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Fang K, Hou Y, Niu L, Han S, Zhang W. Individualized gray matter morphological abnormalities uncover two robust transdiagnostic biotypes. J Affect Disord 2024; 365:193-204. [PMID: 39173920 DOI: 10.1016/j.jad.2024.08.102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 07/22/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024]
Abstract
Psychiatric disorders exhibit a shared neuropathology, yet the diverse presentations among patients necessitate the identification of transdiagnostic subtypes to enhance diagnostic and treatment strategies. This study aims to unveil potential transdiagnostic subtypes based on personalized gray matter morphological abnormalities. A total of 496 patients with psychiatric disorders and 255 healthy controls (HCs) from three distinct datasets (one for discovery and two for validation) were enrolled. Individualized gray matter morphological abnormalities were determined using normative modeling to identify transdiagnostic subtypes. In the discovery dataset, two transdiagnostic subtypes with contrasting patterns of structural abnormalities compared to HCs were identified. Reproducibility and generalizability analyses demonstrated that these subtypes could be generalized to new patients and even to new disorders in the validation datasets. These subtypes were characterized by distinct disease epicenters. The gray matter abnormal pattern in subtype 1 was mainly linked to excitatory receptors, whereas subtype 2 showed a predominant association with inhibitory receptors. Furthermore, we observed that the gray matter abnormal pattern in subtype 2 was correlated with transcriptional profiles of inflammation-related genes, while subtype 1 did not show this association. Our findings reveal two robust transdiagnostic biotypes, offering novel insights into psychiatric nosology.
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Affiliation(s)
- Keke Fang
- Department of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, China; Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, China; Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, China
| | - Ying Hou
- Department of ultrasound, the affiliated cancer hospital of Zhengzhou University & Henan Cancer Hospital, China
| | - Lianjie Niu
- Department of Breast Disease, Henan Breast Cancer Center, the affiliated Cancer Hidospital of Zhengzhou University & Henan Cancer Hospital, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Henan Province, China.
| | - Wenzhou Zhang
- Department of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, China; Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, China; Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, China.
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2
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Zhukovsky P, Ironside M, Duda JM, Moser AD, Null KE, Dhaynaut M, Normandin M, Guehl NJ, El Fakhri G, Alexander M, Holsen LM, Misra M, Narendran R, Hoye JM, Morris ED, Esfand SM, Goldstein JM, Pizzagalli DA. Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for μ and κ Opioid Receptors. Biol Psychiatry 2024; 96:717-726. [PMID: 38395372 PMCID: PMC11339240 DOI: 10.1016/j.biopsych.2024.02.005] [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: 09/05/2023] [Revised: 01/22/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024]
Abstract
BACKGROUND Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps. METHODS Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABAA (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography. RESULTS Results revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies. CONCLUSIONS Acute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in μ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD.
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MESH Headings
- Humans
- Receptors, Opioid, kappa/genetics
- Receptors, Opioid, kappa/metabolism
- Male
- Female
- Adult
- Depressive Disorder, Major/diagnostic imaging
- Depressive Disorder, Major/metabolism
- Depressive Disorder, Major/physiopathology
- Depressive Disorder, Major/genetics
- Stress, Psychological/metabolism
- Stress, Psychological/physiopathology
- Stress, Psychological/diagnostic imaging
- Receptors, Opioid, mu/genetics
- Receptors, Opioid, mu/metabolism
- Magnetic Resonance Imaging
- Cerebral Cortex/diagnostic imaging
- Cerebral Cortex/metabolism
- Cerebral Cortex/physiopathology
- Corpus Striatum/diagnostic imaging
- Corpus Striatum/metabolism
- Young Adult
- Positron-Emission Tomography
- Neural Pathways/diagnostic imaging
- Neural Pathways/physiopathology
- Connectome
- Nerve Net/diagnostic imaging
- Nerve Net/metabolism
- Nerve Net/physiopathology
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Affiliation(s)
- Peter Zhukovsky
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts
| | - Maria Ironside
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts; Laureate Institute for Brain Research, The University of Tulsa, Tulsa, Oklahoma
| | - Jessica M Duda
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts
| | - Amelia D Moser
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Kaylee E Null
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts; Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Maeva Dhaynaut
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marc Normandin
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nicolas J Guehl
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Madeline Alexander
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts
| | - Laura M Holsen
- Division of Women's Health, Brigham and Women's Hospital, Boston, Massachusetts; Innovation Center on Sex Differences in Medicine, Massachusetts General Hospital, Massachusetts General Hospital Research Institute, Harvard Medical School, Boston, Massachusetts; Clinical Neuroscience Laboratory of Sex Differences in the Brain, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Madhusmita Misra
- Division of Pediatric Endocrinology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rajesh Narendran
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jocelyn M Hoye
- Yale Positron Emission Tomography Center, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Evan D Morris
- Yale Positron Emission Tomography Center, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Shiba M Esfand
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jill M Goldstein
- Department of Psychology, Yale University, New Haven, Connecticut; Division of Women's Health, Brigham and Women's Hospital, Boston, Massachusetts; Innovation Center on Sex Differences in Medicine, Massachusetts General Hospital, Massachusetts General Hospital Research Institute, Harvard Medical School, Boston, Massachusetts; Clinical Neuroscience Laboratory of Sex Differences in the Brain, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Departments of Psychiatry and Medicine, Harvard Medical School, Boston, Massachusetts
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts.
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Huang T, Hua Q, Zhao X, Tian W, Cao H, Xu W, Sun J, Zhang L, Wang K, Ji GJ. Abnormal functional lateralization and cooperation in bipolar disorder are associated with neurotransmitter and cellular profiles. J Affect Disord 2024; 369:970-977. [PMID: 39447972 DOI: 10.1016/j.jad.2024.10.108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 10/18/2024] [Accepted: 10/21/2024] [Indexed: 10/26/2024]
Abstract
BACKGROUND Hemispheric lateralization and cooperation are essential for efficient brain function, and aberrations in both have been found in psychiatric disorders such as schizophrenia. This study investigated alterations in hemispheric lateralization and cooperation among patients with bipolar disorder (BD) and associations with neurotransmitter and cell-type density distributions to identify potential molecular and cellular pathomechanisms. METHODS Sixty-seven BD patients and 127 healthy controls (HCs) were examined by resting-state functional MRI (rs-fMRI). Whole-brain maps of the autonomy index (AI) and connectivity between functionally homotopic voxels (CFH) were constructed to reveal BD-specific changes in brain functional lateralization and interhemispheric cooperation, respectively. Spatial associations of regional AI and CFH abnormalities with neurotransmitter and cell-type density distributions were examined by correlation analyses. RESULTS Bipolar disorder patients exhibited higher AI values in left superior parietal gyrus, cerebellar right Crus I, and cerebellar right Crus II, and these regional abnormalities were associated with the relative densities (proportions) of oligodendrocyte precursor cells and microglia. Patients also exhibited lower CFH values in right inferior parietal gyrus, bilateral middle occipital gyrus, left postcentral gyrus, and bilateral cerebellar crus II, and these regional abnormalities were associated with the densities of serotonin 1A and dopamine D2 receptors, oligodendrocyte precursor cells, astrocytes, and neurons. CONCLUSIONS These findings indicate that abnormal functional lateralization and cooperation in BD with potential molecular and cellular basis.
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Affiliation(s)
- Tongqing Huang
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Xiya Zhao
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Weichao Tian
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Hai Cao
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Wenqiang Xu
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Li Zhang
- Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Hefei, Anhui Province, China.
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
| | - Gong-Jun Ji
- School of Mental Health and Psychological Sciences, Anhui Medical University, 81 Meishan Rd, Hefei 230032, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
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Xu X, Zhao H, Song Y, Cai H, Zhao W, Tang J, Zhu J, Yu Y. Molecular mechanisms underlying the neural correlates of working memory. BMC Biol 2024; 22:238. [PMID: 39428484 PMCID: PMC11492763 DOI: 10.1186/s12915-024-02039-0] [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: 10/14/2023] [Accepted: 10/11/2024] [Indexed: 10/22/2024] Open
Abstract
BACKGROUND Working memory (WM), a core component of executive functions, relies on a dedicated brain system that maintains and stores information in the short term. While extensive neuroimaging research has identified a distributed set of neural substrates relevant to WM, their underlying molecular mechanisms remain enigmatic. This study investigated the neural correlates of WM as well as their underlying molecular mechanisms. RESULTS Our voxel-wise analyses of resting-state functional MRI data from 502 healthy young adults showed that better WM performance (higher accuracy and shorter reaction time of the 3-back task) was associated with lower functional connectivity density (FCD) in the left inferior temporal gyrus and higher FCD in the left anterior cingulate cortex. A combination of transcriptome-neuroimaging spatial correlation and the ensemble-based gene category enrichment analysis revealed that the identified neural correlates of WM were associated with expression of diverse gene categories involving important cortical components and their biological processes as well as sodium channels. Cross-region spatial correlation analyses demonstrated significant associations between the neural correlates of WM and a range of neurotransmitters including dopamine, glutamate, serotonin, and acetylcholine. CONCLUSIONS These findings may help to shed light on the molecular mechanisms underlying the neural correlates of WM.
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Affiliation(s)
- Xiaotao Xu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China
| | - Han Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China
| | - Yu Song
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China
| | - Jin Tang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230026, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China.
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China.
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China.
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, 230032, China.
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Liu C, Zhuang K, Zeitlen DC, Chen Q, Wang X, Feng Q, Beaty RE, Qiu J. Neural, genetic, and cognitive signatures of creativity. Commun Biol 2024; 7:1324. [PMID: 39402209 PMCID: PMC11473644 DOI: 10.1038/s42003-024-07007-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 10/02/2024] [Indexed: 10/19/2024] Open
Abstract
Creativity is typically operationalized as divergent thinking (DT) ability, a form of higher-order cognition which relies on memory, attention, and other component processes. Despite recent advances, creativity neuroscience lacks a unified framework to model its complexity across neural, genetic, and cognitive scales. Using task-based fMRI from two independent samples and MVPA, we identified a neural pattern that predicts DT, validated through cognitive decoding, genetic data, and large-scale resting-state fMRI. Our findings reveal that DT neural patterns span brain regions associated with diverse cognitive functions, with positive weights in the default mode and frontoparietal control networks and negative weights in the visual network. The high correlation with the primary gradient of functional connectivity suggests that DT involves extensive integration from concrete sensory information to abstract, higher-level cognition, distinguishing it from other advanced cognitive functions. Moreover, neurobiological analyses show that the DT pattern is positively correlated with dopamine-related neurotransmitters and genes influencing neurotransmitter release, advancing the neurobiological understanding of creativity.
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Affiliation(s)
- Cheng Liu
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Kaixiang Zhuang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Daniel C Zeitlen
- Department of Psychology, Pennsylvania State University, Pennsylvania, USA
| | - Qunlin Chen
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Xueyang Wang
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Qiuyang Feng
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Roger E Beaty
- Department of Psychology, Pennsylvania State University, Pennsylvania, USA
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China.
