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Geisler M, Rizzoni E, Makris N, Pasternak O, Rathi Y, Bouix S, Herbsleb M, Bär KJ, Weiss T, Kikinis Z. Microstructural alterations in medial forebrain bundle are associated with interindividual pain sensitivity. Hum Brain Mapp 2020; 42:1130-1137. [PMID: 33170528 PMCID: PMC7856635 DOI: 10.1002/hbm.25281] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 10/13/2020] [Accepted: 10/29/2020] [Indexed: 01/28/2023] Open
Abstract
The perception of pain to noxious stimuli, also known as pain sensitivity, varies among individuals. The comprised brain structures and their white matter pathways are complex and elusive. Here, we aimed to investigate whether variation of microstructure of the medial forebrain bundle (MFB), a tract connecting the basal forebrain with the brain stem, is associated with interindividual pain sensitivity. We assessed interindividual pain sensitivity as a rating of pain intensity to heat stimuli (45, 47, and 48.9°C) in 38 healthy men (age: 27.05 ± 5.7 years). We also reconstructed the MFB using multitensor tractography from diffusion magnetic resonance imaging (dMRI) and calculated free‐water corrected dMRI measures of fractional anisotropy (FAt), radial diffusivity (RDt), and axial diffusivity (ADt). Lower ratings of interindividual pain intensity correlated with higher FAt and lower RDt of the MFB. As changes in FAt and RDt may reflect abnormalities in myelination, the results might be interpreted as that a lower pain rating is associated with higher degree of myelination of the MFB and could represent an inhibitory pathway of pain. Our results suggest that alteration of microstructure in the MFB contributes to the interindividual variation of pain perception.
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Affiliation(s)
- Maria Geisler
- Department of Clinical Psychology, Friedrich-Schiller-University Jena, Jena, Germany
| | - Elizabeth Rizzoni
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Nikolaos Makris
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA.,Departments of Radiology and Psychiatry, Harvard Medical School, Boston, Massachusetts, USA.,Departments of Radiology and Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA.,Departments of Radiology and Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA.,Departments of Radiology and Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA.,Departments of Radiology and Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Marco Herbsleb
- Department of Sports Medicine and Health Promotion, Friedrich-Schiller-University Jena, Jena, Germany
| | - Karl-Jürgen Bär
- Department of Psychosomatic Medicine, University Hospital Jena, Jena, Germany
| | - Thomas Weiss
- Department of Clinical Psychology, Friedrich-Schiller-University Jena, Jena, Germany
| | - Zora Kikinis
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
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van de Vijver I, Ligneul R. Relevance of working memory for reinforcement learning in older adults varies with timescale of learning. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2020; 27:654-676. [PMID: 31544587 DOI: 10.1080/13825585.2019.1664389] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 09/02/2019] [Indexed: 06/10/2023]
Abstract
In young adults, individual differences in working memory (WM) contribute to reinforcement learning (RL). Age-related RL changes, however, are mostly attributed to decreased reward prediction-error (RPE) signaling. Here, we investigated the contribution of WM to RL in young (18-35) and older (≥65) adults. Because WM supports maintenance across a limited timescale, we only expected a relation between RL and WM with short delays between stimulus repetitions. Our results demonstrated better learning with short than long delays. A week later, however, long-delay associations were remembered better. Computational modeling corroborated that during learning, WM was more engaged by young adults in the short-delay condition than in any other age-condition combination. Crucially, both model-derived and neuropsychological assessments of WM predicted short-delay learning in older adults, who further benefitted from using self-conceived learning strategies. Thus, depending on the timescale of learning, age-related RL changes may not only reflect decreased RPE signaling but also WM decline.
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Affiliation(s)
- Irene van de Vijver
- Behavioural Science Institute, Radboud University , Nijmegen, The Netherlands
- Department of Clinical Psychology, University of Amsterdam , Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam , Amsterdam, The Netherlands
| | - Romain Ligneul
- Champalimaud Neuroscience Program, Champalimaud Foundation , Lisboa, Portugal
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53
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Pergher V, Schoenmakers B, Demaerel P, Tournoy J, Van Hulle MM. Differential Impact of Cognitive Impairment in MCI Patients: A Case-Based Report. Case Rep Neurol 2020; 12:222-231. [PMID: 32774279 PMCID: PMC7383180 DOI: 10.1159/000507977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 04/19/2020] [Indexed: 11/19/2022] Open
Abstract
Mild cognitive impairment (MCI) traditionally refers to an intermediate stage between healthy individuals and early Alzheimer disease. Evidence shows grey and white matter volume changes and decrease in several executive functions, albeit the relation between cognitive performance and brain volume remains unclear. Here, we discuss 3 individual cases of MCI by investigating their MRI scans and cognitive test performance. We also recruited age-matched healthy older adults serving as gold standard for both grey and white matter volume and cognitive test outcomes. Our results show the impact of cognitive impairment on cognitive test performance and grey and white matter volumes, and the role played by cognitive and brain reserve on mitigating cognitive decline. Furthermore, we add evidence to previous studies by showing an increase in white matter volume compared to healthy controls, in all 3 patients. This pattern of increased white matter volume might help us to better understand the pathological mechanisms underlying MCI which in turn could contribute to future investigations.
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Affiliation(s)
- Valentina Pergher
- Department of Cognitive Neuropsychology, Harvard University, Cambridge, Massachusetts, USA.,Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven - University of Leuven, Leuven, Belgium
| | - Birgitte Schoenmakers
- Academic Centre of General Practice, KU Leuven - University of Leuven, Leuven, Belgium
| | - Philippe Demaerel
- Department of Neuroradiology, KU Leuven - University Hospitals Leuven, Leuven, Belgium
| | - Jos Tournoy
- Department of Chronic Diseases, Metabolism and Ageing, KU Leuven - University Hospitals Leuven, Leuven, Belgium.,Department of Geriatric Medicine, KU Leuven - University Hospitals Leuven, Leuven, Belgium
| | - Marc M Van Hulle
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven - University of Leuven, Leuven, Belgium
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54
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Ferrer I, Andrés-Benito P. White matter alterations in Alzheimer's disease without concomitant pathologies. Neuropathol Appl Neurobiol 2020; 46:654-672. [PMID: 32255227 PMCID: PMC7754505 DOI: 10.1111/nan.12618] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 03/23/2020] [Indexed: 12/14/2022]
Abstract
Aims Most individuals with AD neuropathological changes have co‐morbidities which have an impact on the integrity of the WM. This study analyses oligodendrocyte and myelin markers in the frontal WM in a series of AD cases without clinical or pathological co‐morbidities. Methods From a consecutive autopsy series, 206 cases had neuropathological changes of AD; among them, only 33 were AD without co‐morbidities. WM alterations were first evaluated in coronal sections of the frontal lobe in every case. Then, RT‐qPCR and immunohistochemistry were carried out in the frontal WM of AD cases without co‐morbidities to analyse the expression of selected oligodendrocyte and myelin markers. Results WM demyelination was more marked in AD with co‐morbidities when compared with AD cases without co‐morbidities. Regarding the later, mRNA expression levels of MBP, PLP1, CNP, MAG, MAL, MOG and MOBP were preserved at stages I–II/0–A when compared with middle‐aged (MA) individuals, but significantly decreased at stages III–IV/0–C. This was accompanied by reduced expression of NG2 and PDGFRA mRNA, reduced numbers of NG2‐, Olig2‐ and HDAC2‐immunoreactive cells and reduced glucose transporter immunoreactivity. Partial recovery of some of these markers occurred at stages V–VI/B–C. Conclusions The present observations demonstrate that co‐morbidities have an impact on WM integrity in the elderly and in AD, and that early alterations in oligodendrocytes and transcription of genes linked to myelin proteins in WM occur in AD cases without co‐morbidities. These are followed by partial recovery attempts at advanced stages. These observations suggest that oligodendrocytopathy is part of AD.
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Affiliation(s)
- I Ferrer
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Barcelona, Spain.,Bellvitge University Hospital, Barcelona, Spain.,Ministry of Economy and Competitiveness, CIBERNED (Network Centre of Biomedical Research of Neurodegenerative Diseases), Institute of Health Carlos III, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - P Andrés-Benito
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Barcelona, Spain.,Ministry of Economy and Competitiveness, CIBERNED (Network Centre of Biomedical Research of Neurodegenerative Diseases), Institute of Health Carlos III, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
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55
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Bezukladova S, Tuisku J, Matilainen M, Vuorimaa A, Nylund M, Smith S, Sucksdorff M, Mohammadian M, Saunavaara V, Laaksonen S, Rokka J, Rinne JO, Rissanen E, Airas L. Insights into disseminated MS brain pathology with multimodal diffusion tensor and PET imaging. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2020; 7:e691. [PMID: 32123046 PMCID: PMC7136049 DOI: 10.1212/nxi.0000000000000691] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 01/09/2020] [Indexed: 01/30/2023]
Abstract
OBJECTIVE To evaluate in vivo the co-occurrence of microglial activation and microstructural white matter (WM) damage in the MS brain and to examine their association with clinical disability. METHODS 18-kDa translocator protein (TSPO) brain PET imaging was performed for evaluation of microglial activation by using the radioligand [11C](R)-PK11195. TSPO binding was evaluated as the distribution volume ratio (DVR) from dynamic PET images. Diffusion tensor imaging (DTI) and conventional MRI (cMRI) were performed at the same time. Mean fractional anisotropy (FA) and mean (MD), axial, and radial (RD) diffusivities were calculated within the whole normal-appearing WM (NAWM) and segmented NAWM regions appearing normal in cMRI. Fifty-five patients with MS and 15 healthy controls (HCs) were examined. RESULTS Microstructural damage was observed in the NAWM of the MS brain. DTI parameters of patients with MS were significantly altered in the NAWM compared with an age- and sex-matched HC group: mean FA was decreased, and MD and RD were increased. These structural abnormalities correlated with increased TSPO binding in the whole NAWM and in the temporal NAWM (p < 0.05 for all correlations; p < 0.01 for RD in the temporal NAWM). Both compromised WM integrity and increased microglial activation in the NAWM correlated significantly with higher clinical disability measured with the Expanded Disability Status Scale score. CONCLUSIONS Widespread structural disruption in the NAWM is linked to neuroinflammation, and both phenomena associate with clinical disability. Multimodal PET and DTI allow in vivo evaluation of widespread MS pathology not visible using cMRI.
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Affiliation(s)
- Svetlana Bezukladova
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Jouni Tuisku
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Markus Matilainen
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Anna Vuorimaa
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Marjo Nylund
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Sarah Smith
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Marcus Sucksdorff
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Mehrbod Mohammadian
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Virva Saunavaara
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Sini Laaksonen
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Johanna Rokka
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Juha O Rinne
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Eero Rissanen
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland
| | - Laura Airas
- From the Turku PET Centre (S.B., J.T., M. Matilainen, A.V., M.N., S.S., M.S., M. Mohammadian, V.S., S.L., J.R., J.O.R., E.R., L.A.), University of Turku and Turku University Hospital; Division of Clinical Neurosciences (A.V., M.N., S.S., M.S., S.L., E.R., L.A.), Turku University Hospital; and Department of Medical Physics (V.S.), Division of Medical Imaging, Turku University Hospital, Finland.
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56
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Aganj I, Frau-Pascual A, Iglesias JE, Yendiki A, Augustinack JC, Salat DH, Fischl B. COMPENSATORY BRAIN CONNECTION DISCOVERY IN ALZHEIMER'S DISEASE. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2020; 2020:283-287. [PMID: 32587665 PMCID: PMC7316404 DOI: 10.1109/isbi45749.2020.9098440] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Identification of the specific brain networks that are vulnerable or resilient in neurodegenerative diseases can help to better understand the disease effects and derive new connectomic imaging biomarkers. In this work, we use brain connectivity to find pairs of structural connections that are negatively correlated with each other across Alzheimer's disease (AD) and healthy populations. Such anti-correlated brain connections can be informative for identification of compensatory neuronal pathways and the mechanism of brain networks' resilience to AD. We find significantly anti-correlated connections in a public diffusion-MRI database, and then validate the results on other databases.
