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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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Meindl M, Zatcepin A, Gnörich J, Scheifele M, Zaganjori M, Groß M, Lindner S, Schaefer R, Simmet M, Roemer S, Katzdobler S, Levin J, Höglinger G, Bischof AC, Barthel H, Sabri O, Bartenstein P, Saller T, Franzmeier N, Ziegler S, Brendel M. Assessment of [ 18F]PI-2620 Tau-PET Quantification via Non-Invasive Automatized Image Derived Input Function. Eur J Nucl Med Mol Imaging 2024; 51:3252-3266. [PMID: 38717592 PMCID: PMC11368995 DOI: 10.1007/s00259-024-06741-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 05/01/2024] [Indexed: 09/03/2024]
Abstract
PURPOSE [18F]PI-2620 positron emission tomography (PET) detects misfolded tau in progressive supranuclear palsy (PSP) and Alzheimer's disease (AD). We questioned the feasibility and value of absolute [18F]PI-2620 PET quantification for assessing tau by regional distribution volumes (VT). Here, arterial input functions (AIF) represent the gold standard, but cannot be applied in routine clinical practice, whereas image-derived input functions (IDIF) represent a non-invasive alternative. We aimed to validate IDIF against AIF and we evaluated the potential to discriminate patients with PSP and AD from healthy controls by non-invasive quantification of [18F] PET. METHODS In the first part of the study, we validated AIF derived from radial artery whole blood against IDIF by investigating 20 subjects (ten controls and ten patients). IDIF were generated by manual extraction of the carotid artery using the average and the five highest (max5) voxel intensity values and by automated extraction of the carotid artery using the average and the maximum voxel intensity value. In the second part of the study, IDIF quantification using the IDIF with the closest match to the AIF was transferred to group comparison of a large independent cohort of 40 subjects (15 healthy controls, 15 PSP patients and 10 AD patients). We compared VT and VT ratios, both calculated by Logan plots, with distribution volume (DV) ratios using simplified reference tissue modelling and standardized uptake value (SUV) ratios. RESULTS AIF and IDIF showed highly correlated input curves for all applied IDIF extraction methods (0.78 < r < 0.83, all p < 0.0001; area under the curves (AUC): 0.73 < r ≤ 0.82, all p ≤ 0.0003). Regarding the VT values, correlations were mainly found between those generated by the AIF and by the IDIF methods using the maximum voxel intensity values. Lowest relative differences (RD) were observed by applying the manual method using the five highest voxel intensity values (max5) (AIF vs. IDIF manual, avg: RD = -82%; AIF vs. IDIF automated, avg: RD = -86%; AIF vs. IDIF manual, max5: RD = -6%; AIF vs. IDIF automated, max: RD = -26%). Regional VT values revealed considerable variance at group level, which was strongly reduced upon scaling by the inferior cerebellum. The resulting VT ratio values were adequate to detect group differences between patients with PSP or AD and healthy controls (HC) (PSP target region (globus pallidus): HC vs. PSP vs. AD: 1.18 vs. 1.32 vs. 1.16; AD target region (Braak region I): HC vs. PSP vs. AD: 1.00 vs. 1.00 vs. 1.22). VT ratios and DV ratios outperformed SUV ratios and VT in detecting differences between PSP and healthy controls, whereas all quantification approaches performed similarly in comparing AD and healthy controls. CONCLUSION Blood-free IDIF is a promising approach for quantification of [18F]PI-2620 PET, serving as correlating surrogate for invasive continuous arterial blood sampling. Regional [18F]PI-2620 VT show large variance, in contrast to regional [18F]PI-2620 VT ratios scaled with the inferior cerebellum, which are appropriate for discriminating PSP, AD and healthy controls. DV ratios obtained by simplified reference tissue modeling are similarly suitable for this purpose.
