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Rodriguez-Vieitez E, Kumar A, Malarte ML, Ioannou K, Rocha FM, Chiotis K. Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach. Methods Mol Biol 2024; 2785:195-218. [PMID: 38427196 DOI: 10.1007/978-1-0716-3774-6_13] [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] [Indexed: 03/02/2024]
Abstract
The recent progress in the development of in vivo biomarkers is rapidly changing how neurodegenerative diseases are conceptualized and diagnosed and how clinical trials are designed today. Alzheimer's disease (AD) - the most common neurodegenerative disorder - is characterized by a complex neuropathology involving the deposition of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) of hyperphosphorylated tau proteins, accompanied by the activation of glial cells, i.e., astrocytes and microglia, and neuroinflammatory response, leading to neurodegeneration and cognitive dysfunction. An increasing diversity of positron emission tomography (PET) imaging radiotracers is available to selectively target the different pathophysiological processes of AD. Along with the success of Aβ PET and the more recent tau PET imaging, there is a great interest to develop PET tracers to image glial reactivity and neuroinflammation. While most research to date has focused on imaging microgliosis, there is an upsurge of interest in imaging reactive astrocytes in the AD continuum. There is increasing evidence that reactive astrocytes are morphologically and functionally heterogeneous, with different subtypes that express different markers and display various homeostatic or detrimental roles across disease stages. Therefore, multiple biomarkers are desirable to unravel the complex phenomenon of reactive astrocytosis. In the field of in vivo PET imaging in AD, the research concerning reactive astrocytes has predominantly focused on targeting monoamine oxidase B (MAO-B), most often using either 11C-deuterium-L-deprenyl (11C-DED) or 18F-SMBT-1 PET tracers. Additionally, imidazoline2 binding (I2BS) sites have been imaged using 11C-BU99008 PET. Recent studies in our group using 11C-DED PET imaging suggest that astrocytosis may be present from the early stages of disease development in AD. This chapter provides a detailed description of the practical approach used for the analysis of 11C-DED PET imaging data in a multitracer PET paradigm including 11C-Pittsburgh compound B (11C-PiB) and 18F-fluorodeoxyglucose (18F-FDG). The multitracer PET approach allows investigating the comparative regional and temporal patterns of in vivo brain astrocytosis, fibrillar Aβ deposition, glucose metabolism, and brain structural changes. It may also contribute to understanding the potential role of novel plasma biomarkers of reactive astrocytes, in particular the glial fibrillary acidic protein (GFAP), at different stages of disease progression. This chapter attempts to stimulate further research in the field, including the development of novel PET tracers that may allow visualizing different aspects of the complex astrocytic and microglial response in neurodegenerative diseases. Progress in the field will contribute to the incorporation of PET imaging of glial reactivity and neuroinflammation as biomarkers with clinical application and motivate further investigation on glial cells as therapeutic targets in AD and other neurodegenerative diseases.
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Affiliation(s)
- Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
- Division of Neurogeriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | - Amit Kumar
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Mona-Lisa Malarte
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Ioannou
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Filipa M Rocha
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
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Nisar S, Haris M. Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder. Mol Psychiatry 2023; 28:4995-5008. [PMID: 37069342 DOI: 10.1038/s41380-023-02060-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 03/23/2023] [Accepted: 03/28/2023] [Indexed: 04/19/2023]
Abstract
Autism-spectrum disorders (ASDs) are developmental disabilities that manifest in early childhood and are characterized by qualitative abnormalities in social behaviors, communication skills, and restrictive or repetitive behaviors. To explore the neurobiological mechanisms in ASD, extensive research has been done to identify potential diagnostic biomarkers through a neuroimaging genetics approach. Neuroimaging genetics helps to identify ASD-risk genes that contribute to structural and functional variations in brain circuitry and validate biological changes by elucidating the mechanisms and pathways that confer genetic risk. Integrating artificial intelligence models with neuroimaging data lays the groundwork for accurate diagnosis and facilitates the identification of early diagnostic biomarkers for ASD. This review discusses the significance of neuroimaging genetics approaches to gaining a better understanding of the perturbed neurochemical system and molecular pathways in ASD and how these approaches can detect structural, functional, and metabolic changes and lead to the discovery of novel biomarkers for the early diagnosis of ASD.