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Sun J, Dang J, Zhang M, Niu X, Tao Q, Kang Y, Ma L, Mei B, Wei Y, Wang W, Han S, Cheng J, Zhang Y. Altered functional connectivity within the primary visual networks and neurotransmitter activity in male smokers: A group ICA study. Brain Res Bull 2024; 218:111098. [PMID: 39389149 DOI: 10.1016/j.brainresbull.2024.111098] [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: 02/03/2024] [Revised: 10/06/2024] [Accepted: 10/07/2024] [Indexed: 10/12/2024]
Abstract
Smoking puts patients at high risk for cognitive and psychiatric disorders. The aim of this study was to explore the effects of nicotine use on primary visual network (PVN) and its association with neurotransmitters. A total of 59 tobacco use disorder (TUD) patients and 51 healthy controls (HC) participated in this study and underwent resting state functional magnetic resonance imaging scans. Functional connectivity (FC) within the network was explored using independent component analysis. In addition, the spatial correlations of PVN changes with neurotransmitters and their correlations with clinical characteristics of patients were evaluated using the JuSpace toolbox and SPSS. We found reduced FC within the PVN in patients with TUD compared with HC. In terms of relevant analysis, there is a spatial correlation between FC changes in the patient's PVN and a higher distribution of dopamine receptor and gamma-aminobutyric acid receptor. This study revealed changes in the FC and neurotransmitters of the PVN in patients with TUD, expanding the potential neural mechanisms underlying sensory perception and psychiatric disorders.
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Affiliation(s)
- Jieping Sun
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Yimeng Kang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Longyao Ma
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Bohui Mei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for functional magnetic resonance imaging and molecular imaging of Henan Province, Henan Province, China.
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Sun J, Zhang M, Dang J, Niu X, Tao Q, Kang Y, Ma L, Mei B, Wei Y, Wang W, Han S, Cheng J, Zhang Y. Mapping brain activity and neurotransmitters pre-cigarette smoking evolution: A study of male subjects. J Psychiatr Res 2024; 180:39-46. [PMID: 39369637 DOI: 10.1016/j.jpsychires.2024.09.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 09/22/2024] [Accepted: 09/29/2024] [Indexed: 10/08/2024]
Abstract
BACKGROUND The impact of tobacco smoking on global health persists and it is essential to understand the progression of addiction and the involvement of neurotransmitters. METHODS This study assessed 47 participants with tobacco use disorder (TUD) categorized based on changes in Fagerström Test for Nicotine Dependence (FTND) scores over 6 years: progressive TUD (pTUD), regressive TUD (rTUD), and stable TUD (sTUD). Additionally, 35 healthy controls were included. Resting-state functional magnetic resonance imaging was used to evaluate brain regional homogeneity (ReHo) and correlations with neurotransmitter distributions using JuSpace. RESULTS Significant differences in ReHo were observed among pTUD, rTUD, sTUD, and controls. After strict Bonferroni correction, rTUD exhibited increased ReHo in the dorsolateral superior frontal gyrus compared to sTUD (p < 0.001) and controls (p < 0.001). Both pTUD (p < 0.001) and rTUD (p < 0.001) showed decreased ReHo in the superior temporal gyrus compared to sTUD. sTUD had increased ReHo in the supramarginal gyrus compared to all other groups (p < 0.001, p < 0.001, p = 0.002, separately). The strongest association, which survived rigorous Bonferroni correction, was between the ReHo changes in rTUD compared to sTUD and neurotransmitter distribution. This includes 5-hydroxytryptamine receptor 2A (p = 0.001), gamma-aminobutyric acid type A receptor (p < 0.001), norepinephrine transporter (p < 0.001), and N-Methyl-D-Aspartate (p = 0.002). CONCLUSIONS This study provides insights into how smoking behaviors correlate with alterations in brain activity and neurotransmitter function. By elucidating these neural links to tobacco use disorder progression, our findings contribute to a deeper understanding of smoking's neurological impact and potentially inform more targeted therapeutic strategies.
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Affiliation(s)
- Jieping Sun
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Yimeng Kang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Longyao Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Bohui Mei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China.
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8
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Kasper J, Caspers S, Lotter LD, Hoffstaedter F, Eickhoff SB, Dukart J. Resting-State Changes in Aging and Parkinson's Disease Are Shaped by Underlying Neurotransmission: A Normative Modeling Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:986-997. [PMID: 38679325 DOI: 10.1016/j.bpsc.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 03/15/2024] [Accepted: 04/16/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND Human healthy and pathological aging is linked to a steady decline in brain resting-state activity and connectivity measures. The neurophysiological mechanisms that underlie these changes remain poorly understood. METHODS Making use of recent developments in normative modeling and availability of in vivo maps for various neurochemical systems, we tested in the UK Biobank cohort (n = 25,917) whether and how age- and Parkinson's disease-related resting-state changes in commonly applied local and global activity and connectivity measures colocalize with underlying neurotransmitter systems. RESULTS We found that the distributions of several major neurotransmitter systems including serotonergic, dopaminergic, noradrenergic, and glutamatergic neurotransmission correlated with age-related changes across functional activity and connectivity measures. Colocalization patterns in Parkinson's disease deviated from normative aging trajectories for these, as well as for cholinergic and GABAergic (gamma-aminobutyric acidergic) neurotransmission. The deviation from normal colocalization of brain function and GABAA correlated with disease duration. CONCLUSIONS These findings provide new insights into molecular mechanisms underlying age- and Parkinson's-related brain functional changes by extending the existing evidence elucidating the vulnerability of specific neurochemical attributes to normal aging and Parkinson's disease. The results particularly indicate that alongside dopamine and serotonin, increased vulnerability of glutamatergic, cholinergic, and GABAergic systems may also contribute to Parkinson's disease-related functional alterations. Combining normative modeling and neurotransmitter mapping may aid future research and drug development through deeper understanding of neurophysiological mechanisms that underlie specific clinical conditions.
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Affiliation(s)
- Jan Kasper
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Svenja Caspers
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Leon D Lotter
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany; Max Planck School of Cognition, Leipzig, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Juergen Dukart
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany.
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9
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Khan AF, Iturria-Medina Y. Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms. Transl Psychiatry 2024; 14:386. [PMID: 39313512 PMCID: PMC11420368 DOI: 10.1038/s41398-024-03073-w] [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: 02/01/2024] [Revised: 08/20/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024] Open
Abstract
From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.
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Affiliation(s)
- Ahmed Faraz Khan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada.
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10
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Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère ML, Artiges E, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development correlate with underlying neurobiology. Nat Commun 2024; 15:7987. [PMID: 39284858 PMCID: PMC11405413 DOI: 10.1038/s41467-024-52366-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 08/29/2024] [Indexed: 09/22/2024] Open
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
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Affiliation(s)
- Leon D Lotter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
- Max Planck School of Cognition; Stephanstrasse 1A, Leipzig, Germany.
| | - Amin Saberi
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Casey Paquola
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham; University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB); Braunschweig and Berlin, Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
- Department of Psychiatry, EPS Barthélémy Durand, Etampes, France
| | | | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Frauke Nees
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim-Heidelberg-Ulm, Heidelberg, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
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11
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Fang P, Gao Y, Li Y, Li C, Zhang T, Wu L, Zhu Y, Xie Y. Effects of computerized working memory training on neuroplasticity in healthy individuals: A combined neuroimaging and neurotransmitter study. Neuroimage 2024; 298:120785. [PMID: 39154869 DOI: 10.1016/j.neuroimage.2024.120785] [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: 12/16/2023] [Revised: 08/09/2024] [Accepted: 08/12/2024] [Indexed: 08/20/2024] Open
Abstract
Working memory (WM) is an essential cognitive function that underpins various higher-order cognitive processes. Improving WM capacity through targeted training interventions has emergered as a potential approach for enhancing cognitive abilities. The present study employed an 8-week regimen of computerized WM training (WMT) to investigate its effect on neuroplasticity in healthy individuals, utilizing neuroimaging data gathered both before and after the training. The key metrics assessed included the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and the spatial distribution correlations of neurotransmitter. The results indicated that post-training, compared to baseline, there was a reduction in ALFF in the medial superior frontal gyrus and an elevation in ALFF in the left middle occipital gyrus within the training group. In comparison to the control group, the training group also exhibited decreased ALFF in the anterior cingulate cortex, angular gyrus, and superior parietal lobule, along with increased ALFF in the postcentral gyrus post-training. VBM analysis revealed a significant increase in gray matter volume (GMV) in the right dorsal superior frontal gyrus after the training period, compared to the initial baseline measurement. Furthermore, the training group showed GMV increases in the dorsal superior frontal gyrus, Rolandic operculum, precentral gyrus, and postcentral gyrus when compared to the control group. In addition, significant associations were identifed between neuroimaging measurements (AFLL and VBM) and the spatial patterns of neurotransmitters such as serotonin (5-HT), dopamine (DA), and N-methyl-D-aspartate (NMDA), providing insights into the underlying neurochemical processes. These findings clarify the neuroplastic changes caused by WMT, offering a deeper understanding of brain plasticity and highlighting the potential advantages of cognitive training interventions.
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Affiliation(s)
- Peng Fang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China; Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Xi'an, China; Military Medical Innovation Center, Fourth Military Medical University, Xi'an, China; School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Yuntao Gao
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Yijun Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Chenxi Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Tian Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Lin Wu
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Yuanjun Xie
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China.
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12
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Luppi AI, Singleton SP, Hansen JY, Jamison KW, Bzdok D, Kuceyeski A, Betzel RF, Misic B. Contributions of network structure, chemoarchitecture and diagnostic categories to transitions between cognitive topographies. Nat Biomed Eng 2024; 8:1142-1161. [PMID: 39103509 PMCID: PMC11410673 DOI: 10.1038/s41551-024-01242-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/02/2024] [Indexed: 08/07/2024]
Abstract
The mechanisms linking the brain's network structure to cognitively relevant activation patterns remain largely unknown. Here, by leveraging principles of network control, we show how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic database. Specifically, we systematically integrated large-scale multimodal neuroimaging data from functional magnetic resonance imaging, diffusion tractography, cortical morphometry and positron emission tomography to simulate how anatomically guided transitions between cognitive states can be reshaped by neurotransmitter engagement or by changes in cortical thickness. Our model incorporates neurotransmitter-receptor density maps (18 receptors and transporters) and maps of cortical thickness pertaining to a wide range of mental health, neurodegenerative, psychiatric and neurodevelopmental diagnostic categories (17,000 patients and 22,000 controls). The results provide a comprehensive look-up table charting how brain network organization and chemoarchitecture interact to manifest different cognitive topographies, and establish a principled foundation for the systematic identification of ways to promote selective transitions between cognitive topographies.
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Affiliation(s)
- Andrea I Luppi
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
| | - S Parker Singleton
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Keith W Jamison
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Danilo Bzdok
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- MILA, Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Richard F Betzel
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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13
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Chu T, Si X, Xie H, Ma H, Shi Y, Yao W, Xing D, Zhao F, Dong F, Gai Q, Che K, Guo Y, Chen D, Ming D, Mao N. Regional structural-functional connectivity coupling in major depressive disorder is associated with neurotransmitter and genetic profiles. Biol Psychiatry 2024:S0006-3223(24)01555-5. [PMID: 39218135 DOI: 10.1016/j.biopsych.2024.08.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 08/03/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms underlying regional SC-FC coupling patterns are not well understood. METHODS We enrolled 182 patients with MDD and 157 healthy control (HC) subjects, quantifying the intergroup differences in regional SC-FC coupling. The extreme gradient boosting (XGBoost), support vector machines (SVM) and random forest (RF) models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression. RESULTS We observed increased regional SC-FC coupling in default mode network (T = 3.233) and decreased coupling in frontoparietal network (T = -3.471) in MDD relative to HC. XGBoost (AUC = 0.853), SVM (AUC = 0.832) and RF (p < 0.05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of four neurotransmitters (p < 0.05) and expression maps of specific genes. These genes were strongly enriched in genes implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on two brain atlases. CONCLUSIONS This work enhances our understanding of MDD and pave the way for the development of additional targeted therapeutic interventions.
