1
|
Navarri X, Robertson DN, Charfi I, Wünnemann F, Sâmia Fernandes do Nascimento A, Trottier G, Leclerc S, Andelfinger GU, Di Cristo G, Richer L, Pike GB, Pausova Z, Piñeyro G, Paus T. Cells and Molecules Underpinning Cannabis-Related Variations in Cortical Thickness during Adolescence. J Neurosci 2024; 44:e2256232024. [PMID: 39214708 PMCID: PMC11466068 DOI: 10.1523/jneurosci.2256-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 06/05/2024] [Accepted: 07/02/2024] [Indexed: 09/04/2024] Open
Abstract
During adolescence, cannabis experimentation is common, and its association with interindividual variations in brain maturation well studied. Cellular and molecular underpinnings of these system-level relationships are, however, unclear. We thus conducted a three-step study. First, we exposed adolescent male mice to Δ-9-tetrahydrocannabinol (THC) or a synthetic cannabinoid WIN 55,212-2 (WIN) and assessed differentially expressed genes (DEGs), spine numbers, and dendritic complexity in their frontal cortex. Second, in human (male) adolescents, we examined group differences in cortical thickness in 34 brain regions, using magnetic resonance imaging, between those who experimented with cannabis before age 16 (n = 140) and those who did not (n = 327). Finally, we correlated spatially these group differences with gene expression of human homologs of mouse-identified DEGs. The spatial expression of 13 THC-related human homologs of DEGs correlated with cannabis-related variations in cortical thickness, and virtual histology revealed coexpression patterns of these 13 genes with cell-specific markers of astrocytes, microglia, and a type of pyramidal cells enriched in dendrite-regulating genes. Similarly, the spatial expression of 18 WIN-related human homologs of DEGs correlated with group differences in cortical thickness and showed coexpression patterns with the same three cell types. Gene ontology analysis indicated that 37 THC-related human homologs are enriched in neuron projection development, while 33 WIN-related homologs are enriched in processes associated with learning and memory. In mice, we observed spine loss and lower dendritic complexity in pyramidal cells of THC-exposed animals (vs controls). Experimentation with cannabis during adolescence may influence cortical thickness by impacting glutamatergic synapses and dendritic arborization.
Collapse
Affiliation(s)
- Xavier Navarri
- Department of Neuroscience, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
| | | | - Iness Charfi
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pharmacology, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Florian Wünnemann
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pediatrics, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | | | - Giacomo Trottier
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pharmacology, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Sévérine Leclerc
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pediatrics, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Gregor U Andelfinger
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pediatrics, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Graziella Di Cristo
- Department of Neuroscience, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pediatrics, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Louis Richer
- Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, Quebec G7H 2B1, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Zdenka Pausova
- Departments of Physiology and Nutritional Sciences, Hospital for Sick Children, University of Toronto, Peter Gilgan Centre for Research and Learning, Toronto, Ontario M5G 0A4, Canada
| | - Graciela Piñeyro
- Department of Neuroscience, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Pharmacology, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Tomáš Paus
- Department of Neuroscience, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
- CHU Ste-Justine Research Centre, Montréal, Quebec H3T 1C5, Canada
- Department of Psychiatry and Addictology, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| |
Collapse
|
2
|
Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère ML, Artiges E, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development correlate with underlying neurobiology. Nat Commun 2024; 15:7987. [PMID: 39284858 PMCID: PMC11405413 DOI: 10.1038/s41467-024-52366-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 08/29/2024] [Indexed: 09/22/2024] Open
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
Collapse
Affiliation(s)
- Leon D Lotter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
- Max Planck School of Cognition; Stephanstrasse 1A, Leipzig, Germany.
| | - Amin Saberi
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Casey Paquola
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham; University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB); Braunschweig and Berlin, Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli, Gif-sur-Yvette, France
- Department of Psychiatry, EPS Barthélémy Durand, Etampes, France
| | | | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Frauke Nees
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim-Heidelberg-Ulm, Heidelberg, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
| |
Collapse
|
3
|
Shi Z, Li X, Todaro DR, Cao W, Lynch KG, Detre JA, Loughead J, Langleben DD, Wiers CE. Medial prefrontal neuroplasticity during extended-release naltrexone treatment of opioid use disorder - a longitudinal structural magnetic resonance imaging study. Transl Psychiatry 2024; 14:360. [PMID: 39237534 PMCID: PMC11377591 DOI: 10.1038/s41398-024-03061-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 08/20/2024] [Accepted: 08/22/2024] [Indexed: 09/07/2024] Open
Abstract
Opioid use disorder (OUD) has been linked to macroscopic structural alterations in the brain. The monthly injectable, extended-release formulation of μ-opioid antagonist naltrexone (XR-NTX) is highly effective in reducing opioid craving and preventing opioid relapse. Here, we investigated the neuroanatomical effects of XR-NTX by examining changes in cortical thickness during treatment for OUD. Forty-seven OUD patients underwent structural magnetic resonance imaging and subjectively rated their opioid craving ≤1 day before (pre-treatment) and 11 ± 3 days after (on-treatment) the first XR-NTX injection. A sample of fifty-six non-OUD individuals completed a single imaging session and served as the comparison group. A publicly available [¹¹C]carfentanil positron emission tomography dataset was used to assess the relationship between changes in cortical thickness and μ-opioid receptor (MOR) binding potential across brain regions. We found that the thickness of the medial prefrontal and anterior cingulate cortices (mPFC/aCC; regions with high MOR binding potential) was comparable between the non-OUD individuals and the OUD patients at pre-treatment. However, among the OUD patients, mPFC/aCC thickness significantly decreased from pre-treatment to on-treatment. A greater reduction in mPFC/aCC thickness was associated with a greater reduction in opioid craving. Taken together, our study suggests XR-NTX-induced cortical thickness reduction in the mPFC/aCC regions in OUD patients. The reduction in thickness does not appear to indicate a restoration to the non-OUD level but rather reflects XR-NTX's distinct therapeutic impact on an MOR-rich brain structure. Our findings highlight the neuroplastic effects of XR-NTX that may inform the development of novel OUD interventions.