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Affiliation(s)
- Iman Aganj
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
| | - Aina Frau-Pascual
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
| | - Juan E Iglesias
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
- Center for Medical Image Computing (CMIC), University College London, London, UK
| | - Anastasia Yendiki
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
| | - Jean C Augustinack
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
| | - David H Salat
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
| | - Bruce Fischl
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
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57
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Frenzel S, Wittfeld K, Habes M, Klinger-König J, Bülow R, Völzke H, Grabe HJ. A Biomarker for Alzheimer's Disease Based on Patterns of Regional Brain Atrophy. Front Psychiatry 2020; 10:953. [PMID: 31992998 PMCID: PMC6970941 DOI: 10.3389/fpsyt.2019.00953] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 12/03/2019] [Indexed: 11/28/2022] Open
Abstract
Introduction: It has been shown that Alzheimer's disease (AD) is accompanied by marked structural brain changes that can be detected several years before clinical diagnosis via structural magnetic resonance (MR) imaging. In this study, we developed a structural MR-based biomarker for in vivo detection of AD using a supervised machine learning approach. Based on an individual's pattern of brain atrophy a continuous AD score is assigned which measures the similarity with brain atrophy patterns seen in clinical cases of AD. Methods: The underlying statistical model was trained with MR scans of patients and healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI-1 screening). Validation was performed within ADNI-1 and in an independent patient sample from the Open Access Series of Imaging Studies (OASIS-1). In addition, our analyses included data from a large general population sample of the Study of Health in Pomerania (SHIP-Trend). Results: Based on the proposed AD score we were able to differentiate patients from healthy controls in ADNI-1 and OASIS-1 with an accuracy of 89% (AUC = 95%) and 87% (AUC = 93%), respectively. Moreover, we found the AD score to be significantly associated with cognitive functioning as assessed by the Mini-Mental State Examination in the OASIS-1 sample after correcting for diagnosis, age, sex, age·sex, and total intracranial volume (Cohen's f2 = 0.13). Additional analyses showed that the prediction accuracy of AD status based on both the AD score and the MMSE score is significantly higher than when using just one of them. In SHIP-Trend we found the AD score to be weakly but significantly associated with a test of verbal memory consisting of an immediate and a delayed word list recall (again after correcting for age, sex, age·sex, and total intracranial volume, Cohen's f2 = 0.009). This association was mainly driven by the immediate recall performance. Discussion: In summary, our proposed biomarker well differentiated between patients and healthy controls in an independent test sample. It was associated with measures of cognitive functioning both in a patient sample and a general population sample. Our approach might be useful for defining robust MR-based biomarkers for other neurodegenerative diseases, too.
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Affiliation(s)
- Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Greifswald, Germany
| | - Mohamad Habes
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, United States
| | - Johanna Klinger-König
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Greifswald, Germany
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58
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Zhou L, Flores J, Noël A, Beauchet O, Sjöström PJ, LeBlanc AC. Methylene blue inhibits Caspase-6 activity, and reverses Caspase-6-induced cognitive impairment and neuroinflammation in aged mice. Acta Neuropathol Commun 2019; 7:210. [PMID: 31843022 PMCID: PMC6915996 DOI: 10.1186/s40478-019-0856-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 11/25/2019] [Indexed: 12/20/2022] Open
Abstract
Activated Caspase-6 (Casp6) is associated with age-dependent cognitive impairment and Alzheimer disease (AD). Mice expressing human Caspase-6 in hippocampal CA1 neurons develop age-dependent cognitive deficits, neurodegeneration and neuroinflammation. This study assessed if methylene blue (MB), a phenothiazine that inhibits caspases, alters Caspase-6-induced neurodegeneration and cognitive impairment in mice. Aged cognitively impaired Casp6-overexpressing mice were treated with methylene blue in drinking water for 1 month. Methylene blue treatment did not alter Caspase-6 levels, assessed by RT-PCR, western blot and immunohistochemistry, but inhibited fluorescently-labelled Caspase-6 activity in acute brain slice intact neurons. Methylene blue treatment rescued Caspase-6-induced episodic and spatial memory deficits measured by novel object recognition and Barnes maze, respectively. Methylene blue improved synaptic function of hippocampal CA1 neurons since theta-burst long-term potentiation (LTP), measured by field excitatory postsynaptic potentials (fEPSPs) in acute brain slices, was successfully induced in the Schaffer collateral-CA1 pathway in methylene blue-treated, but not in vehicle-treated, Caspase-6 mice. Increased neuroinflammation, measured by ionized calcium binding adaptor molecule 1 (Iba1)-positive microglia numbers and subtypes, and glial fibrillary acidic protein (GFAP)-positive astrocytes, were decreased by methylene blue treatment. Therefore, methylene blue reverses Caspase-6-induced cognitive deficits by inhibiting Caspase-6, and Caspase-6-mediated neurodegeneration and neuroinflammation. Our results indicate that Caspase-6-mediated damage is reversible months after the onset of cognitive deficits and suggest that methylene blue could benefit Alzheimer disease patients by reversing Caspase-6-mediated cognitive decline.
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Affiliation(s)
- Libin Zhou
- Lady Davis Institute for Medical Research at Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
- Department of Anatomy and Cell Biology, McGill University, 3640 University Street Strathcona Anatomy Building, Montreal, QC H3A 0C7 Canada
| | - Joseph Flores
- Lady Davis Institute for Medical Research at Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
| | - Anastasia Noël
- Lady Davis Institute for Medical Research at Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
| | - Olivier Beauchet
- Lady Davis Institute for Medical Research at Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
- Department of Medicine, Division of Geriatric Medicine, Sir Mortimer B. Davis - Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - P. Jesper Sjöström
- Centre for Research in Neuroscience, the BRaIN Program, Department of Neurology and Neurosurgery, McGill University, The Research Institute of the McGill University Health Centre, Montreal General Hospital, 1650 Cedar Avenue, Montreal, QC H3G 1A4 Canada
| | - Andrea C. LeBlanc
- Lady Davis Institute for Medical Research at Jewish General Hospital, 3999 Ch. Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
- Department of Anatomy and Cell Biology, McGill University, 3640 University Street Strathcona Anatomy Building, Montreal, QC H3A 0C7 Canada
- Department of Neurology and Neurosurgery, McGill University, 845 Sherbrooke O, Montreal, QC H3A 0G4 Canada
- Bloomfield Center for Research in Aging, Lady Davis Institute for Medical Research, Sir Mortimer B Davis Jewish General Hospital, 3755 ch. Côte Ste-Catherine, Montréal, QC H3T 1E2 Canada
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59
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Giacosa C, Karpati FJ, Foster NEV, Hyde KL, Penhune VB. The descending motor tracts are different in dancers and musicians. Brain Struct Funct 2019; 224:3229-3246. [PMID: 31620887 DOI: 10.1007/s00429-019-01963-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 10/01/2019] [Indexed: 01/03/2023]
Abstract
Long-term motor training, such as dance or gymnastics, has been associated with increased diffusivity and reduced fiber coherence in regions including the corticospinal tract. Comparisons between different types of motor experts suggest that experience might result in specific structural changes related to the trained effectors (e.g., hands or feet). However, previous studies have not segregated the descending motor pathways from different body-part representations in motor cortex (M1). Further, most previous diffusion tensor imaging studies used whole-brain analyses based on a single tensor, which provide poor information about regions where multiple white matter (WM) tracts cross. Here, we used multi-tensor probabilistic tractography to investigate the specific components of the descending motor pathways in well-matched groups of dancers, musicians and controls. To this aim, we developed a procedure to identify the WM regions below the motor representations of the head, hand, trunk and leg that served as seeds for tractography. Dancers showed increased radial diffusivity (RD) in comparison with musicians, in descending motor pathways from all the regions, particularly in the right hemisphere, whereas musicians had increased fractional anisotropy (FA) in the hand and the trunk/arm motor tracts. Further, dancers showed larger volumes compared to both other groups. Finally, we found negative correlations between RD and FA with the age of start of dance or music training, respectively, and between RD and performance on a melody task, and positive correlations between RD and volume with performance on a whole-body dance task. These findings suggest that different types of training might have different effects on brain structure, likely because dancers must coordinate movements of the entire body, whereas musicians focus on fewer effectors.
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Affiliation(s)
- Chiara Giacosa
- International Laboratory for Brain, Music and Sound Research (BRAMS), Pavillon 1420 Mont Royal, CP 6128, Succ. Centre Ville, Montreal, QC, H3C 3J7, Canada. .,Department of Psychology, Concordia University, 7141 Sherbrooke Street West, Montreal, Quebec, H4B 1R6, Canada.
| | - Falisha J Karpati
- International Laboratory for Brain, Music and Sound Research (BRAMS), Pavillon 1420 Mont Royal, CP 6128, Succ. Centre Ville, Montreal, QC, H3C 3J7, Canada.,Faculty of Medicine, McGill University, 3655 Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada
| | - Nicholas E V Foster
- International Laboratory for Brain, Music and Sound Research (BRAMS), Pavillon 1420 Mont Royal, CP 6128, Succ. Centre Ville, Montreal, QC, H3C 3J7, Canada.,Department of Psychology, University of Montreal, Pavillon Marie-Victorin, 90 avenue Vincent d'Indy, Montreal, Quebec, H2V 2S9, Canada
| | - Krista L Hyde
- International Laboratory for Brain, Music and Sound Research (BRAMS), Pavillon 1420 Mont Royal, CP 6128, Succ. Centre Ville, Montreal, QC, H3C 3J7, Canada.,Faculty of Medicine, McGill University, 3655 Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada.,Department of Psychology, University of Montreal, Pavillon Marie-Victorin, 90 avenue Vincent d'Indy, Montreal, Quebec, H2V 2S9, Canada
| | - Virginia B Penhune
- International Laboratory for Brain, Music and Sound Research (BRAMS), Pavillon 1420 Mont Royal, CP 6128, Succ. Centre Ville, Montreal, QC, H3C 3J7, Canada.,Department of Psychology, Concordia University, 7141 Sherbrooke Street West, Montreal, Quebec, H4B 1R6, Canada
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60
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Thalamic volume loss as an early sign of amnestic mild cognitive impairment. J Clin Neurosci 2019; 68:168-173. [DOI: 10.1016/j.jocn.2019.07.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 06/27/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022]
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61
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Zhao L, Matloff W, Ning K, Kim H, Dinov ID, Toga AW. Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults. Cereb Cortex 2019; 29:4169-4193. [PMID: 30535294 PMCID: PMC6931275 DOI: 10.1093/cercor/bhy300] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 11/05/2018] [Accepted: 11/07/2018] [Indexed: 12/11/2022] Open
Abstract
Brain structural morphology differs with age. This study examined age-differences in surface-based morphometric measures of cortical thickness, volume, and surface area in a well-defined sample of 8137 generally healthy UK Biobank participants aged 45-79 years. We illustrate that the complexity of age-related brain morphological differences may be related to the laminar organization and regional evolutionary history of the cortex, and age of about 60 is a break point for increasing negative associations between age and brain morphology in Alzheimer's disease (AD)-prone areas. We also report novel relationships of age-related cortical differences with individual factors of sex, cognitive functions of fluid intelligence, reaction time and prospective memory, cigarette smoking, alcohol consumption, sleep disruption, genetic markers of apolipoprotein E, brain-derived neurotrophic factor, catechol-O-methyltransferase, and several genome-wide association study loci for AD and further reveal joint effects of cognitive functions, lifestyle behaviors, and education on age-related cortical differences. These findings provide one of the most extensive characterizations of age associations with major brain morphological measures and improve our understanding of normal structural brain aging and its potential modifiers.
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Affiliation(s)
- Lu Zhao
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - William Matloff
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Kaida Ning
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Hosung Kim
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Ivo D Dinov
- Statistics Online Computational Resource, HBBS, University of Michigan, Ann Arbor, MI 48109-2003, USA
- Michigan Institute for Data Science, HBBS, University of Michigan, Ann Arbor, MI 48109-1042, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
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62
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Distinct forms of motion sensitivity impairments in Alzheimer's disease. Sci Rep 2019; 9:12931. [PMID: 31506450 PMCID: PMC6736838 DOI: 10.1038/s41598-019-48942-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 07/31/2019] [Indexed: 11/21/2022] Open
Abstract
Motion sensitivity impairment in Alzheimer’s disease (AD) is often characterized as elevated coherence threshold. An alternative way to measure motion sensitivity is the direction threshold, i.e., the minimal angle of motion direction that can be discriminated. So far, it is less clear whether and how the direction threshold is altered in AD. Here we asked a group of AD patients and two control groups of healthy participants (young and elderly adults) to judge their perceived heading direction based on a field of optic flow stimuli simulating a forward translation in the environment. We manipulated the heading direction and the coherence of the optic flow independently and measured the direction and coherence thresholds from each participant. We found that the direction threshold increased significantly in AD patients as compared to healthy controls, like the coherence threshold. Yet, the elevation in the direction threshold was less pronounced than the coherence threshold. Moreover, the magnitudes of the direction and coherence thresholds in AD patients were not correlated. Our results suggest that coherence and direction impairments are two distinct forms of motion deficits in AD patients which might be associated with independent neural mechanisms.
