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Chen H, Xu J, Li W, Hu Z, Ke Z, Qin R, Xu Y. The characteristic patterns of individual brain susceptibility networks underlie Alzheimer's disease and white matter hyperintensity-related cognitive impairment. Transl Psychiatry 2024; 14:177. [PMID: 38575556 PMCID: PMC10994911 DOI: 10.1038/s41398-024-02861-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 04/06/2024] Open
Abstract
Excessive iron accumulation in the brain cortex increases the risk of cognitive deterioration. However, interregional relationships (defined as susceptibility connectivity) of local brain iron have not been explored, which could provide new insights into the underlying mechanisms of cognitive decline. Seventy-six healthy controls (HC), 58 participants with mild cognitive impairment due to probable Alzheimer's disease (MCI-AD) and 66 participants with white matter hyperintensity (WMH) were included. We proposed a novel approach to construct a brain susceptibility network by using Kullback‒Leibler divergence similarity estimation from quantitative susceptibility mapping and further evaluated its topological organization. Moreover, sparse logistic regression (SLR) was applied to classify MCI-AD from HC and WMH with normal cognition (WMH-NC) from WMH with MCI (WMH-MCI).The altered susceptibility connectivity in the MCI-AD patients indicated that relatively more connectivity was involved in the default mode network (DMN)-related and visual network (VN)-related connectivity, while more altered DMN-related and subcortical network (SN)-related connectivity was found in the WMH-MCI patients. For the HC vs. MCI-AD classification, the features selected by the SLR were primarily distributed throughout the DMN-related and VN-related connectivity (accuracy = 76.12%). For the WMH-NC vs. WMH-MCI classification, the features with high appearance frequency were involved in SN-related and DMN-related connectivity (accuracy = 84.85%). The shared and specific patterns of the susceptibility network identified in both MCI-AD and WMH-MCI may provide a potential diagnostic biomarker for cognitive impairment, which could enhance the understanding of the relationships between brain iron burden and cognitive decline from a network perspective.
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Affiliation(s)
- Haifeng Chen
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Jingxian Xu
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Weikai Li
- School of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, China
- MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing, China
| | - Zheqi Hu
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhihong Ke
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China.
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Bao L, Zhang H, Liao Z. A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping. Phys Med Biol 2024; 69:045030. [PMID: 38286013 DOI: 10.1088/1361-6560/ad237f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/29/2024] [Indexed: 01/31/2024]
Abstract
Objective.Quantitative susceptibility mapping (QSM) is a new imaging technique for non-invasive characterization of the composition and microstructure ofin vivotissues, and it can be reconstructed from local field measurements by solving an ill-posed inverse problem. Even for deep learning networks, it is not an easy task to establish an accurate quantitative mapping between two physical quantities of different units, i.e. field shift in Hz and susceptibility value in ppm for QSM.Approach. In this paper, we propose a spatially adaptive regularization based three-dimensional reconstruction network SAQSM. A spatially adaptive module is specially designed and a set of them at different resolutions are inserted into the network decoder, playing a role of cross-modality based regularization constraint. Therefore, the exact information of both field and magnitude data is exploited to adjust the scale and shift of feature maps, and thus any information loss or deviation occurred in previous layers could be effectively corrected. The network encoding has a dynamic perceptual initialization, which enables the network to overcome receptive field intervals and also strengthens its ability to detect features of various sizes.Main results. Experimental results on the brain data of healthy volunteers, clinical hemorrhage and simulated phantom with calcification demonstrate that SAQSM can achieve more accurate reconstruction with less susceptibility artifacts, while perform well on the stability and generalization even for severe lesion areas.Significance. This proposed framework may provide a valuable paradigm to quantitative mapping or multimodal reconstruction.