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Affiliation(s)
- Tongpeng Chu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China, 300072; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin, China, 300072; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China, 300392; Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin University, Tianjin, China, 300072; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases (Yantai Yuhuangding Hospital); Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China, 300072; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin, China, 300072; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China, 300392; Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin University, Tianjin, China, 300072
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Wei Yao
- Department of Neurology, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong, P. R. China, 253000
| | - Dong Xing
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Feng Zhao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, Shandong, P. R. China, 264000
| | - Fanghui Dong
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Qun Gai
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000
| | - Yuting Guo
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, P. R. China, 264000
| | - Danni Chen
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, P. R. China, 264000
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China, 300072; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin, China, 300072; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China, 300392; Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin University, Tianjin, China, 300072
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases (Yantai Yuhuangding Hospital); Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, P. R. China, 264000.
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14
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Cao H, Sun J, Hua Q, Huang T, Wei Y, Zhan Y, Yao X, Zhang T, Yang Y, Xu W, Bai T, Tian Y, Zhang L, Wang K, Ji GJ. Decreased inter-hemispheric cooperation in major depressive disorder and its association with neurotransmitter profiles. J Affect Disord 2024; 359:109-116. [PMID: 38768823 DOI: 10.1016/j.jad.2024.05.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 05/09/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Inter-hemispheric cooperation is a prominent feature of the human brain, and previous neuroimaging studies have revealed aberrant inter-hemispheric cooperation patterns in patients with major depressive disorder (MDD). Typically, inter-hemispheric cooperation is examined by calculating the functional connectivity (FC) between each voxel in one hemisphere and its anatomical (structurally homotopic) counterpart in the opposite hemisphere. However, bilateral hemispheres are actually asymmetric in anatomy. METHODS In the present study, we utilized connectivity between functionally homotopic voxels (CFH) to investigate abnormal inter-hemispheric cooperation in 96 MDD patients compared to 173 age- and sex-matched healthy controls (HCs). In addition, we analyzed the spatial correlations between abnormal CFH and the density maps of 13 neurotransmitter receptors and transporters. RESULTS The CFH values in bilateral orbital frontal gyri and bilateral postcentral gyri were abnormally decreased in patients with MDD. Furthermore, these CFH abnormalities were correlated with clinical symptoms. In addition, the abnormal CFH pattern in MDD patients was spatially correlated with the distribution pattern of 5-HT1AR. LIMITATIONS drug effect; the cross-sectional research design precludes causal inferences; the neurotransmitter atlases selected were constructed from healthy individuals rather than MDD patients. CONCLUSION These findings characterized the abnormal inter-hemispheric cooperation in MDD using a novel method and the underlying neurotransmitter mechanism, which promotes our understanding of the pathophysiology of depression.
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Affiliation(s)
- Hai Cao
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Tongqing Huang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yuqing Wei
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yuqian Zhan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xiaoqing Yao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ting Zhang
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yinian Yang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Wenqiang Xu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yanghua Tian
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lei Zhang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.
| | - Kai Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
| | - Gong-Jun Ji
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui Province, China; Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Institute of Translational Medicine, Hefei, China.
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15
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Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère ML, Artiges E, Orfanos DP, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development correlate with underlying neurobiology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.05.539537. [PMID: 37205539 PMCID: PMC10187287 DOI: 10.1101/2023.05.05.539537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
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Affiliation(s)
- Leon D. Lotter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
- Max Planck School of Cognition; Stephanstrasse 1A, 04103 Leipzig, Germany
| | - Amin Saberi
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences; Leipzig, Germany
| | - Justine Y. Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University; Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University; Montréal, QC, Canada
| | - Casey Paquola
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
| | - Gareth J. Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London; London, United Kingdom
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin; Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London; London, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim; 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay; F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont; 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham; University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB); Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 “Trajectoires Développementales & Psychiatrie”; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
| | - Marie-Laure Paillère
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 “Trajectoires Développementales & Psychiatrie”; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital; Paris, France
| | - Eric Artiges
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 “Trajectoires Développementales & Psychiatrie”; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- Department of Psychiatry, EPS Barthélémy Durand; Etampes, France
| | | | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal; Montréal, Quebec, Canada
- Department of Psychiatry, McGill University; Montreal, Quebec, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen; von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden; Dresden, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden; Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin; Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin; Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin; Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University; Shanghai, China
| | | | - Frauke Nees
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University; Kiel, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim-Heidelberg-Ulm; Heidelberg, Germany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
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16
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He H, Long J, Song X, Li Q, Niu L, Peng L, Wei X, Zhang R. A connectome-wide association study of altered functional connectivity in schizophrenia based on resting-state fMRI. Schizophr Res 2024; 270:202-211. [PMID: 38924938 DOI: 10.1016/j.schres.2024.06.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 05/09/2024] [Accepted: 06/19/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Aberrant resting-state functional connectivity is a neuropathological feature of schizophrenia (SCZ). Prior investigations into functional connectivity abnormalities have primarily employed seed-based connectivity analysis, necessitating predefined seed locations. To address this limitation, a data-driven multivariate method known as connectome-wide association study (CWAS) has been proposed for exploring whole-brain functional connectivity. METHODS We conducted a CWAS analysis involving 46 patients with SCZ and 40 age- and sex-matched healthy controls. Multivariate distance matrix regression (MDMR) was utilized to identify key nodes in the brain. Subsequently, we conducted a follow-up seed-based connectivity analysis to elucidate specific connectivity patterns between regions of interest (ROIs). Additionally, we explored the spatial correlation between changes in functional connectivity and underlying molecular architectures by examining correlations between neurotransmitter/transporter distribution densities and functional connectivity. RESULTS MDMR revealed the right medial frontal gyrus and the left calcarine sulcus as two key nodes. Follow-up analysis unveiled hypoconnectivity between the right medial frontal superior gyrus and the right fusiform gyrus, as well as hypoconnectivity between the left calcarine sulcus and the right lingual gyrus in SCZ. Notably, a significant association between functional connectivity strength and positive symptom severity was identified. Furthermore, altered functional connectivity patterns suggested potential dysfunctions in the dopamine, serotonin, and gamma-aminobutyric acid systems. CONCLUSIONS This study elucidated reduced functional connectivity both within and between the medial frontal regions and the occipital cortex in patients with SCZ. Moreover, it indicated potential alterations in molecular architecture, thereby expanding current knowledge regarding neurobiological changes associated with SCZ.
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Affiliation(s)
- Huawei He
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jixin Long
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiaoqi Song
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Qian Li
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Lijing Niu
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Lanxin Peng
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xinhua Wei
- Department of Radiology, Guangzhou First Affiliated Hospital, Guangzhou, China.
| | - Ruibin Zhang
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, PRC, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong Joint Laboratory for PsychiatricDisorders, Guangdong Basic Research Center of Excellence for Integrated Traditional and Western Medicine for Qingzhi Diseases, PR China.
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17
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Zhang M, Niu X, Tao Q, Sun J, Dang J, Wang W, Han S, Zhang Y, Cheng J. Altered intrinsic neural timescales and neurotransmitter activity in males with tobacco use disorder. J Psychiatr Res 2024; 175:446-454. [PMID: 38797041 DOI: 10.1016/j.jpsychires.2024.05.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/07/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
Previous researches of tobacco use disorder (TUD) has overlooked the hierarchy of cortical functions and single modality design separated the relationship between macroscopic neuroimaging aberrance and microscopic molecular basis. At present, intrinsic timescale gradient of TUD and its molecular features are not fully understood. Our study recruited 146 male subjects, including 44 heavy smokers, 50 light smokers and 52 non-smokers, then obtained their rs-fMRI data and clinical scales related to smoking. Intrinsic neural timescale (INT) method was performed to describe how long neural information was stored in a brain region by calculating the autocorrelation function (ACF) of each voxel to examine the difference in the ability of information integration among the three groups. Then, correlation analyses were conducted to explore the relationship between INT abnormalities and clinical scales of smokers. Finally, cross-modal JuSpace toolbox was used to investigate the association between INT aberrance and the expression of specific receptor/transporters. Compared to healthy controls, TUD subjects displayed decreased INT in control network (CN), default mode network (DMN), sensorimotor areas and visual cortex, and such trend of decreasing INT was more pronounced in heavy smokers. Moreover, various neurotransmitters (including dopaminergic, acetylcholine and μ-opioid receptors) were involved in the molecular mechanism of timescale decreasing and differed in heavy and light smokers. These findings supplied novel insights into the brain functional aberrance in TUD from an intrinsic neural dynamic perspective and confirm INT was a potential neurobiological marker. And also established the connection between macroscopic imaging aberrance and microscopic molecular changes in TUD.
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Affiliation(s)
- Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
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18
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Ren P, Bao H, Wang S, Wang Y, Bai Y, Lai J, Yi L, Liu Q, Li W, Zhang X, Sun L, Liu Q, Cui X, Zhang X, Liang P, Liang X. Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes. Int J Cancer 2024. [PMID: 38949756 DOI: 10.1002/ijc.35068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 04/11/2024] [Accepted: 06/06/2024] [Indexed: 07/02/2024]
Abstract
Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.
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Affiliation(s)
- Peng Ren
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
- Institute of Science and Technology for Brain-Inspired Intelligence and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongbo Bao
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shuai Wang
- Medical Imaging Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yan Bai
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Jiacheng Lai
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Liye Yi
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qing Liu
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Wenting Li
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xinyu Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lili Sun
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Qiuyi Liu
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xuehua Cui
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xiushi Zhang
- Medical Imaging Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Peng Liang
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xia Liang
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
- Frontiers Science Center for Matter Behave in Space Environment, Harbin Institute of Technology, Harbin, China
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19
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Shi D, Wu S, Zhuang C, Mao Y, Wang Q, Zhai H, Zhao N, Yan G, Wu R. Multimodal data fusion reveals functional and neurochemical correlates of Parkinson's disease. Neurobiol Dis 2024; 197:106527. [PMID: 38740347 DOI: 10.1016/j.nbd.2024.106527] [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: 04/16/2024] [Accepted: 05/09/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Neurotransmitter deficits and spatial associations among neurotransmitter distribution, brain activity, and clinical features in Parkinson's disease (PD) remain unclear. Better understanding of neurotransmitter impairments in PD may provide potential therapeutic targets. Therefore, we aimed to investigate the spatial relationship between PD-related patterns and neurotransmitter deficits. METHODS We included 59 patients with PD and 41 age- and sex-matched healthy controls (HCs). The voxel-wise mean amplitude of the low-frequency fluctuation (mALFF) was calculated and compared between the two groups. The JuSpace toolbox was used to test whether spatial patterns of mALFF alterations in patients with PD were associated with specific neurotransmitter receptor/transporter densities. RESULTS Compared to HCs, patients with PD showed reduced mALFF in the sensorimotor- and visual-related regions. In addition, mALFF alteration patterns were significantly associated with the spatial distribution of the serotonergic, dopaminergic, noradrenergic, glutamatergic, cannabinoid, and acetylcholinergic neurotransmitter systems (p < 0.05, false discovery rate-corrected). CONCLUSIONS Our results revealed abnormal brain activity patterns and specific neurotransmitter deficits in patients with PD, which may provide new insights into the mechanisms and potential targets for pharmacotherapy.
