet R, Wallin A, Eckerstrom C, Molinuevo JL, Engelborghs S, Van Broeckhoven C, Martinez-Lage P, Popp J, Tsolaki M, Verhey FRJ, Baird AL, Legido-Quigley C, Bertram L, Dobricic V, Zetterberg H, Lovestone S, Streffer J, Bianchetti S, Novak GP, Revillard J, Gordon MF, Xie Z, Wottschel V, Frisoni G, Visser PJ, Barkhof F. MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study. Alzheimers Res Ther 2018; 10:100. [PMID: 30261928 PMCID: PMC6161396 DOI: 10.1186/s13195-018-0428-1] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2018] [Accepted: 09/04/2018] [Indexed: 01/30/2023]
Abstract
BACKGROUND With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification. METHODS We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects. RESULTS In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures. CONCLUSIONS Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.
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Affiliation(s)
- Mara ten Kate
- Alzheimer Center & Department of Neurology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Alberto Redolfi
- Laboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Enrico Peira
- Laboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Isabelle Bos
- Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J. Vos
- Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Rik Vandenberghe
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Silvy Gabel
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center & Department of Neurology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Olivier Blin
- AP-HM, CHU Timone, CIC CPCET, Service de Pharmacologie Clinique et Pharmacovigilance, Marseille, France
| | | | - Regis Bordet
- U1171 Inserm, CHU Lille, Degenerative and Vascular Cognitive Disorders, University of Lille, Lille, France
| | - Anders Wallin
- Sahlgrenska Academy, Institute of Neuroscience and Physiology, Section for Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Carl Eckerstrom
- Sahlgrenska Academy, Institute of Neuroscience and Physiology, Section for Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - José Luis Molinuevo
- Barcelona βeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases, Center for Molecular Neurology, VIB, Antwerp, Belgium
- Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Pablo Martinez-Lage
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Julius Popp
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Magdalini Tsolaki
- Memory and Dementia Center, 3rd Department of Neurology, “G Papanicolau” General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Frans R. J. Verhey
- Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | | | | | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lubeck, Germany
- School of Public Health, Imperial College London, London, UK
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lubeck, Germany
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- UCB Biopharma SPRL, Braine-l’Alleud, Belgium
| | - Silvia Bianchetti
- Laboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Gerald P. Novak
- Janssen Pharmaceutical Research and Development, Titusville, NJ USA
| | | | - Mark F. Gordon
- Teva Pharmaceuticals, Inc., Malvern, PA USA
- Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT USA
| | - Zhiyong Xie
- Worldwide Research and Development, Pfizer Inc, Cambridge, MA USA
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, VUMC, Amsterdam, the Netherlands
| | - Giovanni Frisoni
- Laboratory of Epidemiology & Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- University of Geneva, Geneva, Switzerland
| | - Pieter Jelle Visser
- Alzheimer Center & Department of Neurology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
- Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VUMC, Amsterdam, the Netherlands
- Institutes of Neurology and Healthcare Engineering, UCL, London, UK
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Lazarou I, Adam K, Georgiadis K, Tsolaki A, Nikolopoulos S, Yiannis Kompatsiaris I, Tsolaki M. Can a Novel High-Density EEG Approach Disentangle the Differences of Visual Event Related Potential (N170), Elicited by Negative Facial Stimuli, in People with Subjective Cognitive Impairment? J Alzheimers Dis 2018; 65:543-575. [PMID: 30103320 DOI: 10.3233/jad-180223] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
BACKGROUND Studies on subjective cognitive impairment (SCI) and neural activation report controversial results. OBJECTIVE To evaluate the ability to disentangle the differences of visual N170 ERP, generated by facial stimuli (Anger & Fear) as well as the cognitive deterioration of SCI, mild cognitive impairment (MCI), and Alzheimer's disease (AD) compared to healthy controls (HC). METHOD 57 people took part in this study. Images corresponding to facial stimuli of "Anger" and "Fear" were presented to 12 HC, 14 SCI, 17 MCI and 14 AD participants. EEG data were recorded by using a HD-EEG HydroCel with 256 channels. RESULTS Results showed that the amplitude of N170 can contribute in distinguishing the SCI group, since statistically significant differences were observed with the HC (p < 0.05) and the MCI group from HC (p < 0.001), as well as AD from HC (p = 0.05) during the processing of facial stimuli. Noticeable differences were also observed in the topographic distribution of the N170 amplitude, while localization analysis by using sLORETA images confirmed the activation of superior, middle-temporal, and frontal lobe brain regions. Finally, in the case of "Fear", SCI and HC demonstrated increased activation in the orbital and inferior frontal gyrus, respectively, MCI in the inferior temporal gyrus, and AD in the lingual gyrus. CONCLUSION These preliminary findings suggest that the amplitude of N170 elicited after negative facial stimuli could be modulated by the decline related to pathological cognitive aging and can contribute in distinguishing HC from SCI, MCI, and AD.