Collapse
Affiliation(s)
- Zhenhao Shi
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Xinyi Li
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dustin R Todaro
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wen Cao
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kevin G Lynch
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - James Loughead
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel D Langleben
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Corinde E Wiers
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| |
Collapse
|
4
|
González-Peñas J, Alloza C, Brouwer R, Díaz-Caneja CM, Costas J, González-Lois N, Gallego AG, de Hoyos L, Gurriarán X, Andreu-Bernabeu Á, Romero-García R, Fañanás L, Bobes J, González-Pinto A, Crespo-Facorro B, Martorell L, Arrojo M, Vilella E, Gutiérrez-Zotes A, Perez-Rando M, Moltó MD, Buimer E, van Haren N, Cahn W, O'Donovan M, Kahn RS, Arango C, Pol HH, Janssen J, Schnack H. Accelerated Cortical Thinning in Schizophrenia Is Associated With Rare and Common Predisposing Variation to Schizophrenia and Neurodevelopmental Disorders. Biol Psychiatry 2024; 96:376-389. [PMID: 38521159 DOI: 10.1016/j.biopsych.2024.03.011] [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: 08/17/2023] [Revised: 02/22/2024] [Accepted: 03/05/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Schizophrenia is a highly heritable disorder characterized by increased cortical thinning throughout the life span. Studies have reported a shared genetic basis between schizophrenia and cortical thickness. However, no genes whose expression is related to abnormal cortical thinning in schizophrenia have been identified. METHODS We conducted linear mixed models to estimate the rates of accelerated cortical thinning across 68 regions from the Desikan-Killiany atlas in individuals with schizophrenia compared with healthy control participants from a large longitudinal sample (ncases = 169 and ncontrols = 298, ages 16-70 years). We studied the correlation between gene expression data from the Allen Human Brain Atlas and accelerated thinning estimates across cortical regions. Finally, we explored the functional and genetic underpinnings of the genes that contribute most to accelerated thinning. RESULTS We found a global pattern of accelerated cortical thinning in individuals with schizophrenia compared with healthy control participants. Genes underexpressed in cortical regions that exhibit this accelerated thinning were downregulated in several psychiatric disorders and were enriched for both common and rare disrupting variation for schizophrenia and neurodevelopmental disorders. In contrast, none of these enrichments were observed for baseline cross-sectional cortical thickness differences. CONCLUSIONS Our findings suggest that accelerated cortical thinning, rather than cortical thickness alone, serves as an informative phenotype for neurodevelopmental disruptions in schizophrenia. We highlight the genetic and transcriptomic correlates of this accelerated cortical thinning, emphasizing the need for future longitudinal studies to elucidate the role of genetic variation and the temporal-spatial dynamics of gene expression in brain development and aging in schizophrenia.
Collapse
Affiliation(s)
- Javier González-Peñas
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain.
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Rachel Brouwer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier Costas
- Instituto de Investigación Sanitària de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde, Santiago de Compostela, Galicia, Spain
| | - Noemí González-Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Ana Guil Gallego
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Xaquín Gurriarán
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Rafael Romero-García
- Department of Medical Physiology and Biophysics, Instituto de Biomedicina de Sevilla, HUVR/CSIC/Universidad de Sevilla/CIBERSAM, Instituto de Salud Carlos III, Sevilla, Spain; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Lourdes Fañanás
- CIBERSAM, Madrid, Spain; Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Julio Bobes
- CIBERSAM, Madrid, Spain; Faculty of Medicine and Health Sciences-Psychiatry, Universidad de Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias, Instituto de Neurociencias del Principado de Asturias, Oviedo, Spain
| | - Ana González-Pinto
- CIBERSAM, Madrid, Spain; BIOARABA Health Research Institute, Organización Sanitaria Integrada Araba, University Hospital, University of the Basque Country, Vitoria, Spain
| | - Benedicto Crespo-Facorro
- CIBERSAM, Madrid, Spain; Hospital Universitario Virgen del Rocío, Department of Psychiatry, Universidad de Sevilla, Sevilla, Spain
| | - Lourdes Martorell
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Manuel Arrojo
- Instituto de Investigación Sanitària de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde, Santiago de Compostela, Galicia, Spain
| | - Elisabet Vilella
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Alfonso Gutiérrez-Zotes
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Marta Perez-Rando
- Fundación Investigación Hospital Clínico de València, Fundación Investigación Hospital Clínico de Valencia, València, Spain; Unidad de Neurobiología, Instituto de Biotecnología y Biomedicina, Universitat de València, València, Spain
| | - María Dolores Moltó
- CIBERSAM, Madrid, Spain; Unidad de Neurobiología, Instituto de Biotecnología y Biomedicina, Universitat de València, València, Spain; Department of Genetics, Universitat de València, Campus of Burjassot, València, Spain
| | - Elizabeth Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Neeltje van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Altrecht Mental Health Institute, Altrecht Science, Utrecht, the Netherlands
| | - Michael O'Donovan
- Medical Research Council for Neuropsychiatric Genetics and Genomics and Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Hilleke Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hugo Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| |
Collapse
|
5
|
Ren H, Li Z, Li J, Zhou J, He Y, Li C, Wang Q, Chen X, Tang J. Correlation Between Cortical Thickness Abnormalities of the Olfactory Sulcus and Olfactory Identification Disorder and Persistent Auditory Verbal Hallucinations in Chinese Patients With Chronic Schizophrenia. Schizophr Bull 2024; 50:1232-1242. [PMID: 38577952 PMCID: PMC11349016 DOI: 10.1093/schbul/sbae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
BACKGROUND AND HYPOTHESIS Persistent auditory verbal hallucinations (pAVHs) and olfactory identification impairment are common in schizophrenia (SCZ), but the neuroimaging mechanisms underlying both pAVHs and olfactory identification impairment are unclear. This study aimed to investigate whether pAVHs and olfactory identification impairment in SCZ patients are associated with changes in cortical thickness. STUDY DESIGN In this study, cortical thickness was investigated in 78 SCZ patients with pAVHs (pAVH group), 58 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group) using 3T magnetic resonance imaging. The severity of pAVHs was assessed by the Auditory Hallucination Rating Scale. Olfactory identification deficits were assessed using the Odor Stick Identification Test for Japanese (OSIT-J). In addition, the relationship between the severity of pAVHs and olfactory identification disorder and cortical thickness abnormalities was determined. STUDY RESULTS Significant reductions in cortical thickness were observed in the right medial orbital sulcus (olfactory sulcus) and right orbital sulcus (H-shaped sulcus) in the pAVH group compared to both the non-AVH and HC groups (P < .003, Bonferroni correction). Furthermore, the severity of pAVHs was found to be negatively correlated with the reduction in cortical thickness in the olfactory sulcus and H-shaped sulcus. Additionally, a decrease in cortical thickness in the olfactory sulcus showed a positive correlation with the OSIT-J scores (P < .05, false discovery rate correction). CONCLUSIONS Cortical thickness abnormalities in the olfactory sulcus may be a common neuroimaging mechanism for pAVHs and olfactory identification deficits in SCZ patients.