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Affiliation(s)
- Maria Meindl
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
| | - Artem Zatcepin
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Johannes Gnörich
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Maximilian Scheifele
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Mirlind Zaganjori
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Mattes Groß
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Institute for Stroke and Dementia Research (ISD), Munich, Germany
| | - Simon Lindner
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Rebecca Schaefer
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Marcel Simmet
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sebastian Roemer
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sabrina Katzdobler
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Johannes Levin
- Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Günter Höglinger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, Medizinische Hochschule Hannover, Hannover, Germany
- Department of Neurology, Technical University Munich, Munich, Germany
| | - Ann-Cathrin Bischof
- Department of Anesthesiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Thomas Saller
- Department of Anesthesiology, LMU University Hospital, LMU Munich, Munich, Germany
| | | | - Sibylle Ziegler
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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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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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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de Araújo AS, Pinho MS, Marques da Silva AM, Fiorentini LF, Becker J. A 2.5D Self-Training Strategy for Carotid Artery Segmentation in T1-Weighted Brain Magnetic Resonance Images. J Imaging 2024; 10:161. [PMID: 39057732 PMCID: PMC11278143 DOI: 10.3390/jimaging10070161] [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: 06/02/2024] [Revised: 06/25/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
Precise annotations for large medical image datasets can be time-consuming. Additionally, when dealing with volumetric regions of interest, it is typical to apply segmentation techniques on 2D slices, compromising important information for accurately segmenting 3D structures. This study presents a deep learning pipeline that simultaneously tackles both challenges. Firstly, to streamline the annotation process, we employ a semi-automatic segmentation approach using bounding boxes as masks, which is less time-consuming than pixel-level delineation. Subsequently, recursive self-training is utilized to enhance annotation quality. Finally, a 2.5D segmentation technique is adopted, wherein a slice of a volumetric image is segmented using a pseudo-RGB image. The pipeline was applied to segment the carotid artery tree in T1-weighted brain magnetic resonance images. Utilizing 42 volumetric non-contrast T1-weighted brain scans from four datasets, we delineated bounding boxes around the carotid arteries in the axial slices. Pseudo-RGB images were generated from these slices, and recursive segmentation was conducted using a Res-Unet-based neural network architecture. The model's performance was tested on a separate dataset, with ground truth annotations provided by a radiologist. After recursive training, we achieved an Intersection over Union (IoU) score of (0.68 ± 0.08) on the unseen dataset, demonstrating commendable qualitative results.
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Affiliation(s)
- Adriel Silva de Araújo
- School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre 90619-900, Brazil;
| | - Márcio Sarroglia Pinho
- School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre 90619-900, Brazil;
| | | | - Luis Felipe Fiorentini
- Centro de Diagnóstico por Imagem, Santa Casa de Misericórdia de Porto Alegre, Porto Alegre 90020-090, Brazil
- Grupo Hospitalar Conceição, Porto Alegre 91350-200, Brazil
| | - Jefferson Becker
- Hospital São Lucas, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre 90610-000, Brazil
- Brain Institute, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre 90619-900, Brazil
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Saberi A, Wischnewski KJ, Jung K, Lotter LD, Schaare HL, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Lemaitre H, Poustka L, Hohmann S, Holz N, Baeuchl C, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Paus T, Dukart J, Bernhardt BC, Popovych OV, Eickhoff SB, Valk SL. Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.18.599509. [PMID: 38948771 PMCID: PMC11213014 DOI: 10.1101/2024.06.18.599509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.
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Affiliation(s)
- Amin Saberi
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Kevin J Wischnewski
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Mathematics, Faculty of Mathematics and Natural Sciences, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Kyesam Jung
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Leon D Lotter
- Institute of Neuroscience and Medicine - Brain and Behaviour (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 School of Cognition, Stephanstrasse 1A, 04103 Leipzig, Germany
| | - H Lina Schaare
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 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
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College 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
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College 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
- German Center for Mental Health (DZPG), site Berlin-Potsdam, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli; Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli; Gif-sur-Yvette, France
- AP-HP. Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli; Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- 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 Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, 33076 Bordeaux, France
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University Hospital Heidelberg, Heidelberg, 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
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Christian Baeuchl