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Affiliation(s)
- Lijun Bao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, People's Republic of China
| | - Hongyuan Zhang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, People's Republic of China
- Zhangzhou Institute of Science and Technology, Zhangzhou City, Fujian Province, People's Republic of China
| | - Zeyu Liao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, People's Republic of China
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Madden DJ, Merenstein JL. Quantitative susceptibility mapping of brain iron in healthy aging and cognition. Neuroimage 2023; 282:120401. [PMID: 37802405 PMCID: PMC10797559 DOI: 10.1016/j.neuroimage.2023.120401] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/14/2023] [Accepted: 09/30/2023] [Indexed: 10/10/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA
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Spence H, McNeil CJ, Waiter GD. Cognition and brain iron deposition in whole grey matter regions and hippocampal subfields. Eur J Neurosci 2022; 56:6039-6054. [PMID: 36215153 PMCID: PMC10092357 DOI: 10.1111/ejn.15838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 12/29/2022]
Abstract
Regional brain iron accumulation is observed in many neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, and is associated with cognitive decline. We explored associations between age, cognition and iron content in grey matter regions and hippocampal subfields in 380 participants of the Aberdeen children of the 1950s cohort and their first-generation relatives (aged 26-72 years). Participants underwent cognitive assessment at the time of MRI scanning. Quantitative susceptibility mapping of these MRI data was used to assess iron content in grey matter regions and in hippocampal subfields. Principle component analysis was performed on cognitive test scores to create a general cognition score. Spline analysis was used with the Akaike information criterion to determine if order 1, 2 or 3 natural splines were optimal for assessing non-linear relationships between regional iron and age. Multivariate linear models were used to assess associations between regional iron and cognition. Higher iron correlated with older age in the left putamen across all ages and in the right putamen of only participants over 58. Whereas a decrease in iron with older age was observed in the right thalamus and left pallidum across all ages. Right amygdala iron levels were associated with poorer general cognition scores and poorer immediate recall scores. Iron was not associated with any measures of cognitive performance in other regions of interest. Our results suggest that, whilst iron in some regions was associated with cognitive performance, there is an overall lack of association between regional iron content and cognitive ability in cognitively healthy individuals.
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Affiliation(s)
- Holly Spence
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Chris J McNeil
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
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Merenstein JL, Bennett IJ. Bridging patterns of neurocognitive aging across the older adult lifespan. Neurosci Biobehav Rev 2022; 135:104594. [PMID: 35227712 PMCID: PMC9888009 DOI: 10.1016/j.neubiorev.2022.104594] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/27/2022] [Accepted: 02/23/2022] [Indexed: 02/02/2023]
Abstract
Magnetic resonance imaging (MRI) studies of brain and neurocognitive aging rarely include oldest-old adults (ages 80 +). But predictions of neurocognitive aging theories derived from MRI findings in younger-old adults (ages ~55-80) may not generalize into advanced age, particularly given the increased prevalence of cognitive impairment/dementia in the oldest-old. Here, we reviewed the MRI literature in oldest-old adults and interpreted findings within the context of regional variation, compensation, brain maintenance, and reserve theories. Structural MRI studies revealed regional variation in brain aging as larger age effects on medial temporal and posterior regions for oldest-old than younger-old adults. They also revealed that brain maintenance explained preserved cognitive functioning into the tenth decade of life. Very few functional MRI studies examined compensatory activity in oldest-old adults who perform as well as younger groups, although there was evidence that higher brain reserve in oldest-old adults may mediate effects of brain aging on cognition. Despite some continuity, different cognitive and neural profiles across the older adult lifespan should be addressed in modern neurocognitive aging theories.
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Kagerer SM, Schroeder C, van Bergen JMG, Schreiner SJ, Meyer R, Steininger SC, Vionnet L, Gietl AF, Treyer V, Buck A, Pruessmann KP, Hock C, Unschuld PG. Low Subicular Volume as an Indicator of Dementia-Risk Susceptibility in Old Age. Front Aging Neurosci 2022; 14:811146. [PMID: 35309894 PMCID: PMC8926841 DOI: 10.3389/fnagi.2022.811146] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Hippocampal atrophy is an established Alzheimer’s Disease (AD) biomarker. Volume loss in specific subregions as measurable with ultra-high field magnetic resonance imaging (MRI) may reflect earliest pathological alterations. Methods Data from positron emission tomography (PET) for estimation of cortical amyloid β (Aβ) and high-resolution 7 Tesla T1 MRI for assessment of hippocampal subfield volumes were analyzed in 61 non-demented elderly individuals who were divided into risk-categories as defined by high levels of cortical Aβ and low performance in standardized episodic memory tasks. Results High cortical Aβ and low episodic memory interactively predicted subicular volume [F(3,57) = 5.90, p = 0.018]. The combination of high cortical Aβ and low episodic memory was associated with significantly lower subicular volumes, when compared to participants with high episodic memory (p = 0.004). Discussion Our results suggest that low subicular volume is linked to established indicators of AD risk, such as increased cortical Aβ and low episodic memory. Our data support subicular volume as a marker of dementia-risk susceptibility in old-aged non-demented persons.