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Affiliation(s)
- Ioulietta Lazarou
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece.,1st Department of Neurology, G.H. "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Macedonia, Greece
| | - Katerina Adam
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece
| | - Kostas Georgiadis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece.,Informatics Department, Aristotle University of Thessaloniki, Thessaloniki, Macedonia, Greece
| | - Anthoula Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece.,Laboratory of Medical Physic, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Macedonia, Greece
| | - Spiros Nikolopoulos
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece
| | | | - Magda Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Macedonia, Greece.,1st Department of Neurology, G.H. "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Macedonia, Greece.,Greek Alzheimer's Association and Related Disorders (GAADRD), Thessaloniki, Macedonia, Greece
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45
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Bos I, Vos S, Vandenberghe R, Scheltens P, Engelborghs S, Frisoni G, Molinuevo JL, Wallin A, Lleó A, Popp J, Martinez-Lage P, Baird A, Dobson R, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Bertram L, ten Kate M, Barkhof F, Zetterberg H, Lovestone S, Streffer J, Visser PJ. The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics. Alzheimers Res Ther 2018; 10:64. [PMID: 29980228 PMCID: PMC6035398 DOI: 10.1186/s13195-018-0396-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 06/08/2018] [Indexed: 02/04/2023]
Abstract
BACKGROUND There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer's disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants. METHODS Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (Aβ) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling. RESULTS We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage Aβ+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE ε4 allele was more frequent amongst Aβ+ individuals (p < 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p < 0.001). Aβ+ had a faster rate of decline on the MMSE during follow-up in the NC (p < 0.001) and MCI (p < 0.001) groups. CONCLUSIONS The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of Aβ and APOE ε4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog.
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Affiliation(s)
- Isabelle Bos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Universiteitssingel 40, Box 34, P.O. Box 616, 6200 MD Maastricht, the Netherlands
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Rik Vandenberghe
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
- University of Antwerp, Antwerp, Belgium
| | - Giovanni Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - José Luis Molinuevo
- Alzheimer’s Disease & Other Cognitive Disorders Unit, Hospital Clínic—IDIBAPS, Barcelona, Spain
- Barcelona Beta Brain Research Center, Fundació Pasqual Maragall, Barcelona, Spain
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Moelndal, Sweden
| | - Alberto Lleó
- Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Julius Popp
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA—Alzheimer Foundation, San Sebastian, Spain
| | | | - Richard Dobson
- King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | | | - Kristel Sleegers
- Neurodegenerative Brain Diseases Group, VIB—Department of Molecular Genetics, Antwerp, Belgium
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, VIB—Department of Molecular Genetics, Antwerp, Belgium
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- School of Public Health, Imperial College London, London, UK
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Mara ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, London, UK
| | | | - Johannes Streffer
- Experimental Medicine, Janssen Pharmaceutical Companies, Beerse, Belgium
| | - Pieter Jelle Visser
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
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Martin-Trias P, Lanteaume L, Solana E, Cassé-Perrot C, Fernández-Cabello S, Babiloni C, Marzano N, Junqué C, Rossini PM, Micallef J, Truillet R, Charles E, Jouve E, Bordet R, Santamaria J, Jovicich J, Rossi S, Pascual-Leone A, Blin O, Richardson J, Bartrés-Faz D. Adaptability and reproducibility of a memory disruption rTMS protocol in the PharmaCog IMI European project. Sci Rep 2018; 8:9371. [PMID: 29921865 PMCID: PMC6008461 DOI: 10.1038/s41598-018-27502-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 06/03/2018] [Indexed: 11/29/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) can interfere with cognitive processes, such as transiently impairing memory. As part of a multi-center European project, we investigated the adaptability and reproducibility of a previously published TMS memory interfering protocol in two centers using EEG or fMRI scenarios. Participants were invited to attend three experimental sessions on different days, with sham repetitive TMS (rTMS) applied on day 1 and real rTMS on days 2 and 3. Sixty-eight healthy young men were included. On each experimental day, volunteers were instructed to remember visual pictures while receiving neuronavigated rTMS trains (20 Hz, 900 ms) during picture encoding at the left dorsolateral prefrontal cortex (L-DLPFC) and the vertex. Mixed ANOVA model analyses were performed. rTMS to the L-DLPFC significantly disrupted recognition memory on experimental day 2. No differences were found between centers or between fMRI and EEG recordings. Subjects with lower baseline memory performances were more susceptible to TMS disruption. No stability of TMS-induced memory interference could be demonstrated on day 3. Our data suggests that adapted cognitive rTMS protocols can be implemented in multi-center studies incorporating standardized experimental procedures. However, our center and modality effects analyses lacked sufficient statistical power, hence highlighting the need to conduct further studies with larger samples. In addition, inter and intra-subject variability in response to TMS might limit its application in crossover or longitudinal studies.