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Affiliation(s)
- Sabah Nisar
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, Doha, Qatar
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Mohammad Haris
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, Doha, Qatar.
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Laboratory Animal Research Center, Qatar University, Doha, Qatar.
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Nam MH, Ko HY, Kim D, Lee S, Park YM, Hyeon SJ, Won W, Chung JI, Kim SY, Jo HH, Oh KT, Han YE, Lee GH, Ju YH, Lee H, Kim H, Heo J, Bhalla M, Kim KJ, Kwon J, Stein TD, Kong M, Lee H, Lee SE, Oh SJ, Chun JH, Park MA, Park KD, Ryu H, Yun M, Lee CJ. Visualizing reactive astrocyte-neuron interaction in Alzheimer's disease using 11C-acetate and 18F-FDG. Brain 2023; 146:2957-2974. [PMID: 37062541 PMCID: PMC10517195 DOI: 10.1093/brain/awad037] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 04/18/2023] Open
Abstract
Reactive astrogliosis is a hallmark of Alzheimer's disease (AD). However, a clinically validated neuroimaging probe to visualize the reactive astrogliosis is yet to be discovered. Here, we show that PET imaging with 11C-acetate and 18F-fluorodeoxyglucose (18F-FDG) functionally visualizes the reactive astrocyte-mediated neuronal hypometabolism in the brains with neuroinflammation and AD. To investigate the alterations of acetate and glucose metabolism in the diseased brains and their impact on the AD pathology, we adopted multifaceted approaches including microPET imaging, autoradiography, immunohistochemistry, metabolomics, and electrophysiology. Two AD rodent models, APP/PS1 and 5xFAD transgenic mice, one adenovirus-induced rat model of reactive astrogliosis, and post-mortem human brain tissues were used in this study. We further curated a proof-of-concept human study that included 11C-acetate and 18F-FDG PET imaging analyses along with neuropsychological assessments from 11 AD patients and 10 healthy control subjects. We demonstrate that reactive astrocytes excessively absorb acetate through elevated monocarboxylate transporter-1 (MCT1) in rodent models of both reactive astrogliosis and AD. The elevated acetate uptake is associated with reactive astrogliosis and boosts the aberrant astrocytic GABA synthesis when amyloid-β is present. The excessive astrocytic GABA subsequently suppresses neuronal activity, which could lead to glucose uptake through decreased glucose transporter-3 in the diseased brains. We further demonstrate that 11C-acetate uptake was significantly increased in the entorhinal cortex, hippocampus and temporo-parietal neocortex of the AD patients compared to the healthy controls, while 18F-FDG uptake was significantly reduced in the same regions. Additionally, we discover a strong correlation between the patients' cognitive function and the PET signals of both 11C-acetate and 18F-FDG. We demonstrate the potential value of PET imaging with 11C-acetate and 18F-FDG by visualizing reactive astrogliosis and the associated neuronal glucose hypometablosim for AD patients. Our findings further suggest that the acetate-boosted reactive astrocyte-neuron interaction could contribute to the cognitive decline in AD.