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Affiliation(s)
- Sonja M. Kagerer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Clemens Schroeder
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | | | - Simon J. Schreiner
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Rafael Meyer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Stefanie C. Steininger
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
| | - Anton F. Gietl
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alfred Buck
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren, Switzerland
| | - Paul G. Unschuld
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
- Geriatric Psychiatry, Department of Psychiatry, University Hospitals of Geneva, University of Geneva, Geneva, Switzerland
- *Correspondence: Paul G. Unschuld,
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Association between symbol digit modalities test and regional cortex thickness in young adults with relapsing-remitting multiple sclerosis. Clin Neurol Neurosurg 2021; 207:106805. [PMID: 34280674 DOI: 10.1016/j.clineuro.2021.106805] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Multiple sclerosis (MS) is a demyelinating disease of the central nervous system, predominating within young adults. Cognitive disorders are common in MS and have are associated with several Magnetic Resonance Imaging (MRI) markers, especially brain atrophy. Many have found the symbol digit modalities test (SDMT) to be the most sensitive individual cognitive measure relevant to MS. However, the relationship between SDMT and regional brain cortex thickness in young adults with relapsing-remitting multiple sclerosis (YA-RRMS) has been little explored. The purpose of this study was to investigate the association between the SDMT and regional cortex thickness in YA-RRMS by FreeSurfer, which is an automatic brain structure segmentation method. METHOD Twenty-eight YA-RRMS patients (18-35 years old) were enrolled in the present study. Informed consent and information including gender, age, disease duration, number of relapses, annual relapse rate was collected from all patients. Clinical cognitive evaluations (SDMT and auditory verbal learning test (AVLT)) and daily performance: activities of daily living (ADL) were assessed in the present study. MRI scans were performed at the Institute of Neurosurgery of Tiantan Hospital. Twenty-eight matched healthy controls (HC) MRI data were obtained from Tiantan Hospital database. Data on thirty-four points of bilateral cortical structure thickness using statistically defined brain regions-of-interest from FreeSurfer were obtained from all participants. RESULTS Patients with RRMS exhibited extensively thinner cerebellar cortex compared with HC. SDMT scores were significantly correlated with AVLT subentries (IM, immediate memory; DRM, delayed recall memory; LTRM, long-term recognition memory) in YA-RRMS patients (P < 0.05). SDMT was strongly correlated with regional cortex thickness differences of the right temporal pole (r = 0.68) and bilateral parahippocampal areas (right r = 0.62; left r = 0.60), and moderately correlated with regional cortex thickness differences including the left superior temporal and right insula (r = 0.57 and 0.56, respectively) in YA-RRMS patients. CONCLUSION The present study has shown the SDMT is strongly correlated with selected cortex regions including the bilateral parahippocampal area and the right temporal pole which are involved in geometric structures processing.
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Woodworth DC, Scambray KA, Corrada MM, Kawas CH, Sajjadi SA. Neuroimaging in the Oldest-Old: A Review of the Literature. J Alzheimers Dis 2021; 82:129-147. [PMID: 33998539 DOI: 10.3233/jad-201578] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The oldest-old, those 85 years and older, are the fastest growing segment of the population and present with the highest prevalence of dementia. Given the importance of neuroimaging measures to understand aging and dementia, the objective of this study was to review neuroimaging studies performed in oldest-old participants. We used PubMed, Google Scholar, and Web of Science search engines to identify in vivo CT, MRI, and PET neuroimaging studies either performed in the oldest-old or that addressed the oldest-old as a distinct group in analyses. We identified 60 studies and summarized the main group characteristics and findings. Generally, oldest-old participants presented with greater atrophy compared to younger old participants, with most studies reporting a relatively stable constant decline in brain volumes over time. Oldest-old participants with greater global atrophy and atrophy in key brain structures such as the medial temporal lobe were more likely to have dementia or cognitive impairment. The oldest-old presented with a high burden of white matter lesions, which were associated with various lifestyle factors and some cognitive measures. Amyloid burden as assessed by PET, while high in the oldest-old compared to younger age groups, was still predictive of transition from normal to impaired cognition, especially when other adverse neuroimaging measures (atrophy and white matter lesions) were also present. While this review highlights past neuroimaging research in the oldest-old, it also highlights the dearth of studies in this important population. It is imperative to perform more neuroimaging studies in the oldest-old to better understand aging and dementia.
