1
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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. Nat Neurosci 2024; 27:2500-2511. [PMID: 39414973 PMCID: PMC11614745 DOI: 10.1038/s41593-024-01787-0] [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: 11/06/2023] [Accepted: 09/13/2024] [Indexed: 10/18/2024]
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. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified 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 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 replicated all findings using 3-Tesla data from the same participants. Collectively, this work demonstrates 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, Quebec, 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, National Institutes of Health, 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, Mexico
| | - James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, 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, Quebec, Canada.
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2
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Zhang X, Huang L, Zhang J, Li L, An X. Association between post-stroke depression and post-stroke sleep disorders: a systematic review and meta-analysis. Sleep Breath 2024; 29:5. [PMID: 39585438 DOI: 10.1007/s11325-024-03200-3] [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: 07/18/2024] [Revised: 08/30/2024] [Accepted: 10/07/2024] [Indexed: 11/26/2024]
Abstract
BACKGROUND Post-stroke depression (PSD) and post-stroke sleep disorders (PSSD) are common concurrent symptoms in post-stroke patients, and their early detection may have an impact on stroke recovery and prognosis. The purpose of this study is to determine the relationship between PSD and PSSD. METHODS We systematically searched PubMed, Embase, Web of Science, Cochrane Library, APA PsycInfo, Medline, Scopus, Technology Periodical Database (VIP), China Biology Medicine (CBM), China National Knowledge Infrastructure (CNKI), and WanFang Data databases for studies on the association between PSD and PSSD, with a search timeframe ranging from database construction to May 9, 2024, two researchers independently performed literature search, screening and quality assessment, and RevMan (version 5.4) and Stata (version 15.1) software were used for statistical analysis. RESULTS We included 16 studies, nine in Chinese and seven in English, with 2,284 stroke patients. The results showed that the pooled Fisher's Z was 0.58 (95% CI = 0.52-0.65, P < 0.00001). After data transformation, the pooled r-value was 0.52, indicating a positive correlation between PSD and PSSD. CONCLUSIONS The available evidence suggested that PSD was positively correlated with PSSD. Given the correlation between PSD and PSSD, alleviating PSSD may reduce the incidence of PSD, and improving PSD may also improve patients' sleep quality.
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Affiliation(s)
- Xingling Zhang
- School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Linyu Huang
- School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jie Zhang
- School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Long Li
- School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xuemei An
- Department of Nursing, Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- Deyang Hospital, Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
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3
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Saberi A, Ebneabbasi A, Rahimi S, Sarebannejad S, Sen ZD, Graf H, Walter M, Sorg C, Camilleri JA, Laird AR, Fox PT, Valk SL, Eickhoff SB, Tahmasian M. Convergent functional effects of antidepressants in major depressive disorder: a neuroimaging meta-analysis. Mol Psychiatry 2024:10.1038/s41380-024-02780-6. [PMID: 39406999 DOI: 10.1038/s41380-024-02780-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 09/27/2024] [Accepted: 10/01/2024] [Indexed: 10/23/2024]
Abstract
BACKGROUND Neuroimaging studies have provided valuable insights into the macroscale impacts of antidepressants on brain functions in patients with major depressive disorder. However, the findings of individual studies are inconsistent. Here, we aimed to provide a quantitative synthesis of the literature to identify convergence of the reported findings at both regional and network levels and to examine their associations with neurotransmitter systems. METHODS Through a comprehensive search in PubMed and Scopus databases, we reviewed 5258 abstracts and identified 36 eligible functional neuroimaging studies on antidepressant effects in major depressive disorder. Activation likelihood estimation was used to investigate regional convergence of the reported foci of antidepressant effects, followed by functional decoding and connectivity mapping of the convergent clusters. Additionally, utilizing group-averaged data from the Human Connectome Project, we assessed convergent resting-state functional connectivity patterns of the reported foci. Next, we compared the convergent circuit with the circuits targeted by transcranial magnetic stimulation therapy. Last, we studied the association of regional and network-level convergence maps with selected neurotransmitter receptors/transporters maps. RESULTS No regional convergence was found across foci of treatment-associated alterations in functional imaging. Subgroup analysis in the Treated > Untreated contrast revealed a convergent cluster in the left dorsolateral prefrontal cortex, which was associated with working memory and attention behavioral domains. Moreover, we found network-level convergence of the treatment-associated alterations in a circuit more prominent in the frontoparietal areas. This circuit was co-aligned with circuits targeted by "anti-subgenual" and "Beam F3" transcranial magnetic stimulation therapy. We observed no significant correlations between our meta-analytic findings with the maps of neurotransmitter receptors/transporters. CONCLUSION Our findings highlight the importance of the frontoparietal network and the left dorsolateral prefrontal cortex in the therapeutic effects of antidepressants, which may relate to their role in improving executive functions and emotional processing.