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63
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Zarnani K, Nichols TE, Alfaro-Almagro F, Fagerlund B, Lauritzen M, Rostrup E, Smith SM. Discovering markers of healthy aging: a prospective study in a Danish male birth cohort. Aging (Albany NY) 2019; 11:5943-5974. [PMID: 31480020 PMCID: PMC6738442 DOI: 10.18632/aging.102151] [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] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/31/2019] [Indexed: 01/23/2023]
Abstract
There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, Pcorrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study.
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Affiliation(s)
- Kiyana Zarnani
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.,Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Big Data Institute, Li Ka Shing, Centre For Health Information and Discovery, Nuffield Department of Population Health University of Oxford, Oxford, UK.,Department of Statistics, University of Warwick, Coventry, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Medicine, Glostrup, Denmark
| | - Egill Rostrup
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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64
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Shellikeri S, Myers M, Black SE, Abrahao A, Zinman L, Yunusova Y. Speech network regional involvement in bulbar ALS: a multimodal structural MRI study. Amyotroph Lateral Scler Frontotemporal Degener 2019; 20:385-395. [PMID: 31088163 DOI: 10.1080/21678421.2019.1612920] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Objective: To examine gray (GM) and white matter (WM) structural changes in regions of the speech network (SpN) in ALS patients with varying degree of bulbar disease. Methods: T1 and DTI images were obtained for 19 ALS participants and 13 neurologically-intact controls. Surface-based, volumetric, and DTI metrics were obtained for 6 regions-of-interest (ROIs) including the primary motor cortex (PMC), pars triangularis (parsT), pars opercularis (ParsO), posterior superior temporal gyrus (pSTG), and transverse temporal (TT). Disease-effects and brain-behavioral correlates between neuroanatomy and clinical measures of bulbar, limb, and overall disability were examined using linear models. Results: Structural changes were observed in the right oral and limb PMC and left ParsT, TT, and pSTG in ALS. Bulbar motor dysfunction was associated with WM abnormalities in the right oral PMC and left pSTG, and GM changes in bilateral TT. In contrast, symptom progression rate predicted GM and WM changes in bilateral pars opercularis (part of Broca's area). Grip strength and disease duration models were non-significant. Conclusions: The findings suggested that regions of the left-dominant SpN may be implicated in ALS and degeneration of these areas are related to bulbar disease severity. Involvement of regions that overlap across multiple connectomes such as Broca's area, however, may be dependent on the rate of disease progression. The work contributes to our understanding of bulbar ALS subtype, which is crucial for predicting disease progression, delivering targeted clinical care, and appropriate recruitment into clinical trials.
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Affiliation(s)
- Sanjana Shellikeri
- a Department of Speech Language Pathology , University of Toronto , Ontario , Canada.,b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada
| | - Matthew Myers
- b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada
| | - Sandra E Black
- b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada.,c L.C. Campbell Cognitive Neurology Research Unit , Sunnybrook Research Institute, University of Toronto , Toronto , Canada.,d Department of Medicine, Division of Neurology , Sunnybrook Health Sciences Centre , Toronto , Canada.,e Rotman Research Institute, Baycrest , Toronto , Canada , and
| | - Agessandro Abrahao
- b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada.,d Department of Medicine, Division of Neurology , Sunnybrook Health Sciences Centre , Toronto , Canada
| | - Lorne Zinman
- b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada.,c L.C. Campbell Cognitive Neurology Research Unit , Sunnybrook Research Institute, University of Toronto , Toronto , Canada.,d Department of Medicine, Division of Neurology , Sunnybrook Health Sciences Centre , Toronto , Canada
| | - Yana Yunusova
- a Department of Speech Language Pathology , University of Toronto , Ontario , Canada.,b Hurvitz Brain Sciences Program , Sunnybrook Research Institute , Ontario , Canada.,f University Health Network, Toronto Rehabilitation Institute , Ontario , Canada
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65
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Abstract
The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.
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Affiliation(s)
- Hannah Humayun
- Photoacoustic Imaging Laboratory, Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Junjie Yao
- Photoacoustic Imaging Laboratory, Department of Biomedical Engineering, Duke University, Durham, NC, USA
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66
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Zhang Y, Chao FL, Zhang L, Jiang L, Zhou CN, Chen LM, Lu W, Jiang R, Tang Y. Quantitative study of the capillaries within the white matter of the Tg2576 mouse model of Alzheimer's disease. Brain Behav 2019; 9:e01268. [PMID: 30900389 PMCID: PMC6456816 DOI: 10.1002/brb3.1268] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 02/25/2019] [Accepted: 03/02/2019] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION To quantitatively investigate the capillaries within the white matter of Tg2576 Alzheimer's disease (AD) transgenic mice during the early stage. METHODS In the current study, 10-month-old male Tg2576 AD mice were used as the early-stage AD group and age-matched nontransgenic littermate mice were used as the wild-type group. Then, the Morris water maze was used to examine the spatial learning and memory abilities of the mice in both groups, and unbiased stereological methods were used to accurately quantify the volume of white matter and the parameters of the capillaries within the white matter, such as the total length, total volume, and total surface area of capillaries. RESULTS The Morris water maze performance of the Tg2576 group was worse than that of the wild-type group, while the white matter volume did not significantly differ between the wild-type group and the Tg2576 group. The total length, total volume, and total surface area of the capillaries within the white matter of the Tg2576 group were significantly decreased compared to those of the wild-type group. CONCLUSIONS The current study provide structural basis for understanding the pathological changes of the early stage of AD and cognitive decline in AD might be associated with changes in the white matter capillaries. Capillaries within the white matter might, thus, serve as a valid target for the prevention and treatment of early-stage AD.
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Affiliation(s)
- Yi Zhang
- Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine, Ministry of Education, Chongqing Medical University, Chongqing, China.,Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Feng-Lei Chao
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Lei Zhang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Lin Jiang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Chun-Ni Zhou
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Lin-Mu Chen
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Wei Lu
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Rong Jiang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Yong Tang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China.,Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
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67
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Song Y, Wang H. Motion-induced position mis-localization predicts the severity of Alzheimer's disease. J Neuropsychol 2019; 14:333-345. [PMID: 30859737 DOI: 10.1111/jnp.12181] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/31/2019] [Indexed: 01/16/2023]
Abstract
Patients with Alzheimer's disease (AD) often exhibit motion processing deficits. It is unclear whether the localization of moving objects - a perceptual process tightly linked to motion - is impaired or intact in AD. In this study, we used the phenomenon of illusory shift of position induced by motion as a behavioural paradigm to probe how the spatial representation differs between AD patients and healthy elderly controls. We measured the magnitudes of motion-induced position shift in a group of AD participants (N = 24) and age-matched elderly observers (N = 24). We found that AD patients showed weakened position mis-localization, but only for motion stimuli of slow speeds. For fast motion, the position mis-localization did not differ significantly between groups. Furthermore, we showed that the magnitudes of position mis-localization can predict the severity of AD; that is, patients with more severe symptoms had less preserved position mis-localization. Our results suggest that AD pathology impacts not only motion processing per se, but also the perceptual process related to motion such as the localization of moving objects.
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Affiliation(s)
- Yamin Song
- Department of Neurology, Liaocheng People's Hospital, China
| | - Huiting Wang
- Department of Neurology, Liaocheng People's Hospital, China
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68
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Wang Q, Wang Y, Liu J, Sutphen CL, Cruchaga C, Blazey T, Gordon BA, Su Y, Chen C, Shimony JS, Ances BM, Cairns NJ, Fagan AM, Morris JC, Benzinger TLS. Quantification of white matter cellularity and damage in preclinical and early symptomatic Alzheimer's disease. Neuroimage Clin 2019; 22:101767. [PMID: 30901713 PMCID: PMC6428957 DOI: 10.1016/j.nicl.2019.101767] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 02/12/2019] [Accepted: 03/10/2019] [Indexed: 02/08/2023]
Abstract
Interest in understanding the roles of white matter (WM) inflammation and damage in the pathophysiology of Alzheimer disease (AD) has been growing significantly in recent years. However, in vivo magnetic resonance imaging (MRI) techniques for imaging inflammation are still lacking. An advanced diffusion-based MRI method, neuro-inflammation imaging (NII), has been developed to clinically image and quantify WM inflammation and damage in AD. Here, we employed NII measures in conjunction with cerebrospinal fluid (CSF) biomarker classification (for β-amyloid (Aβ) and neurodegeneration) to evaluate 200 participants in an ongoing study of memory and aging. Elevated NII-derived cellular diffusivity was observed in both preclinical and early symptomatic phases of AD, while disruption of WM integrity, as detected by decreased fractional anisotropy (FA) and increased radial diffusivity (RD), was only observed in the symptomatic phase of AD. This may suggest that WM inflammation occurs earlier than WM damage following abnormal Aβ accumulation in AD. The negative correlation between NII-derived cellular diffusivity and CSF Aβ42 level (a marker of amyloidosis) may indicate that WM inflammation is associated with increasing Aβ burden. NII-derived FA also negatively correlated with CSF t-tau level (a marker of neurodegeneration), suggesting that disruption of WM integrity is associated with increasing neurodegeneration. Our findings demonstrated the capability of NII to simultaneously image and quantify WM cellularity changes and damage in preclinical and early symptomatic AD. NII may serve as a clinically feasible imaging tool to study the individual and composite roles of WM inflammation and damage in AD.
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Affiliation(s)
- Qing Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA
| | - Yong Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University School of Engineering & Applied Science, St. Louis, MO 63015, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Jingxia Liu
- Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Courtney L Sutphen
- Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tyler Blazey
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ 85006, USA
| | - Charlie Chen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Beau M Ances
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, 4488 Forest Park, Suite 101, St. Louis, MO 63108, USA; Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO 63110, USA
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69
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Wu T, Merkley TL, Wilde EA, Barnes A, Li X, Chu ZD, McCauley SR, Hunter JV, Levin HS. A preliminary report of cerebral white matter microstructural changes associated with adolescent sports concussion acutely and subacutely using diffusion tensor imaging. Brain Imaging Behav 2019; 12:962-973. [PMID: 28812290 DOI: 10.1007/s11682-017-9752-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Diffusion tensor imaging (DTI) has demonstrated its utility in detecting microscopic post-concussion cerebral white matter structural changes, which are not routinely evident on conventional neuroimaging modalities. In this study, we compared 10 adolescents with sports concussion (SC) to 12 orthopedically-injured (OI) individuals within 96 h and three months post injury to 12 typically-developing (TD) participants using DTI and volumetric analyses. In terms of volume, no group differences were noted between SC, OI and TD groups at both 96 h and three months post concussion. Results did not show significant differences between SC, OI, and TD groups for both fractional anisotropy (FA) and apparent diffusion coefficient (ADC) in all regions of interest within 96 h post concussion. However, at three months post-injury, the SC group exhibited significantly lower FA than the TD group in various regions of interest. In terms of ADC, significant group differences between SC and TD groups were found in some regions, with SC group having higher ADC than TD. No group differences for FA and ADC were noted between SC and OI groups at three months post-injury. However, several moderate effect sizes on between-group analyses were noted such that FA was lower and ADC was higher in SC relative to OI. Longitudinally, the SC group demonstrated decreased FA and increased ADC in some areas. The findings highlight the fact that the brain continues to change during the post-injury recovery period, and raises the possibility that adverse changes may result from the neurometabolic cascade that purportedly ensues following SC. DTI may potentially be used to characterize the nature of brain changes that occur following sports-related concussions.