Collapse
Affiliation(s)
- Honghong Ren
- Department of Clinical Psychology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Clinical Psychology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinguang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jun Zhou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chunwang Li
- Department of Radiology, Hunan Children’s Hospital, Changsha, China
| | - Qianjin Wang
- Department of Clinical Psychology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Clinical Psychology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Hunan Provincial Brain Hospital (The second people's Hospital of Hunan Province), Changsha, China
- Zigong Mental Health Center, Zigong, China
| |
Collapse
|
6
|
Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère ML, Artiges E, Orfanos DP, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development correlate with underlying neurobiology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.05.539537. [PMID: 37205539 PMCID: PMC10187287 DOI: 10.1101/2023.05.05.539537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
Collapse
Affiliation(s)
- Leon D Lotter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
- Max Planck School of Cognition; Stephanstrasse 1A, 04103 Leipzig, Germany
| | - Amin Saberi
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences; Leipzig, Germany
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University; Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University; Montréal, QC, Canada
| | - Casey Paquola
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London; London, United Kingdom
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin; Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London; London, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim; 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay; F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont; 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham; University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB); Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
| | - Marie-Laure Paillère
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital; Paris, France
| | - Eric Artiges
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Université paris Cité, INSERM U1299 "Trajectoires Développementales & Psychiatrie"; Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- Department of Psychiatry, EPS Barthélémy Durand; Etampes, France
| | | | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal; Montréal, Quebec, Canada
- Department of Psychiatry, McGill University; Montreal, Quebec, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen; von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden; Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden; Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin; Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin; Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin; Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University; Shanghai, China
| | - Frauke Nees
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University; Kiel, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University; Square J5, 68159 Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim-Heidelberg-Ulm; Heidelberg, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich; Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University; Düsseldorf, Germany
| |
Collapse
|
7
|
Recht G, Hou J, Buddenbaum C, Cheng H, Newman SD, Saykin AJ, Kawata K. Multiparameter cortical surface morphology in former amateur contact sport athletes. Cereb Cortex 2024; 34:bhae301. [PMID: 39077916 DOI: 10.1093/cercor/bhae301] [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: 04/26/2024] [Revised: 06/29/2024] [Accepted: 07/08/2024] [Indexed: 07/31/2024] Open
Abstract
The lifetime effects of repetitive head impacts have captured considerable public and scientific interest over the past decade, yet a knowledge gap persists in our understanding of midlife neurological well-being, particularly in amateur level athletes. This study aimed to identify the effects of lifetime exposure to sports-related head impacts on brain morphology in retired, amateur athletes. This cross-sectional study comprised of 37 former amateur contact sports athletes and 21 age- and sex-matched noncontact athletes. High-resolution anatomical, T1 scans were analyzed for the cortical morphology, including cortical thickness, sulcal depth, and sulcal curvature, and cognitive function was assessed using the Dementia Rating Scale-2. Despite no group differences in cognitive functions, the contact group exhibited significant cortical thinning particularly in the bilateral frontotemporal regions and medial brain regions, such as the cingulate cortex and precuneus, compared to the noncontact group. Deepened sulcal depth and increased sulcal curvature across all four lobes of the brain were also notable in the contact group. These data suggest that brain morphology of middle-aged former amateur contact athletes differs from that of noncontact athletes and that lifetime exposure to repetitive head impacts may be associated with neuroanatomical changes.