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Affiliation(s)
- Min-Ho Nam
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Department of KHU-KIST Convergence Science and Technology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Hae Young Ko
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Dongwoo Kim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Sangwon Lee
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Yongmin Mason Park
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
- IBS School, University of Science and Technology, Daejeon 34126, Republic of Korea
| | - Seung Jae Hyeon
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Woojin Won
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Jee-In Chung
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Seon Yoo Kim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Han Hee Jo
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Kyeong Taek Oh
- Department of Medical Engineering, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Young-Eun Han
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Gwan-Ho Lee
- Research Resources Division, KIST, Seoul 02792, Republic of Korea
| | - Yeon Ha Ju
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
- IBS School, University of Science and Technology, Daejeon 34126, Republic of Korea
| | - Hyowon Lee
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Hyunjin Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Department of KHU-KIST Convergence Science and Technology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Jaejun Heo
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Mridula Bhalla
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
- IBS School, University of Science and Technology, Daejeon 34126, Republic of Korea
| | - Ki Jung Kim
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Jea Kwon
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Thor D Stein
- Boston University Alzheimer’s Disease Research Center and Department of Pathology, Chobanian and Avedisian Boston University School of Medicine, Boston, MA 02130, USA
| | - Mingyu Kong
- Molecular Recognition Research Center, KIST, Seoul 02792, Republic of Korea
| | - Hyunbeom Lee
- Molecular Recognition Research Center, KIST, Seoul 02792, Republic of Korea
| | - Seung Eun Lee
- Research Resources Division, KIST, Seoul 02792, Republic of Korea
| | - Soo-Jin Oh
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Joong-Hyun Chun
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Mi-Ae Park
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Ki Duk Park
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Hoon Ryu
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Boston University Alzheimer’s Disease Research Center and Department of Pathology, Chobanian and Avedisian Boston University School of Medicine, Boston, MA 02130, USA
| | - Mijin Yun
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - C Justin Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea
- IBS School, University of Science and Technology, Daejeon 34126, Republic of Korea
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Westi EW, Andersen JV, Aldana BI. Using stable isotope tracing to unravel the metabolic components of neurodegeneration: Focus on neuron-glia metabolic interactions. Neurobiol Dis 2023; 182:106145. [PMID: 37150307 DOI: 10.1016/j.nbd.2023.106145] [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: 02/23/2023] [Revised: 04/17/2023] [Accepted: 05/04/2023] [Indexed: 05/09/2023] Open
Abstract
Disrupted brain metabolism is a critical component of several neurodegenerative diseases. Energy metabolism of both neurons and astrocytes is closely connected to neurotransmitter recycling via the glutamate/GABA-glutamine cycle. Neurons and astrocytes hereby work in close metabolic collaboration which is essential to sustain neurotransmission. Elucidating the mechanistic involvement of altered brain metabolism in disease progression has been aided by the advance of techniques to monitor cellular metabolism, in particular by mapping metabolism of substrates containing stable isotopes, a technique known as isotope tracing. Here we review key aspects of isotope tracing including advantages, drawbacks and applications to different cerebral preparations. In addition, we narrate how isotope tracing has facilitated the discovery of central metabolic features in neurodegeneration with a focus on the metabolic cooperation between neurons and astrocytes.
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Affiliation(s)
- Emil W Westi
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Jens V Andersen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Blanca I Aldana
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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Andersen JV, Schousboe A, Verkhratsky A. Astrocyte energy and neurotransmitter metabolism in Alzheimer's disease: integration of the glutamate/GABA-glutamine cycle. Prog Neurobiol 2022; 217:102331. [PMID: 35872221 DOI: 10.1016/j.pneurobio.2022.102331] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/14/2022] [Accepted: 07/19/2022] [Indexed: 02/06/2023]
Abstract
Astrocytes contribute to the complex cellular pathology of Alzheimer's disease (AD). Neurons and astrocytes function in close collaboration through neurotransmitter recycling, collectively known as the glutamate/GABA-glutamine cycle, which is essential to sustain neurotransmission. Neurotransmitter recycling is intimately linked to astrocyte energy metabolism. In the course of AD, astrocytes undergo extensive metabolic remodeling, which may profoundly affect the glutamate/GABA-glutamine cycle. The consequences of altered astrocyte function and metabolism in relation to neurotransmitter recycling are yet to be comprehended. Metabolic alterations of astrocytes in AD deprive neurons of metabolic support, thereby contributing to synaptic dysfunction and neurodegeneration. In addition, several astrocyte-specific components of the glutamate/GABA-glutamine cycle, including glutamine synthesis and synaptic neurotransmitter uptake, are perturbed in AD. Integration of the complex astrocyte biology within the context of AD is essential for understanding the fundamental mechanisms of the disease, while restoring astrocyte metabolism may serve as an approach to arrest or even revert clinical progression of AD.
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Affiliation(s)
- Jens V Andersen
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
| | - Arne Schousboe
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Alexei Verkhratsky
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Achucarro Center for Neuroscience, IKERBASQUE, 48011 Bilbao, Spain; Department of Stem Cell Biology, State Research Institute Centre for Innovative Medicine, LT-01102 Vilnius, Lithuania.
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7
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Duong MT, Das SR, Lyu X, Xie L, Richardson H, Xie SX, Yushkevich PA, Wolk DA, Nasrallah IM. Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer's disease. Nat Commun 2022; 13:1495. [PMID: 35314672 PMCID: PMC8938426 DOI: 10.1038/s41467-022-28941-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 02/11/2022] [Indexed: 11/08/2022] Open
Abstract
Alzheimer's disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer's Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.