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Affiliation(s)
- Pablo Martin-Trias
- Medical Psychology Unit, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Laura Lanteaume
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Elisabeth Solana
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Catherine Cassé-Perrot
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Sara Fernández-Cabello
- Medical Psychology Unit, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Claudio Babiloni
- Department of Physiology and Pharmacology, University of Rome "La Sapienza", Rome, Italy
- Department of Neuroscience, IRCCS San Raffaele Pisana, Rome, Italy
| | | | - Carme Junqué
- Medical Psychology Unit, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Paolo Maria Rossini
- Department of Neuroscience, IRCCS San Raffaele Pisana, Rome, Italy
- Department of Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic Gemelli, Rome, Italy
| | - Joëlle Micallef
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Romain Truillet
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Estelle Charles
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Elisabeth Jouve
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171, Degenerative and Vascular Cognitive Disorders, Lille, France
| | - Joan Santamaria
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Sleep Unit, Neurology Department, Hospital Clinic, Barcelona, Spain
| | - Jorge Jovicich
- Center for Mind/Brain Sciences (CIMEC), University of Trento, Trento, Italy
| | - Simone Rossi
- Dipartimento di Scienze Mediche, Chirurgiche e Neuroscienze, Brain Investigation & Neuromodulation Laboratory (Si-BIN Lab), University of Siena, Siena, Italy
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, MA, 02215, USA
- Institut Guttmann de Neurorehabilitacio, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Olivier Blin
- Department of Clinical Pharmacology CIC-CPCET, AP-HM and Institut de Neurosciences des Systèmes (INS) UMR1106, Aix-Marseille University, Marseille, France
| | - Jill Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage, UK
| | - David Bartrés-Faz
- Medical Psychology Unit, Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
- Institut Guttmann de Neurorehabilitacio, Universitat Autonoma de Barcelona, Barcelona, Spain.
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Lin L, Xing G, Han Y. Advances in Resting State Neuroimaging of Mild Cognitive Impairment. Front Psychiatry 2018; 9:671. [PMID: 30574100 PMCID: PMC6291484 DOI: 10.3389/fpsyt.2018.00671] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 11/21/2018] [Indexed: 01/27/2023] Open
Abstract
The rapidly increasing number of patients with Alzheimer's disease (AD) worldwide has become a major public concern. Mild cognitive impairment (MCI), characterized with accelerated memory decline than normal aging, is a stage between cognitively unimpaired and dementia. Identification of MCI in the Alzheimer's continuum from normal aging, is important for early diagnosis and improved intervention of AD. The imaging technique has been extensively used for diagnose and understanding the mechanisms of MCI. Firstly, we review the recent progresses in the research framework of MCI depending on the clinical and/or biomarker findings. Secondly, we cover studies that use of rs-fMRI (resting state functional magnetic resonance imaging) for the brain activities and functional connectivity between normal aging and MCI. Other methodologies and multi-modal studies for investigating the mechanism and early diagnosis of MCI are also discussed. Finally, we discuss how genetic and environmental factors such as education could interact with in MCI. Overall, MCI is a heterogeneous state and employing resting state neuroimaging with other AD biomarker approaches will be able to target in the more precise population and AD-related pathology process.