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Affiliation(s)
- Davis C Woodworth
- Department of Neurology, University of California, Irvine, CA, USA.,Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Kiana A Scambray
- Department of Neurology, University of California, Irvine, CA, USA.,Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - María M Corrada
- Department of Neurology, University of California, Irvine, CA, USA.,Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA.,Department of Epidemiology, University of California, Irvine, CA, USA
| | - Claudia H Kawas
- Department of Neurology, University of California, Irvine, CA, USA.,Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA.,Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - S Ahmad Sajjadi
- Department of Neurology, University of California, Irvine, CA, USA.,Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
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Treyer V, Meyer RS, Buchmann A, Crameri GAG, Studer S, Saake A, Gruber E, Unschuld PG, Nitsch RM, Hock C, Gietl AF. Physical activity is associated with lower cerebral beta-amyloid and cognitive function benefits from lifetime experience-a study in exceptional aging. PLoS One 2021; 16:e0247225. [PMID: 33606797 PMCID: PMC7895362 DOI: 10.1371/journal.pone.0247225] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 02/03/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Exceptional agers (85+ years) are characterized by preserved cognition presumably due to high cognitive reserve. In the current study, we examined whether personality, risk and protective factors for dementia as well as quality of life are associated with core features of Alzheimer's disease (amyloid-deposition and hippocampal volume) as well as cognition in exceptional aging. METHODS We studied 49 exceptional agers (average 87.8 years, range 84-94 years), with preserved activities of daily living and absence of dementia. All participants received a detailed clinical and neuropsychological examination. We used established questionnaires to measure lifetime experience, personality, recent physical and cognitive activity as well as quality of life. Cerebral amyloid-deposition was estimated by 18-[F]-Flutemetamol-PET and manual hippocampal volumetry was performed on 3D T1 MRI images. RESULTS In this sample of exceptional agers with preserved activities of daily living, we found intact cognitive performance in the subjects with the highest amyloid-load in the brain, but a lower quality of life with respect to autonomy as well as higher neuroticism. Higher self-reported physical activity in the last twelve months went with a lower amyloid load. Higher self-reported leisure-time/ not work-related activity went with better executive functioning at older age. CONCLUSION Even in exceptional aging, high amyloid load may subtly influence personality and quality of life. Our findings support a close relationship between high physical activity and low amyloid-deposition and underscore the importance of extracurricular activities for executive functions. As executive functions are known to be a central resource for everyday functioning in fostering extracurricular activities may be effective in delaying the onset of dementia.
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Affiliation(s)
- Valerie Treyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Rafael S. Meyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Andreas Buchmann
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | | | - Sandro Studer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Paul G. Unschuld
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Roger M. Nitsch
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren-Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren-Zurich, Switzerland
| | - Anton F. Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
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Pelkmans W, Legdeur N, Ten Kate M, Barkhof F, Yaqub MM, Holstege H, van Berckel BNM, Scheltens P, van der Flier WM, Visser PJ, Tijms BM. Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old. Ann Clin Transl Neurol 2021; 8:348-358. [PMID: 33421355 PMCID: PMC7886045 DOI: 10.1002/acn3.51273] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 12/14/2022] Open
Abstract
Objective To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition. Methods We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [18F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas. Results Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy. Interpretation These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.
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Affiliation(s)
- Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Nienke Legdeur
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Queen Square Institute of Neurology and Centre for Medical Image Computing, UCL, London, UK
| | - Maqsood M Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Bao L, Xiong C, Wei W, Chen Z, van Zijl PCM, Li X. Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain. Med Image Anal 2020; 67:101827. [PMID: 33166777 DOI: 10.1016/j.media.2020.101827] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Revised: 08/19/2020] [Accepted: 08/31/2020] [Indexed: 10/23/2022]
Abstract
Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
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Affiliation(s)
- Lijun Bao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China.