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Affiliation(s)
- Michael Tran Duong
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandhitsu R Das
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xueying Lyu
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hayley Richardson
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon X Xie
- Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul A Yushkevich
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ilya M Nasrallah
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
- Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Potential of Multiscale Astrocyte Imaging for Revealing Mechanisms Underlying Neurodevelopmental Disorders. Int J Mol Sci 2021; 22:ijms221910312. [PMID: 34638653 PMCID: PMC8508625 DOI: 10.3390/ijms221910312] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 01/18/2023] Open
Abstract
Astrocytes provide trophic and metabolic support to neurons and modulate circuit formation during development. In addition, astrocytes help maintain neuronal homeostasis through neurovascular coupling, blood-brain barrier maintenance, clearance of metabolites and nonfunctional proteins via the glymphatic system, extracellular potassium buffering, and regulation of synaptic activity. Thus, astrocyte dysfunction may contribute to a myriad of neurological disorders. Indeed, astrocyte dysfunction during development has been implicated in Rett disease, Alexander's disease, epilepsy, and autism, among other disorders. Numerous disease model mice have been established to investigate these diseases, but important preclinical findings on etiology and pathophysiology have not translated into clinical interventions. A multidisciplinary approach is required to elucidate the mechanism of these diseases because astrocyte dysfunction can result in altered neuronal connectivity, morphology, and activity. Recent progress in neuroimaging techniques has enabled noninvasive investigations of brain structure and function at multiple spatiotemporal scales, and these technologies are expected to facilitate the translation of preclinical findings to clinical studies and ultimately to clinical trials. Here, we review recent progress on astrocyte contributions to neurodevelopmental and neuropsychiatric disorders revealed using novel imaging techniques, from microscopy scale to mesoscopic scale.
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Zhou R, Ji B, Kong Y, Qin L, Ren W, Guan Y, Ni R. PET Imaging of Neuroinflammation in Alzheimer's Disease. Front Immunol 2021; 12:739130. [PMID: 34603323 PMCID: PMC8481830 DOI: 10.3389/fimmu.2021.739130] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 08/27/2021] [Indexed: 12/15/2022] Open
Abstract
Neuroinflammation play an important role in Alzheimer's disease pathogenesis. Advances in molecular imaging using positron emission tomography have provided insights into the time course of neuroinflammation and its relation with Alzheimer's disease central pathologies in patients and in animal disease models. Recent single-cell sequencing and transcriptomics indicate dynamic disease-associated microglia and astrocyte profiles in Alzheimer's disease. Mitochondrial 18-kDa translocator protein is the most widely investigated target for neuroinflammation imaging. New generation of translocator protein tracers with improved performance have been developed and evaluated along with tau and amyloid imaging for assessing the disease progression in Alzheimer's disease continuum. Given that translocator protein is not exclusively expressed in glia, alternative targets are under rapid development, such as monoamine oxidase B, matrix metalloproteinases, colony-stimulating factor 1 receptor, imidazoline-2 binding sites, cyclooxygenase, cannabinoid-2 receptor, purinergic P2X7 receptor, P2Y12 receptor, the fractalkine receptor, triggering receptor expressed on myeloid cells 2, and receptor for advanced glycation end products. Promising targets should demonstrate a higher specificity for cellular locations with exclusive expression in microglia or astrocyte and activation status (pro- or anti-inflammatory) with highly specific ligand to enable in vivo brain imaging. In this review, we summarised recent advances in the development of neuroinflammation imaging tracers and provided an outlook for promising targets in the future.
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Affiliation(s)
- Rong Zhou
- Department of Nephrology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Bin Ji
- Department of Radiopharmacy and Molecular Imaging, School of Pharmacy, Fudan University, Shanghai, China
| | - Yanyan Kong
- Positron Emission Tomography (PET) Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Limei Qin
- Inner Mongolia Baicaotang Qin Chinese Mongolia Hospital, Hohhot, China
| | - Wuwei Ren
- School of Information Science and Technology, Shanghaitech University, Shanghai, China
| | - Yihui Guan
- Positron Emission Tomography (PET) Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ruiqing Ni
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, University of Zurich & Eidgenössische Technische Hochschule Zürich (ETH Zurich), Zurich, Switzerland
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