- 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 Psychotherapy, Charité Universitätsmedizin 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, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
| | - Juergen Dukart
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Oleksandr V Popovych
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sofie L Valk
- Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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7
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Chen G, Wang W, Wu H, Zhao X, Kang X, Ren J, Zhang J, Sun Y, He J, Sun S, Zhong Z, Shang D, Fan M, Cheng J, Zhang D, Su C, Lin J. Disrupted topological properties of structural brain networks present a glutamatergic neuropathophysiology in people with narcolepsy. Sleep 2024; 47:zsae002. [PMID: 38173348 DOI: 10.1093/sleep/zsae002] [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: 07/26/2023] [Revised: 11/18/2023] [Indexed: 01/05/2024] Open
Abstract
STUDY OBJECTIVES Growing evidences have documented various abnormalities of the white matter bundles in people with narcolepsy. We sought to evaluate topological properties of brain structural networks, and their association with symptoms and neuropathophysiological features in people with narcolepsy. METHODS Diffusion tensor imaging was conducted for people with narcolepsy (n = 30) and matched healthy controls as well as symptoms assessment. Structural connectivity for each participant was generated to analyze global and regional topological properties and their correlations with narcoleptic features. Further human brain transcriptome was extracted and spatially registered for connectivity vulnerability. Genetic functional enrichment analysis was performed and further clarified using in vivo emission computed tomography data. RESULTS A wide and dramatic decrease in structural connectivities was observed in people with narcolepsy, with descending network degree and global efficiency. These metrics were not only correlated with sleep latency and awakening features, but also reflected alterations of sleep macrostructure in people with narcolepsy. Network-based statistics identified a small hyperenhanced subnetwork of cingulate gyrus that was closely related to rapid eye movement sleep behavior disorder (RBD) in narcolepsy. Further imaging genetics analysis suggested glutamatergic signatures were responsible for the preferential vulnerability of connectivity alterations in people with narcolepsy, while additional PET/SPECT data verified that structural alteration was significantly correlated with metabotropic glutamate receptor 5 (mGlutR5) and N-methyl-D-aspartate receptor (NMDA). CONCLUSIONS People with narcolepsy endured a remarkable decrease in the structural architecture, which was not only closely related to narcolepsy symptoms but also glutamatergic signatures.
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Affiliation(s)
- Guoyan Chen
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Wen Wang
- Department of Radiology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Haoyang Wu
- Basic Medicine School, Air Force Medical University, Xi'an, China
| | - Xianchao Zhao
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Xiaopeng Kang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Jiafeng Ren
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Jun Zhang
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Yingzhi Sun
- Department of Radiology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Jiaxiu He
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Shihui Sun
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Zhao Zhong
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Danqing Shang
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Mengmeng Fan
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Jinxiang Cheng
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Dan Zhang
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Changjun Su
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Jiaji Lin
- Department of Neurology, The Second Affiliated Hospital of Air Force Medical University, Xi'an, China
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, China
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8
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Mohr P, van Sluis J, Lub-de Hooge MN, Lammertsma AA, Brouwers AH, Tsoumpas C. Advances and challenges in immunoPET methodology. FRONTIERS IN NUCLEAR MEDICINE (LAUSANNE, SWITZERLAND) 2024; 4:1360710. [PMID: 39355220 PMCID: PMC11440922 DOI: 10.3389/fnume.2024.1360710] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 02/05/2024] [Indexed: 10/03/2024]
Abstract
Immuno-positron emission tomography (immunoPET) enables imaging of specific targets that play a role in targeted therapy and immunotherapy, such as antigens on cell membranes, targets in the disease microenvironment, or immune cells. The most common immunoPET applications use a monoclonal antibody labeled with a relatively long-lived positron emitter such as 89Zr (T 1/2 = 78.4 h), but smaller antibody-based constructs labeled with various other positron emitting radionuclides are also being investigated. This molecular imaging technique can thus guide the development of new drugs and may have a pivotal role in selecting patients for a particular therapy. In early phase immunoPET trials, multiple imaging time points are used to examine the time-dependent biodistribution and to determine the optimal imaging time point, which may be several days after tracer injection due to the slow kinetics of larger molecules. Once this has been established, usually only one static scan is performed and semi-quantitative values are reported. However, total PET uptake of a tracer is the sum of specific and nonspecific uptake. In addition, uptake may be affected by other factors such as perfusion, pre-/co-administration of the unlabeled molecule, and the treatment schedule. This article reviews imaging methodologies used in immunoPET studies and is divided into two parts. The first part summarizes the vast majority of clinical immunoPET studies applying semi-quantitative methodologies. The second part focuses on a handful of studies applying pharmacokinetic models and includes preclinical and simulation studies. Finally, the potential and challenges of immunoPET quantification methodologies are discussed within the context of the recent technological advancements provided by long axial field of view PET/CT scanners.