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Affiliation(s)
- Trevor Wu
- Mercy Health St. Mary's, Michigan State University, 220 Cherry St SE, Grand Rapids, MI, 49503, USA
| | - Tricia L Merkley
- Barrow Neurological Institute, 222 W. Thomas Road, Suite 315, Phoenix, AZ, 85013, USA
| | - Elisabeth A Wilde
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA.
| | - Amanda Barnes
- University of Miami Miller School of Medicine, 1600 NW 10th Ave #1440, Miami, FL, 33136, USA
| | - Xiaoqi Li
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA
| | - Zili David Chu
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA
| | - Stephen R McCauley
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA
| | - Jill V Hunter
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA
| | - Harvey S Levin
- Baylor College of Medicine, One Baylor Plaza BCM637, Houston, TX, 77030-3411, USA
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Racine AM, Merluzzi AP, Adluru N, Norton D, Koscik RL, Clark LR, Berman SE, Nicholas CR, Asthana S, Alexander AL, Blennow K, Zetterberg H, Kim WH, Singh V, Carlsson CM, Bendlin BB, Johnson SC. Association of longitudinal white matter degeneration and cerebrospinal fluid biomarkers of neurodegeneration, inflammation and Alzheimer's disease in late-middle-aged adults. Brain Imaging Behav 2019; 13:41-52. [PMID: 28600739 PMCID: PMC5723250 DOI: 10.1007/s11682-017-9732-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease (AD) is characterized by substantial neurodegeneration, including both cortical atrophy and loss of underlying white matter fiber tracts. Understanding longitudinal alterations to white matter may provide new insights into trajectories of brain change in both healthy aging and AD, and fluid biomarkers may be particularly useful in this effort. To examine this, 151 late-middle-aged participants enriched with risk for AD with at least one lumbar puncture and two diffusion tensor imaging (DTI) scans were selected for analysis from two large observational and longitudinally followed cohorts. Cerebrospinal fluid (CSF) was assayed for biomarkers of AD-specific pathology (phosphorylated-tau/Aβ42 ratio), axonal degeneration (neurofilament light chain protein, NFL), dendritic degeneration (neurogranin), and inflammation (chitinase-3-like protein 1, YKL-40). Linear mixed effects models were performed to test the hypothesis that biomarkers for AD, neurodegeneration, and inflammation, or two-year change in those biomarkers, would be associated with worse white matter health overall and/or progressively worsening white matter health over time. At baseline in the cingulum, phosphorylated-tau/Aβ42 was associated with higher mean diffusivity (MD) overall (intercept) and YKL-40 was associated with increases in MD over time. Two-year change in neurogranin was associated with higher mean diffusivity and lower fractional anisotropy overall (intercepts) across white matter in the entire brain and in the cingulum. These findings suggest that biomarkers for AD, neurodegeneration, and inflammation are potentially important indicators of declining white matter health in a cognitively healthy, late-middle-aged cohort.
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Affiliation(s)
- Annie M Racine
- Neuroscience and Public Policy Program, University of Wisconsin, Madison, WI, USA
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
| | - Andrew P Merluzzi
- Neuroscience and Public Policy Program, University of Wisconsin, Madison, WI, USA
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Derek Norton
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, 53792, USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
| | - Lindsay R Clark
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Sara E Berman
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
| | - Christopher R Nicholas
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Sanjay Asthana
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Andrew L Alexander
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53719, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neurology, University College London, London, UK
| | - Won Hwa Kim
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, 53792, USA
- Department of Computer Sciences, University of Wisconsin - Madison, Madison, WI, 53706, USA
| | - Vikas Singh
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, 53792, USA
- Department of Computer Sciences, University of Wisconsin - Madison, Madison, WI, 53706, USA
| | - Cynthia M Carlsson
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Barbara B Bendlin
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA
| | - Sterling C Johnson
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA.
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53705, USA.
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA.
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71
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Tsai RM, Bejanin A, Lesman-Segev O, LaJoie R, Visani A, Bourakova V, O’Neil JP, Janabi M, Baker S, Lee SE, Perry DC, Bajorek L, Karydas A, Spina S, Grinberg LT, Seeley WW, Ramos EM, Coppola G, Gorno-Tempini ML, Miller BL, Rosen HJ, Jagust W, Boxer AL, Rabinovici GD. 18F-flortaucipir (AV-1451) tau PET in frontotemporal dementia syndromes. Alzheimers Res Ther 2019; 11:13. [PMID: 30704514 PMCID: PMC6357510 DOI: 10.1186/s13195-019-0470-7] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 01/17/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND The tau positron emission tomography (PET) ligand 18F-flortaucipir binds to paired helical filaments of tau in aging and Alzheimer's disease (AD), but its utility in detecting tau aggregates in frontotemporal dementia (FTD) is uncertain. METHODS We performed 18F-flortaucipir imaging in patients with the FTD syndromes (n = 45): nonfluent variant primary progressive aphasia (nfvPPA) (n = 11), corticobasal syndrome (CBS) (n = 10), behavioral variant frontotemporal dementia (bvFTD) (n = 10), semantic variant primary progressive aphasia (svPPA) (n = 2) and FTD associated pathogenic genetic mutations microtubule-associated protein tau (MAPT) (n = 6), chromosome 9 open reading frame 72 (C9ORF72) (n = 5), and progranulin (GRN) (n = 1). All patients underwent MRI and β-amyloid biomarker testing via 11C-PiB or cerebrospinal fluid. 18F-flortaucipir uptake in patients was compared to 53 β-amyloid negative normal controls using voxelwise and pre-specified region of interest approaches. RESULTS On qualitative assessment, patients with nfvPPA showed elevated 18F-flortacupir binding in the left greater than right inferior frontal gyrus. Patients with CBS showed elevated binding in frontal white matter, with higher cortical gray matter uptake in a subset of β-amyloid-positive patients. Five of ten patients with sporadic bvFTD demonstrated increased frontotemporal binding. MAPT mutation carriers had elevated 18F-flortaucipir retention primarily, but not exclusively, in mutations with Alzheimer's-like neurofibrillary tangles. However, tracer retention was also seen in patients with svPPA, and the mutations C9ORF72, GRN predicted to have TDP-43 pathology. Quantitative region-of-interest differences between patients and controls were seen only in inferior frontal gyrus in nfvPPA and left insula and bilateral temporal poles in MAPT carriers. No significant regional differences were found in CBS or sporadic bvFTD. Two patients underwent postmortem neuropathological examination. A patient with C9ORF72, TDP-43-type B pathology, and incidental co-pathology of scattered neurofibrillary tangles in the middle frontal, inferior temporal gyrus showed corresponding mild 18F-flortaucipir retention without additional uptake matching the widespread TDP-43 type B pathology. A patient with sporadic bvFTD demonstrated punctate inferior temporal and hippocampus tracer retention, corresponding to the area of severe argyrophilic grain disease pathology. CONCLUSIONS 18F-flortaucipir in patients with FTD and predicted tauopathy or TDP-43 pathology demonstrated limited sensitivity and specificity. Further postmortem pathological confirmation and development of FTD tau-specific ligands are needed.
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Affiliation(s)
- Richard M. Tsai
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Alexandre Bejanin
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Orit Lesman-Segev
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Renaud LaJoie
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Adrienne Visani
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Viktoriya Bourakova
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - James P. O’Neil
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Mustafa Janabi
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Suzanne Baker
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Suzee E. Lee
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - David C. Perry
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Lynn Bajorek
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Anna Karydas
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Salvatore Spina
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Lea T. Grinberg
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - William W. Seeley
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Eliana M. Ramos
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Giovanni Coppola
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Bruce L. Miller
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Howard J. Rosen
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Adam L. Boxer
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Gil D. Rabinovici
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
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72
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Aging, neurocognitive reserve, and the healthy brain. PSYCHOLOGY OF LEARNING AND MOTIVATION 2019. [DOI: 10.1016/bs.plm.2019.07.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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73
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Zhang Y, Liu S. Analysis of structural brain MRI and multi-parameter classification for Alzheimer's disease. ACTA ACUST UNITED AC 2018. [PMID: 28622141 DOI: 10.1515/bmt-2016-0239] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Incorporating with machine learning technology, neuroimaging markers which extracted from structural Magnetic Resonance Images (sMRI), can help distinguish Alzheimer's Disease (AD) patients from Healthy Controls (HC). In the present study, we aim to investigate differences in atrophic regions between HC and AD and apply machine learning methods to classify these two groups. T1-weighted sMRI scans of 158 patients with AD and 145 age-matched HC were acquired from the ADNI database. Five kinds of parameters (i.e. cortical thickness, surface area, gray matter volume, curvature and sulcal depth) were obtained through the preprocessing steps. The recursive feature elimination (RFE) method for support vector machine (SVM) and leave-one-out cross validation (LOOCV) were applied to determine the optimal feature dimensions. Each kind of parameter was trained by SVM algorithm to acquire a classifier, which was used to classify HC and AD ultimately. Moreover, the ROC curves were depicted for testing the classifiers' performance and the SVM classifiers of two-dimensional spaces took the top two important features as classification features for separating HC and AD to the maximum extent. The results showed that the decreased cortical thickness and gray matter volume dramatically exhibited the trend of atrophy. The key differences between AD and HC existed in the cortical thickness and gray matter volume of the entorhinal cortex and medial orbitofrontal cortex. In terms of classification results, an optimal accuracy of 90.76% was obtained via multi-parameter combination (i.e. cortical thickness, gray matter volume and surface area). Meanwhile, the receiver operating characteristic (ROC) curves and area under the curve (AUC) were also verified multi-parameter combination could reach a better classification performance (AUC=0.94) after the SVM-RFE method. The results could be well prove that multi-parameter combination could provide more useful classified features from multivariate anatomical structure than single parameter. In addition, as cortical thickness and multi-parameter combination contained more important classified information with fewer feature dimensions after feature selection, it could be optimum to separate HC from AD to take the top two important features of them to construct SVM classifiers in two-dimensional space. The proposed work is a promising approach suggesting an important role for machine-learning based diagnostic image analysis for clinical practice.
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Affiliation(s)
- Yingteng Zhang
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
| | - Shenquan Liu
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
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74
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Kim WH, Racine AM, Adluru N, Hwang SJ, Blennow K, Zetterberg H, Carlsson CM, Asthana S, Koscik RL, Johnson SC, Bendlin BB, Singh V. Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis. Neuroimage Clin 2018; 21:101586. [PMID: 30502079 PMCID: PMC6411581 DOI: 10.1016/j.nicl.2018.10.024] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 10/10/2018] [Accepted: 10/21/2018] [Indexed: 11/24/2022]
Abstract
In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia.
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Affiliation(s)
- Won Hwa Kim
- Department of Computer Sciences and Engineering, University of Texas, Arlington, TX, U.S.A.; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
| | - Annie M Racine
- Institute for Aging Research, Harvard Medical School, Boston, MA, U.S.A.; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin - Madison, Madison, WI, USA
| | - Seong Jae Hwang
- Department of Computer Science, University of Wisconsin - Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, London, UK
| | - Cynthia M Carlsson
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sanjay Asthana
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Institute on Aging, University of Wisconsin - Madison, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Barbara B Bendlin
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Vikas Singh
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, USA; Department of Computer Science, University of Wisconsin - Madison, Madison, WI, USA
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75
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The Lifespan Human Connectome Project in Aging: An overview. Neuroimage 2018; 185:335-348. [PMID: 30332613 DOI: 10.1016/j.neuroimage.2018.10.009] [Citation(s) in RCA: 168] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 09/21/2018] [Accepted: 10/04/2018] [Indexed: 12/31/2022] Open
Abstract
The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).
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76
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Ocklenburg S, Anderson C, Gerding WM, Fraenz C, Schlüter C, Friedrich P, Raane M, Mädler B, Schlaffke L, Arning L, Epplen JT, Güntürkün O, Beste C, Genç E. Myelin Water Fraction Imaging Reveals Hemispheric Asymmetries in Human White Matter That Are Associated with Genetic Variation in PLP1. Mol Neurobiol 2018; 56:3999-4012. [PMID: 30242727 DOI: 10.1007/s12035-018-1351-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 09/13/2018] [Indexed: 12/18/2022]
Abstract
Myelination of axons in the central nervous system is critical for human cognition and behavior. The predominant protein in myelin is proteolipid protein-making PLP1, the gene that encodes for proteolipid protein, one of the primary candidate genes for white matter structure in the human brain. Here, we investigated the relation of genetic variation within PLP1 and white matter microstructure as assessed with myelin water fraction imaging, a neuroimaging technique that has the advantage over conventional diffusion tensor imaging in that it allows for a more direct assessment of myelin content. We observed significant asymmetries in myelin water fraction that were strongest and rightward in the parietal lobe. Importantly, these parietal myelin water fraction asymmetries were associated with genetic variation in PLP1. These findings support the assumption that genetic variation in PLP1 affects white matter myelination in the healthy human brain.
