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Sun J, Xie Y, Li T, Zhao Y, Zhao W, Yu Z, Wang S, Zhang Y, Xue H, Chen Y, Sun Z, Zhang Z, Liu Y, Zhang N, Liu F. Causal relationships of grey matter structures in multiple sclerosis and neuromyelitis optica spectrum disorder: insights from Mendelian randomization. Brain Commun 2024; 6:fcae308. [PMID: 39318784 PMCID: PMC11420985 DOI: 10.1093/braincomms/fcae308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 05/17/2024] [Accepted: 09/10/2024] [Indexed: 09/26/2024] Open
Abstract
Multiple sclerosis and neuromyelitis optica spectrum disorder are two debilitating inflammatory demyelinating diseases of the CNS. Although grey matter alterations have been linked to both multiple sclerosis and neuromyelitis optica spectrum disorder in observational studies, it is unclear whether these associations indicate causal relationships between these diseases and grey matter changes. Therefore, we conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationships between 202 grey matter imaging-derived phenotypes (33 224 individuals) and multiple sclerosis (47 429 cases and 68 374 controls) as well as neuromyelitis optica spectrum disorder (215 cases and 1244 controls). Our results suggested that genetically predicted multiple sclerosis was positively associated with the surface area of the left parahippocampal gyrus (β = 0.018, P = 2.383 × 10-4) and negatively associated with the volumes of the bilateral caudate (left: β = -0.020, P = 7.203 × 10-5; right: β = -0.021, P = 3.274 × 10-5) and putamen nuclei (left: β = -0.030, P = 2.175 × 10-8; right: β = -0.024, P = 1.047 × 10-5). In addition, increased neuromyelitis optica spectrum disorder risk was associated with an increased surface area of the left paracentral gyrus (β = 0.023, P = 1.025 × 10-4). Conversely, no evidence was found for the causal impact of grey matter imaging-derived phenotypes on disease risk in the opposite direction. We provide suggestive evidence that genetically predicted multiple sclerosis and neuromyelitis optica spectrum disorder are associated with increased cortical surface area and decreased subcortical volume in specific regions. Our findings shed light on the associations of grey matter alterations with the risk of multiple sclerosis and neuromyelitis optica spectrum disorder.
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Affiliation(s)
- Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fujian 350005, China
| | - Tongli Li
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yunfei Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wenjin Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zeyang Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yujie Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhang Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
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Zivadinov R, Schweser F, Jakimovski D, Bergsland N, Dwyer MG. Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging. Neuroimaging Clin N Am 2024; 34:453-468. [PMID: 38942527 DOI: 10.1016/j.nic.2024.03.007] [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: 06/30/2024]
Abstract
Multiple sclerosis (MS) is increasingly understood not only as a white matter disease but also involving both the deep and cortical gray matter (GM). GM pathology in people with MS (pwMS) includes the presence of lesions, leptomeningeal inflammation, atrophy, altered iron concentration, and microstructural changes. Studies using 7T and 3T MR imaging with optimized protocols established that GM damage is a principal driver of disease progression in pwMS. Future work is needed to incorporate the assessment of these GM imaging biomarkers into the clinical workup of pwMS and the assessment of treatment efficacy.
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Affiliation(s)
- Robert Zivadinov
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA.
| | - Ferdinand Schweser
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Dejan Jakimovski
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Michael G Dwyer
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
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Mainero C, Treaba CA, Barbuti E. Imaging cortical lesions in multiple sclerosis. Curr Opin Neurol 2023; 36:222-228. [PMID: 37078649 DOI: 10.1097/wco.0000000000001152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
PURPOSE OF REVIEW Cortical lesions are an established pathological feature of multiple sclerosis, develop from the earliest disease stages and contribute to disease progression. Here, we discuss current imaging approaches for detecting cortical lesions in vivo and their contribution for improving our understanding of cortical lesion pathogenesis as well as their clinical significance. RECENT FINDINGS Although a variable portion of cortical lesions goes undetected at clinical field strength and even at ultra-high field MRI, their evaluation is still clinically relevant. Cortical lesions are important for differential multiple sclerosis (MS) diagnosis, have relevant prognostic value and independently predict disease progression. Some studies also show that cortical lesion assessment could be used as a therapeutic outcome target in clinical trials. Advances in ultra-high field MRI not only allow increased cortical lesion detection in vivo but also the disclosing of some interesting features of cortical lesions related to their pattern of development and evolution as well to the nature of associated pathological changes, which might prove relevant for better understanding the pathogenesis of these lesions. SUMMARY Despite some limitations, imaging of cortical lesions is of paramount importance in MS for elucidating disease mechanisms as well as for improving patient management in clinic.
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Affiliation(s)
- Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elena Barbuti
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Ospedale Sant'Andrea, University "La Sapienza", Rome, Italy
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Shen S, Cheng X, Zhou L, Zhao Y, Wang H, Zhang J, Sun X, Wang Y, Shu Y, Xu Y, Tao Y, Li M, Lu Z, Cai W, Nie G, Qiu W. Neutrophil Nanovesicle Protects against Experimental Autoimmune Encephalomyelitis through Enhancing Myelin Clearance by Microglia. ACS NANO 2022; 16:18886-18897. [PMID: 36288210 DOI: 10.1021/acsnano.2c07798] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Timely clearance of myelin debris is the premise of neuroinflammation termination and tissue regeneration in multiple sclerosis (MS). Microglia are the main scavengers of myelin debris in MS lesions, but its phagocytic capability is limited in MS patients. Here, we develop neutrophil-derived nanovesicles (NNVs) to enhance the efficiency of myelin debris clearance in microglia for MS therapy. RNA sequencing (RNAseq) results demonstrate that NNVs treatment ameliorates lesional neuroinflammation of experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. Consequently, EAE mice exhibit favorable neurological functions and white matter integrity after NNVs treatment. Specifically, NNVs treatment upregulates the expression of nuclear factor E2-related factor 2 (NRF2) in microglia, as revealed by Assay for Transposase Accessible Chromatin using sequencing (ATACseq). We also demonstrate that NRF2 can activate the transcription of RUBCN (RUN domain and cysteine-rich domain containing Beclin 1-interacting protein), which in turn enhances LC3-associated phagocytosis (LAP) in microglia. As a result, myelin debris engulfed by microglia can be efficiently catabolized in NNVs-treated EAE mice without obvious side effects. Together, this study proves that NNVs can modulate neuroinflammation by clearing myelin debris and is a promising MS treatment strategy.
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Affiliation(s)
- Shishi Shen
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
- CAS Key Laboratory for Biomedical Effects of Nanomaterials & Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Xi Cheng
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Luyao Zhou
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Yipeng Zhao
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Hai Wang
- CAS Key Laboratory for Biomedical Effects of Nanomaterials & Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jie Zhang
- CAS Key Laboratory for Biomedical Effects of Nanomaterials & Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Xiaobo Sun
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Yuge Wang
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Yaqing Shu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Yanteng Xu
- Laboratory of Biomaterials and Translational Medicine, Center for Nanomedicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Yu Tao
- Laboratory of Biomaterials and Translational Medicine, Center for Nanomedicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Mingqiang Li
- Laboratory of Biomaterials and Translational Medicine, Center for Nanomedicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Zhengqi Lu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Wei Cai
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Guangjun Nie
- CAS Key Laboratory for Biomedical Effects of Nanomaterials & Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Qiu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510000, China
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