1
|
Aziz AL, Giusiano B, Joubert S, Duprat L, Didic M, Gueriot C, Koric L, Boucraut J, Felician O, Ranjeva JP, Guedj E, Ceccaldi M. Difference in imaging biomarkers of neurodegeneration between early and late-onset amnestic Alzheimer's disease. Neurobiol Aging 2017; 54:22-30. [PMID: 28314160 DOI: 10.1016/j.neurobiolaging.2017.02.010] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 01/31/2017] [Accepted: 02/13/2017] [Indexed: 12/21/2022]
Abstract
Neuroimaging biomarkers differ between patients with early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). Whether these changes reflect cognitive heterogeneity or differences in disease severity is still unknown. This study aimed at investigating changes in neuroimaging biomarkers, according to the age of onset of the disease, in mild amnestic Alzheimer's disease patients with positive amyloid biomarkers in cerebrospinal fluid. Both patient groups were impaired on tasks assessing verbal and visual recognition memory. EOAD patients showed greater executive and linguistic deficits, while LOAD patients showed greater semantic memory impairment. In EOAD and LOAD, hypometabolism involved the bilateral temporoparietal junction and the posterior cingulate cortex. In EOAD, atrophy was widespread, including frontotemporoparietal areas, whereas it was limited to temporal regions in LOAD. Atrophic volumes were greater in EOAD than in LOAD. Hypometabolic volumes were similar in the 2 groups. Greater extent of atrophy in EOAD, despite similar extent of hypometabolism, could reflect different underlying pathophysiological processes, different glucose-based compensatory mechanisms or distinct level of premorbid atrophic lesions.
Collapse
Affiliation(s)
- Anne-Laure Aziz
- Aix-Marseille Université, INSERM UMR 1106, Institut de Neurosciences des Systèmes, Marseille, France.
| | - Bernard Giusiano
- Aix-Marseille Université, INSERM UMR 1106, Institut de Neurosciences des Systèmes, Marseille, France; APHM, Public Health Department, Marseille, France
| | - Sven Joubert
- Département de psychologie, Université de Montréal, Montréal, Quebec, Canada; Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Quebec, Canada
| | - Lauréline Duprat
- Aix-Marseille Université, Centre de Résonance Magnétique Biologique et Médicale - CRMBM, UMR 7339 AMU-CNRS, Marseille, France
| | - Mira Didic
- Aix-Marseille Université, INSERM UMR 1106, Institut de Neurosciences des Systèmes, Marseille, France; Neurology and Neuropyschology Department & CMRR PACA Ouest, AP-HM, Marseille, France
| | - Claude Gueriot
- Neurology and Neuropyschology Department & CMRR PACA Ouest, AP-HM, Marseille, France
| | - Lejla Koric
- Neurology and Neuropyschology Department & CMRR PACA Ouest, AP-HM, Marseille, France
| | - José Boucraut
- Immunology and Immunopathology Department, Assistance Publique-Hôpitaux de Marseille, Marseille, France; Aix Marseille Université, CRN2M, CNRS UMR 7286, Marseille Cedex 15, France
| | - Olivier Felician
- Aix-Marseille Université, INSERM UMR 1106, Institut de Neurosciences des Systèmes, Marseille, France; Neurology and Neuropyschology Department & CMRR PACA Ouest, AP-HM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, Centre de Résonance Magnétique Biologique et Médicale - CRMBM, UMR 7339 AMU-CNRS, Marseille, France
| | - Eric Guedj
- Nuclear Medicine Department, Assistance Publique-Hôpitaux de Marseille, Timone Hospital, Marseille, France; Institut de Neurosciences de la Timone, UMR 7289, Aix-Marseille Université & CNRS, Assistance Publique-Hôpitaux de Marseille, Marseille, France; CERIMED, Aix-Marseille Université, Marseille, France
| | - Mathieu Ceccaldi
- Aix-Marseille Université, INSERM UMR 1106, Institut de Neurosciences des Systèmes, Marseille, France; Neurology and Neuropyschology Department & CMRR PACA Ouest, AP-HM, Marseille, France
| |
Collapse
|
2
|
Three-Dimensional Face Recognition in Mild Cognitive Impairment: A Psychophysical and Structural MR Study. J Int Neuropsychol Soc 2016; 22:744-54. [PMID: 27406061 DOI: 10.1017/s135561771600059x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVES Mild cognitive impairment (MCI) has been associated with a high risk of conversion to Alzheimer's dementia. In addition to memory complaints, impairments in the visuospatial domain have been reported in this condition. We have previously shown that deficits in perceiving structure-from-motion (SFM) objects are reflected in functional reorganization of brain activity within the visual ventral stream. Here we aimed to identify structural correlates of psychophysical complex face and object recognition performance in amnestic MCI patients (n=30 vs. n=25 controls). This study was, therefore, motivated by evidence from recent studies showing that a combination of visual information across dorsal and ventral visual streams may be needed for the perception of three-dimensional (3D) SFM objects. METHODS In our experimental paradigm, participants had to discriminate 3D SFM shapes (faces and objects) from 3D SFM meaningless (scrambled) shapes. RESULTS Morphometric analysis established neuroanatomical evidence for impairment in MCI as demonstrated by smaller hippocampal volumes. We found association between cortical thickness and face recognition performance, comprising the occipital lobe and visual ventral stream fusiform regions (overlapping the known location of face fusiform area) in the right hemisphere, in MCI. CONCLUSIONS We conclude that impairment of 3D visual integration exists at the MCI stage involving also the visual ventral stream and contributing to face recognition deficits. The specificity of such observed structure-function correlation for faces suggests a special role of this processing pathway in health and disease. (JINS, 2016, 22, 744-754).