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Affiliation(s)
- Amin Saberi
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Amir Ebneabbasi
- Department of Clinical Neurosciences, University of Cambridge, Biomedical Campus, Cambridge, UK
- Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Sama Rahimi
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Neuroscience Center, Goethe University, Frankfurt, Hessen, Germany
| | - Sara Sarebannejad
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Zumrut Duygu Sen
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, University Tübingen, Tübingen, Germany
- German Center for Mental Health, partner site Halle-Jena-Magdeburg, Jena, Germany
| | - Heiko Graf
- Department of Psychiatry and Psychotherapy III, University of Ulm, Ulm, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, University Tübingen, Tübingen, Germany
- German Center for Mental Health, partner site Halle-Jena-Magdeburg, Jena, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Christian Sorg
- TUM-Neuroimaging Center, School of Medicine and Healthy, Technical University Munich, Munich, Germany
- Department of Neuroradiology,School of Medicine and Healthy, Technical University Munich, Munich, Germany
- Department of Psychiatry, School of Medicine and Healthy, Technical University Munich, Munich, Germany
| | - Julia A Camilleri
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Sofie L Valk
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Simon B Eickhoff
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Masoud Tahmasian
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
- Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.
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4
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Saberi A, Ebneabbasi A, Rahimi S, Sarebannejad S, Sen ZD, Graf H, Walter M, Sorg C, Camilleri JA, Laird AR, Fox PT, Valk SL, Eickhoff SB, Tahmasian M. Convergent functional effects of antidepressants in major depressive disorder: a neuroimaging meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.24.23298991. [PMID: 38076878 PMCID: PMC10705609 DOI: 10.1101/2023.11.24.23298991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
Background Neuroimaging studies have provided valuable insights into the macroscale impacts of antidepressants on brain functions in patients with major depressive disorder. However, the findings of individual studies are inconsistent. Here, we aimed to provide a quantitative synthesis of the literature to identify convergence of the reported findings at both regional and network levels and to examine their associations with neurotransmitter systems. Methods Through a comprehensive search in PubMed and Scopus databases, we reviewed 5,258 abstracts and identified 36 eligible functional neuroimaging studies on antidepressant effects in major depressive disorder. Activation likelihood estimation was used to investigate regional convergence of the reported foci of consistent antidepressant effects, followed by functional decoding and connectivity mapping of the convergent clusters. Additionally, utilizing group-averaged data from the Human Connectome Project, we assessed convergent resting-state functional connectivity patterns of the reported foci. Next, we compared the convergent circuit with the circuits targeted by transcranial magnetic stimulation (TMS) therapy. Last, we studied the association of regional and network-level convergence maps with selected neurotransmitter receptors/transporters maps. Results No regional convergence was found across foci of treatment-associated alterations in functional imaging. Subgroup analysis across the Treated > Untreated contrast revealed a convergent cluster in the left dorsolateral prefrontal cortex, which was associated with working memory and attention behavioral domains. Moreover, we found network-level convergence of the treatment-associated alterations in a circuit more prominent in the frontoparietal areas. This circuit was co-aligned with circuits targeted by "anti-subgenual" and "Beam F3" TMS therapy. We observed no significant correlations between our meta-analytic findings with the maps of neurotransmitter receptors/transporters. Conclusion Our findings highlight the importance of the frontoparietal network and the left dorsolateral prefrontal cortex in the therapeutic effects of antidepressants, which may relate to their role in improving executive functions and emotional processing.
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5
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Qu J, Qu Y, Zhu R, Wu Y, Xu G, Wang D. Transcriptional expression patterns of the cortical morphometric similarity network in progressive supranuclear palsy. CNS Neurosci Ther 2024; 30:e14901. [PMID: 39097922 PMCID: PMC11298202 DOI: 10.1111/cns.14901] [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: 06/10/2024] [Revised: 07/09/2024] [Accepted: 07/24/2024] [Indexed: 08/06/2024] Open
Abstract
BACKGROUND It has been demonstrated that progressive supranuclear palsy (PSP) correlates with structural abnormalities in several distinct regions of the brain. However, whether there are changes in the morphological similarity network (MSN) and the relationship between changes in brain structure and gene expression remain largely unknown. METHODS We used two independent cohorts (discovery dataset: PSP: 51, healthy controls (HC): 82; replication dataset: PSP: 53, HC: 55) for MSN analysis and comparing the longitudinal changes in the MSN of PSP. Then, we applied partial least squares regression to determine the relationships between changes in MSN and spatial transcriptional features and identified specific genes associated with MSN differences in PSP. We further investigated the biological processes enriched in PSP-associated genes and the cellular characteristics of these genes, and finally, we performed an exploratory analysis of the relationship between MSN changes and neurotransmitter receptors. RESULTS We found that the MSN in PSP patients was mainly decreased in the frontal and temporal cortex but increased in the occipital cortical region. This difference is replicable. In longitudinal studies, MSN differences are mainly manifested in the frontal and parietal regions. Furthermore, the expression pattern associated with MSN changes in PSP involves genes implicated in astrocytes and excitatory and inhibitory neurons and is functionally enriched in neuron-specific biological processes related to synaptic signaling. Finally, we found that the changes in MSN were mainly negatively correlated with the levels of serotonin, norepinephrine, and opioid receptors. CONCLUSIONS These results have enhanced our understanding of the microscale genetic and cellular mechanisms responsible for large-scale morphological abnormalities in PSP patients, suggesting potential targets for future therapeutic trials.