| | - Congcong Xiong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Wenping Wei
- Medical Imaging Diagnostic Center, First Affiliated Hospital of Xiamen University, Xiamen 361000, China
| | - Zhong Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Xu Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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12
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Quevenco FC, van Bergen JM, Treyer V, Studer ST, Kagerer SM, Meyer R, Gietl AF, Kaufmann PA, Nitsch RM, Hock C, Unschuld PG. Functional Brain Network Connectivity Patterns Associated With Normal Cognition at Old-Age, Local β-amyloid, Tau, and APOE4. Front Aging Neurosci 2020; 12:46. [PMID: 32210782 PMCID: PMC7075450 DOI: 10.3389/fnagi.2020.00046] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 02/10/2020] [Indexed: 12/30/2022] Open
Abstract
Background: Integrity of functional brain networks is closely associated with maintained cognitive performance at old age. Consistently, both carrier status of Apolipoprotein E ε4 allele (APOE4), and age-related aggregation of Alzheimer’s disease (AD) pathology result in altered brain network connectivity. The posterior cingulate and precuneus (PCP) is a node of particular interest due to its role in crucial memory processes. Moreover, the PCP is subject to the early aggregation of AD pathology. The current study aimed at characterizing brain network properties associated with unimpaired cognition in old aged adults. To determine the effects of age-related brain change and genetic risk for AD, pathological proteins β-amyloid and tau were measured by Positron-emission tomography (PET), PCP connectivity as a proxy of cognitive network integrity, and genetic risk by APOE4 carrier status. Methods: Fifty-seven cognitively unimpaired old-aged adults (MMSE = 29.20 ± 1.11; 73 ± 8.32 years) were administered 11C Pittsburgh Compound B and 18F Flutemetamol PET for assessing β-amyloid, and 18F AV-1451 PET for tau. Individual functional connectivity seed maps of the PCP were obtained by resting-state multiband BOLD functional MRI at 3-Tesla for increased temporal resolution. Voxelwise correlations between functional connectivity, β-amyloid- and tau-PET were explored by Biological Parametric Mapping (BPM). Results: Local β-amyloid was associated with increased connectivity in frontal and parietal regions of the brain. Tau was linked to increased connectivity in more spatially distributed clusters in frontal, parietal, occipital, temporal, and cerebellar regions. A positive interaction was observable for APOE4 carrier status and functional connectivity with brain regions characterized by increased local β-amyloid and tau tracer retention. Conclusions: Our data suggest an association between spatially differing connectivity systems and local β-amyloid, and tau aggregates in cognitively normal, old-aged adults, which is moderated by APOE4. Additional longitudinal studies may determine protective connectivity patterns associated with healthy aging trajectories of AD-pathology aggregation.
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Affiliation(s)
- Frances C Quevenco
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Jiri M van Bergen
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University of Zurich, Zurich, Switzerland
| | - Sandro T Studer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Sonja M Kagerer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Neurimmune, Schlieren, Switzerland
| | - Rafael Meyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Anton F Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine, University of Zurich, Zurich, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Neurimmune, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Neurimmune, Schlieren, Switzerland
| | - Paul G Unschuld
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Department of Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland.,Zurich Neuroscience Center (ZNZ), Zurich, Switzerland
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13
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Kagerer SM, van Bergen JMG, Li X, Quevenco FC, Gietl AF, Studer S, Treyer V, Meyer R, Kaufmann PA, Nitsch RM, van Zijl PCM, Hock C, Unschuld PG. APOE4 moderates effects of cortical iron on synchronized default mode network activity in cognitively healthy old-aged adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12002. [PMID: 32211498 PMCID: PMC7085281 DOI: 10.1002/dad2.12002] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 10/21/2019] [Accepted: 11/01/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Apolipoprotein E ε4 (APOE4)-related genetic risk for sporadic Alzheimer's disease is associated with an early impairment of cognitive brain networks. The current study determines relationships between APOE4 carrier status, cortical iron, and cortical network-functionality. METHODS Sixty-nine cognitively healthy old-aged individuals (mean age [SD] 66.1 [± 7.2] years; Mini-Mental State Exam [MMSE] 29.3 ± 1.1) were genotyped for APOE4 carrier-status and received 3 Tesla magnetic resonance imaging (MRI) for blood oxygen level-dependent functional magnetic resonance imaging (MRI) at rest, three-dimensional (3D)-gradient echo (six echoes) for cortical gray-matter, non-heme iron by quantitative susceptibility mapping, and 18F-flutemetamol positron emission tomography for amyloid-β. RESULTS A spatial pattern consistent with the default mode network (DMN) could be identified by independent component analysis. DMN activity was enhanced in APOE4 carriers and related to cortical iron burden. APOE4 and cortical iron synergistically interacted with DMN activity. Secondary analysis revealed a positive, APOE4 associated, relationship between cortical iron and DMN connectivity. DISCUSSION Our findings suggest that APOE4 moderates effects of iron on brain functionality prior to manifestation of cognitive impairment.