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Affiliation(s)
- Sebastian Ocklenburg
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany.
| | - Catrona Anderson
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany.,Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Wanda M Gerding
- Department of Human Genetics, Ruhr University Bochum, Bochum, Germany
| | - Christoph Fraenz
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Caroline Schlüter
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Patrick Friedrich
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Maximilian Raane
- Faculty of Health, ZBAF, University of Witten/Herdecke, Witten, Germany
| | | | - Lara Schlaffke
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Larissa Arning
- Department of Human Genetics, Ruhr University Bochum, Bochum, Germany
| | - Jörg T Epplen
- Department of Human Genetics, Ruhr University Bochum, Bochum, Germany.,Faculty of Health, ZBAF, University of Witten/Herdecke, Witten, Germany
| | - Onur Güntürkün
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Erhan Genç
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr University Bochum, Bochum, Germany
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Harrison TM, Maass A, Baker SL, Jagust WJ. Brain morphology, cognition, and β-amyloid in older adults with superior memory performance. Neurobiol Aging 2018; 67:162-170. [PMID: 29665578 PMCID: PMC5955827 DOI: 10.1016/j.neurobiolaging.2018.03.024] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 02/22/2018] [Accepted: 03/21/2018] [Indexed: 02/04/2023]
Abstract
The mechanisms underlying superior cognitive performance in some older adults are poorly understood. We used a multimodal approach to characterize imaging and cognitive features of 26 successful agers (SA; defined by superior episodic memory ability) and 103 typical older adults. Cortical thickness was greater in multiple regions in SA including right anterior cingulate and prefrontal cortex and was related to baseline memory performance. Similarly, hippocampal volume was greater in SA and associated with baseline memory. SA also had lower white matter hypointensity volumes and faster processing speed. While PiB burden did not differ, there was a significant group interaction in the relationship between age and PiB such that older SA individuals were less likely to have high brain β-amyloid. Over time, memory performance in typical older adults declined more rapidly than in SA, although there was limited evidence for different rates of brain atrophy. These findings indicate that superior memory in aging is related to greater cortical and white matter integrity as well as slower decline in memory performance.
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Affiliation(s)
| | - Anne Maass
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA; German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | | | - William J Jagust
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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78
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Temporal lobe epilepsy lateralization using retrospective cerebral blood volume MRI. NEUROIMAGE-CLINICAL 2018; 19:911-917. [PMID: 30003028 PMCID: PMC6039834 DOI: 10.1016/j.nicl.2018.05.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 04/27/2018] [Accepted: 05/09/2018] [Indexed: 11/22/2022]
Abstract
Steady-state cerebral blood volume (CBV) is tightly coupled to regional cerebral metabolism, and CBV imaging is a variant of MRI that has proven useful in mapping brain dysfunction. CBV derived from exogenous contrast-enhanced MRI can generate sub-millimeter functional maps. Higher resolution helps to more accurately interrogate smaller cortical regions, such as functionally distinct regions of the hippocampus. Many MRIs have fortuitously adequate sequences required for CBV mapping. However, these scans vary substantially in acquisition parameters. Here, we determined whether previously acquired contrast-enhanced MRI scans ordered in patients with unilateral temporal lobe epilepsy can be used to generate hippocampal CBV. We used intrinsic reference regions to correct for intensity scaling on a research CBV dataset to identify white matter as a robust marker for scaling correction. Next, we tested the technique on a sample of unilateral focal epilepsy patients using clinical MRI scans. We find evidence suggestive of significant hypometabolism in the ipsilateral-hippocampus of unilateral TLE subjects. We also highlight the subiculum as a potential driver of this effect. This study introduces a technique that allows CBV maps to be generated retrospectively from clinical scans, potentially with broad application for mapping dysfunction throughout the brain. Clinically obtained structural MRI parameters overlap with contrast enhanced CBV MRI. Intensity differences can be corrected using white matter signal. CBV in unilateral TLE suggest metabolic but not structural ipsilateral changes. Subiculum implicated as potential driver of unilateral TLE metabolic deficit. Functional metrics can be potentially extracted from millions of clinical brain MRIs.
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79
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Rivas-Grajales AM, Sawyer KS, Karmacharya S, Papadimitriou G, Camprodon JA, Harris GJ, Kubicki M, Oscar-Berman M, Makris N. Sexually dimorphic structural abnormalities in major connections of the medial forebrain bundle in alcoholism. Neuroimage Clin 2018; 19:98-105. [PMID: 30035007 PMCID: PMC6051309 DOI: 10.1016/j.nicl.2018.03.025] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2017] [Revised: 01/24/2018] [Accepted: 03/21/2018] [Indexed: 12/22/2022]
Abstract
Background The mesocorticolimbic system is particularly susceptible to the effects of chronic alcoholism. Disruption of this system has been linked to drug seeking and the development of Reward Deficiency Syndrome, a neurobiological framework for describing the development and relapsing patterns of addictions. In this study, we evaluated the association of alcoholism and sex with major connections of the medial forebrain bundle (MFB), a prominent mesocorticolimbic fiber pathway connecting the ventral tegmental area with the basal forebrain. Given sex differences in clinical consequences of alcohol consumption, we hypothesized that alcoholic men and women would differ in structural abnormalities of the MFB. Methods Diffusion magnetic resonance imaging (dMRI) data were acquired from 30 abstinent long-term alcoholic individuals (ALC; 9 men) and 25 non-alcoholic controls (NC; 8 men). Major connections of the MFB were extracted using multi-tensor tractography. We compared groups on MFB volume, fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD), with hemisphere and sex as independent variables. We also evaluated associations between abnormal structural measures and drinking measures. Results Analyses revealed significant group-by-sex interactions for FA and RD: while ALC men had lower FA and higher RD compared to NC men, ALC women had higher FA and lower RD compared to NC women. We also detected a significant negative association between FA and number of daily drinks in ALC women. Conclusion Alcoholism is associated with sexually dimorphic structural abnormalities in the MFB. The results expand upon other findings of differences in brain reward circuitry of alcoholic men and women.
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Affiliation(s)
- Ana María Rivas-Grajales
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Kayle S Sawyer
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Sawyer Scientific, LLC, Boston, MA, USA
| | - Sarina Karmacharya
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - George Papadimitriou
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, USA
| | - Joan A Camprodon
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Gordon J Harris
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, USA; Radiology Computer Aided Diagnostics Laboratory, Massachusetts General Hospital, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, USA
| | - Marlene Oscar-Berman
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Nikos Makris
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, USA.
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80
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Cho H, Seo SW, Choi JY, Lee HS, Ryu YH, Lee MS, Na DL, Kim HJ, Lyoo CH. Predominant subcortical accumulation of 18F-flortaucipir binding in behavioral variant frontotemporal dementia. Neurobiol Aging 2018; 66:112-121. [PMID: 29554554 DOI: 10.1016/j.neurobiolaging.2018.02.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 02/13/2018] [Accepted: 02/15/2018] [Indexed: 11/28/2022]
Abstract
Behavioral variant frontotemporal dementia (bvFTD) is the most common form of frontotemporal dementia, and tau pathology can be found in 40%-50% of bvFTD patients. In this study, we sought to investigate 18F-flortaucipir-binding patterns and their correlates in clinically diagnosed bvFTD patients by comparing with results for Alzheimer's disease (AD) patients. We enrolled 20 bvFTD, 20 AD, and 20 age-matched healthy subjects who underwent neuropsychological tests, magnetic resonance imaging, and tau positron emission tomography scans with 18F-flortaucipir. Regional standardized uptake value ratios for the cerebral cortex and underlying white matter were compared between the 2 groups. The bvFTD patients showed increased 18F-flortaucipir binding in the putamen and globus pallidus when compared to the healthy controls. In addition, bvFTD was associated with increased binding in the white matter regions underlying the frontal, anterior cingulate, and insula cortices. The bvFTD patients may exhibit predominantly subcortical 18F-flortaucipir-binding pattern that is distinct from the patterns seen in AD patients. We hypothesize that the clinical characteristics of bvFTD patients may be attributable to the dysfunctional frontal-subcortical networks. However, concerns remain regarding unknown "off-target" binding in the white matter and the basal ganglia.
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Affiliation(s)
- Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sang Won Seo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jae Yong Choi
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea; Division of RI-Convergence Research, Korea Institute Radiological and Medical Sciences, Seoul, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Myung Sik Lee
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Duk L Na
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hee Jin Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
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81
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Fazlollahi A, Ayton S, Bourgeat P, Diouf I, Raniga P, Fripp J, Doecke J, Ames D, Masters CL, Rowe CC, Villemagne VL, Bush AI, Salvado O. A Framework to Objectively Identify Reference Regions for Normalizing Quantitative Imaging. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2018 2018. [DOI: 10.1007/978-3-030-00928-1_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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82
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Cross-sectional variations of white and grey matter in older hypertensive patients with subjective memory complaints. NEUROIMAGE-CLINICAL 2017; 17:804-810. [PMID: 29276677 PMCID: PMC5738235 DOI: 10.1016/j.nicl.2017.12.024] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 11/23/2017] [Accepted: 12/16/2017] [Indexed: 11/24/2022]
Abstract
Mild cognitive impairment and Alzheimer's dementia involve a grey matter disease, quantifiable by 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET), but also white matter damage, evidenced by diffusion tensor magnetic resonance imaging (DTI), which may play an additional pathogenic role. This study aimed to determine whether such DTI and PET variations are also interrelated in a high-risk population of older hypertensive patients with only subjective memory complaints (SMC). Sixty older hypertensive patients (75 ± 5 years) with SMC were referred to DTI and FDG-PET brain imaging, executive and memory tests, as well as peripheral and central blood pressure (BP) measurements. Mean apparent diffusion coefficient (ADCmean) was determined in overall white matter and correlated with the grey matter distribution of the metabolic rate of glucose (CMRGlc) using whole-brain voxel-based analyses of FDG-PET images. ADCmean was variable between individuals, ranging from 0.82 to 1.01.10− 3 mm2 sec− 1, and mainly in relation with CMRGlc of areas involved in Alzheimer's disease such as internal temporal areas, posterior associative junctions, posterior cingulum but also insulo-opercular areas (global correlation coefficient: − 0.577, p < 0.001). Both the ADCmean and CMRGlc of the interrelated grey matter areas were additionally and concordantly linked to the results of executive and memory tests and to systolic central BP (all p < 0.05). Altogether, our findings show that cross-sectional variations in overall white brain matter are linked to the metabolism of Alzheimer-like cortical areas and to cognitive performance in older hypertensive patients with only subjective memory complaints. Additional relationships with central BP strengthen the hypothesis of a contributing pathogenic role of hypertension. Changes in grey and white matter are interrelated in elderly hypertensive patients. They can be documented in the absence of any objective memory complaint. These interrelationships are associated with cognitive test results. The interrelated grey matter areas are likely to define an Alzheimer-like pattern. These interrelationships are linked to the level of central blood pressure.
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83
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Carey D, Caprini F, Allen M, Lutti A, Weiskopf N, Rees G, Callaghan MF, Dick F. Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure. Neuroimage 2017; 182:429-440. [PMID: 29203455 PMCID: PMC6189523 DOI: 10.1016/j.neuroimage.2017.11.066] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 10/19/2017] [Accepted: 11/29/2017] [Indexed: 12/17/2022] Open
Abstract
Measuring the structural composition of the cortex is critical to understanding typical development, yet few investigations in humans have charted markers in vivo that are sensitive to tissue microstructural attributes. Here, we used a well-validated quantitative MR protocol to measure four parameters (R1, MT, R2*, PD*) that differ in their sensitivity to facets of the tissue microstructural environment (R1, MT: myelin, macromolecular content; R2*: myelin, paramagnetic ions, i.e., iron; PD*: free water content). Mapping these parameters across cortical regions in a young adult cohort (18–39 years, N = 93) revealed expected patterns of increased macromolecular content as well as reduced tissue water content in primary and primary adjacent cortical regions. Mapping across cortical depth within regions showed decreased expression of myelin and related processes – but increased tissue water content – when progressing from the grey/white to the grey/pial boundary, in all regions. Charting developmental change in cortical microstructure cross-sectionally, we found that parameters with sensitivity to tissue myelin (R1 & MT) showed linear increases with age across frontal and parietal cortex (change 0.5–1.0% per year). Overlap of robust age effects for both parameters emerged in left inferior frontal, right parietal and bilateral pre-central regions. Our findings afford an improved understanding of ontogeny in early adulthood and offer normative quantitative MR data for inter- and intra-cortical composition, which may be used as benchmarks in further studies. We mapped multi-parameter maps (MPMs) across and within cortical regions. We charted age effects (ages 18–39) on myelin and related processes. MPMs sensitive to myelin (R1, MT) showed elevated values in primary areas over most cortical depths. R2* map foci tended to overlap MPMs sensitive to myelin (R1, MT). R1 and MT increased with age (0.5–1.0% per year) at mid-depth in frontal and parietal cortex.