Collapse
Affiliation(s)
- Grace Recht
- Department of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E. 10th Street, Bloomington, IN 47405, United States
| | - Jiancheng Hou
- Department of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E. 10th Street, Bloomington, IN 47405, United States
- Research Center for Cross-Straits Cultural Development, Fujian Normal University, Cangshan Campus, No. 8 Shangshan Road, Cangshan District, Fuzhou, Fujian 350007, China
| | - Claire Buddenbaum
- Department of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E. 10th Street, Bloomington, IN 47405, United States
| | - Hu Cheng
- Department of Psychological and Brain Sciences, College of Arts and Sciences, Indiana University, 1101 E. 10th Street, Bloomington, IN 47405, United States
- Program in Neuroscience, The College of Arts and Sciences, Indiana University, 1101 East 10th Street, Bloomington, IN 47405, United States
| | - Sharlene D Newman
- Alabama Life Research Institute, College of Arts & Sciences, University of Alabama, 211 Peter Bryce Blvd., Tuscaloosa, AL 35401, United States
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, 355 West 16th Street, Indianapolis, IN 46202, United States
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 University Blvd, Indianapolis, IN 46202, United States
| | - Keisuke Kawata
- Department of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E. 10th Street, Bloomington, IN 47405, United States
- Program in Neuroscience, The College of Arts and Sciences, Indiana University, 1101 East 10th Street, Bloomington, IN 47405, United States
- Department of Pediatrics, Indiana University School of Medicine, 1130 W Michigan St, Indianapolis, IN 46202, United States
| |
Collapse
|
8
|
Patel Y, Woo A, Shi S, Ayoub R, Shin J, Botta A, Ketela T, Sung HK, Lerch J, Nieman B, Paus T, Pausova Z. Obesity and the cerebral cortex: Underlying neurobiology in mice and humans. Brain Behav Immun 2024; 119:637-647. [PMID: 38663773 DOI: 10.1016/j.bbi.2024.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 05/01/2024] Open
Abstract
Obesity is a major modifiable risk factor for Alzheimer's disease (AD), characterized by progressive atrophy of the cerebral cortex. The neurobiology of obesity contributions to AD is poorly understood. Here we show with in vivo MRI that diet-induced obesity decreases cortical volume in mice, and that higher body adiposity associates with lower cortical volume in humans. Single-nuclei transcriptomics of the mouse cortex reveals that dietary obesity promotes an array of neuron-adverse transcriptional dysregulations, which are mediated by an interplay of excitatory neurons and glial cells, and which involve microglial activation and lowered neuronal capacity for neuritogenesis and maintenance of membrane potential. The transcriptional dysregulations of microglia, more than of other cell types, are like those in AD, as assessed with single-nuclei cortical transcriptomics in a mouse model of AD and two sets of human donors with the disease. Serial two-photon tomography of microglia demonstrates microgliosis throughout the mouse cortex. The spatial pattern of adiposity-cortical volume associations in human cohorts interrogated together with in silico bulk and single-nucleus transcriptomic data from the human cortex implicated microglia (along with other glial cells and subtypes of excitatory neurons), and it correlated positively with the spatial profile of cortical atrophy in patients with mild cognitive impairment and AD. Thus, multi-cell neuron-adverse dysregulations likely contribute to the loss of cortical tissue in obesity. The dysregulations of microglia may be pivotal to the obesity-related risk of AD.
Collapse
Affiliation(s)
- Yash Patel
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada; Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Anita Woo
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Sammy Shi
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Ramy Ayoub
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada
| | - Jean Shin
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Amy Botta
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada
| | - Troy Ketela
- Princess Margaret Genomics Centre, Toronto, ON, Canada
| | - Hoon-Ki Sung
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada
| | - Jason Lerch
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, Great Britton
| | - Brian Nieman
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Tomas Paus
- Department of Psychiatry and Addictology and Department of Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, QC, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, Translational Medicine Program, Toronto, ON, Canada; Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada; Department of Pediatrics and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, QC, Canada.
| |
Collapse
|
9
|
Bottenhorn KL, Sukumaran K, Cardenas-Iniguez C, Habre R, Schwartz J, Chen JC, Herting MM. Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development. ENVIRONMENT INTERNATIONAL 2024; 189:108769. [PMID: 38823157 DOI: 10.1016/j.envint.2024.108769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 05/08/2024] [Accepted: 05/21/2024] [Indexed: 06/03/2024]
Abstract
Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
Collapse
Affiliation(s)
- Katherine L Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Department of Psychology, Florida International University, Miami, FL, USA.
| | - Kirthana Sukumaran
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Rima Habre
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiu-Chiuan Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
| |
Collapse
|
10
|
Heij J, van der Zwaag W, Knapen T, Caan MWA, Forstman B, Veltman DJ, van Wingen G, Aghajani M. Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder. Transl Psychiatry 2024; 14:262. [PMID: 38902245 PMCID: PMC11190139 DOI: 10.1038/s41398-024-02976-y] [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: 08/09/2023] [Revised: 05/31/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024] Open
Abstract
Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p's < 0.05, Cohen's D = 0.55-0.66) and symptom severity (p's < 0.01, r = 0.271-0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.
Collapse
Affiliation(s)
- Jurjen Heij
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wietske van der Zwaag
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
| | - Tomas Knapen
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Birte Forstman
- Department of Brain & Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Guido van Wingen
- Department of Psychiatry, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Institute of Education and Child Studies, Section Forensic Family & Youth Care, Leiden University, Leiden, The Netherlands.
| |
Collapse
|
11
|
d’Almeida NA, Tipping M. Flight to insight: maximizing the potential of Drosophila models of C9orf72-FTD. Front Mol Neurosci 2024; 17:1434443. [PMID: 38915937 PMCID: PMC11194461 DOI: 10.3389/fnmol.2024.1434443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 05/22/2024] [Indexed: 06/26/2024] Open
Abstract
Advancements in understanding the pathogenesis of C9orf72-associated frontotemporal dementia (C9orf72-FTD) have highlighted the role of repeat-associated non-ATG (RAN) translation and dipeptide repeat proteins (DPRs), with Drosophila melanogaster models providing valuable insights. While studies have primarily focused on RAN translation and DPR toxicity, emerging areas of investigation in fly models have expanded to neuronal dysfunction, autophagy impairment, and synaptic dysfunction, providing potential directions for new therapeutic targets and mechanisms of neurodegeneration. Despite this progress, there are still significant gaps in Drosophila models of C9orf72-FTD, namely in the areas of metabolism and circadian rhythm. Metabolic dysregulation, particularly lipid metabolism, autophagy, and insulin signaling, has been implicated in disease progression with findings from animal models and human patients with C9orf72 repeat expansions. Moreover, circadian disruptions have been observed in C9of72-FTD, with alterations in rest-activity patterns and cellular circadian machinery, suggesting a potential role in disease pathophysiology. Drosophila models offer unique opportunities to explore these aspects of C9orf72-FTD and identify novel therapeutic targets aimed at mitigating neurodegeneration.
Collapse
|
12
|
Cao Z, Zhan G, Qin J, Cupertino RB, Ottino-Gonzalez J, Murphy A, Pancholi D, Hahn S, Yuan D, Callas P, Mackey S, Garavan H. Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics. Neuroimage 2024; 293:120622. [PMID: 38648869 PMCID: PMC11132826 DOI: 10.1016/j.neuroimage.2024.120622] [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: 03/10/2023] [Revised: 04/17/2024] [Accepted: 04/19/2024] [Indexed: 04/25/2024] Open
Abstract
Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.