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Affiliation(s)
- Dafa Shi
- Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
| | - Shuohua Wu
- Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Caiyu Zhuang
- Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Yumeng Mao
- Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Qianqi Wang
- Department of Basic Medical Sciences, School of Medicine, Xiamen University, Xiamen, China
| | - Huige Zhai
- Center of Morphological Experiment, Medical College of Yanbian University, Yanji, China
| | - Nannan Zhao
- Center of Morphological Experiment, Medical College of Yanbian University, Yanji, China
| | - Gen Yan
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China.
| | - Renhua Wu
- Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
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20
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Liu H, Chen D, Liu C, Liu P, Yang H, Lu H. Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes. Pediatr Res 2024; 96:184-189. [PMID: 38431664 DOI: 10.1038/s41390-024-03118-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/29/2024] [Accepted: 02/15/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome, accompanied by behavioral problems and cognitive impairments. Previous studies of BECTS-related brain structures applied univariate analysis and showed inconsistent results. And neurotransmitter patterns associated with brain structural alterations were still unclear. METHODS Structural images of twenty-one drug-naïve children with BECTS and thirty-five healthy controls (HCs) were scanned. Segmented gray matter volume (GMV) images were decomposed into independent components (ICs) using the source-based morphometry method. Then spatial correlation analyses were applied to examine possible relationships between GMV changes and neurotransmitter systems. RESULTS Compared with HCs, drug-naïve children with BECTS showed increased volume in one GMV component (IC7), including bilateral precentral gyrus, bilateral supplementary motor area, left superior frontal cortex, bilateral middle/ inferior frontal cortex and bilateral anterior/ middle cingulate cortex. A positive correlation was observed between one GMV component (IC6) and seizure frequency. There were significantly positive correlations between abnormal GMV in IC7 and serotonergic, GABAergic and glutamatergic systems. CONCLUSION These findings provided further evidence of changed GMV in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments, and associated neurotransmitters which could help to better understand neurobiological mechanisms and underlying molecular mechanisms of BECTS. IMPACT The article provides further evidence of changed gray matter volume in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments as well as associated neurotransmitters. Most literature to date has applied univariate analysis and showed inconsistent results, and neurotransmitter patterns associated with brain structural alterations were still unclear. Therefore, this article uses multivariate method and JuSpace toolbox to fill the gap. Significantly increased gray matter volume was found in drug-naïve children with BECTS compared with healthy controls. Abnormal gray matter volume was significantly correlated with clinical data and specific neurotransmitters.
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Affiliation(s)
- Heng Liu
- Department of Radiology, The Seventh People's Hospital of Chongqing, The Central Hospital Affiliated to Chongqing University of Technology, Chongqing, China.
- Department of Radiology, The Affiliated Hospital of Zunyi Medical University, Zunyi, China.
| | - Duoli Chen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Chengxiang Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Peng Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Hua Yang
- Department of Medical Imaging, Chongqing Traditional Chinese Medicine Hospital, Chongqing, China.
| | - Hong Lu
- Department of Radiology, The Seventh People's Hospital of Chongqing, The Central Hospital Affiliated to Chongqing University of Technology, Chongqing, China.
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Morys F, Tremblay C, Rahayel S, Hansen JY, Dai A, Misic B, Dagher A. Neural correlates of obesity across the lifespan. Commun Biol 2024; 7:656. [PMID: 38806652 PMCID: PMC11133431 DOI: 10.1038/s42003-024-06361-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 05/20/2024] [Indexed: 05/30/2024] Open
Abstract
Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.
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Affiliation(s)
- Filip Morys
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada.
| | - Christina Tremblay
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Shady Rahayel
- Department of Medicine and Medical Specialties, University of Montreal, Montreal, QC, Canada
- Center for Advanced Research in Sleep Medicine, Hopital du Sacre-Coeur de Montreal, Montreal, QC, Canada
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Alyssa Dai
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
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22
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Caminiti SP, Galli A, Jonghi-Lavarini L, Boccalini C, Nicastro N, Chiti A, Garibotto V, Perani D. Mapping brain metabolism, connectivity and neurotransmitters topography in early and late onset dementia with lewy bodies. Parkinsonism Relat Disord 2024; 122:106061. [PMID: 38430691 DOI: 10.1016/j.parkreldis.2024.106061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 02/17/2024] [Accepted: 02/21/2024] [Indexed: 03/05/2024]
Abstract
INTRODUCTION Early-onset dementia with Lewy bodies (EO-DLB) is associated with rapid cognitive decline and severe neuropsychiatric symptoms at onset. METHODS Using FDG-PET imaging for 62 patients (21 EO-DLB, 41 LO (late-onset)-DLB), we explored brain hypometabolism, and metabolic connectivity in the whole-brain network and resting-state networks (RSNs). We also evaluated the spatial association between brain hypometabolism and neurotransmitter pathways topography. RESULTS Direct comparisons between the two clinical subgroups showed that EO-DLB was characterized by a lower metabolism in posterior cingulate/precuneus and occipital cortex. Metabolic connectivity analysis revealed significant alterations in posterior regions in both EO-DLB and LO-DLB. The EO-DLB, however, showed more severe loss of connectivity between occipital and parietal nodes and hyperconnectivity between frontal and cerebellar nodes. Spatial topography association analysis indicated significant correlations between neurotransmitter maps (i.e. acetylcholine, GABA, serotonin, dopamine) and brain hypometabolism in both EO and LO-DLB, with significantly higher metabolic correlation in the presynaptic serotonergic system for EO-DLB, supporting its major dysfunction. CONCLUSIONS Our study revealed greater brain hypometabolism and loss of connectivity in posterior brain region in EO- than LO-DLB. Serotonergic mapping emerges as a relevant factor for further investigation addressing clinical differences between DLB subtypes.
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Affiliation(s)
- Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alice Galli
- Vita-Salute San Raffaele University, Milan, Italy
| | | | - Cecilia Boccalini
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy; Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Nicastro
- Division of Neurorehabilitation, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - Arturo Chiti
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy.
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Boccalini C, Nicastro N, Perani D, Garibotto V. Distinctive clinical and imaging trajectories in SWEDD and Parkinson's disease patients. Neuroimage Clin 2024; 42:103592. [PMID: 38493585 PMCID: PMC10958480 DOI: 10.1016/j.nicl.2024.103592] [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: 11/03/2023] [Revised: 02/16/2024] [Accepted: 03/13/2024] [Indexed: 03/19/2024]
Abstract
A proportion of patients clinically diagnosed with Parkinson's disease (PD) can have a 123I-FP-CIT-SPECT scan without evidence of dopaminergic deficit (SWEDD), generating a debate about the underlying biological mechanisms. This study investigated differences in clinical features, 123I-FP-CIT binding, molecular connectivity, as well as clinical and imaging progression between SWEDD and PD patients. We included 36 SWEDD, 49 de novo idiopathic PD, and 49 healthy controls with 123I-FP-CIT-SPECT from the Parkinson's Progression Markers Initiative. Clinical and imaging 2-year follow-ups were available for 27 SWEDD and 40 PD. Regional-based and voxel-wise analysis assessed dopaminergic integrity in dorsal and ventral striatal, as well as extrastriatal regions, at baseline and follow-up. Molecular connectivity analyses evaluated dopaminergic pathways. Spatial correlation analyses tested whether 123I-FP-CIT-binding alterations would also pertain to the serotoninergic system. SWEDD and PD patients showed comparable symptoms at baseline, except for hyposmia, which was more severe for PD. PD showed significantly lower striatal and extrastriatal 123I-FP-CIT-binding compared to SWEDD and controls. SWEDD exhibited lower binding than controls in striatal regions, insula, and olfactory cortex. Both PD and SWEDD showed extensive altered connectivity of dopaminergic pathways, however, with major impairment in the mesocorticolimbic system for SWEDD. Motor symptoms and dopaminergic deficits worsened after 2 years for PD only. The limited dopaminergic impairment and its stability over time observed for SWEDD, as well as the presence of extrastriatal 123I-FP-CIT binding alterations and prevalent mesocorticolimbic connectivity impairment, suggest other mechanisms contributing to SWEDD pathophysiology.
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Affiliation(s)
- Cecilia Boccalini
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy; Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Nicastro
- Division of Neurorehabilitation, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy; IRCCS San Raffaele Scientific Institute, Milan, Italy; Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland; CIBM Center for Biomedical Imaging, Geneva, Switzerland.
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24
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Betzel R, Puxeddu MG, Seguin C, Bazinet V, Luppi A, Podschun A, Singleton SP, Faskowitz J, Parakkattu V, Misic B, Markett S, Kuceyeski A, Parkes L. Controlling the human connectome with spatially diffuse input signals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.581006. [PMID: 38463980 PMCID: PMC10925126 DOI: 10.1101/2024.02.27.581006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The human brain is never at "rest"; its activity is constantly fluctuating over time, transitioning from one brain state-a whole-brain pattern of activity-to another. Network control theory offers a framework for understanding the effort - energy - associated with these transitions. One branch of control theory that is especially useful in this context is "optimal control", in which input signals are used to selectively drive the brain into a target state. Typically, these inputs are introduced independently to the nodes of the network (each input signal is associated with exactly one node). Though convenient, this input strategy ignores the continuity of cerebral cortex - geometrically, each region is connected to its spatial neighbors, allowing control signals, both exogenous and endogenous, to spread from their foci to nearby regions. Additionally, the spatial specificity of brain stimulation techniques is limited, such that the effects of a perturbation are measurable in tissue surrounding the stimulation site. Here, we adapt the network control model so that input signals have a spatial extent that decays exponentially from the input site. We show that this more realistic strategy takes advantage of spatial dependencies in structural connectivity and activity to reduce the energy (effort) associated with brain state transitions. We further leverage these dependencies to explore near-optimal control strategies such that, on a per-transition basis, the number of input signals required for a given control task is reduced, in some cases by two orders of magnitude. This approximation yields network-wide maps of input site density, which we compare to an existing database of functional, metabolic, genetic, and neurochemical maps, finding a close correspondence. Ultimately, not only do we propose a more efficient framework that is also more adherent to well-established brain organizational principles, but we also posit neurobiologically grounded bases for optimal control.