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Affiliation(s)
- Philipp Mohr
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Joyce van Sluis
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Marjolijn N Lub-de Hooge
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Adriaan A Lammertsma
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Adrienne H Brouwers
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Charalampos Tsoumpas
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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9
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Bucci M, Rebelos E, Oikonen V, Rinne J, Nummenmaa L, Iozzo P, Nuutila P. Kinetic Modeling of Brain [ 18-F]FDG Positron Emission Tomography Time Activity Curves with Input Function Recovery (IR) Method. Metabolites 2024; 14:114. [PMID: 38393006 PMCID: PMC10890269 DOI: 10.3390/metabo14020114] [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: 12/16/2023] [Revised: 02/01/2024] [Accepted: 02/03/2024] [Indexed: 02/25/2024] Open
Abstract
Accurate positron emission tomography (PET) data quantification relies on high-quality input plasma curves, but venous blood sampling may yield poor-quality data, jeopardizing modeling outcomes. In this study, we aimed to recover sub-optimal input functions by using information from the tail (5th-100th min) of curves obtained through the frequent sampling protocol and an input recovery (IR) model trained with reference curves of optimal shape. Initially, we included 170 plasma input curves from eight published studies with clamp [18F]-fluorodeoxyglucose PET exams. Model validation involved 78 brain PET studies for which compartmental model (CM) analysis was feasible (reference (ref) + training sets). Recovered curves were compared with original curves using area under curve (AUC), max peak standardized uptake value (maxSUV). CM parameters (ref + training sets) and fractional uptake rate (FUR) (all sets) were computed. Original and recovered curves from the ref set had comparable AUC (d = 0.02, not significant (NS)), maxSUV (d = 0.05, NS) and comparable brain CM results (NS). Recovered curves from the training set were different from the original according to maxSUV (d = 3) and biologically plausible according to the max theoretical K1 (53//56). Brain CM results were different in the training set (p < 0.05 for all CM parameters and brain regions) but not in the ref set. FUR showed reductions similarly in the recovered curves of the training and test sets compared to the original curves (p < 0.05 for all regions for both sets). The IR method successfully recovered the plasma inputs of poor quality, rescuing cases otherwise excluded from the kinetic modeling results. The validation approach proved useful and can be applied to different tracers and metabolic conditions.
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Affiliation(s)
- Marco Bucci
- Turku PET Centre, Turku University Hospital, 20521 Turku, Finland
- Turku PET Centre, University of Turku, 20521 Turku, Finland
- Turku PET Centre, Åbo Akademi University, 20521 Turku, Finland
- Theme Inflammation and Aging, Karolinska University Hospital, SE-141 86 Stockholm, Sweden
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska University, SE-141 84 Stockholm, Sweden
| | - Eleni Rebelos
- Turku PET Centre, University of Turku, 20521 Turku, Finland
| | - Vesa Oikonen
- Turku PET Centre, University of Turku, 20521 Turku, Finland
| | - Juha Rinne
- Turku PET Centre, Turku University Hospital, 20521 Turku, Finland
| | - Lauri Nummenmaa
- Turku PET Centre, University of Turku, 20521 Turku, Finland
- Department of Psychology, University of Turku, 20520 Turku, Finland
| | - Patricia Iozzo
- Institute of Clinical Physiology (IFC), National Research Council (CNR), 56124 Pisa, Italy
| | - Pirjo Nuutila
- Turku PET Centre, University of Turku, 20521 Turku, Finland
- Department of Endocrinology, Turku University Hospital, 20521 Turku, Finland
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10
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Volpi T, Maccioni L, Colpo M, Debiasi G, Capotosti A, Ciceri T, Carson RE, DeLorenzo C, Hahn A, Knudsen GM, Lammertsma AA, Price JC, Sossi V, Wang G, Zanotti-Fregonara P, Bertoldo A, Veronese M. An update on the use of image-derived input functions for human PET studies: new hopes or old illusions? EJNMMI Res 2023; 13:97. [PMID: 37947880 PMCID: PMC10638226 DOI: 10.1186/s13550-023-01050-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 11/02/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. MAIN BODY This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF. CONCLUSION Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.