Collapse
Affiliation(s)
- Zhipeng Cao
- Shanghai Xuhui Mental Health Center, Shanghai 200232, China; Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA.
| | - Guilai Zhan
- Shanghai Xuhui Mental Health Center, Shanghai 200232, China
| | - Jinmei Qin
- Shanghai Xuhui Mental Health Center, Shanghai 200232, China
| | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jonatan Ottino-Gonzalez
- Division of Endocrinology, The Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Alistair Murphy
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| | - Devarshi Pancholi
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| | - Sage Hahn
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| | - Dekang Yuan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| | - Peter Callas
- Department of Mathematics and Statistics, University of Vermont College of Engineering and Mathematical Sciences, Burlington VT, 05401, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington VT, 05401, USA
| |
Collapse
|
13
|
Andrews DS, Diers K, Lee JK, Harvey DJ, Heath B, Cordero D, Rogers SJ, Reuter M, Solomon M, Amaral DG, Nordahl CW. Sex differences in trajectories of cortical development in autistic children from 2-13 years of age. Mol Psychiatry 2024:10.1038/s41380-024-02592-8. [PMID: 38755243 DOI: 10.1038/s41380-024-02592-8] [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: 10/04/2023] [Revised: 04/30/2024] [Accepted: 05/02/2024] [Indexed: 05/18/2024]
Abstract
Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.
Collapse
Affiliation(s)
- Derek S Andrews
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA.
| | - Kersten Diers
- AI in Medical Imaging, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Joshua K Lee
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Danielle J Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, University of California, Davis, CA, USA
| | - Brianna Heath
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Devani Cordero
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Sally J Rogers
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Martin Reuter
- AI in Medical Imaging, German Center for Neurodegenerative Diseases, Bonn, Germany
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Marjorie Solomon
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - David G Amaral
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Christine Wu Nordahl
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| |
Collapse
|
14
|
Bottenhorn KL, Sukumaran K, Cardenas-Iniguez C, Habre R, Schwartz J, Chen JC, Herting MM. Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.21.563430. [PMID: 38798573 PMCID: PMC11118378 DOI: 10.1101/2023.10.21.563430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
Collapse
|
15
|
van der Pal Z, Walhovd KB, Amlien IK, Guichelaar CJ, Kaiser A, Bottelier MA, Geurts HM, Reneman L, Schrantee A. Stimulant medication use and apparent cortical thickness development in attention-deficit/hyperactivity disorder: a prospective longitudinal study. Front Psychiatry 2024; 15:1365159. [PMID: 38774436 PMCID: PMC11107082 DOI: 10.3389/fpsyt.2024.1365159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 04/09/2024] [Indexed: 05/24/2024] Open
Abstract
Background Stimulant medication is commonly prescribed as treatment for attention-deficit/hyperactivity disorder (ADHD). While we previously found that short-term stimulant-treatment influences apparent cortical thickness development in an age-dependent manner, it remains unknown whether these effects persist throughout development into adulthood. Purpose Investigate the long-term age-dependent effects of stimulant medication use on apparent cortical thickness development in adolescents and adults previously diagnosed with ADHD. Methods This prospective study included the baseline and 4-year follow-up assessment of the "effects of Psychotropic drugs On the Developing brain-MPH" ("ePOD-MPH") project, conducted between June-1-2011 and December-28-2019. The analyses were pre-registered (https://doi.org/10.17605/OSF.IO/32BHF). T1-weighted MR scans were obtained from male adolescents and adults, and cortical thickness was estimated for predefined regions of interest (ROIs) using Freesurfer. We determined medication use and assessed symptoms of ADHD, anxiety, and depression at both time points. Linear mixed models were constructed to assess main effects and interactions of stimulant medication use, time, and age group on regional apparent cortical thickness. Results A total of 32 male adolescents (aged mean ± SD, 11.2 ± 0.9 years at baseline) and 24 men (aged mean ± SD, 29.9 ± 5.0 years at baseline) were included that previously participated in the ePOD-MPH project. We found no evidence for long-term effects of stimulant medication use on ROI apparent cortical thickness. As expected, we did find age-by-time interaction effects in all ROIs (left prefrontal ROI: P=.002, right medial and posterior ROIs: P<.001), reflecting reductions in apparent cortical thickness in adolescents. Additionally, ADHD symptom severity (adolescents: P<.001, adults: P=.001) and anxiety symptoms (adolescents: P=0.03) were reduced, and more improvement of ADHD symptoms was associated with higher medication use in adults (P=0.001). Conclusion We found no evidence for long-term effects of stimulant-treatment for ADHD on apparent cortical thickness development in adolescents and adults. The identified age-dependent differences in apparent cortical thickness development are consistent with existing literature on typical cortical development.
Collapse
Affiliation(s)
- Zarah van der Pal
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center (UMC) location University of Amsterdam, Amsterdam, Netherlands
| | - Kristine B. Walhovd
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Inge K. Amlien
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | | | - Antonia Kaiser
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center (UMC) location University of Amsterdam, Amsterdam, Netherlands
- CIBM, Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
| | - Marco A. Bottelier
- Accare, Centre for Academic Child and Adolescent Psychiatry, University Medical Center (UMC) Groningen, Groningen, Netherlands
| | - Hilde M. Geurts
- Division of Brain & Cognition, Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center (UMC) location University of Amsterdam, Amsterdam, Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center (UMC) location University of Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
16
|
Paus T. Population Neuroscience: Principles and Advances. Curr Top Behav Neurosci 2024. [PMID: 38589637 DOI: 10.1007/7854_2024_474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
In population neuroscience, three disciplines come together to advance our knowledge of factors that shape the human brain: neuroscience, genetics, and epidemiology (Paus, Human Brain Mapping 31:891-903, 2010). Here, I will come back to some of the background material reviewed in more detail in our previous book (Paus, Population Neuroscience, 2013), followed by a brief overview of current advances and challenges faced by this integrative approach.