Collapse
|
3
|
Botosoa E, Zhu M, Marbeuf-Gueye C, Triba M, Dutheil F, Duyckäerts C, Beaune P, Loriot M, Le Moyec L. NMR metabolomic of frontal cortex extracts: First study comparing two neurodegenerative diseases, Alzheimer disease and amyotrophic lateral sclerosis. Ing Rech Biomed 2012. [DOI: 10.1016/j.irbm.2012.08.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
|
4
|
Belleville S, Bherer L. Biomarkers of Cognitive Training Effects in Aging. CURRENT TRANSLATIONAL GERIATRICS AND EXPERIMENTAL GERONTOLOGY REPORTS 2012; 1:104-110. [PMID: 23864998 PMCID: PMC3693427 DOI: 10.1007/s13670-012-0014-5] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
An increasing number of studies have relied on brain imaging to assess the effects of cognitive training in healthy aging populations and in persons with early Alzheimer's disease or mild cognitive impairment (MCI). At the structural level, cognitive training in healthy aging individuals has been associated with increased brain volume, cortical thickness, and density and coherence of white matter tracts. At the functional level, task-related brain activation (using fMRI and PET) and fluorodeoxyglucose positron emission tomography (FDG-PET) were found to be sensitive to the effects of training. In persons with MCI, cognitive training increased brain metabolism and task-related brain activation, whereas healthy older adults showed patterns of increased and decreased activation. Further studies are required to generalize these findings to larger groups and to investigate more diverse training protocols. Research will also need to address important methodological issues regarding the use of biomarkers in cognitive aging, including reliability, clinical validity, and relevance to the pathophysiological process.
Collapse
Affiliation(s)
- Sylvie Belleville
- Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Quebec H3W-1 W5 Canada
- Département de Psychologie, Université de Montréal, Montréal, Quebec Canada
| | - Louis Bherer
- Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Quebec H3W-1 W5 Canada
- Département de Psychologie, Université du Québec à Montréal, Montréal, Quebec Canada
| |
Collapse
|
5
|
Jacobs HIL, Gronenschild EHBM, Evers EAT, Ramakers IHGB, Hofman PAM, Backes WH, Jolles J, Verhey FRJ, Van Boxtel MPJ. Visuospatial processing in early Alzheimer's disease: a multimodal neuroimaging study. Cortex 2012; 64:394-406. [PMID: 22342463 DOI: 10.1016/j.cortex.2012.01.005] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2011] [Revised: 11/15/2011] [Accepted: 01/10/2012] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Dorsal pathway dysfunctions are thought to underlie visuospatial processing problems in Alzheimer disease (AD). Prior studies reported compensatory mechanisms in the dorsal or ventral pathway in response to these functional changes. Since functional and structural connectivity are interrelated, these functional changes could be interpreted as a disconnection between both pathways. To better understand functional alterations in the dorsal pathway, we combined functional imaging with diffusion tensor imaging (DTI) in patients with mild cognitive impairment (MCI), a likely prodromal stage of AD. METHODS Eighteen older male individuals with amnestic MCI (aMCI) and 18 male cognitively healthy individuals, matched for age (range 59-75 years) and education, performed an object recognition task in the Magnetic Resonance Imaging (MRI) scanner. Neural activation was measured during recognition of non-canonically versus canonically oriented objects. Regions showing activation differences between groups were also investigated by DTI. RESULTS Recognition of non-canonical objects elicited increased frontal, temporal and parietal activation. Combining the functional MRI (fMRI) with the DTI results showed less deactivation in areas with decreased diffusion (mediolateral parietal and orbitofrontal) and increased activation in areas with increased diffusion (parietal and temporal) in aMCI patients. Finally, in aMCI patients decreased diffusion was found in the hippocampal cingulum, connecting both pathways. CONCLUSIONS Our results showed increased activation in early AD patients in ventral and dorsal pathways. A decrease in deactivation and diffusion suggests functional reorganization, while increased activation and diffusion suggests compensatory processes. This is the first study showing structural evidence for functional reorganization, which may be related to connectivity loss in the cingulum.