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Affiliation(s)
- Daniel Carey
- The Irish Longitudinal Study on Aging (TILDA), Trinity College Dublin, Dublin 2, Ireland; Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK.
| | - Francesco Caprini
- Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK
| | - Micah Allen
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London, UK
| | - Antoine Lutti
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Laboratoire de Recherche en Neuroimagerie - LREN, Departement des Neurosciences Cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Nikolaus Weiskopf
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Geraint Rees
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London, UK
| | - Martina F Callaghan
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK
| | - Frederic Dick
- Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK; Birkbeck/UCL Centre for Neuroimaging (BUCNI), 26 Bedford Way, London, UK
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84
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McKenzie AT, Moyon S, Wang M, Katsyv I, Song WM, Zhou X, Dammer EB, Duong DM, Aaker J, Zhao Y, Beckmann N, Wang P, Zhu J, Lah JJ, Seyfried NT, Levey AI, Katsel P, Haroutunian V, Schadt EE, Popko B, Casaccia P, Zhang B. Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer's disease. Mol Neurodegener 2017; 12:82. [PMID: 29110684 PMCID: PMC5674813 DOI: 10.1186/s13024-017-0219-3] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 10/17/2017] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Oligodendrocytes (OLs) and myelin are critical for normal brain function and have been implicated in neurodegeneration. Several lines of evidence including neuroimaging and neuropathological data suggest that Alzheimer's disease (AD) may be associated with dysmyelination and a breakdown of OL-axon communication. METHODS In order to understand this phenomenon on a molecular level, we systematically interrogated OL-enriched gene networks constructed from large-scale genomic, transcriptomic and proteomic data obtained from human AD postmortem brain samples. We then validated these networks using gene expression datasets generated from mice with ablation of major gene expression nodes identified in our AD-dysregulated networks. RESULTS The robust OL gene coexpression networks that we identified were highly enriched for genes associated with AD risk variants, such as BIN1 and demonstrated strong dysregulation in AD. We further corroborated the structure of the corresponding gene causal networks using datasets generated from the brain of mice with ablation of key network drivers, such as UGT8, CNP and PLP1, which were identified from human AD brain data. Further, we found that mice with genetic ablations of Cnp mimicked aspects of myelin and mitochondrial gene expression dysregulation seen in brain samples from patients with AD, including decreased protein expression of BIN1 and GOT2. CONCLUSIONS This study provides a molecular blueprint of the dysregulation of gene expression networks of OL in AD and identifies key OL- and myelination-related genes and networks that are highly associated with AD.
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Affiliation(s)
- Andrew T. McKenzie
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Sarah Moyon
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Neuroscience Initiative, The City University of New York, Advanced Science Research Center, 85 St. Nicholas Terrace, New York, NY 10031 USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Igor Katsyv
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Won-Min Song
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Xianxiao Zhou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Eric B. Dammer
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322 USA
| | - Duc M. Duong
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322 USA
- Integrated Proteomics Core Facility, Emory University School of Medicine, Atlanta, GA 30322 USA
| | - Joshua Aaker
- Department of Neurology, The University of Chicago Pritzker School of Medicine, 5841 S. Maryland Avenue, Chicago, IL 60637 USA
| | - Yongzhong Zhao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Noam Beckmann
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Jun Zhu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - James J. Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322 USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322 USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322 USA
- Integrated Proteomics Core Facility, Emory University School of Medicine, Atlanta, GA 30322 USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322 USA
| | - Allan I. Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322 USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322 USA
| | - Pavel Katsel
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
| | - Vahram Haroutunian
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
- Mental Illness Research, Education, and Clinical Center (VISN 3), James J. Peters VA Medical Center, Bronx, NY 10468 USA
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Brian Popko
- Department of Neurology, The University of Chicago Pritzker School of Medicine, 5841 S. Maryland Avenue, Chicago, IL 60637 USA
| | - Patrizia Casaccia
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
- Neuroscience Initiative, The City University of New York, Advanced Science Research Center, 85 St. Nicholas Terrace, New York, NY 10031 USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1470 Madison Avenue, Room S8-111, New York, NY 10029 USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
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85
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Ayton S, Fazlollahi A, Bourgeat P, Raniga P, Ng A, Lim YY, Diouf I, Farquharson S, Fripp J, Ames D, Doecke J, Desmond P, Ordidge R, Masters CL, Rowe CC, Maruff P, Villemagne VL, Salvado O, Bush AI. Cerebral quantitative susceptibility mapping predicts amyloid-β-related cognitive decline. Brain 2017; 140:2112-2119. [PMID: 28899019 DOI: 10.1093/brain/awx137] [Citation(s) in RCA: 188] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Accepted: 05/07/2017] [Indexed: 11/14/2022] Open
Abstract
See Derry and Kent (doi:10.1093/awx167) for a scientific commentary on this article.The large variance in cognitive deterioration in subjects who test positive for amyloid-β by positron emission tomography indicates that convergent pathologies, such as iron accumulation, might combine with amyloid-β to accelerate Alzheimer's disease progression. Here, we applied quantitative susceptibility mapping, a relatively new magnetic resonance imaging method sensitive to tissue iron, to assess the relationship between iron, amyloid-β load, and cognitive decline in 117 subjects who underwent baseline magnetic resonance imaging and amyloid-β positron emission tomography from the Australian Imaging, Biomarkers and Lifestyle study (AIBL). Cognitive function data were collected every 18 months for up to 6 years from 100 volunteers who were either cognitively normal (n = 64) or diagnosed with mild cognitive impairment (n = 17) or Alzheimer's disease (n = 19). Among participants with amyloid pathology (n = 45), higher hippocampal quantitative susceptibility mapping levels predicted accelerated deterioration in composite cognition tests for episodic memory [β(standard error) = -0.169 (0.034), P = 9.2 × 10-7], executive function [β(standard error) = -0.139 (0.048), P = 0.004), and attention [β(standard error) = -0.074 (0.029), P = 0.012]. Deteriorating performance in a composite of language tests was predicted by higher quantitative susceptibility mapping levels in temporal lobe [β(standard error) = -0.104 (0.05), P = 0.036] and frontal lobe [β(standard error) = -0.154 (0.055), P = 0.006]. These findings indicate that brain iron might combine with amyloid-β to accelerate clinical progression and that quantitative susceptibility mapping could be used in combination with amyloid-β positron emission tomography to stratify individuals at risk of decline.
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Affiliation(s)
- Scott Ayton
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Amir Fazlollahi
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Pierrick Bourgeat
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Parnesh Raniga
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Amanda Ng
- Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Yen Ying Lim
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Ibrahima Diouf
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Shawna Farquharson
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia.,University of Melbourne Academic Unit for the Psychiatry of Old Age, Parkville, Australia
| | - James Doecke
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Patricia Desmond
- Department of Medicine and Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
| | - Roger Ordidge
- Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Christopher C Rowe
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Austin Health, Heidelberg, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cogstate Ltd, Melbourne, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Austin Health, Heidelberg, Australia
| | | | - Olivier Salvado
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Ashley I Bush
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
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86
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Abstract
BACKGROUND Deterministic diffusion tractography obtained from high angular resolution diffusion imaging (HARDI) requires user-defined quantitative anisotropy (QA) thresholds. Most studies employ a common threshold across all subjects even though there is a strong degree of individual variation within groups. We sought to explore whether it would be beneficial to use individual thresholds in order to accommodate individual variance. To do this, we conducted two independent experiments. METHOD First, tractography of the arcuate fasciculus and network connectivity measures were examined in a sample of 14 healthy participants. Second, we assessed the effects of QA threshold on group differences in network connectivity measures between healthy young (n=19) and old (n=14) individuals. RESULTS The results of both experiments were significantly influenced by QA threshold. Common thresholds set too high failed to produce sufficient reconstructions in most subjects, thus decreasing the likelihood of detecting meaningful group differences. On the other hand, common thresholds set too low resulted in spurious reconstructions, providing deleterious results. COMPARISON WITH EXISTING METHODS Subject specific thresholds acquired using our QA threshold selection method (QATS) appeared to provide the most meaningful networks while ensuring that data from all subjects contributed to the analyses. CONCLUSIONS Together, these results support the use of a subject-specific threshold to ensure that data from all subjects are included in the analyses being conducted.
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87
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Girard G, Daducci A, Petit L, Thiran JP, Whittingstall K, Deriche R, Wassermann D, Descoteaux M. AxTract: Toward microstructure informed tractography. Hum Brain Mapp 2017; 38:5485-5500. [PMID: 28766853 DOI: 10.1002/hbm.23741] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 07/13/2017] [Accepted: 07/13/2017] [Indexed: 12/13/2022] Open
Abstract
Diffusion-weighted (DW) magnetic resonance imaging (MRI) tractography has become the tool of choice to probe the human brain's white matter in vivo. However, tractography algorithms produce a large number of erroneous streamlines (false positives), largely due to complex ambiguous tissue configurations. Moreover, the relationship between the resulting streamlines and the underlying white matter microstructure characteristics remains poorly understood. In this work, we introduce a new approach to simultaneously reconstruct white matter fascicles and characterize the apparent distribution of axon diameters within fascicles. To achieve this, our method, AxTract, takes full advantage of the recent development DW-MRI microstructure acquisition, modeling, and reconstruction techniques. This enables AxTract to separate parallel fascicles with different microstructure characteristics, hence reducing ambiguities in areas of complex tissue configuration. We report a decrease in the incidence of erroneous streamlines compared to the conventional deterministic tractography algorithms on simulated data. We also report an average increase in streamline density over 15 known fascicles of the 34 healthy subjects. Our results suggest that microstructure information improves tractography in crossing areas of the white matter. Moreover, AxTract provides additional microstructure information along the fascicle that can be studied alongside other streamline-based indices. Overall, AxTract provides the means to distinguish and follow white matter fascicles using their microstructure characteristics, bringing new insights into the white matter organization. This is a step forward in microstructure informed tractography, paving the way to a new generation of algorithms able to deal with intricate configurations of white matter fibers and providing quantitative brain connectivity analysis. Hum Brain Mapp 38:5485-5500, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Gabriel Girard
- Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada.,Project Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France.,Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Alessandro Daducci
- Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Computer Science Department, University of Verona, Verona, Italy.,Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Laurent Petit
- Groupe d'Imagie Neurofonctionnelle, Institut des Maladies Neurodégénératives - UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Jean-Philippe Thiran
- Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Kevin Whittingstall
- Department of Diagnostic Radiology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, Canada.,Sherbrooke Molecular Imaging Center (CIMS), Centre de Recherche CHUS (CR-CHUS), Sherbrooke, Canada
| | - Rachid Deriche
- Project Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France
| | - Demian Wassermann
- Project Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada.,Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Sherbrooke Molecular Imaging Center (CIMS), Centre de Recherche CHUS (CR-CHUS), Sherbrooke, Canada
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88
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Nenert R, Allendorfer JB, Martin AM, Banks C, Ball A, Vannest J, Dietz AR, Szaflarski JP. Neuroimaging Correlates of Post-Stroke Aphasia Rehabilitation in a Pilot Randomized Trial of Constraint-Induced Aphasia Therapy. Med Sci Monit 2017; 23:3489-3507. [PMID: 28719572 PMCID: PMC5529460 DOI: 10.12659/msm.902301] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Background Recovery from post-stroke aphasia is a long and complex process with an uncertain outcome. Various interventions have been proposed to augment the recovery, including constraint-induced aphasia therapy (CIAT). CIAT has been applied to patients suffering from post-stroke aphasia in several unblinded studies to show mild-to-moderate linguistic gains. The aim of the present study was to evaluate the neuroimaging correlates of CIAT in patients with chronic aphasia related to left middle cerebral artery stroke. Material/Methods Out of 24 patients recruited in a pilot randomized blinded trial of CIAT, 19 patients received fMRI of language. Eleven of them received CIAT (trained) and eight served as a control group (untrained). Each patient participated in three fMRI sessions (before training, after training, and 3 months later) that included semantic decision and verb generation fMRI tasks, and a battery of language tests. Matching healthy control participants were also included (N=38; matching based on age, handedness, and sex). Results Language testing showed significantly improved performance on Boston Naming Test (BNT; p<0.001) in both stroke groups over time and fMRI showed differences in the distribution of the areas involved in language production between groups that were not present at baseline. Further, regression analysis with BNT indicated changes in brain regions correlated with behavioral performance (temporal gyrus, postcentral gyrus, precentral gyrus, thalamus, left middle and superior frontal gyri). Conclusions Overall, our results suggest the possibility of language-related cortical plasticity following stroke-induced aphasia with no specific effect from CIAT training.