Collapse
Affiliation(s)
- Tomáš Paus
- Department of Psychiatry and Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada
| |
Collapse
|
17
|
Pak V, Adewale Q, Bzdok D, Dadar M, Zeighami Y, Iturria-Medina Y. Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions. eLife 2024; 12:RP89368. [PMID: 38512130 PMCID: PMC10957173 DOI: 10.7554/elife.89368] [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] [Indexed: 03/22/2024] Open
Abstract
For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.
Collapse
Affiliation(s)
- Veronika Pak
- Department of Neurology and Neurosurgery, McGill UniversityMontrealCanada
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
- Ludmer Centre for Neuroinformatics & Mental HealthMontrealCanada
| | - Quadri Adewale
- Department of Neurology and Neurosurgery, McGill UniversityMontrealCanada
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
- Ludmer Centre for Neuroinformatics & Mental HealthMontrealCanada
| | - Danilo Bzdok
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
- Department of Biomedical Engineering, McGill UniversityMontrealCanada
- School of Computer Science, McGill UniversityMontrealCanada
- Mila – Quebec Artificial Intelligence InstituteMontrealCanada
| | | | | | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, McGill UniversityMontrealCanada
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
- Ludmer Centre for Neuroinformatics & Mental HealthMontrealCanada
- Department of Biomedical Engineering, McGill UniversityMontrealCanada
- McGill Centre for Studies in AgingMontrealCanada
| |
Collapse
|
18
|
Vande Casteele T, Laroy M, Van Cauwenberge M, Koole M, Dupont P, Sunaert S, Van den Stock J, Bouckaert F, Van Laere K, Emsell L, Vandenbulcke M. Preliminary evidence for preserved synaptic density in late-life depression. Transl Psychiatry 2024; 14:145. [PMID: 38485934 PMCID: PMC10940592 DOI: 10.1038/s41398-024-02837-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 02/11/2024] [Accepted: 02/14/2024] [Indexed: 03/18/2024] Open
Abstract
Late-life depression has been consistently associated with lower gray matter volume, the origin of which remains largely unexplained. Recent in-vivo PET findings in early-onset depression and Alzheimer's Disease suggest that synaptic deficits contribute to the pathophysiology of these disorders and may therefore contribute to lower gray matter volume in late-life depression. Here, we investigate synaptic density in vivo for the first time in late-life depression using the synaptic vesicle glycoprotein 2A receptor radioligand 11C-UCB-J. We included 24 currently depressed adults with late-life depression (73.0 ± 6.2 years, 16 female, geriatric depression scale = 19.5 ± 6.8) and 36 age- and gender-matched healthy controls (70.4 ± 6.2 years, 21 female, geriatric depression scale = 2.7 ± 2.9) that underwent simultaneous 11C-UCB-J positron emission tomography (PET) and 3D T1- and T2-FLAIR weighted magnetic resonance (MR) imaging on a 3-tesla PET-MR scanner. We used analyses of variance to test for 11C-UCB-J binding and gray matter volumes differences in regions implicated in depression. The late-life depression group showed a trend in lower gray matter volumes in the hippocampus (p = 0.04), mesial temporal (p = 0.02) and prefrontal cortex (p = 0.02) compared to healthy control group without surviving correction for multiple comparison. However, no group differences in 11C-UCB-J binding were found in these regions nor were any associations between 11C-UCB-J and depressive symptoms. Our data suggests that, in contrast to Alzheimer's Disease, lower gray matter volume in late-life depression is not associated with synaptic density changes. From a therapeutic standpoint, preserved synaptic density in late-life depression may be an encouraging finding.
Collapse
Affiliation(s)
- Thomas Vande Casteele
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium.
| | - Maarten Laroy
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
| | - Margot Van Cauwenberge
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
- Neurology, University Hospitals Leuven, B-3000, Leuven, Belgium
| | - Michel Koole
- KU Leuven, Leuven Brain Institute, Department of Imaging and Pathology, Nuclear Medicine, B-3000, Leuven, Belgium
| | - Patrick Dupont
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Laboratory for Cognitive Neurology, B-3000, Leuven, Belgium
| | - Stefan Sunaert
- KU Leuven, Leuven Brain Institute, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium
- Radiology, University Hospitals Leuven, B-3000, Leuven, Belgium
| | - Jan Van den Stock
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
- Geriatric Psychiatry, University Psychiatric Center KU Leuven, B-3000, Leuven, Belgium
| | - Filip Bouckaert
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
- Geriatric Psychiatry, University Psychiatric Center KU Leuven, B-3000, Leuven, Belgium
| | - Koen Van Laere
- KU Leuven, Leuven Brain Institute, Department of Imaging and Pathology, Nuclear Medicine, B-3000, Leuven, Belgium
- Nuclear Medicine, University Hospitals Leuven, B-3000, Leuven, Belgium
| | - Louise Emsell
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
- KU Leuven, Leuven Brain Institute, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium
- Geriatric Psychiatry, University Psychiatric Center KU Leuven, B-3000, Leuven, Belgium
| | - Mathieu Vandenbulcke
- KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry, B-3000, Leuven, Belgium
- Geriatric Psychiatry, University Psychiatric Center KU Leuven, B-3000, Leuven, Belgium
| |
Collapse
|
19
|
Crews FT, Macht V, Vetreno RP. Epigenetic regulation of microglia and neurons by proinflammatory signaling following adolescent intermittent ethanol (AIE) exposure and in human AUD. ADVANCES IN DRUG AND ALCOHOL RESEARCH 2024; 4:12094. [PMID: 38524847 PMCID: PMC10957664 DOI: 10.3389/adar.2024.12094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 02/05/2024] [Indexed: 03/26/2024]
Abstract
Adolescent alcohol drinking is linked to high rates of adult alcohol problems and alcohol use disorder (AUD). The Neurobiology of Alcohol Drinking in Adulthood (NADIA) consortium adolescent intermittent ethanol (AIE) models adolescent binge drinking, followed by abstinent maturation to adulthood to determine the persistent AIE changes in neurobiology and behavior. AIE increases adult alcohol drinking and preference, increases anxiety and reward seeking, and disrupts sleep and cognition, all risks for AUD. In addition, AIE induces changes in neuroimmune gene expression in neurons and glia that alter neurocircuitry and behavior. HMGB1 is a unique neuroimmune signal released from neurons and glia by ethanol that activates multiple proinflammatory receptors, including Toll-like receptors (TLRs), that spread proinflammatory gene induction. HMGB1 expression is increased by AIE in rat brain and in post-mortem human AUD brain, where it correlates with lifetime alcohol consumption. HMGB1 activation of TLR increase TLR expression. Human AUD brain and rat brain following AIE show increases in multiple TLRs. Brain regional differences in neurotransmitters and cell types impact ethanol responses and neuroimmune gene