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Affiliation(s)
- Junyu Qu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Yancai Qu
- Department of NeurosurgeryTraditional Chinese Medicine Hospital of Muping DistrictYantaiChina
| | - Rui Zhu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Yongsheng Wu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Guihua Xu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Dawei Wang
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
- Magnetic Field‐free Medicine & Functional ImagingResearch Institute of Shandong UniversityJinanChina
- Magnetic Field‐free Medicine & Functional Imaging (MF)Shandong Key LaboratoryJinanChina
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6
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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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7
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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. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564245. [PMID: 37961347 PMCID: PMC10634864 DOI: 10.1101/2023.10.26.564245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
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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8
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Hansen JY, Shafiei G, Markello RD, Smart K, Cox SML, Nørgaard M, Beliveau V, Wu Y, Gallezot JD, Aumont É, Servaes S, Scala SG, DuBois JM, Wainstein G, Bezgin G, Funck T, Schmitz TW, Spreng RN, Galovic M, Koepp MJ, Duncan JS, Coles JP, Fryer TD, Aigbirhio FI, McGinnity CJ, Hammers A, Soucy JP, Baillet S, Guimond S, Hietala J, Bedard MA, Leyton M, Kobayashi E, Rosa-Neto P, Ganz M, Knudsen GM, Palomero-Gallagher N, Shine JM, Carson RE, Tuominen L, Dagher A, Misic B. Mapping neurotransmitter systems to the structural and functional organization of the human neocortex. Nat Neurosci 2022; 25:1569-1581. [PMID: 36303070 PMCID: PMC9630096 DOI: 10.1038/s41593-022-01186-3] [Citation(s) in RCA: 190] [Impact Index Per Article: 95.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 09/20/2022] [Indexed: 01/13/2023]
Abstract
Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
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Affiliation(s)
- Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ross D Markello
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Kelly Smart
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Sylvia M L Cox
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Martin Nørgaard
- Department of Psychology, Center for Reproducible Neuroscience, Stanford University, Stanford, CA, USA
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Vincent Beliveau
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Yanjun Wu
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Jean-Dominique Gallezot
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Étienne Aumont
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Stijn Servaes
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | | | | | | | - Gleb Bezgin
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Thomas Funck
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Taylor W Schmitz
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - R Nathan Spreng
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Jonathan P Coles
- Department of Medicine, Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Colm J McGinnity
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Alexander Hammers
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Jean-Paul Soucy
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Sylvain Baillet
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Synthia Guimond
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychoeducation and Psychology, University of Quebec in Outaouais, Gatineau, QC, Canada
| | - Jarmo Hietala
- Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Marc-André Bedard
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Eliane Kobayashi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Pedro Rosa-Neto
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Melanie Ganz
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - James M Shine
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Richard E Carson
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lauri Tuominen
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Alain Dagher
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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9
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Fu H, Rong J, Chen Z, Zhou J, Collier T, Liang SH. Positron Emission Tomography (PET) Imaging Tracers for Serotonin Receptors. J Med Chem 2022; 65:10755-10808. [PMID: 35939391 DOI: 10.1021/acs.jmedchem.2c00633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Serotonin (5-hydroxytryptamine, 5-HT) and 5-HT receptors (5-HTRs) have crucial roles in various neuropsychiatric disorders and neurodegenerative diseases, making them attractive diagnostic and therapeutic targets. Positron emission tomography (PET) is a noninvasive nuclear molecular imaging technique and is an essential tool in clinical diagnosis and drug discovery. In this context, numerous PET ligands have been developed for "visualizing" 5-HTRs in the brain and translated into human use to study disease mechanisms and/or support drug development. Herein, we present a comprehensive repertoire of 5-HTR PET ligands by focusing on their chemotypes and performance in PET imaging studies. Furthermore, this Perspective summarizes recent 5-HTR-focused drug discovery, including biased agonists and allosteric modulators, which would stimulate the development of more potent and subtype-selective 5-HTR PET ligands and thus further our understanding of 5-HTR biology.
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Affiliation(s)
- Hualong Fu
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Jian Rong
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.,Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Zhen Chen
- Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Chemical Engineering, Nanjing Forestry University, Nanjing, Jiangsu 210037, China
| | - Jingyin Zhou
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Thomas Collier
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.,Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Steven H Liang
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.,Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115, United States
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