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Affiliation(s)
- Li Lin
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China
| | - Guoqiang Xing
- Department of Imaging & Imaging Institute of Rehabilitation and Development of Brain Function, The Second Clinical Institute of North Sichuan Medical College, Nanchong Central Hospital, Nanchong, China
| | - Ying Han
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China.,Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
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48
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Molinuevo JL, Minguillon C, Rami L, Gispert JD. The Rationale Behind the New Alzheimer's Disease Conceptualization: Lessons Learned During the Last Decades. J Alzheimers Dis 2018; 62:1067-1077. [PMID: 29562531 PMCID: PMC5869992 DOI: 10.3233/jad-170698] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2017] [Indexed: 12/31/2022]
Abstract
In the last decades, progress in neuroimaging techniques and cerebrospinal fluid assays has enabled the characterization of several Alzheimer's disease (AD) biomarkers. This knowledge has shifted the conceptualization of AD from a clinical-pathological construct, where its diagnosis required the presence of dementia with distinct pathologic features, toward a clinical-biological one that recognizes AD as a pathological continuum with a clinical picture that ranges from normal cognition to a dementia stage. Specifically, AD is now divided into three stages: preclinical (abnormal biomarkers and no or only subtle cognitive impairment), mild cognitive impairment or prodromal AD (abnormal pathophysiological biomarkers and episodic memory impairment), and dementia (abnormal biomarkers and clear cognitive and functional impairment). The possibility of assessing AD pathophysiology in vivo before the onset of clinical symptoms in the preclinical stage provides the unprecedented opportunity to intervene at earlier stages of the continuum in secondary prevention trials. Currently, large cohort studies of cognitively healthy participants are undergoing with the main aim of disentangling the natural history of AD to identify individuals with an increased risk of developing AD in the near future to be recruited in these clinical trials. In this paper, we review how the concept of AD has changed over the years as well as discuss the implications of this conceptual change.
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Affiliation(s)
- José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Lorena Rami
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
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49
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Neu SC, Pa J, Kukull W, Beekly D, Kuzma A, Gangadharan P, Wang LS, Romero K, Arneric SP, Redolfi A, Orlandi D, Frisoni GB, Au R, Devine S, Auerbach S, Espinosa A, Boada M, Ruiz A, Johnson SC, Koscik R, Wang JJ, Hsu WC, Chen YL, Toga AW. Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease: A Meta-analysis. JAMA Neurol 2017; 74:1178-1189. [PMID: 28846757 PMCID: PMC5759346 DOI: 10.1001/jamaneurol.2017.2188] [Citation(s) in RCA: 412] [Impact Index Per Article: 58.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance It is unclear whether female carriers of the apolipoprotein E (APOE) ε4 allele are at greater risk of developing Alzheimer disease (AD) than men, and the sex-dependent association of mild cognitive impairment (MCI) and APOE has not been established. Objective To determine how sex and APOE genotype affect the risks for developing MCI and AD. Data Sources Twenty-seven independent research studies in the Global Alzheimer's Association Interactive Network with data on nearly 58 000 participants. Study Selection Non-Hispanic white individuals with clinical diagnostic and APOE genotype data. Data Extraction and Synthesis Homogeneous data sets were pooled in case-control analyses, and logistic regression models were used to compute risks. Main Outcomes and Measures Age-adjusted odds ratios (ORs) and 95% confidence intervals for developing MCI and AD were calculated for men and women across APOE genotypes. Results Participants were men and women between ages 55 and 85 years. Across data sets most participants were white, and for many participants, racial/ethnic information was either not collected or not known. Men (OR, 3.09; 95% CI, 2.79-3.42) and women (OR, 3.31; CI, 3.03-3.61) with the APOE ε3/ε4 genotype from ages 55 to 85 years did not show a difference in AD risk; however, women had an increased risk compared with men between the ages of 65 and 75 years (women, OR, 4.37; 95% CI, 3.82-5.00; men, OR, 3.14; 95% CI, 2.68-3.67; P = .002). Men with APOE ε3/ε4 had an increased risk of AD compared with men with APOE ε3/ε3. The APOE ε2/ε3 genotype conferred a protective effect on women (OR, 0.51; 95% CI, 0.43-0.61) decreasing their risk of AD more (P value = .01) than men (OR, 0.71; 95% CI, 0.60-0.85). There was no difference between men with APOE ε3/ε4 (OR, 1.55; 95% CI, 1.36-1.76) and women (OR, 1.60; 95% CI, 1.43-1.81) in their risk of developing MCI between the ages of 55 and 85 years, but women had an increased risk between 55 and 70 years (women, OR, 1.43; 95% CI, 1.19-1.73; men, OR, 1.07; 95% CI, 0.87-1.30; P = .05). There were no significant differences between men and women in their risks for converting from MCI to AD between the ages of 55 and 85 years. Individuals with APOE ε4/ε4 showed increased risks vs individuals with ε3/ε4, but no significant differences between men and women with ε4/ε4 were seen. Conclusions and Relevance Contrary to long-standing views, men and women with the APOE ε3/ε4 genotype have nearly the same odds of developing AD from age 55 to 85 years, but women have an increased risk at younger ages.