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Affiliation(s)
- Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
- Cognitive Science Program, Indiana University, Bloomington IN 47401
- Program in Neuroscience, Indiana University, Bloomington IN 47401
| | - Maria Grazia Puxeddu
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Caio Seguin
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Andrea Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | | | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Vibin Parakkattu
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
- Cognitive Science Program, Indiana University, Bloomington IN 47401
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY
- Department of Computational Biology, Cornell University, Ithaca, NY
| | - Linden Parkes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
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25
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Boecker H, Daamen M, Maurer A, Bodensohn L, Werkhausen J, Lohaus M, Manunzio C, Manunzio U, Radbruch A, Attenberger U, Dukart J, Upadhyay N. Fractional amplitude of low-frequency fluctuations associated with μ-opioid and dopamine receptor distributions in the central nervous system after high-intensity exercise bouts. FRONTIERS IN NEUROIMAGING 2024; 3:1332384. [PMID: 38455686 PMCID: PMC10917966 DOI: 10.3389/fnimg.2024.1332384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 01/29/2024] [Indexed: 03/09/2024]
Abstract
Introduction Dopaminergic, opiod and endocannabinoid neurotransmission are thought to play an important role in the neurobiology of acute exercise and, in particular, in mediating positive affective responses and reward processes. Recent evidence indicates that changes in fractional amplitude of low-frequency fluctuations (zfALFF) in resting-state functional MRI (rs-fMRI) may reflect changes in specific neurotransmitter systems as tested by means of spatial correlation analyses. Methods Here, we investigated this relationship at different exercise intensities in twenty young healthy trained athletes performing low-intensity (LIIE), high-intensity (HIIE) interval exercises, and a control condition on three separate days. Positive And Negative Affect Schedule (PANAS) scores and rs-fMRI were acquired before and after each of the three experimental conditions. Respective zfALFF changes were analyzed using repeated measures ANOVAs. We examined the spatial correspondence of changes in zfALFF before and after training with the available neurotransmitter maps across all voxels and additionally, hypothesis-driven, for neurotransmitter maps implicated in the neurobiology of exercise (dopaminergic, opiodic and endocannabinoid) in specific brain networks associated with "reward" and "emotion." Results Elevated PANAS Positive Affect was observed after LIIE and HIIE but not after the control condition. HIIE compared to the control condition resulted in differential zfALFF decreases in precuneus, temporo-occipital, midcingulate and frontal regions, thalamus, and cerebellum, whereas differential zfALFF increases were identified in hypothalamus, pituitary, and periaqueductal gray. The spatial alteration patterns in zfALFF during HIIE were positively associated with dopaminergic and μ-opioidergic receptor distributions within the 'reward' network. Discussion These findings provide new insight into the neurobiology of exercise supporting the importance of reward-related neurotransmission at least during high-intensity physical activity.
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Affiliation(s)
- Henning Boecker
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Marcel Daamen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
- Clinical Research, German Center for Neurodegenerative Diseases (DZNE) Bonn, Bonn, Germany
| | - Angelika Maurer
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Luisa Bodensohn
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Judith Werkhausen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Marvin Lohaus
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Christian Manunzio
- Sportsmedicine, Department of Paediatric Cardiology, University Hospital Bonn, Bonn, Germany
| | - Ursula Manunzio
- Sportsmedicine, Department of Paediatric Cardiology, University Hospital Bonn, Bonn, Germany
| | | | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Neeraj Upadhyay
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
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26
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Taso M, Alsop DC. Arterial Spin Labeling Perfusion Imaging. Magn Reson Imaging Clin N Am 2024; 32:63-72. [PMID: 38007283 DOI: 10.1016/j.mric.2023.08.005] [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: 11/27/2023]
Abstract
Noninvasive imaging of tissue perfusion is a valuable tool for both research and clinical applications. Arterial spin labeling (ASL) is a contrast-free perfusion imaging method that enables measuring and quantifying tissue blood flow using MR imaging. ASL uses radiofrequency and magnetic field gradient pulses to label arterial blood water, which then serves as an endogenous tracer. This review highlights the basic mechanism of ASL perfusion imaging, labeling strategies, and quantification. ASL has been widely used during the past 30 years for the study of normal brain function as well as in multiple neurovascular, neuro-oncological and degenerative pathologic conditions.
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Affiliation(s)
- Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
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27
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Hahn L, Eickhoff SB, Mueller K, Schilbach L, Barthel H, Fassbender K, Fliessbach K, Kornhuber J, Prudlo J, Synofzik M, Wiltfang J, Diehl-Schmid J, Otto M, Dukart J, Schroeter ML. Resting-state alterations in behavioral variant frontotemporal dementia are related to the distribution of monoamine and GABA neurotransmitter systems. eLife 2024; 13:e86085. [PMID: 38224473 PMCID: PMC10789488 DOI: 10.7554/elife.86085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 12/14/2023] [Indexed: 01/16/2024] Open
Abstract
Background Aside to clinical changes, behavioral variant frontotemporal dementia (bvFTD) is characterized by progressive structural and functional alterations in frontal and temporal regions. We examined if there is a selective vulnerability of specific neurotransmitter systems in bvFTD by evaluating the link between disease-related functional alterations and the spatial distribution of specific neurotransmitter systems and their underlying gene expression levels. Methods Maps of fractional amplitude of low-frequency fluctuations (fALFF) were derived as a measure of local activity from resting-state functional magnetic resonance imaging for 52 bvFTD patients (mean age = 61.5 ± 10.0 years; 14 females) and 22 healthy controls (HC) (mean age = 63.6 ± 11.9 years; 13 females). We tested if alterations of fALFF in patients co-localize with the non-pathological distribution of specific neurotransmitter systems and their coding mRNA gene expression. Furthermore, we evaluated if the strength of co-localization is associated with the observed clinical symptoms. Results Patients displayed significantly reduced fALFF in frontotemporal and frontoparietal regions. These alterations co-localized with the distribution of serotonin (5-HT1b and 5-HT2a) and γ-aminobutyric acid type A (GABAa) receptors, the norepinephrine transporter (NET), and their encoding mRNA gene expression. The strength of co-localization with NET was associated with cognitive symptoms and disease severity of bvFTD. Conclusions Local brain functional activity reductions in bvFTD followed the distribution of specific neurotransmitter systems indicating a selective vulnerability. These findings provide novel insight into the disease mechanisms underlying functional alterations. Our data-driven method opens the road to generate new hypotheses for pharmacological interventions in neurodegenerative diseases even beyond bvFTD. Funding This study has been supported by the German Consortium for Frontotemporal Lobar Degeneration, funded by the German Federal Ministry of Education and Research (BMBF; grant no. FKZ01GI1007A).
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Affiliation(s)
- Lisa Hahn
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Karsten Mueller
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Leonhard Schilbach
- LVR-Klinikum DüsseldorfDüsseldorfGermany
- Medical Faculty, Ludwig-Maximilians-UniversitätMünchenGermany
| | - Henryk Barthel
- Department for Nuclear Medicine, University Hospital LeipzigLeipzigGermany
| | - Klaus Fassbender
- Department of Neurology, Saarland University HospitalHomburgGermany
| | - Klaus Fliessbach
- Department of Psychiatry and Psychotherapy, University Hospital BonnBonnGermany
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-NurembergErlangenGermany
| | - Johannes Prudlo
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Department of Neurology, University Medicine RostockRostockGermany
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Department of Neurodegenerative Diseases, Center of Neurology, Hertie Institute for Clinical Brain ResearchTübingenGermany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Medical University GöttingenGöttingenGermany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of AveiroAveiroPortugal
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Technical University of MunichMunichGermany
- kbo-Inn-Salzach-Klinikum, Clinical Center for Psychiatry, Psychotherapy, Psychosomatic Medicine, Geriatrics and NeurologyWasserburg/InnGermany
| | | | - Markus Otto
- Department of Neurology, Ulm UniversityUlmGermany
- Department of Neurology, Martin-Luther-University Halle-WittenbergHalleGermany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Matthias L Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Clinic for Cognitive Neurology, University Hospital LeipzigLeipzigGermany
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Li B, Lin Y, Ren C, Cheng J, Zhang Y, Han S. Gray matter volume abnormalities in obsessive-compulsive disorder correlate with molecular and transcriptional profiles. J Affect Disord 2024; 344:182-190. [PMID: 37838261 DOI: 10.1016/j.jad.2023.10.076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/17/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023]
Abstract
Neuroimaging studies have consistently established altered brain structure in obsessive-compulsive disorder (OCD). However, the molecular and genetic mechanisms underlying structural brain abnormalities remain unclear. In this study, we aimed to investigate altered gray matter volume and its underlying molecular and genetic mechanisms in patients with OCD. Gray matter morphological abnormalities measured with voxel based morphometry analysis were identified in patients with OCD in comparison to sex- and age-matched healthy controls (HCs). Spatial correlations between gray matter morphological abnormalities and neurotransmitter maps were calculated to identify neurotransmitters relating to structural abnormalities. Structural abnormalities related genes were identified by conducting transcriptome-neuroimaging spatial correlations. Compared with HCs, patients with OCD demonstrated significant morphological abnormalities in distributed brain areas, including gray matter atrophy in the anterior cingulate and increased gray matter volume in the thalamus, caudate and precentral and postcentral gyrus. The morphological abnormalities were significantly associated with dopamine synthesis capacity and expression profiles of 1110 genes enriched for trans-synaptic signaling, regulation of membrane potential, modulation of chemical synaptic transmission, brain development, synapse organization and regulation of neurotransmitter levels. These results elucidate the molecular and transcriptional basis of altered gray matter morphology and build linking between molecular, transcriptional and neuroimaging information facilitating an integrative understanding of OCD.
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Affiliation(s)
- Beibei Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Yanan Lin
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Cuiping Ren
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
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29
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Vogelsang DA, Furman DJ, Nee DE, Pappas I, White RL, Kayser AS, D'Esposito M. Dopamine Modulates Effective Connectivity in Frontal Cortex. J Cogn Neurosci 2024; 36:155-166. [PMID: 37902578 DOI: 10.1162/jocn_a_02077] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
There is increasing evidence that the left lateral frontal cortex is hierarchically organized such that higher-order regions have an asymmetric top-down influence over lower order regions. However, questions remain about the underlying neuroarchitecture of this hierarchical control organization. Within the frontal cortex, dopamine plays an important role in cognitive control functions, and we hypothesized that dopamine may preferentially influence top-down connections within the lateral frontal hierarchy. Using a randomized, double-blind, within-subject design, we analyzed resting-state fMRI data of 66 healthy young participants who were scanned once each after administration of bromocriptine (a dopamine agonist with preferential affinity for D2 receptor), tolcapone (an inhibitor of catechol-O-methyltransferase), and placebo, to determine whether dopaminergic stimulation modulated effective functional connectivity between hierarchically organized frontal regions in the left hemisphere. We found that dopaminergic drugs modulated connections from the caudal middle frontal gyrus and the inferior frontal sulcus to both rostral and caudal frontal areas. In dorsal frontal regions, effectivity connectivity strength was increased, whereas in ventral frontal regions, effective connectivity strength was decreased. These findings suggest that connections within frontal cortex are differentially modulated by dopamine, which may bias the influence that frontal regions exert over each other.
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Affiliation(s)
| | | | | | - Ioannis Pappas
- University of California
- University of Southern California
| | - Robert L White
- Washington University School of Medicine, Saint Louis, MO
| | - Andrew S Kayser
- University of California
- VA Northern California Health Care System
| | - Mark D'Esposito
- University of California
- VA Northern California Health Care System
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30
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Li Z, Li J, Wang N, Lv Y, Zou Q, Wang J. Single-subject cortical morphological brain networks: Phenotypic associations and neurobiological substrates. Neuroimage 2023; 283:120434. [PMID: 37907157 DOI: 10.1016/j.neuroimage.2023.120434] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 10/28/2023] [Accepted: 10/28/2023] [Indexed: 11/02/2023] Open
Abstract
Although single-subject morphological brain networks provide an important way for human connectome studies, their roles and origins are poorly understood. Combining cross-sectional and repeated structural magnetic resonance imaging scans from adults, children and twins with behavioral and cognitive measures and brain-wide transcriptomic, cytoarchitectonic and chemoarchitectonic data, this study examined phenotypic associations and neurobiological substrates of single-subject morphological brain networks. We found that single-subject morphological brain networks explained inter-individual variance and predicted individual outcomes in Motor and Cognition domains, and distinguished individuals from each other. The performance can be further improved by integrating different morphological indices for network construction. Low-moderate heritability was observed for single-subject morphological brain networks with the highest heritability for sulcal depth-derived networks and higher heritability for inter-module connections. Furthermore, differential roles of genetic, cytoarchitectonic and chemoarchitectonic factors were observed for single-subject morphological brain networks. Cortical thickness-derived networks were related to the three factors with contributions from genes enriched in membrane and transport related functions, genes preferentially located in supragranular and granular layers, overall thickness in the molecular layer and thickness of wall in the infragranular layers, and metabotropic glutamate receptor 5 and dopamine transporter; fractal dimension-, gyrification index- and sulcal depth-derived networks were only associated with the chemoarchitectonic factor with contributions from different sets of neurotransmitter receptors. Most results were reproducible across different parcellation schemes and datasets. Altogether, this study demonstrates phenotypic associations and neurobiological substrates of single-subject morphological brain networks, which provide intermediate endophenotypes to link molecular and cellular architecture and behavior and cognition.