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Affiliation(s)
- Tommaso Volpi
- Department of Radiology and Biomedical Imaging, Yale University, 801 Howard Avenue, PO Box 208048, New Haven, CT, 06520-8048, USA.
| | - Lucia Maccioni
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Maria Colpo
- Department of Information Engineering, University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Giulia Debiasi
- Department of Information Engineering, University of Padova, Padua, Italy
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | - Amedeo Capotosti
- Department of Information Engineering, University of Padova, Padua, Italy
- Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Tommaso Ciceri
- Department of Information Engineering, University of Padova, Padua, Italy
- Neuroimaging Laboratory, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, LC, Italy
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale University, 801 Howard Avenue, PO Box 208048, New Haven, CT, 06520-8048, USA
| | - Christine DeLorenzo
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Healthy (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Adriaan A Lammertsma
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, Netherlands
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA
| | - Vesna Sossi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Guobao Wang
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA, USA
| | | | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Mattia Veronese
- Department of Information Engineering, University of Padova, Padua, Italy
- Department of Neuroimaging, King's College London, London, UK
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11
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Baracchini G, Zhou Y, da Silva Castanheira J, Hansen JY, Rieck J, Turner GR, Grady CL, Misic B, Nomi J, Uddin LQ, Spreng RN. The biological role of local and global fMRI BOLD signal variability in human brain organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563476. [PMID: 37961684 PMCID: PMC10634715 DOI: 10.1101/2023.10.22.563476] [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
Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.
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Affiliation(s)
- Giulia Baracchini
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Yigu Zhou
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jason da Silva Castanheira
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Justine Y. Hansen
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | | | - Gary R. Turner
- Department of Psychology, York University, Toronto, ON, Canada
| | - Cheryl L. Grady
- Rotman Research Institute at Baycrest, and Department of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jason Nomi
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - Lucina Q. Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - R. Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
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12
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Bazinet V, Hansen JY, Vos de Wael R, Bernhardt BC, van den Heuvel MP, Misic B. Assortative mixing in micro-architecturally annotated brain connectomes. Nat Commun 2023; 14:2850. [PMID: 37202416 DOI: 10.1038/s41467-023-38585-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 05/08/2023] [Indexed: 05/20/2023] Open
Abstract
The wiring of the brain connects micro-architecturally diverse neuronal populations, but the conventional graph model, which encodes macroscale brain connectivity as a network of nodes and edges, abstracts away the rich biological detail of each regional node. Here, we annotate connectomes with multiple biological attributes and formally study assortative mixing in annotated connectomes. Namely, we quantify the tendency for regions to be connected based on the similarity of their micro-architectural attributes. We perform all experiments using four cortico-cortical connectome datasets from three different species, and consider a range of molecular, cellular, and laminar annotations. We show that mixing between micro-architecturally diverse neuronal populations is supported by long-distance connections and find that the arrangement of connections with respect to biological annotations is associated to patterns of regional functional specialization. By bridging scales of cortical organization, from microscale attributes to macroscale connectivity, this work lays the foundation for next-generation annotated connectomics.
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Affiliation(s)
- Vincent Bazinet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Martijn P van den Heuvel
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
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13
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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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14
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Galovic M, Al-Diwani A, Vivekananda U, Walker MC, Irani SR, Koepp MJ. In Vivo N-Methyl-d-Aspartate Receptor (NMDAR) Density as Assessed Using Positron Emission Tomography During Recovery From NMDAR-Antibody Encephalitis. JAMA Neurol 2023; 80:211-213. [PMID: 36469313 PMCID: PMC9857588 DOI: 10.1001/jamaneurol.2022.4352] [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: 07/06/2022] [Accepted: 09/09/2022] [Indexed: 12/12/2022]
Abstract
This case-control study uses a radiotracer and positron emission tomography to assess N-methyl-d-aspartate receptor (NMDAR) density changes during recovery from NMDAR-antibody encephalitis.