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Affiliation(s)
- Scott C Neu
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles
| | - Judy Pa
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles
| | - Walter Kukull
- National Alzheimer's Coordinating Center, University of Washington, Seattle
| | - Duane Beekly
- National Alzheimer's Coordinating Center, University of Washington, Seattle
| | - Amanda Kuzma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | | | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Klaus Romero
- Coalition Against Major Disease, Critical Path Institute, Tucson, Arizona
| | - Stephen P Arneric
- Coalition Against Major Disease, Critical Path Institute, Tucson, Arizona
| | - Alberto Redolfi
- IRCCS Fatebenefratelli, The National Centre for Alzheimer's Disease, Brescia, Italy
| | - Daniele Orlandi
- IRCCS Fatebenefratelli, The National Centre for Alzheimer's Disease, Brescia, Italy
| | - Giovanni B Frisoni
- IRCCS Fatebenefratelli, The National Centre for Alzheimer's Disease, Brescia, Italy
- University Hospitals and University of Geneva, Geneva, Switzerland
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department Neurology and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Framingham Heart Study, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Sherral Devine
- Department of Neurology, Framingham Heart Study, Boston University School of Medicine, Boston, Massachusetts
| | - Sanford Auerbach
- Department of Neurology, Framingham Heart Study, Boston University School of Medicine, Boston, Massachusetts
| | - Ana Espinosa
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Barcelona, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Barcelona, Spain
| | - Agustín Ruiz
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Barcelona, Spain
| | | | - Rebecca Koscik
- University of Wisconsin School of Medicine and Public Health, Madison
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan
| | - Wen-Chuin Hsu
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan
- Dementia Center, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan
| | - Yao-Liang Chen
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan
- Department of Medical Imaging and Intervention, Keelung Branch, Chang Gung Memorial Hospital, Keelung City, Taiwan
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles
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50
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Taneja A, Della Pasqua O, Danhof M. Challenges in translational drug research in neuropathic and inflammatory pain: the prerequisites for a new paradigm. Eur J Clin Pharmacol 2017; 73:1219-1236. [PMID: 28894907 PMCID: PMC5599481 DOI: 10.1007/s00228-017-2301-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 07/03/2017] [Indexed: 12/21/2022]
Abstract
AIM Despite an improved understanding of the molecular mechanisms of nociception, existing analgesic drugs remain limited in terms of efficacy in chronic conditions, such as neuropathic pain. Here, we explore the underlying pathophysiological mechanisms of neuropathic and inflammatory pain and discuss the prerequisites and opportunities to reduce attrition and high-failure rate in the development of analgesic drugs. METHODS A literature search was performed on preclinical and clinical publications aimed at the evaluation of analgesic compounds using MESH terms in PubMed. Publications were selected, which focused on (1) disease mechanisms leading to chronic/neuropathic pain and (2) druggable targets which are currently under evaluation in drug development. Attention was also given to the role of biomarkers and pharmacokinetic-pharmacodynamic modelling. RESULTS Multiple mechanisms act concurrently to produce pain, which is a non-specific manifestation of underlying nociceptive pathways. Whereas these manifestations can be divided into neuropathic and inflammatory pain, it is now clear that inflammatory mechanisms are a common trigger for both types of pain. This has implications for drug development, as the assessment of drug effects in experimental models of neuropathic and chronic pain is driven by overt behavioural measures. By contrast, the use of mechanistic biomarkers in inflammatory pain has provided the pharmacological basis for dose selection and evaluation of non-steroidal anti-inflammatory drugs (NSAIDs). CONCLUSION A different paradigm is required for the identification of relevant targets and candidate molecules whereby pain is coupled to the cause of sensorial signal processing dysfunction rather than clinical symptoms. Biomarkers which enable the characterisation of drug binding and target activity are needed for a more robust dose rationale in early clinical development. Such an approach may be facilitated by quantitative clinical pharmacology and evolving technologies in brain imaging, allowing accurate assessment of target engagement, and prediction of treatment effects before embarking on large clinical trials.
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Affiliation(s)
- A Taneja
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - O Della Pasqua
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline, Uxbridge, UK.,Clinical Pharmacology & Therapeutics Group, University College London, London, UK
| | - M Danhof
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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