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Affiliation(s)
- Zhen Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Ningkai Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Yating Lv
- Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
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Chou CC, Wang CH, McCullick B, Hsueh MC. Effects of Coordinative Exercise on Sustained Attention and Perceptual Discrimination in Elementary School Physical Education. RESEARCH QUARTERLY FOR EXERCISE AND SPORT 2023; 94:948-958. [PMID: 35797729 DOI: 10.1080/02701367.2022.2085863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 05/30/2022] [Indexed: 06/15/2023]
Abstract
Purpose: This study examined the effects of coordinative exercise on children's sustained attention and perceptual discrimination in a school-based physical education (SBPE) setting. Methods: Seventy-three children received an intervention of moderate-to-vigorous intensity coordinative exercise, and 75 children participated in a moderate-to-vigorous intensity physical activity as part of a regular physical education class. Two neuropsychological tests of executive function (EF) were used to assess attention and perceptual discrimination functions before and after each treatment. Results: The results found that coordinative exercise significantly improved the performances on sustained attention and perceptual discrimination, as evidenced by enhanced response accuracy and improved speed of responding. Specifically, higher progressions in task performance were seen following coordinative exercise relative to regular physical activity. Conclusion: These findings suggest that coordinative exercise could enable more robust improvements in sustained attention and perceptual discrimination among children. Overall, we conclude that structured coordinative exercise, implemented in SBPE settings, may be a promising alternative to promote children's cognitive abilities.
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. RESEARCH SQUARE 2023:rs.3.rs-3569352. [PMID: 38076888 PMCID: PMC10705693 DOI: 10.21203/rs.3.rs-3569352/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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He K, Hua Q, Li Q, Zhang Y, Yao X, Yang Y, Xu W, Sun J, Wang L, Wang A, Ji GJ, Wang K. Abnormal interhemispheric functional cooperation in schizophrenia follows the neurotransmitter profiles. J Psychiatry Neurosci 2023; 48:E452-E460. [PMID: 38123242 PMCID: PMC10743641 DOI: 10.1503/jpn.230037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/26/2023] [Accepted: 09/05/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Interhemispheric cooperation is one of the most prominent functional architectures of the human brain. In patients with schizophrenia, interhemispheric cooperation deficits have been reported using increasingly powerful neurobehavioural and neuroimaging measures. However, these methods rely in part on the assumption of anatomic symmetry between hemispheres. In the present study, we explored interhemispheric cooperation deficits in schizophrenia using a newly developed index, connectivity between functionally homotopic voxels (CFH), which is unbiased by hemispheric asymmetry. METHODS Patients with schizophrenia and age- and sexmatched healthy controls underwent multimodal MRI, and whole-brain CFH maps were constructed for comparison between groups. We examined the correlations of differing CFH values between the schizophrenia and control groups using various neurotransmitter receptor and transporter densities. RESULTS We included 86 patients with schizophrenia and 86 matched controls in our analysis. Patients with schizophrenia showed significantly lower CFH values in the frontal lobes, left postcentral gyrus and right inferior temporal gyrus, and significantly greater CFH values in the right caudate nucleus than healthy controls. Moreover, the differing CFH values in patients with schizophrenia were significantly correlated with positive symptom score and illness duration. Functional connectivity within frontal lobes was significantly reduced at the voxel cluster level compared with healthy controls. Finally, the abnormal CFH map of patients with schizophrenia was spatially associated with the densities of the dopamine D1 and D2 receptors, fluorodopa, dopamine transporter, serotonin transporter and acetylcholine transporter. CONCLUSION Regional abnormalities in interhemispheric cooperation may contribute to the clinical symptoms of schizophrenia. These CFH abnormalities may be associated with dysfunction in neurotransmitter systems strongly implicated in schizophrenia.
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Affiliation(s)
- Kongliang He
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Qiang Hua
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Qianqian Li
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Yan Zhang
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Xiaoqing Yao
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Yinian Yang
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Wenqiang Xu
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Jinmei Sun
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Lu Wang
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Anzhen Wang
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Gong-Jun Ji
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
| | - Kai Wang
- From the Affiliated Psychological Hospital of Anhui Medical University, Hefei, China (He, A. Wang); the Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China (He, Hua, Yao, Sun, L. Wang, Ji, K. Wang); the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (He, Zhang, Yang, Xu, A. Wang, Ji, K. Wang); the Hefei Fourth People's Hospital, Hefei, China (He, A. Wang); the Anhui Mental Health Center, Hefei, China (He, A. Wang); the Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China (Li); the Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China (Hua, Li, Zhang, Yang, Xu, Sun, L. Wang, Ji, K. Wang); the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China (K. Wang); and the Anhui Institute of Translational Medicine, Hefei, China (K. Wang)
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Schinz D, Schmitz‐Koep B, Zimmermann J, Brandes E, Tahedl M, Menegaux A, Dukart J, Zimmer C, Wolke D, Daamen M, Boecker H, Bartmann P, Sorg C, Hedderich DM. Indirect evidence for altered dopaminergic neurotransmission in very premature-born adults. Hum Brain Mapp 2023; 44:5125-5138. [PMID: 37608591 PMCID: PMC10502650 DOI: 10.1002/hbm.26451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 06/23/2023] [Accepted: 07/28/2023] [Indexed: 08/24/2023] Open
Abstract
While animal models indicate altered brain dopaminergic neurotransmission after premature birth, corresponding evidence in humans is scarce due to missing molecular imaging studies. To overcome this limitation, we studied dopaminergic neurotransmission changes in human prematurity indirectly by evaluating the spatial co-localization of regional alterations in blood oxygenation fluctuations with the distribution of adult dopaminergic neurotransmission. The study cohort comprised 99 very premature-born (<32 weeks of gestation and/or birth weight below 1500 g) and 107 full-term born young adults, being assessed by resting-state functional MRI (rs-fMRI) and IQ testing. Normative molecular imaging dopamine neurotransmission maps were derived from independent healthy control groups. We computed the co-localization of local (rs-fMRI) activity alterations in premature-born adults with respect to term-born individuals to different measures of dopaminergic neurotransmission. We performed selectivity analyses regarding other neuromodulatory systems and MRI measures. In addition, we tested if the strength of the co-localization is related to perinatal measures and IQ. We found selectively altered co-localization of rs-fMRI activity in the premature-born cohort with dopamine-2/3-receptor availability in premature-born adults. Alterations were specific for the dopaminergic system but not for the used MRI measure. The strength of the co-localization was negatively correlated with IQ. In line with animal studies, our findings support the notion of altered dopaminergic neurotransmission in prematurity which is associated with cognitive performance.
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Affiliation(s)
- David Schinz
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Benita Schmitz‐Koep
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Elin Brandes
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Marlene Tahedl
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Aurore Menegaux
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Juergen Dukart
- Institute of Neuroscience and MedicineBrain & Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical FacultyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Claus Zimmer
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Dieter Wolke
- Department of PsychologyUniversity of WarwickCoventryUK
- Warwick Medical SchoolUniversity of WarwickCoventryUK
| | - Marcel Daamen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
- Department of NeonatologyUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
| | - Peter Bartmann
- Department of NeonatologyUniversity Hospital BonnBonnGermany
| | - Christian Sorg
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
- Department of Psychiatry, School of MedicineTechnical University of MunichMunichGermany
| | - Dennis M. Hedderich
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
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35
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Hare SM, Adhikari BM, Mo C, Chen S, Wijtenburg SA, Seneviratne C, Kane-Gerard S, Sathyasaikumar KV, Notarangelo FM, Schwarcz R, Kelly DL, Rowland LM, Buchanan RW. Tryptophan challenge in individuals with schizophrenia and healthy controls: acute effects on circulating kynurenine and kynurenic acid, cognition and cerebral blood flow. Neuropsychopharmacology 2023; 48:1594-1601. [PMID: 37118058 PMCID: PMC10516920 DOI: 10.1038/s41386-023-01587-3] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 03/31/2023] [Accepted: 04/06/2023] [Indexed: 04/30/2023]
Abstract
Cognitive impairments predict poor functional outcomes in people with schizophrenia. These impairments may be causally related to increased levels of kynurenic acid (KYNA), a major metabolic product of tryptophan (TRYP). In the brain, KYNA acts as an antagonist of the of α7-nicotinic acetylcholine and NMDA receptors, both of which are involved in cognitive processes. To examine whether KYNA plays a role in the pathophysiology of schizophrenia, we compared the acute effects of a single oral dose of TRYP (6 g) in 32 healthy controls (HC) and 37 people with either schizophrenia (Sz), schizoaffective or schizophreniform disorder, in a placebo-controlled, randomized crossover study. We examined plasma levels of KYNA and its precursor kynurenine; selected cognitive measures from the MATRICS Consensus Cognitive Battery; and resting cerebral blood flow (CBF) using arterial spin labeling imaging. In both cohorts, the TRYP challenge produced significant, time-dependent elevations in plasma kynurenine and KYNA. The resting CBF signal (averaged across all gray matter) was affected differentially, such that TRYP was associated with higher CBF in HC, but not in participants with a Sz-related disorder. While TRYP did not significantly impair cognitive test performance, there was a trend for TRYP to worsen visuospatial memory task performance in HC. Our results demonstrate that oral TRYP challenge substantially increases plasma levels of kynurenine and KYNA in both groups, but exerts differential group effects on CBF. Future studies are required to investigate the mechanisms underlying these CBF findings, and to evaluate the impact of KYNA fluctuations on brain function and behavior. (Clinicaltrials.gov: NCT02067975).
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Affiliation(s)
- Stephanie M Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Chen Mo
- Harvard Medical School, Boston, MA, 02115, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - S Andrea Wijtenburg
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Chamindi Seneviratne
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Samuel Kane-Gerard
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Korrapati V Sathyasaikumar
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Francesca M Notarangelo
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Robert Schwarcz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Deanna L Kelly
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Laura M Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
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Khan AF, Adewale Q, Lin SJ, Baumeister TR, Zeighami Y, Carbonell F, Palomero-Gallagher N, Iturria-Medina Y. Patient-specific models link neurotransmitter receptor mechanisms with motor and visuospatial axes of Parkinson's disease. Nat Commun 2023; 14:6009. [PMID: 37752107 PMCID: PMC10522603 DOI: 10.1038/s41467-023-41677-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 09/08/2023] [Indexed: 09/28/2023] Open
Abstract
Parkinson's disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson's disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson's disease.