Collapse
Affiliation(s)
- Heidi I L Jacobs
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands; Cognitive Neurology Section, Institute of Neuroscience and Medicine-3, Research Centre Jülich, Jülich, Germany.
| | - Ed H B M Gronenschild
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands
| | - Elisabeth A T Evers
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Inez H G B Ramakers
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands
| | - Paul A M Hofman
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Walter H Backes
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Jelle Jolles
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands; AZIRE Research Institute, Faculty of Psychology and Education, Vrije Universiteit, Amsterdam, The Netherlands
| | - Frans R J Verhey
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands
| | - Martin P J Van Boxtel
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands; European Graduate School of Neuroscience EURON, Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
6
|
Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI, Stevens MC, Calhoun VD, Glahn DC, Shen L, Risacher SL, Saykin AJ, Pearlson GD. A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. Neuroimage 2012; 60:1608-21. [PMID: 22245343 DOI: 10.1016/j.neuroimage.2011.12.076] [Citation(s) in RCA: 90] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2011] [Revised: 12/16/2011] [Accepted: 12/19/2011] [Indexed: 11/16/2022] Open
Abstract
The underlying genetic etiology of late onset Alzheimer's disease (LOAD) remains largely unknown, likely due to its polygenic architecture and a lack of sophisticated analytic methods to evaluate complex genotype-phenotype models. The aim of the current study was to overcome these limitations in a bi-multivariate fashion by linking intermediate magnetic resonance imaging (MRI) phenotypes with a genome-wide sample of common single nucleotide polymorphism (SNP) variants. We compared associations between 94 different brain regions of interest derived from structural MRI scans and 533,872 genome-wide SNPs using a novel multivariate statistical procedure, parallel-independent component analysis, in a large, national multi-center subject cohort. The study included 209 elderly healthy controls, 367 subjects with amnestic mild cognitive impairment and 181 with mild, early-stage LOAD, all of them Caucasian adults, from the Alzheimer's Disease Neuroimaging Initiative cohort. Imaging was performed on comparable 1.5 T scanners at over 50 sites in the USA/Canada. Four primary "genetic components" were associated significantly with a single structural network including all regions involved neuropathologically in LOAD. Pathway analysis suggested that each component included several genes already known to contribute to LOAD risk (e.g. APOE4) or involved in pathologic processes contributing to the disorder, including inflammation, diabetes, obesity and cardiovascular disease. In addition significant novel genes identified included ZNF673, VPS13, SLC9A7, ATP5G2 and SHROOM2. Unlike conventional analyses, this multivariate approach identified distinct groups of genes that are plausibly linked in physiologic pathways, perhaps epistatically. Further, the study exemplifies the value of this novel approach to explore large-scale data sets involving high-dimensional gene and endophenotype data.
Collapse
Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatric Research Center, Hartford Hospital/IOL, Hartford, CT 06106, USA.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
7
|
Jacobs HI, Van Boxtel MP, Jolles J, Verhey FR, Uylings HB. Parietal cortex matters in Alzheimer's disease: An overview of structural, functional and metabolic findings. Neurosci Biobehav Rev 2012; 36:297-309. [DOI: 10.1016/j.neubiorev.2011.06.009] [Citation(s) in RCA: 189] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2011] [Revised: 06/15/2011] [Accepted: 06/21/2011] [Indexed: 01/18/2023]
|