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Affiliation(s)
- Sonja M. Kagerer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | | | - Xu Li
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | | | - Anton F. Gietl
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Sandro Studer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
| | - Valerie Treyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Rafael Meyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Philipp A. Kaufmann
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Roger M. Nitsch
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Peter C. M. van Zijl
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | - Christoph Hock
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Paul G. Unschuld
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
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14
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Baker SL, Harrison TM, Maass A, La Joie R, Jagust WJ. Effect of Off-Target Binding on 18F-Flortaucipir Variability in Healthy Controls Across the Life Span. J Nucl Med 2019; 60:1444-1451. [PMID: 30877180 DOI: 10.2967/jnumed.118.224113] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/20/2019] [Indexed: 02/04/2023] Open
Abstract
Measuring early tau accumulation is important in studying aging and Alzheimer disease and is only as accurate as the signal-to-noise ratio of the tracer. Along with aggregated tau in the form of neurofibrillary tangles, 18F-flortaucipir has been reported to bind to neuromelanin, monoamine oxidase, calcifications, iron, leptomeningeal melanocytes, and microhemorrages. Although 18F-flortaucipir successfully differentiates healthy controls (HCs) from subjects with Alzheimer disease, variability exists in the cortical signal in amyloid-negative HCs. We aimed to explore the relationship between off-target binding signal and variability in the cortical signal in HCs. Methods: Subjects (n = 139) received 11C-Pittsburgh compound B (PIB) and 18F-flortaucipir PET scans and a magnetization-prepared rapid gradient echo MRI scan. PET frames were realigned and coregistered to the MR images, which were segmented using FreeSurfer. In amyloid-negative HCs (n = 90; age range, 21-94 y), 7 nonspecific or off-target binding regions were considered: caudate, pallidum, putamen, thalamus, cerebellar white matter, hemispheric white matter, and choroid plexus. These regions of interest were assigned to 3 similarly behaving groups using principle components analysis, exploratory factor analysis, and Pearson correlations for caudate, putamen, and pallidum (also correlated with age); thalamus and white matter; and choroid plexus. In amyloid-negative HCs with 11C-PIB and 18F-flortaucipir scans, correlations were calculated between white and gray matter before and after partial-volume correction. Results: The correlation between white and gray matter disappeared after partial-volume correction in 11C-PIB (r 2 = 0) but persisted for 18F-flortaucipir (r 2 = 0.27), demonstrating that the correlation between white and gray matter signal in 18F-flortaucipir is not solely due to partial-volume effects. A linear regression showed that off-target signal from putamen and thalamus together explained 64% of the variability in the cortical signal in amyloid-negative HCs (not seen in amyloid-positive HCs). Variability in amyloid-negative HCs but not amyloid-positive HCs correlated with white matter signal (unrelated to partial-volume effects) and age-related off-target signal (possibly related to iron load). Conclusion: The noise in the 18F-flortaucipir measurement could pose challenges when studying early tau accumulation.
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Affiliation(s)
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California
| | - Anne Maass
- Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California.,German Center for Neurodegenerative Diseases, Magdeburg, Germany; and
| | - Renaud La Joie
- Memory and Aging Center, University of California-San Francisco, San Francisco, California
| | - William J Jagust
- Lawrence Berkeley National Laboratory, Berkeley, California.,Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California
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15
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Masaldan S, Bush AI, Devos D, Rolland AS, Moreau C. Striking while the iron is hot: Iron metabolism and ferroptosis in neurodegeneration. Free Radic Biol Med 2019; 133:221-233. [PMID: 30266679 DOI: 10.1016/j.freeradbiomed.2018.09.033] [Citation(s) in RCA: 295] [Impact Index Per Article: 59.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/19/2018] [Accepted: 09/20/2018] [Indexed: 02/07/2023]
Abstract
Perturbations in iron homeostasis and iron accumulation feature in several neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD) and Amyotrophic lateral sclerosis (ALS). Proteins such as α-synuclein, tau and amyloid precursor protein that are pathologically associated with neurodegeneration are involved in molecular crosstalk with iron homeostatic proteins. Quantitative susceptibility mapping, an MRI based non-invasive technique, offers proximal evaluations of iron load in regions of the brain and powerfully predicts cognitive decline. Further, small molecules that target elevated iron have shown promise against PD and AD in preclinical studies and clinical trials. Despite these strong links between altered iron homeostasis and neurodegeneration the molecular biology to describe the association between enhanced iron levels and neuron death, synaptic impairment and cognitive decline is ill defined. In this review we discuss the current understanding of brain iron homeostasis and how it may be perturbed under pathological conditions. Further, we explore the ramifications of a novel cell death pathway called ferroptosis that has provided a fresh impetus to the "metal hypothesis" of neurodegeneration. While lipid peroxidation plays a central role in the execution of this cell death modality the removal of iron through chelation or genetic modifications appears to extinguish the ferroptotic pathway. Conversely, tissues that harbour elevated iron may be predisposed to ferroptotic damage. These emerging findings are of relevance to neurodegeneration where ferroptotic signalling may offer new targets to mitigate cell death and dysfunction.