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Affiliation(s)
- Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Adam Al-Diwani
- Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Matthew C. Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarosh R. Irani
- Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Matthias J. Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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15
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van der Weijden CWJ, Mossel P, Bartels AL, Dierckx RAJO, Luurtsema G, Lammertsma AA, Willemsen ATM, de Vries EFJ. Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies. Eur J Nucl Med Mol Imaging 2023; 50:1636-1650. [PMID: 36651951 PMCID: PMC10119247 DOI: 10.1007/s00259-022-06057-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/21/2022] [Indexed: 01/19/2023]
Abstract
Pharmacokinetic modelling with arterial sampling is the gold standard for analysing dynamic PET data of the brain. However, the invasive character of arterial sampling prevents its widespread clinical application. Several methods have been developed to avoid arterial sampling, in particular reference region methods. Unfortunately, for some tracers or diseases, no suitable reference region can be defined. For these cases, other potentially non-invasive approaches have been proposed: (1) a population based input function (PBIF), (2) an image derived input function (IDIF), or (3) simultaneous estimation of the input function (SIME). This systematic review aims to assess the correspondence of these non-invasive methods with the gold standard. Studies comparing non-invasive pharmacokinetic modelling methods with the current gold standard methods using an input function derived from arterial blood samples were retrieved from PubMed/MEDLINE (until December 2021). Correlation measurements were extracted from the studies. The search yielded 30 studies that correlated outcome parameters (VT, DVR, or BPND for reversible tracers; Ki or CMRglu for irreversible tracers) from a potentially non-invasive method with those obtained from modelling using an arterial input function. Some studies provided similar results for PBIF, IDIF, and SIME-based methods as for modelling with an arterial input function (R2 = 0.59-1.00, R2 = 0.71-1.00, R2 = 0.56-0.96, respectively), if the non-invasive input curve was calibrated with arterial blood samples. Even when the non-invasive input curve was calibrated with venous blood samples or when no calibration was applied, moderate to good correlations were reported, especially for the IDIF and SIME (R2 = 0.71-1.00 and R2 = 0.36-0.96, respectively). Overall, this systematic review illustrates that non-invasive methods to generate an input function are still in their infancy. Yet, IDIF and SIME performed well, not only with arterial blood calibration, but also with venous or no blood calibration, especially for some tracers without plasma metabolites, which would potentially make these methods better suited for clinical application. However, these methods should still be properly validated for each individual tracer and application before implementation.
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Affiliation(s)
- Chris W J van der Weijden
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands.,Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Pascalle Mossel
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Anna L Bartels
- Department of Neurology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Gert Luurtsema
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Adriaan A Lammertsma
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Antoon T M Willemsen
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Erik F J de Vries
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands.
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16
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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: 141] [Impact Index Per Article: 70.5] [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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17
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Okazawa H, Ikawa M, Tsujikawa T, Mori T, Makino A, Kiyono Y, Nakamoto Y, Kosaka H, Yoneda M. Cerebral Oxidative Stress in Early Alzheimer's Disease Evaluated by 64Cu-ATSM PET/MRI: A Preliminary Study. Antioxidants (Basel) 2022; 11:1022. [PMID: 35624886 PMCID: PMC9138060 DOI: 10.3390/antiox11051022] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/16/2022] [Accepted: 05/20/2022] [Indexed: 12/17/2022] Open
Abstract
Oxidative stress imaging using diacetyl-bis (N4-methylthiosemicarbazone) (Cu-ATSM) was applied to the evaluation of patients with early Alzheimer's disease (eAD). Ten eAD patients (72 ± 9 years) and 10 age-matched healthy controls (HCs) (73 ± 9 years) participated in this study. They underwent dynamic PET/MRI using 11C-PiB and 64Cu-ATSM with multiple MRI sequences. To evaluate cerebral oxidative stress, three parameters of 64Cu-ATSM PET were compared: standardized uptake value (SUV), tracer influx rate (Kin), and a rate constant k3. The input functions were estimated by the image-derived input function method. The relative differences were analyzed by statistical parametric mapping (SPM) using SUV and Kin images. All eAD patients had positive and HC subjects had negative PiB accumulation, and MMSE scores were significantly different between them. The 64Cu-ATSM accumulation tended to be higher in eAD than in HCs for both SUV and Kin. When comparing absolute values, eAD patients had a greater Kin in the posterior cingulate cortex and a greater k3 in the hippocampus compared with lobar cortical values of HCs. In SPM analysis, eAD had an increased left operculum and decreased bilateral hippocampus and anterior cingulate cortex compared to HCs. 64Cu-ATSM PET/MRI and tracer kinetic analysis elucidated cerebral oxidative stress in the eAD patients, particularly in the cingulate cortex and hippocampus.
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Affiliation(s)
- Hidehiko Okazawa
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
| | - Masamichi Ikawa
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui 910-1193, Japan;
| | - Tetsuya Tsujikawa
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
| | - Tetsuya Mori
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
| | - Akira Makino
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
| | - Yasushi Kiyono
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
| | - Yasunari Nakamoto
- Second Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Fukui 910-1193, Japan;
| | - Hirotaka Kosaka
- Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui 910-1193, Japan;
| | - Makoto Yoneda
- Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan; (M.I.); (T.T.); (T.M.); (A.M.); (Y.K.); (M.Y.)