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Affiliation(s)
- Rodolphe Nenert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jane B Allendorfer
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Amber M Martin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Christi Banks
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Jennifer Vannest
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Jerzy P Szaflarski
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurology, University of Cincinnati Academic Health Center, Cincinnati, OH, USA
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89
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Schiffler P, Tenberge JG, Wiendl H, Meuth SG. Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects. Front Hum Neurosci 2017; 11:352. [PMID: 28729829 PMCID: PMC5498510 DOI: 10.3389/fnhum.2017.00352] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 06/20/2017] [Indexed: 11/13/2022] Open
Abstract
The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.
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Affiliation(s)
- Patrick Schiffler
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Jan-Gerd Tenberge
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Heinz Wiendl
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Sven G Meuth
- Department of Neurology, University Hospital MünsterMünster, Germany
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90
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Wang J, Guo X, Zhuang X, Chen T, Yan W. Disrupted pursuit compensation during self-motion perception in early Alzheimer's disease. Sci Rep 2017. [PMID: 28642572 PMCID: PMC5481347 DOI: 10.1038/s41598-017-04377-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Our perception of the world is remarkably stable despite of distorted retinal input due to frequent eye movements. It is considered that the brain uses corollary discharge, efference copies of signals sent from motor to visual regions, to compensate for distortions and stabilize visual perception. In this study, we tested whether patients with Alzheimer’s disease (AD) have impaired corollary discharge functions as evidenced by reduced compensation during the perception of optic flow that mimics self-motion in the environment. We asked a group of early-stage AD patients and age-matched healthy controls to indicate the perceived direction of self-motion based on optic flow while tracking a moving target with smooth pursuit eye movement, or keeping eye fixation at a stationary target. We first replicated the previous findings that healthy participants were able to compensate for distorted optic flow in the presence of eye movements, as indicated by similar performance of self-motion perception between pursuit and fixation conditions. In stark contrast, AD patients showed impaired self-motion perception when the optic flow was distorted by eye movements. Our results suggest that early-stage AD pathology is associated with disrupted eye movement compensation during self-motion perception.
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Affiliation(s)
- Jingru Wang
- Department of Neurology, Liaocheng People's Hospital and Liaocheng Clinical School of Taishan Medical University, Liaocheng city, Shandong Province, 252000, China
| | - Xiaojun Guo
- Department of Neurology, Liaocheng People's Hospital and Liaocheng Clinical School of Taishan Medical University, Liaocheng city, Shandong Province, 252000, China
| | - Xianbo Zhuang
- Department of Neurology, Liaocheng People's Hospital and Liaocheng Clinical School of Taishan Medical University, Liaocheng city, Shandong Province, 252000, China
| | - Tuanzhi Chen
- Department of Neurology, Liaocheng People's Hospital and Liaocheng Clinical School of Taishan Medical University, Liaocheng city, Shandong Province, 252000, China
| | - Wei Yan
- Department of Neurology, Liaocheng People's Hospital and Liaocheng Clinical School of Taishan Medical University, Liaocheng city, Shandong Province, 252000, China.
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91
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Delaparte L, Yeh FC, Adams P, Malchow A, Trivedi MH, Oquendo MA, Deckersbach T, Ogden T, Pizzagalli DA, Fava M, Cooper C, McInnis M, Kurian BT, Weissman MM, McGrath PJ, Klein DN, Parsey RV, DeLorenzo C. A comparison of structural connectivity in anxious depression versus non-anxious depression. J Psychiatr Res 2017; 89:38-47. [PMID: 28157545 PMCID: PMC5374003 DOI: 10.1016/j.jpsychires.2017.01.012] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Revised: 12/16/2016] [Accepted: 01/19/2017] [Indexed: 12/13/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) and anxiety disorders are highly co-morbid. Research has shown conflicting evidence for white matter alteration and amygdala volume reduction in mood and anxiety disorders. To date, no studies have examined differences in structural connectivity between anxious depressed and non-anxious depressed individuals. This study compared fractional anisotropy (FA) and density of selected white matter tracts and amygdala volume between anxious depressed and non-anxious depressed individuals. METHODS 64- direction DTI and T1 scans were collected from 110 unmedicated subjects with MDD, 39 of whom had a co-morbid anxiety disorder diagnosis. Region of interest (ROI) and tractography methods were performed to calculate amygdala volume and FA in the uncinate fasciculus, respectively. Diffusion connectometry was performed to identify whole brain group differences in white matter health. Correlations were computed between biological and clinical measures. RESULTS Tractography and ROI analyses showed no significant differences between bilateral FA values or bilateral amygdala volumes when comparing the anxious depressed and non-anxious depressed groups. The diffusion connectometry analysis showed no significant differences in anisotropy between the groups. Furthermore, there were no significant relationships between MRI-based and clinical measures. CONCLUSION The lack of group differences could indicate that structural connectivity and amygdalae volumes of those with anxious-depression are not significantly altered by a co-morbid anxiety disorder. Improving understanding of anxiety co-morbid with MDD would facilitate development of treatments that more accurately target the underlying networks.
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Affiliation(s)
- Lauren Delaparte
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA; Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA.
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pittsburgh
| | - Phil Adams
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Ashley Malchow
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maria A. Oquendo
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Todd Ogden
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | | | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Benji T. Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Myrna M. Weissman
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Patrick J. McGrath
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Daniel N. Klein
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Ramin V. Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York,Department of Radiology, Stony Brook University, Stony Brook, New York
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92
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Zajac L, Koo BB, Bauer CM, Killiany R. Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer's Disease. Brain Sci 2017; 7:brainsci7040037. [PMID: 28383490 PMCID: PMC5406694 DOI: 10.3390/brainsci7040037] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Revised: 02/28/2017] [Accepted: 03/31/2017] [Indexed: 01/03/2023] Open
Abstract
Whole-brain networks derived from diffusion tensor imaging (DTI) data require the identification of seed and target regions of interest (ROIs) to assess connectivity patterns. This study investigated how initiating tracts from gray matter (GM) or white matter (WM) seed ROIs impacts (1) structural networks constructed from DTI data from healthy elderly (control) and individuals with Alzheimer’s disease (AD) and (2) between-group comparisons using these networks. DTI datasets were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Deterministic tractography was used to build two whole-brain networks for each subject; one in which tracts were initiated from WM ROIs and another in which they were initiated from GM ROIs. With respect to the first goal, in both groups, WM-seeded networks had approximately 400 more connections and stronger connections (as measured by number of streamlines per connection) than GM-seeded networks, but shared 94% of the connections found in the GM-seed networks. With respect to the second goal, between-group comparisons revealed a stronger subnetwork (as measured by number of streamlines per connection) in controls compared to AD using both WM-seeded and GM-seeded networks. The comparison using WM-seeded networks produced a larger (i.e., a greater number of connections) and more significant subnetwork in controls versus AD. Global, local, and nodal efficiency were greater in controls compared to AD, and between-group comparisons of these measures using WM-seeded networks had larger effect sizes than those using GM-seeded networks. These findings affirm that seed location significantly affects the ability to detect between-group differences in structural networks.
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Affiliation(s)
- Lauren Zajac
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
| | - Bang-Bon Koo
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
| | - Corinna M Bauer
- Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA 02114, USA.
| | - Ron Killiany
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
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93
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Aging of cerebral white matter. Ageing Res Rev 2017; 34:64-76. [PMID: 27865980 DOI: 10.1016/j.arr.2016.11.006] [Citation(s) in RCA: 157] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 10/21/2016] [Accepted: 11/04/2016] [Indexed: 12/12/2022]
Abstract
White matter (WM) occupies a large volume of the human cerebrum and is mainly composed of myelinated axons and myelin-producing glial cells. The myelinated axons within WM are the structural foundation for efficient neurotransmission between cortical and subcortical areas. Similar to neuron-enriched gray matter areas, WM undergoes a series of changes during the process of aging. WM malfunction can induce serious neurobehavioral and cognitive impairments. Thus, age-related changes in WM may contribute to the functional decline observed in the elderly. In addition, aged WM becomes more susceptible to neurological disorders, such as stroke, traumatic brain injury (TBI), and neurodegeneration. In this review, we summarize the structural and functional alterations of WM in natural aging and speculate on the underlying mechanisms. We also discuss how age-related WM changes influence the progression of various brain disorders, including ischemic and hemorrhagic stroke, TBI, Alzheimer's disease, and Parkinson's disease. Although the physiology of WM is still poorly understood relative to gray matter, WM is a rational therapeutic target for a number of neurological and psychiatric conditions.
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94
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Gallaway PJ, Miyake H, Buchowski MS, Shimada M, Yoshitake Y, Kim AS, Hongu N. Physical Activity: A Viable Way to Reduce the Risks of Mild Cognitive Impairment, Alzheimer's Disease, and Vascular Dementia in Older Adults. Brain Sci 2017; 7:E22. [PMID: 28230730 PMCID: PMC5332965 DOI: 10.3390/brainsci7020022] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 01/23/2017] [Accepted: 02/03/2017] [Indexed: 11/17/2022] Open
Abstract
A recent alarming rise of neurodegenerative diseases in the developed world is one of the major medical issues affecting older adults. In this review, we provide information about the associations of physical activity (PA) with major age-related neurodegenerative diseases and syndromes, including Alzheimer's disease, vascular dementia, and mild cognitive impairment. We also provide evidence of PA's role in reducing the risks of these diseases and helping to improve cognitive outcomes in older adults. Finally, we describe some potential mechanisms by which this protective effect occurs, providing guidelines for future research.
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Affiliation(s)
- Patrick J Gallaway
- Department of Nutritional Sciences, The University of Arizona, Tucson, AZ 85721-0038, USA.
| | - Hiroji Miyake
- Nishinomiya Kyoritsu Neurosurgical Hospital, Hyogo 663-8211, Japan.
| | - Maciej S Buchowski
- Department of Medicine, Vanderbilt University, Nashville, TN 37232-5280, USA.
| | - Mieko Shimada
- Chiba Prefectural University of Health Sciences, Chiba 261-0014, Japan.
| | - Yutaka Yoshitake
- National Institute of Fitness & Sport in Kanoya, Kagoshima 891-2311, Japan.
| | - Angela S Kim
- Department of Nutritional Sciences, The University of Arizona, Tucson, AZ 85721-0038, USA.
| | - Nobuko Hongu
- Department of Nutritional Sciences, The University of Arizona, Tucson, AZ 85721-0038, USA.