induction. Microglia are monocyte-like cells that provide trophic and synaptic functions, that ethanol proinflammatory signals sensitize or "prime" during repeated drinking cycles, impacting neurocircuitry. Neurocircuits are differently impacted dependent upon neuronal-glial signaling. Acetylcholine is an anti-inflammatory neurotransmitter. AIE increases HMGB1-TLR4 signaling in forebrain, reducing cholinergic neurons by silencing multiple cholinergic defining genes through upregulation of RE-1 silencing factor (REST), a transcription inhibitor known to regulate neuronal differentiation. HMGB1 REST induction reduces cholinergic neurons in basal forebrain and cholinergic innervation of hippocampus. Adult brain hippocampal neurogenesis is regulated by a neurogenic niche formed from multiple cells. In vivo AIE and in vitro studies find ethanol increases HMGB1-TLR4 signaling and other proinflammatory signaling as well as reducing trophic factors, NGF, and BDNF, coincident with loss of the cholinergic synapse marker vChAT. These changes in gene expression-transcriptomes result in reduced adult neurogenesis. Excitingly, HMGB1 antagonists, anti-inflammatories, and epigenetic modifiers like histone deacetylase inhibitors restore trophic the neurogenesis. These findings suggest anti-inflammatory and epigenetic drugs should be considered for AUD therapy and may provide long-lasting reversal of psychopathology.
Collapse
Affiliation(s)
- Fulton T. Crews
- Departments of Pharmacology and Psychiatry, Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | | | | |
Collapse
|
20
|
Norbom LB, Rokicki J, Eilertsen EM, Wiker T, Hanson J, Dahl A, Alnæs D, Fernández‐Cabello S, Beck D, Agartz I, Andreassen OA, Westlye LT, Tamnes CK. Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years. JCPP ADVANCES 2024; 4:e12220. [PMID: 38486948 PMCID: PMC10933599 DOI: 10.1002/jcv2.12220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/21/2023] [Indexed: 03/17/2024] Open
Abstract
Background A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth. Methods To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Results Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. Conclusion Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.
Collapse
Affiliation(s)
- Linn B. Norbom
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jaroslav Rokicki
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Centre of Research and Education in Forensic PsychiatryOslo University HospitalOsloNorway
| | - Espen M. Eilertsen
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
| | - Thea Wiker
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Jamie Hanson
- Learning Research and Development Center University of PittsburghPennsylvaniaPittsburghUSA
- Department of PsychologyUniversity of PittsburghPennsylvaniaPittsburghUSA
| | - Andreas Dahl
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Dag Alnæs
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyPedagogy and LawKristiania University CollegeOsloNorway
| | | | - Dani Beck
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Ingrid Agartz
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care ServicesStockholmSweden
| | - Ole A. Andreassen
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Christian K. Tamnes
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| |
Collapse
|
21
|
Moodie JE, Harris SE, Harris MA, Buchanan CR, Davies G, Taylor A, Redmond P, Liewald DCM, Valdés Hernández MDC, Shenkin S, Russ TC, Muñoz Maniega S, Luciano M, Corley J, Stolicyn A, Shen X, Steele D, Waiter G, Sandu A, Bastin ME, Wardlaw JM, McIntosh A, Whalley H, Tucker‐Drob EM, Deary IJ, Cox SR. General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning. Hum Brain Mapp 2024; 45:e26641. [PMID: 38488470 PMCID: PMC10941541 DOI: 10.1002/hbm.26641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/29/2024] [Accepted: 02/18/2024] [Indexed: 03/18/2024] Open
Abstract
Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
Collapse
Affiliation(s)
- Joanna E. Moodie
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Mathew A. Harris
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Colin R. Buchanan
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Gail Davies
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Adele Taylor
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Paul Redmond
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - David C. M. Liewald
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Maria del C. Valdés Hernández
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | - Susan Shenkin
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
- Ageing and Health Research Group, Usher InstituteUniversity of EdinburghUK
| | - Tom C. Russ
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
- Alzheimer Scotland Dementia Research CentreUniversity of EdinburghUK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | - Michelle Luciano
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Janie Corley
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Aleks Stolicyn
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | - Xueyi Shen
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | - Douglas Steele
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Gordon Waiter
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Anca‐Larisa Sandu
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Mark E. Bastin
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | - Joanna M. Wardlaw
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghUK
| | | | | | | | - Ian J. Deary
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of PsychologyThe University of EdinburghEdinburghUK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| |
Collapse
|
22
|
Abondio P, Bruno F, Passarino G, Montesanto A, Luiselli D. Pangenomics: A new era in the field of neurodegenerative diseases. Ageing Res Rev 2024; 94:102180. [PMID: 38163518 DOI: 10.1016/j.arr.2023.102180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/14/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024]
Abstract
A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.
Collapse
Affiliation(s)
- Paolo Abondio
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy.
| | - Francesco Bruno
- Academy of Cognitive Behavioral Sciences of Calabria (ASCoC), Lamezia Terme, Italy; Regional Neurogenetic Centre (CRN), Department of Primary Care, Azienda Sanitaria Provinciale Di Catanzaro, Viale A. Perugini, 88046 Lamezia Terme, CZ, Italy; Association for Neurogenetic Research (ARN), Lamezia Terme, CZ, Italy
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende 87036, Italy
| | - Alberto Montesanto
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende 87036, Italy
| | - Donata Luiselli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
| |
Collapse
|
23
|
Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Li Q, Xu Z, Men W, Wang Y, Tan S, Gao JH, Qin S, Tao S, Dong Q, Zhao T, He Y. Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence. Nat Commun 2024; 15:784. [PMID: 38278807 PMCID: PMC10817914 DOI: 10.1038/s41467-024-44863-6] [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: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.