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Affiliation(s)
- Shashank Masaldan
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Ashley I Bush
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia.
| | - David Devos
- Department of Neurology, ALS Center, Lille University, INSERM UMRS_1171, University Hospital Center, LICEND COEN Center, Lille, France; Department of Medical Pharmacology, Lille University, INSERM UMRS_1171, University Hospital Center, LICEND COEN Center, Lille, France
| | - Anne Sophie Rolland
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1171, University Hospital Center, LICEND COEN Center, Lille, France
| | - Caroline Moreau
- Department of Neurology, ALS Center, Lille University, INSERM UMRS_1171, University Hospital Center, LICEND COEN Center, Lille, France; Department of Medical Pharmacology, Lille University, INSERM UMRS_1171, University Hospital Center, LICEND COEN Center, Lille, France
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16
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Hua J, Lee S, Blair NIS, Wyss M, van Bergen JMG, Schreiner SJ, Kagerer SM, Leh SE, Gietl AF, Treyer V, Buck A, Nitsch RM, Pruessmann KP, Lu H, Van Zijl PCM, Albert M, Hock C, Unschuld PG. Increased cerebral blood volume in small arterial vessels is a correlate of amyloid-β-related cognitive decline. Neurobiol Aging 2019; 76:181-193. [PMID: 30738323 DOI: 10.1016/j.neurobiolaging.2019.01.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 01/01/2019] [Accepted: 01/02/2019] [Indexed: 12/22/2022]
Abstract
The protracted accumulation of amyloid-β (Aβ) is a major pathologic hallmark of Alzheimer's disease and may trigger secondary pathological processes that include neurovascular damage. This study was aimed at investigating long-term effects of Aβ burden on cerebral blood volume of arterioles and pial arteries (CBVa), possibly present before manifestation of dementia. Aβ burden was assessed by 11C Pittsburgh compound-B positron emission tomography in 22 controls and 18 persons with mild cognitive impairment (MCI), [ages: 75(±6) years]. After 2 years, inflow-based vascular space occupancy at ultra-high field strength of 7-Tesla was administered for measuring CBVa, and neuropsychological testing for cognitive decline. Crushing gradients were incorporated during MR-imaging to suppress signals from fast-flowing blood in large arteries, and thereby sensitize inflow-based vascular space occupancy to CBVa in pial arteries and arterioles. CBVa was significantly elevated in MCI compared to cognitively normal controls and regional CBVa related to local Aβ deposition. For both MCI and controls, Aβ burden and follow-up CBVa in several brain regions synergistically predicted cognitive decline over 2 years. Orbitofrontal CBVa was positively associated with apolipoprotein E e4 carrier status. Increased CBVa may reflect long-term effects of region-specific pathology associated with Aβ deposition. Additional studies are needed to clarify the role of the arteriolar system and the potential of CBVa as a biomarker for Aβ-related vascular downstream pathology.
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Affiliation(s)
- Jun Hua
- Neurosection, Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - SeungWook Lee
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nicholas I S Blair
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Wyss
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Jiri M G van Bergen
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland
| | - Simon J Schreiner
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - Sonja M Kagerer
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - Sandra E Leh
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland
| | - Anton F Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland; Department of Nuclear Medicine, University Hospital Zurich, Switzerland
| | - Alfred Buck
- Department of Nuclear Medicine, University Hospital Zurich, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Hanzhang Lu
- Neurosection, Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter C M Van Zijl
- Neurosection, Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland
| | - Paul G Unschuld
- Institute for Regenerative Medicine (IREM), University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland.