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95
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Kuhn T, Schonfeld D, Sayegh P, Arentoft A, Jones JD, Hinkin CH, Bookheimer SY, Thames AD. The effects of HIV and aging on subcortical shape alterations: A 3D morphometric study. Hum Brain Mapp 2017; 38:1025-1037. [PMID: 27778407 PMCID: PMC5225033 DOI: 10.1002/hbm.23436] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 08/28/2016] [Accepted: 10/04/2016] [Indexed: 12/21/2022] Open
Abstract
Standard volumetric neuroimaging studies have demonstrated preferential atrophy of subcortical structures among individuals with HIV. However, to our knowledge, no study has investigated subcortical shape alterations secondary to HIV and whether advancing age impacts that relationship. This study employed 3D morphometry to examine the independent and interactive effects of HIV and age on shape differences in nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus in 81 participants ranging in age from 24 to 76 including 59 HIV+ individuals and 22 HIV-seronegative controls. T1-weighted MRI underwent a preprocessing pipeline followed by automated subcortical segmentation. Parametric statistical analyses were used to determine independent effects of HIV infection and age on volume and shape in each region of interest (ROI) and the interaction between age and HIV serostatus in predicting volume/shape in each ROI. Significant main effects for HIV were found in the shape of right caudate and nucleus accumbens, left pallidum, and hippocampus. Age was associated with differences in shape in left pallidum, right nucleus accumbens and putamen, and bilateral caudate, hippocampus, and thalamus. Of greatest interest, an age × HIV interaction effect was found in the shape of bilateral nucleus accumbens, amygdala, caudate, and thalamus as well as right pallidum and putamen such that increasing age in HIV participants was associated with greater shape alterations. Traditional volumemetric analyses revealed main effects for both HIV and age but no age × HIV interaction. These findings may suggest that age and HIV infection conferred additional deleterious effects on subcortical shape abnormalities beyond the independent effects of these factors. Hum Brain Mapp 38:1025-1037, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Taylor Kuhn
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
- Veterans Association Greater Los Angeles Healthcare Center11301 Wilshire BlvdLos AngelesCalifornia
| | - Daniel Schonfeld
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
- Veterans Association Greater Los Angeles Healthcare Center11301 Wilshire BlvdLos AngelesCalifornia
- Imaging Genetics CenterKeck School of Medicine of University of Southern California1975 Zonal AveLos AngelesCalifornia
| | - Philip Sayegh
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
| | - Alyssa Arentoft
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
| | - Jacob D. Jones
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
- Veterans Association Greater Los Angeles Healthcare Center11301 Wilshire BlvdLos AngelesCalifornia
| | - Charles H. Hinkin
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
- Veterans Association Greater Los Angeles Healthcare Center11301 Wilshire BlvdLos AngelesCalifornia
| | - Susan Y. Bookheimer
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
- Department of Cognitive PsychologyTennenbaum Center for the Biology of Creativity, University of California Los Angeles635 Charles E Young Dr. S,260‐MLos AngelesCalifornia
| | - April D. Thames
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles740 Westwood PlazaC8‐746Los AngelesCalifornia
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Lindemer ER, Greve DN, Fischl BR, Augustinack JC, Salat DH. Regional staging of white matter signal abnormalities in aging and Alzheimer's disease. Neuroimage Clin 2017; 14:156-165. [PMID: 28180074 PMCID: PMC5279704 DOI: 10.1016/j.nicl.2017.01.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 01/02/2017] [Accepted: 01/20/2017] [Indexed: 11/07/2022]
Abstract
White matter lesions, quantified as 'white matter signal abnormalities' (WMSA) on neuroimaging, are common incidental findings on brain images of older adults. This tissue damage is linked to cerebrovascular dysfunction and is associated with cognitive decline. The regional distribution of WMSA throughout the cerebral white matter has been described at a gross scale; however, to date no prior study has described regional patterns relative to cortical gyral landmarks which may be important for understanding functional impact. Additionally, no prior study has described how regional WMSA volume scales with total global WMSA. Such information could be used in the creation of a pathologic 'staging' of WMSA through a detailed regional characterization at the individual level. Magnetic resonance imaging data from 97 cognitively-healthy older individuals (OC) aged 52-90 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were processed using a novel WMSA labeling procedure described in our prior work. WMSA were quantified regionally using a procedure that segments the cerebral white matter into 35 bilateral units based on proximity to landmarks in the cerebral cortex. An initial staging was performed by quantifying the regional WMSA volume in four groups based on quartiles of total WMSA volume (quartiles I-IV). A consistent spatial pattern of WMSA accumulation was observed with increasing quartile. A clustering procedure was then used to distinguish regions based on patterns of scaling of regional WMSA to global WMSA. Three patterns were extracted that showed high, medium, and non-scaling with global WMSA. Regions in the high-scaling cluster included periventricular, caudal and rostral middle frontal, inferior and superior parietal, supramarginal, and precuneus white matter. A data-driven staging procedure was then created based on patterns of WMSA scaling and specific regional cut-off values from the quartile analyses. Individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were then additionally staged, and significant differences in the percent of each diagnostic group in Stages I and IV were observed, with more AD individuals residing in Stage IV and more OC and MCI individuals residing in Stage I. These data demonstrate a consistent regional scaling relationship between global and regional WMSA that can be used to classify individuals into one of four stages of white matter disease. White matter staging could play an important role in a better understanding and the treatment of cerebrovascular contributions to brain aging and dementia.
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Affiliation(s)
- Emily R. Lindemer
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Douglas N. Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce R. Fischl
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Jean C. Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David H. Salat
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA
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97
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Lakhani B, Hayward KS, Boyd LA. Hemispheric asymmetry in myelin after stroke is related to motor impairment and function. NEUROIMAGE-CLINICAL 2017; 14:344-353. [PMID: 28229041 PMCID: PMC5312556 DOI: 10.1016/j.nicl.2017.01.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 01/03/2017] [Accepted: 01/10/2017] [Indexed: 02/02/2023]
Abstract
The relationships between impairment, function, arm use and underlying brain structure following stroke remain unclear. Although diffusion weighted imaging is useful in broadly assessing white matter structure, it has limited utility in identifying specific underlying neurobiological components, such as myelin. The purpose of the present study was to explore relationships between myelination and impairment, function and activity in individuals with chronic stroke. Assessments of paretic upper-extremity impairment and function were administered, and 72-hour accelerometer based activity monitoring was conducted on 19 individuals with chronic stroke. Participants completed a magnetic resonance imaging protocol that included a high resolution T1 anatomical scan and a multi-component T2 relaxation imaging scan to quantify myelin water fraction (MWF). MWF was automatically parcellated from pre- and post-central subcortical regions of interest and quantified as an asymmetry ratio (contralesional/ipsilesional). Cluster analysis was used to group more and less impaired individuals based on Fugl-Meyer upper extremity scores. A significantly higher precentral MWF asymmetry ratio was found in the more impaired group compared to the less impaired group (p < 0.001). There were no relationships between MWF asymmetry ratio and upper-limb use. Stepwise multiple linear regression identified precentral MWF asymmetry as the only variable to significantly predict impairment and motor function in the upper extremity (UE). These results suggest that asymmetric myelination in a motor specific brain area is a significant predictor of upper-extremity impairment and function in individuals with chronic stroke. As such, myelination may be utilized as a more specific marker of the neurobiological changes that predict long term impairment and recovery from stroke.
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Key Words
- AC, Activity Count
- ANCOVA, Analysis of Covariance
- AR, Asymmetry Ratio
- Accelerometry
- Biomarkers
- CST, Corticospinal Tract
- DTI, Diffusion Tensor Imaging
- FM, Fugl-Meyer
- GRASE, Gradient and Spin Echo
- MANCOVA, Multivariate Analysis of Covariance
- MR, Magnetic Resonance
- MWF, Myelin Water Fraction
- Motor control
- Myelin
- Stroke
- UE, Upper Extremity
- WMFT, Wolf Motor Function Test
- White matter
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Affiliation(s)
- Bimal Lakhani
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Kathryn S Hayward
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada; Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC 3084, Australia; NHMRC Centre of Research Excellence in Stroke Rehabilitation and Brain Recovery, Australia
| | - Lara A Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
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98
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Lindemer ER, Greve DN, Fischl B, Augustinack JC, Salat DH. Differential Regional Distribution of Juxtacortical White Matter Signal Abnormalities in Aging and Alzheimer's Disease. J Alzheimers Dis 2017; 57:293-303. [PMID: 28222518 PMCID: PMC5534349 DOI: 10.3233/jad-161057] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND White matter signal abnormalities (WMSA) (also known as 'hyperintensities') on MRI are commonly seen in normal aging and increases have been noted in Alzheimer's disease (AD), but whether there is a spatial specificity to these increases is unknown. OBJECTIVE To discern whether or not there is a spatial pattern of WMSA in the brains of individuals with AD that differs from those who exhibit cognitively healthy aging. METHOD Structural MRI data from the Alzheimer's Disease Neuroimaging Initiative public database were used to quantify WMSA in 35 regions of interest (ROIs). Regional measures were compared between cognitively healthy older controls (OC; n = 107) and individuals with a clinical diagnosis of AD (n = 127). Regional WMSA volume was also assessed in individuals with mild cognitive impairment (MCI; n = 74) who were 6, 12, and 24 months away from AD conversion. RESULTS WMSA volume was significantly greater in AD compared to OC in 24 out of 35 ROIs after controlling for age, and nine were significantly higher after normalizing for total WMSA. Regions with greater WMSA volume in AD included rostral frontal, inferior temporal, and inferior parietal WM. In MCI, frontal and temporal regions demonstrated significantly greater WMSA volume with decreasing time-to-AD-conversion. DISCUSSION Individuals with AD have greater regional volume of WMSA compared to OC regardless of age or total WMSA volume. Accumulation of regional WMSA is linked to time to AD conversion in individuals with MCI. These findings indicate WMSA is an important pathological component of AD development.
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Affiliation(s)
- Emily R. Lindemer
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Douglas N. Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce Fischl
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Jean C. Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David H. Salat
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA
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Toepper M. Dissociating Normal Aging from Alzheimer's Disease: A View from Cognitive Neuroscience. J Alzheimers Dis 2017; 57:331-352. [PMID: 28269778 PMCID: PMC5366251 DOI: 10.3233/jad-161099] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2017] [Indexed: 02/07/2023]
Abstract
Both normal aging and Alzheimer's disease (AD) are associated with changes in cognition, grey and white matter volume, white matter integrity, neural activation, functional connectivity, and neurotransmission. Obviously, all of these changes are more pronounced in AD and proceed faster providing the basis for an AD diagnosis. Since these differences are quantitative, however, it was hypothesized that AD might simply reflect an accelerated aging process. The present article highlights the different neurocognitive changes associated with normal aging and AD and shows that, next to quantitative differences, there are multiple qualitative differences as well. These differences comprise different neurocognitive dissociations as different cognitive deficit profiles, different weights of grey and white matter atrophy, and different gradients of structural decline. These qualitative differences clearly indicate that AD cannot be simply described as accelerated aging process but on the contrary represents a solid entity.
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Affiliation(s)
- Max Toepper
- Department of Psychiatry and Psychotherapy Bethel, Research Division, Evangelisches Krankenhaus Bielefeld (EvKB), Bielefeld, Germany
- Department of Psychiatry and Psychotherapy Bethel, Department of Geriatric Psychiatry, Evangelisches Krankenhaus Bielefeld (EvKB), Bielefeld, Germany
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100
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Garcia-Lazaro HG, Becerra-Laparra I, Cortez-Conradis D, Roldan-Valadez E. Global fractional anisotropy and mean diffusivity together with segmented brain volumes assemble a predictive discriminant model for young and elderly healthy brains: a pilot study at 3T. FUNCTIONAL NEUROLOGY 2016; 31:39-46. [PMID: 27027893 DOI: 10.11138/fneur/2016.31.1.039] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Several parameters of brain integrity can be derived from diffusion tensor imaging. These include fractional anisotropy (FA) and mean diffusivity (MD). Combination of these variables using multivariate analysis might result in a predictive model able to detect the structural changes of human brain aging. Our aim was to discriminate between young and older healthy brains by combining structural and volumetric variables from brain MRI: FA, MD, and white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) volumes. This was a cross-sectional study in 21 young (mean age, 25.71±3.04 years; range, 21-34 years) and 10 elderly (mean age, 70.20±4.02 years; range, 66-80 years) healthy volunteers. Multivariate discriminant analysis, with age as the dependent variable and WM, GM and CSF volumes, global FA and MD, and gender as the independent variables, was used to assemble a predictive model. The resulting model was able to differentiate between young and older brains: Wilks' λ = 0.235, χ² (6) = 37.603, p = .000001. Only global FA, WM volume and CSF volume significantly discriminated between groups. The total accuracy was 93.5%; the sensitivity, specificity and positive and negative predictive values were 91.30%, 100%, 100% and 80%, respectively. Global FA, WM volume and CSF volume are parameters that, when combined, reliably discriminate between young and older brains. A decrease in FA is the strongest predictor of membership of the older brain group, followed by an increase in WM and CSF volumes. Brain assessment using a predictive model might allow the follow-up of selected cases that deviate from normal aging.
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