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Affiliation(s)
- Ahmed Faraz Khan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
| | - Quadri Adewale
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
| | - Sue-Jin Lin
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
| | - Tobias R Baumeister
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
| | - Yashar Zeighami
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute of Brain Research, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Medical Faculty, RWTH Aachen, and JARA - Translational Brain Medicine, Aachen, Germany
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada.
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37
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Rahayel S, Tremblay C, Vo A, Misic B, Lehéricy S, Arnulf I, Vidailhet M, Corvol JC, Gagnon JF, Postuma RB, Montplaisir J, Lewis S, Matar E, Ehgoetz Martens K, Borghammer P, Knudsen K, Hansen AK, Monchi O, Gan-Or Z, Dagher A. Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies. Brain 2023; 146:3301-3318. [PMID: 36826230 PMCID: PMC10393413 DOI: 10.1093/brain/awad044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/12/2023] [Accepted: 02/03/2023] [Indexed: 02/25/2023] Open
Abstract
Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.
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Affiliation(s)
- Shady Rahayel
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
| | - Christina Tremblay
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Andrew Vo
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Bratislav Misic
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Stéphane Lehéricy
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Isabelle Arnulf
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Marie Vidailhet
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-Christophe Corvol
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-François Gagnon
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychology, University of Quebec in Montreal, Montreal H2X 3P2, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
| | - Ronald B Postuma
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Neurology, Montreal General Hospital, Montreal H3G 1A4, Canada
| | - Jacques Montplaisir
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychiatry, University of Montreal, Montreal H3T 1J4, Canada
| | - Simon Lewis
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Elie Matar
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Kaylena Ehgoetz Martens
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
- Department of Kinesiology, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Per Borghammer
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Karoline Knudsen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Oury Monchi
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
- Department of Radiology, Radio-Oncology, and Nuclear Medicine, University of Montreal, Montreal H3T 1A4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
- Department of Human Genetics, McGill University, Montreal H3A 0C7, Canada
| | - Alain Dagher
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
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38
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Mahadevan AS, Cornblath EJ, Lydon-Staley DM, Zhou D, Parkes L, Larsen B, Adebimpe A, Kahn AE, Gur RC, Gur RE, Satterthwaite TD, Wolf DH, Bassett DS. Alprazolam modulates persistence energy during emotion processing in first-degree relatives of individuals with schizophrenia: a network control study. Mol Psychiatry 2023; 28:3314-3323. [PMID: 37353585 PMCID: PMC10618098 DOI: 10.1038/s41380-023-02121-z] [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: 01/12/2022] [Revised: 04/28/2023] [Accepted: 06/06/2023] [Indexed: 06/25/2023]
Abstract
Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia. Here, we use pharmacological modulation and computational modeling to study the contribution of GABAergic abnormalities toward emotion processing deficits in schizophrenia. Specifically, we apply principles from network control theory to model persistence energy - the control energy required to maintain brain activation states - during emotion identification and recall tasks, with and without administration of alprazolam, in a sample of first-degree relatives and healthy controls. Here, persistence energy quantifies the magnitude of theoretical external inputs during the task. We find that alprazolam increases persistence energy in relatives but not in controls during threatening face processing, suggesting a compensatory mechanism given the relative absence of behavioral abnormalities in this sample of unaffected relatives. Further, we demonstrate that regions in the fusiform and occipital cortices are important for facilitating state transitions during facial affect processing. Finally, we uncover spatial relationships (i) between regional variation in differential control energy (alprazolam versus placebo) and (ii) both serotonin and dopamine neurotransmitter systems, indicating that alprazolam may exert its effects by altering neuromodulatory systems. Together, these findings provide a new perspective on the distributed emotion processing network and the effect of GABAergic modulation on this network, in addition to identifying an association between schizophrenia risk and abnormal GABAergic effects on persistence energy during threat processing.
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Affiliation(s)
- Arun S Mahadevan
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Eli J Cornblath
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - David M Lydon-Staley
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dale Zhou
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Linden Parkes
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bart Larsen
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ari E Kahn
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel H Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM, 87501, USA.
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Dipasquale O, Cohen A, Martins D, Zelaya F, Turkheimer F, Veronese M, Mehta MA, Williams SCR, Yang B, Banerjee S, Wang Y. Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI. Sci Rep 2023; 13:11751. [PMID: 37474568 PMCID: PMC10359289 DOI: 10.1038/s41598-023-38573-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 07/11/2023] [Indexed: 07/22/2023] Open
Abstract
Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test-retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits.
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Affiliation(s)
- Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK.
| | - Alexander Cohen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Mitul A Mehta
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Steven C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | | | | | - Yang Wang
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
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40
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Lawn T, Howard MA, Turkheimer F, Misic B, Deco G, Martins D, Dipasquale O. From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging. Neurosci Biobehav Rev 2023; 150:105193. [PMID: 37086932 PMCID: PMC10390343 DOI: 10.1016/j.neubiorev.2023.105193] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 04/01/2023] [Accepted: 04/19/2023] [Indexed: 04/24/2023]
Abstract
The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.
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Affiliation(s)
- Timothy Lawn
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Matthew A Howard
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Bratislav Misic
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona 08005, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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41
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Luppi AI, Hansen JY, Adapa R, Carhart-Harris RL, Roseman L, Timmermann C, Golkowski D, Ranft A, Ilg R, Jordan D, Bonhomme V, Vanhaudenhuyse A, Demertzi A, Jaquet O, Bahri MA, Alnagger NL, Cardone P, Peattie AR, Manktelow AE, de Araujo DB, Sensi SL, Owen AM, Naci L, Menon DK, Misic B, Stamatakis EA. In vivo mapping of pharmacologically induced functional reorganization onto the human brain's neurotransmitter landscape. SCIENCE ADVANCES 2023; 9:eadf8332. [PMID: 37315149 PMCID: PMC10266734 DOI: 10.1126/sciadv.adf8332] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 05/10/2023] [Indexed: 06/16/2023]
Abstract
To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain's rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs' effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain's functional architecture.
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Affiliation(s)
- Andrea I. Luppi
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Justine Y. Hansen
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ram Adapa
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Robin L. Carhart-Harris
- Psychedelics Division - Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - Christopher Timmermann
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniel Golkowski
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, München, Germany
| | - Andreas Ranft
- School of Medicine, Department of Anesthesiology and Intensive Care, Technical University of Munich, Munich, Germany
| | - Rüdiger Ilg
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, München, Germany
- Department of Neurology, Asklepios Clinic, Bad Tölz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der Isar, Technical University Munich, München, Germany
- University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Vincent Bonhomme
- Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
| | - Audrey Vanhaudenhuyse
- Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium
| | - Athena Demertzi
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liege, Liege, Belgium
| | - Oceane Jaquet
- Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium
| | - Mohamed Ali Bahri
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liege, Liege, Belgium
| | - Naji L. N. Alnagger
- Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium
| | - Paolo Cardone
- Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium
| | - Alexander R. D. Peattie
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | | | - Stefano L. Sensi
- Department of Neuroscience and Imaging and Clinical Science, Center for Advanced Studies and Technology, Institute for Advanced Biomedical Technologies, University "G. d'Annunzio" Chieti-Pescara, Chieti, Italy
- Institute for Memory Impairments and Neurological Disorders, University of California-Irvine, Irvine, CA, USA
| | - Adrian M. Owen
- Department of Psychology and Department of Physiology and Pharmacology, Western Institute for Neuroscience (WIN), Western University, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - David K. Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Wolfon Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Bratislav Misic
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Emmanuel A. Stamatakis
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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42
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Boccalini C, Nicastro N, Peretti DE, Caminiti SP, Perani D, Garibotto V. Sex differences in dementia with Lewy bodies: an imaging study of neurotransmission pathways. Eur J Nucl Med Mol Imaging 2023; 50:2036-2046. [PMID: 36826477 PMCID: PMC10199852 DOI: 10.1007/s00259-023-06132-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/29/2023] [Indexed: 02/25/2023]
Abstract
PURPOSE Dementia with Lewy bodies (DLB) is characterized by a wide clinical and biological heterogeneity, with sex differences reported in both clinical and pathologically confirmed DLB cohorts. No research evidence is available on sex differences regarding molecular neurotransmission. This study aimed to assess whether sex can influence neurotransmitter systems in patients with probable DLB (pDLB). METHODS We included 123 pDLB patients (male/female: 77/46) and 78 control subjects (male/female: 34/44) for comparison, who underwent 123I-FP-CIT SPECT imaging. We assessed sex differences in the dopaminergic activity of the nigrostriatal and mesolimbic systems using regional-based and voxel-wise analyses of 123I-FP-CIT binding. We tested whether sex-specific binding alterations would also pertain to the serotoninergic and noradrenergic systems by applying spatial correlation analyses. We applied molecular connectivity analyses to assess potential sex differences in the dopaminergic pathways. RESULTS We found comparable 123I-FP-CIT binding decreases in the striatum for pDLB males and females compared to controls. However, pDLB females showed lower binding in the extrastriatal projections of the nigrostriatal and mesolimbic dopaminergic systems compared to pDLB males. According to the spatial correlation analysis, sex-specific molecular alterations were also associated with serotonergic and noradrenergic systems. Nigrostriatal and mesolimbic systems' connectivity was impaired in both groups, with males showing local alterations and females presenting long-distance disconnections between subcortical and cortical regions. CONCLUSIONS Sex-specific differences in 123I-FP-CIT binding were found in our cohort, namely, a trend for lower 123I-FP-CIT binding in females, significant in the presence of a pDLB diagnosis. pDLB females showed also different patterns of connectivity compared to males, mostly involving extrastriatal regions. The results suggest the presence of a sex-related regional vulnerability to alpha-synuclein pathology, possibly complicated also by the higher prevalence of Alzheimer's disease co-pathology in females, as previously reported in pDLB populations.
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Affiliation(s)
- Cecilia Boccalini
- Vita-Salute San Raffaele University, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Nicastro
- Division of Neurorehabilitation, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Debora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, University of Geneva, Geneva, Switzerland.
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland.
- CIBM Center for Biomedical Imaging, Geneva, Switzerland.
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Liu Y, Sun J, Jiang J, Wan K, Tang Y, Zhang M, Chen L, Hua Q, Fang W, Zhu C, Wang K. Brain functional specialization in obsessive-compulsive disorder associated with neurotransmitter profiles. J Affect Disord 2023; 329:477-482. [PMID: 36871908 DOI: 10.1016/j.jad.2023.02.146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 02/22/2023] [Accepted: 02/27/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Cerebral specialization is an important functional architecture of the human brain. Abnormal cerebral specialization may be the underlying pathogenesis of obsessive-compulsive disorder (OCD). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to show that the specialization pattern of OCD was of great significance for early warning and precise intervention of the disease. METHOD The autonomy index (AI) based on the rs-fMRI was calculated to compare brain specializations between 80 OCD patients and 81 matched healthy controls (HCs). In addition, we also correlated the AI alteration patterns with neurotransmitter receptor/transporter densities. RESULTS OCD patients showed increased AI in the right insula and right superior temporal gyrus when compared with HCs. In addition, AI differences were associated with serotonin receptors (5-HT1AR and 5HT4R), dopamine D2 receptors, norepinephrine transporters, and metabotropic glutamate receptor densities. LIMITATIONS Drug effect; cross-sectional study design; the selection of positron emission tomography template. CONCLUSIONS This study showed abnormal specialization patterns in OCD patients, which may lead to the elucidation of the underlying pathological mechanism of the disease.