- Faculty of Nursing and Social Welfare Science, Fukui Prefectural University, Fukui 910-1195, Japan
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18
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Lam MTY, Duttke SH, Odish MF, Le HD, Hansen EA, Nguyen CT, Trescott S, Kim R, Deota S, Chang MW, Patel A, Hepokoski M, Alotaibi M, Rolfsen M, Perofsky K, Warden AS, Foley J, Ramirez SI, Dan JM, Abbott RK, Crotty S, Crotty Alexander LE, Malhotra A, Panda S, Benner CW, Coufal NG. Profiling Transcription Initiation in Peripheral Leukocytes Reveals Severity-Associated Cis-Regulatory Elements in Critical COVID-19. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.08.24.457187. [PMID: 34462742 DOI: 10.1101/2021.10.28.466336] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The contribution of transcription factors (TFs) and gene regulatory programs in the immune response to COVID-19 and their relationship to disease outcome is not fully understood. Analysis of genome-wide changes in transcription at both promoter-proximal and distal cis-regulatory DNA elements, collectively termed the 'active cistrome,' offers an unbiased assessment of TF activity identifying key pathways regulated in homeostasis or disease. Here, we profiled the active cistrome from peripheral leukocytes of critically ill COVID-19 patients to identify major regulatory programs and their dynamics during SARS-CoV-2 associated acute respiratory distress syndrome (ARDS). We identified TF motifs that track the severity of COVID- 19 lung injury, disease resolution, and outcome. We used unbiased clustering to reveal distinct cistrome subsets delineating the regulation of pathways, cell types, and the combinatorial activity of TFs. We found critical roles for regulatory networks driven by stimulus and lineage determining TFs, showing that STAT and E2F/MYB regulatory programs targeting myeloid cells are activated in patients with poor disease outcomes and associated with single nucleotide genetic variants implicated in COVID-19 susceptibility. Integration with single-cell RNA-seq found that STAT and E2F/MYB activation converged in specific neutrophils subset found in patients with severe disease. Collectively we demonstrate that cistrome analysis facilitates insight into disease mechanisms and provides an unbiased approach to evaluate global changes in transcription factor activity and stratify patient disease severity.
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Affiliation(s)
- Michael Tun Yin Lam
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
- Laboratory of Regulatory Biology, Salk Institute of Biological Studies, La Jolla, CA, USA
| | - Sascha H Duttke
- Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Diego, CA, USA
| | - Mazen F Odish
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Hiep D Le
- Laboratory of Regulatory Biology, Salk Institute of Biological Studies, La Jolla, CA, USA
| | - Emily A Hansen
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, CA, USA
| | - Celina T Nguyen
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
| | - Samantha Trescott
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, CA, USA
| | - Roy Kim
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, CA, USA
| | - Shaunak Deota
- Laboratory of Regulatory Biology, Salk Institute of Biological Studies, La Jolla, CA, USA
| | - Max W Chang
- Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Diego, CA, USA
| | - Arjun Patel
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Mark Hepokoski
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Mona Alotaibi
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Mark Rolfsen
- Internal Medicine Residency Program, Department of Medicine, UC San Diego, CA, USA
| | - Katherine Perofsky
- Department of Pediatrics, University of California, San Diego, CA, USA
- Rady Children's Hospital, San Diego, CA
| | - Anna S Warden
- Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Diego, CA, USA
| | | | - Sydney I Ramirez
- Division of Infectious Diseases, Department of Medicine, University of California, San Diego
- Center for Infectious Diseases and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA
| | - Jennifer M Dan
- Division of Infectious Diseases, Department of Medicine, University of California, San Diego
- Center for Infectious Diseases and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA
| | - Robert K Abbott
- Center for Infectious Diseases and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA
- Consortium for HIV/AIDS Vaccine Development (CHVAD), The Scripps Research Institute, La Jolla, CA, USA
| | - Shane Crotty
- Center for Infectious Diseases and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA
| | - Laura E Crotty Alexander
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Atul Malhotra
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California, San Diego, CA USA
| | - Satchidananda Panda
- Laboratory of Regulatory Biology, Salk Institute of Biological Studies, La Jolla, CA, USA
| | - Christopher W Benner
- Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Diego, CA, USA
| | - Nicole G Coufal
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, CA, USA
- Rady Children's Hospital, San Diego, CA
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