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17
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Fang J, Bao L, Li X, van Zijl PCM, Chen Z. Background field removal for susceptibility mapping of human brain with large susceptibility variations. Magn Reson Med 2018; 81:2025-2037. [PMID: 30298547 DOI: 10.1002/mrm.27492] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 07/19/2018] [Accepted: 07/19/2018] [Indexed: 01/01/2023]
Abstract
PURPOSE In quantitative susceptibility mapping (QSM) of human brain, the background field induced by air-tissue interface varies significantly with respect to the rotation angle between the head and the static field, which may result in substantial error in the estimated magnetic susceptibility values. The goal of this study was to develop a strategy to better remove such orientation dependent background field. METHODS An improved background field removal method is proposed based on the sophisticated harmonic artifact reduction for phase data using a region adaptive kernel (R-SHARP), named iRSHARP. It uses a spatially weighted spherical Gaussian kernel exploiting the amplitude, gradient, and wrap count of the phase map. The method was validated using both numerical simulations and in vivo human brain data at multiple head orientations. Performance was compared with the variable kernel (V-SHARP) and R-SHARP methods. RESULTS The proposed iRSHARP method showed improved background removal over R-SHARP while cutting the computational time in half. As compared to V-SHARP and R-SHARP, the iRSHARP generated local field and susceptibility maps showed fewer artifacts in regions of large susceptibility variations, and for the in vivo human brain, the susceptibilities of the deep gray matter nuclei were consistent with the in vivo gold-standard "Calculation of Susceptibility through Multiple Orientation Sampling" (COSMOS) values. CONCLUSION iRSHARP can remove the orientation dependent background field effectively. Using iRSHARP, the paranasal sinus regions can be preserved in the brain mask and the brain integrity was conserved, which may facilitate further data analysis and clinical application.
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Affiliation(s)
- Jinsheng Fang
- Department of Electronic Science, Xiamen University, Xiamen, China
| | - Lijun Bao
- Department of Electronic Science, Xiamen University, Xiamen, China
| | - Xu Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Zhong Chen
- Department of Electronic Science, Xiamen University, Xiamen, China
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18
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van Bergen JMG, Li X, Quevenco FC, Gietl AF, Treyer V, Meyer R, Buck A, Kaufmann PA, Nitsch RM, van Zijl PCM, Hock C, Unschuld PG. Simultaneous quantitative susceptibility mapping and Flutemetamol-PET suggests local correlation of iron and β-amyloid as an indicator of cognitive performance at high age. Neuroimage 2018; 174:308-316. [PMID: 29548847 DOI: 10.1016/j.neuroimage.2018.03.021] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 02/17/2018] [Accepted: 03/10/2018] [Indexed: 12/11/2022] Open
Abstract
The accumulation of β-amyloid plaques is a hallmark of Alzheimer's disease (AD), and recently published data suggest that increased brain iron burden may reflect pathologies that synergistically contribute to the development of cognitive dysfunction. While preclinical disease stages are considered most promising for therapeutic intervention, the link between emerging AD-pathology and earliest clinical symptoms remains largely unclear. In the current study we therefore investigated local correlations between iron and β-amyloid plaques, and their possible association with cognitive performance in healthy older adults. 116 older adults (mean age 75 ± 7.4 years) received neuropsychological testing to calculate a composite cognitive score of performance in episodic memory, executive functioning, attention, language and communication. All participants were scanned on a combined PET-MRI instrument and were administered T1-sequences for anatomical mapping, quantitative susceptibility mapping (QSM) for assessing iron, and 18F-Flutemetamol-PET for estimating β-amyloid plaque load. Biological parametric mapping (BPM) was used to generate masks indicating voxels with significant (p < 0.05) correlation between susceptibility and 18F-Flutemetamol-SUVR. We found a bilateral pattern of clusters characterized by a statistical relationship between magnetic susceptibility and 18F-Flutemetamol-SUVR, indicating local correlations between iron and β-amyloid plaque deposition. For two bilateral clusters, located in the frontal and temporal cortex, significant relationships (p<0.05) between local β-amyloid and the composite cognitive performance score could be observed. No relationship between whole-cortex β-amyloid plaque load and cognitive performance was observable. Our data suggest that the local correlation of β-amyloid plaque load and iron deposition may provide relevant information regarding cognitive performance of healthy older adults. Further studies are needed to clarify pathological correlates of the local interaction of β-amyloid, iron and other causes of altered magnetic susceptibility.
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Affiliation(s)
- J M G van Bergen
- Institute for Regenerative Medicine, University of Zurich, Switzerland.
| | - X Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - F C Quevenco
- Institute for Regenerative Medicine, University of Zurich, Switzerland
| | - A F Gietl
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Switzerland
| | - V Treyer
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - R Meyer
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Switzerland
| | - A Buck
- Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - P A Kaufmann
- Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - R M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Switzerland
| | - P C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - C Hock
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Switzerland
| | - P G Unschuld
- Institute for Regenerative Medicine, University of Zurich, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Switzerland
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