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Affiliation(s)
- Yueling Liu
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Jin Jiang
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ke Wan
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yan Tang
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Mengzhu Zhang
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Lu Chen
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Wenmei Fang
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China; Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China; Anhui Mental Health Center, Hefei, China.
| | - Chunyan Zhu
- Department of Psychology, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Department of Psychology, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
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Lawn T, Martins D, O'Daly O, Williams S, Howard M, Dipasquale O. The effects of propofol anaesthesia on molecular-enriched networks during resting-state and naturalistic listening. Neuroimage 2023; 271:120018. [PMID: 36935083 PMCID: PMC10410200 DOI: 10.1016/j.neuroimage.2023.120018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/09/2023] [Indexed: 03/19/2023] Open
Abstract
Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact the system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alter neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory stimulation. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the dopamine transporter showed reduced FC within bilateral regions of temporal and mid/posterior cingulate cortices, with the right temporal cluster showing an interaction between auditory stimulation and level of consciousness. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic and dopaminergic-related network changes under propofol sedation. Further, we delineate a cognition-related reconfiguration of the dopaminergic network, highlighting the utility of REACT to explore the molecular substrates of consciousness and cognition.
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Affiliation(s)
- Timothy Lawn
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK.
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Steve Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Matthew Howard
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
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Premi E, Dukart J, Mattioli I, Libri I, Pengo M, Gadola Y, Cotelli M, Manenti R, Binetti G, Gazzina S, Alberici A, Magoni M, Koch G, Gasparotti R, Padovani A, Borroni B. Unravelling neurotransmitters impairment in primary progressive aphasias. Hum Brain Mapp 2023; 44:2245-2253. [PMID: 36649260 PMCID: PMC10028634 DOI: 10.1002/hbm.26206] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/15/2022] [Accepted: 01/04/2023] [Indexed: 01/18/2023] Open
Abstract
Primary progressive aphasias (PPAs) are a group of neurodegenerative diseases mainly characterized by language impairment, and with variably presence of dysexecutive syndrome, behavioural disturbances and parkinsonism. Detailed knowledge of neurotransmitters impairment and its association with clinical features hold the potential to develop new tailored therapeutic approaches. In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of magnetic resonance imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 103 PPA patients and 80 age-matched healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in PPA patients (relative to HC) are correlated with specific neurotransmitter systems. As compared to HC, voxel-based brain changes in PPA were significantly associated with spatial distribution of serotonin, dopamine, and glutamatergic pathways (p < .05, False Discovery Rate corrected-corrected). Disease severity was negatively correlated with the strength of GMV colocalization of D1 receptors (p = .035) and serotonin transporter (p = .020). Moreover, we observed a significant negative correlation between positive behavioural symptoms, as measured with Frontal Behavioural Inventory, and GMV colocalization of D1 receptors (p = .007) and serotonin transporter (p < .001). This pilot study suggests that JuSpace is a helpful tool to indirectly assess neurotransmitter deficits in neurodegenerative dementias and may provide novel insight into disease mechanisms and associated clinical features.
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Affiliation(s)
- Enrico Premi
- Stroke Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM‐7)Research CentreJülichJülichGermany
- Institute of Systems Neuroscience, Medical FacultyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Irene Mattioli
- Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Ilenia Libri
- Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Marta Pengo
- Department of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
| | - Yasmine Gadola
- Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Maria Cotelli
- Neuropsychology UnitIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Rosa Manenti
- Neuropsychology UnitIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Giuliano Binetti
- MAC Memory Clinic and Molecular Markers LaboratoryIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Stefano Gazzina
- Neurophysiology Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
| | - Antonella Alberici
- Neurology Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
| | - Mauro Magoni
- Stroke Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
| | - Giacomo Koch
- Department of Neuroscience and RehabilitationUniversity of Ferrara and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT)FerraraItaly
- Department of Clinical and Behavioural NeurologySanta Lucia Foundation IRCCSRomeItaly
| | | | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
- Neurology Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
- Neurology Unit, Department of Neurological and Vision SciencesASST Spedali CiviliBresciaItaly
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Premi E, Pengo M, Mattioli I, Cantoni V, Dukart J, Gasparotti R, Buratti E, Padovani A, Bocchetta M, Todd EG, Bouzigues A, Cash DM, Convery RS, Russell LL, Foster P, Thomas DL, van Swieten JC, Jiskoot LC, Seelaar H, Galimberti D, Sanchez-Valle R, Laforce R, Moreno F, Synofzik M, Graff C, Masellis M, Tartaglia MC, Rowe JB, Tsvetanov KA, Vandenberghe R, Finger E, Tiraboschi P, de Mendonça A, Santana I, Butler CR, Ducharme S, Gerhard A, Levin J, Otto M, Sorbi S, Le Ber I, Pasquier F, Rohrer JD, Borroni B. Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study. Neurobiol Dis 2023; 179:106068. [PMID: 36898614 DOI: 10.1016/j.nbd.2023.106068] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/01/2023] [Accepted: 03/04/2023] [Indexed: 03/12/2023] Open
Abstract
BACKGROUND Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. METHODS In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. RESULTS In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01). CONCLUSIONS This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.
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Affiliation(s)
- Enrico Premi
- Neurology, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Marta Pengo
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Irene Mattioli
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Valentina Cantoni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research CentreJülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Roberto Gasparotti
- Neuroradiology Unit, Department of Medical and Surgical Specialties, University of Brescia, Brescia, Italy
| | | | - Alessandro Padovani
- Neurology, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy; Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Centre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, United Kingdom
| | - Emily G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Arabella Bouzigues
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Rhian S Convery
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Phoebe Foster
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - David L Thomas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - John C van Swieten
- Department of Neurology and Alzheimer center, Erasmus Medical Center Rotterdam, the Netherlands
| | - Lize C Jiskoot
- Department of Neurology and Alzheimer center, Erasmus Medical Center Rotterdam, the Netherlands
| | - Harro Seelaar
- Department of Neurology and Alzheimer center, Erasmus Medical Center Rotterdam, the Netherlands
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy; Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Raquel Sanchez-Valle
- Neurology Department, Hospital Clinic, Institut d'Investigacions Biomèdiques, Barcelona, Spain
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, Faculté de Médecine, Université Laval, Québec, Canada
| | - Fermin Moreno
- Hospital Universitario Donostia, San Sebastian, Spain
| | - Matthis Synofzik
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research (HIH), University of Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Caroline Graff
- Karolinska Institutet, Department NVS, Division of Neurogeriatrics, Stockholm, Sweden; Unit for Hereditray Dementia, Theme Aging, Karolinska University Hospital, Solna, Stockholm, Sweden
| | - Mario Masellis
- Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Toronto Western Hospital, Tanz Centre for Research in Neurodegenerative Disease, Toronto, ON, Canada
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Kamen A Tsvetanov
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
| | - Pietro Tiraboschi
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Chris R Butler
- Department of Clinical Neurology, University of Oxford, Oxford, United Kingdom
| | - Simon Ducharme
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, United Kingdom; Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg-Essen, Germany
| | - Johannes Levin
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster of System Neurology, Munich, Germany
| | - Markus Otto
- Department of Neurology, University Hospital Halle, Halle, Germany
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France; Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France; Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France; Reference Network for Rare Neurological Diseases (ERN-RND)
| | - Florence Pasquier
- University of Lille, France; Inserm 1172, Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Barbara Borroni
- Neurology, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy; Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
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Luppi AI, Singleton SP, Hansen JY, Bzdok D, Kuceyeski A, Betzel RF, Misic B. Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532981. [PMID: 36993597 PMCID: PMC10055141 DOI: 10.1101/2023.03.16.532981] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain's network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.
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Affiliation(s)
- Andrea I. Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | - Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- MILA, Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, U.S.A
| | - Richard F. Betzel
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, U.S.A
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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Bao H, Ren P, Yi L, Lv Z, Ding W, Li C, Li S, Li Z, Yang X, Liang X, Liang P. New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction. Int J Cancer 2023; 152:998-1012. [PMID: 36305649 PMCID: PMC10100131 DOI: 10.1002/ijc.34336] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 09/18/2022] [Accepted: 10/17/2022] [Indexed: 01/06/2023]
Abstract
Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower-grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel-based lesion-symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel-related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor-to-predilection distance metrics, which were able to predict GBM 1-year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.
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Affiliation(s)
- Hongbo Bao
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China.,Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China.,School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Peng Ren
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China.,School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Liye Yi
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhonghua Lv
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Wencai Ding
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chenlong Li
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Siyang Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China.,School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Zhipeng Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China.,School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xue Yang
- Department of Information, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xia Liang
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, China
| | - Peng Liang
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, China
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Chen Y, Chen Y, Zheng R, Jiang Y, Zhou B, Xue K, Li S, Pang J, Li H, Zhang Y, Han S, Cheng J. Convergent molecular and structural neuroimaging signatures of first-episode depression. J Affect Disord 2023; 320:22-28. [PMID: 36181910 DOI: 10.1016/j.jad.2022.09.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/31/2022] [Accepted: 09/26/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Convergent studies have demonstrated morphological abnormalities in various brain regions in depression patients. However, the molecular underpinnings of the structural impairments remain largely unknown, despite a pressing need for treatment targets and mechanisms. Here, we investigated the gray matter volume (GMV) alteration in patients with depression and its underlying molecular architecture. METHODS We recruited 195 first-episode, treatment-naïve depression patients and 78 gender-, age-, and education level-matched healthy controls (HCs) who underwent high-resolution T1-weighted magnetic resonance scans. Voxel-based morphometry (VBM) was adopted to calculate the GMV differences between two groups. Then we analyzed the spatial correlation between depression-induced alteration in GMV and density maps of 10 receptors/transporters deriving from prior molecular imaging in healthy people. RESULTS Compared to HCs, the depression group had significantly increased GMV in the left ventral portions of the ventral medial prefrontal cortex, parahippocampal gyrus, amygdala, the right superior parietal lobule and precuneus while decreased GMV in the bilateral hippocampus extending to the thalamus and cerebellum. The GMV alteration introduced by depression was spatially correlated with serotonin receptors (5-HT1a, 5-HT1b, and 5-HT2a), dopamine receptors (D1 and D2) and GABAergic receptor (GABAa) densities. LIMITATIONS The conclusions drawn in this study were obtained from a single dataset. CONCLUSIONS This study reveals abnormal GMV alteration and provides a series of neurotransmitters receptors possibly related to GMV alteration in depression, which facilitates an integrative understanding of the molecular mechanism underlying the structural abnormalities in depression and may provide clues to new treatment strategies.
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Affiliation(s)
- Yuan Chen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China
| | - Yi Chen
- Clinical Research Service Center, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jianyue Pang
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hengfen Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, Henan 450052, China; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, Henan 450052, China; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, Henan 450052, China; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, Henan 450052, China.
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Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain. Neuroimage 2022; 264:119671. [PMID: 36209794 DOI: 10.1016/j.neuroimage.2022.119671] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/29/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022] Open
Abstract
Neurotransmitter receptors modulate signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression measuring mRNA transcripts is often used as a proxy for receptor densities. In the present report, we comprehensively test the spatial correlation between gene expression and protein density for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography radioligand-based imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT1A, CB1, D2, and MOR). These expression-density associations are related to gene differential stability and can vary between cortical and subcortical structures. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function.
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