Collapse
Affiliation(s)
- Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
| |
Collapse
|
24
|
Graïc JM, Corain L, Finos L, Vadori V, Grisan E, Gerussi T, Orekhova K, Centelleghe C, Cozzi B, Peruffo A. Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins ( Tursiops truncatus) are located in the upper cortical layers. Front Neuroanat 2024; 17:1330384. [PMID: 38250022 PMCID: PMC10796513 DOI: 10.3389/fnana.2023.1330384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 12/06/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction The auditory system of dolphins and whales allows them to dive in dark waters, hunt for prey well below the limit of solar light absorption, and to communicate with their conspecific. These complex behaviors require specific and sufficient functional circuitry in the neocortex, and vicarious learning capacities. Dolphins are also precocious animals that can hold their breath and swim within minutes after birth. However, diving and hunting behaviors are likely not innate and need to be learned. Our hypothesis is that the organization of the auditory cortex of dolphins grows and mature not only in the early phases of life, but also in adults and aging individuals. These changes may be subtle and involve sub-populations of cells specificall linked to some circuits. Methods In the primary auditory cortex of 11 bottlenose dolphins belonging to three age groups (calves, adults, and old animals), neuronal cell shapes were analyzed separately and by cortical layer using custom computer vision and multivariate statistical analysis, to determine potential minute morphological differences across these age groups. Results The results show definite changes in interneurons, characterized by round and ellipsoid shapes predominantly located in upper cortical layers. Notably, neonates interneurons exhibited a pattern of being closer together and smaller, developing into a more dispersed and diverse set of shapes in adulthood. Discussion This trend persisted in older animals, suggesting a continuous development of connections throughout the life of these marine animals. Our findings further support the proposition that thalamic input reach upper layers in cetaceans, at least within a cortical area critical for their survival. Moreover, our results indicate the likelihood of changes in cell populations occurring in adult animals, prompting the need for characterization.
Collapse
Affiliation(s)
- Jean-Marie Graïc
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Livio Corain
- Department of Management and Engineering, University of Padova, Vicenza, Italy
| | - Livio Finos
- Department of Statistical Sciences, University of Padova, Padua, Italy
| | - Valentina Vadori
- Department of Computer Science and Informatics, London South Bank University, London, United Kingdom
| | - Enrico Grisan
- Department of Computer Science and Informatics, London South Bank University, London, United Kingdom
| | - Tommaso Gerussi
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Ksenia Orekhova
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Cinzia Centelleghe
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Bruno Cozzi
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Antonella Peruffo
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| |
Collapse
|
25
|
Kohli JS, Reyes A, Hopper A, Stasenko A, Menendez N, Tringale KR, Salans M, Karunamuni R, Hattangadi-Gluth JA, McDonald CR. Neuroanatomical profiles of cognitive phenotypes in patients with primary brain tumors. Neurooncol Adv 2024; 6:vdae152. [PMID: 39359697 PMCID: PMC11445899 DOI: 10.1093/noajnl/vdae152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024] Open
Abstract
Background Patients with brain tumors demonstrate heterogeneous patterns of cognitive impairment, likely related to multifactorial etiologies and variable tumor-specific factors. Cognitive phenotyping offers a patient-centered approach to parsing heterogeneity by classifying individuals based on patterns of impairment. The aim of this study was to investigate the neuroanatomical patterns associated with each phenotype to gain a better understanding of the mechanisms underlying impairments. Methods Patients with primary brain tumors were recruited for a prospective, observational study. Patients were cognitively phenotyped using latent profile analysis in a prior study, revealing 3 distinct groups: generalized, isolated verbal memory, and minimal impairment. Whole brain cortical thickness (CT), fractional anisotropy, and mean diffusivity (MD) were compared across phenotypes, and associations between imaging metrics and cognitive scores were explored. Results Neurocognitive, structural MRI, and diffusion MRI data were available for 82 participants at baseline. Compared to the minimal impairment group, the generalized impairment group showed a widespread, bi-hemispheric pattern of decreased CT (P-value range: .004-.049), while the verbal memory impairment group showed decreased CT (P-value range: .006-.049) and increased MD (P-value range: .015-.045) bilaterally in the temporal lobes. In the verbal memory impairment group only, increased parahippocampal MD was associated with lower verbal memory scores (P-values < .01). Conclusions Cognitive phenotypes in patients with brain tumors showed unique patterns of brain pathology, suggesting different underlying mechanisms of their impairment profiles. These distinct patterns highlight the biological relevance of our phenotyping approach and help to identify areas of structural and microstructural vulnerability that could inform treatment decisions.
Collapse
Affiliation(s)
- Jiwandeep S Kohli
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Anny Reyes
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Austin Hopper
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Alena Stasenko
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Natalia Menendez
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Kathryn R Tringale
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Mia Salans
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California, USA
| | - Roshan Karunamuni
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Jona A Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Carrie R McDonald
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| |
Collapse
|
26
|
Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023; 24:747-760. [PMID: 37848663 DOI: 10.1038/s41583-023-00752-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2023] [Indexed: 10/19/2023]
Abstract
The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.
Collapse
Affiliation(s)
- Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada.
| |
Collapse
|
27
|
Pulli EP, Nolvi S, Eskola E, Nordenswan E, Holmberg E, Copeland A, Kumpulainen V, Silver E, Merisaari H, Saunavaara J, Parkkola R, Lähdesmäki T, Saukko E, Kataja E, Korja R, Karlsson L, Karlsson H, Tuulari JJ. Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study. Hum Brain Mapp 2023; 44:5582-5601. [PMID: 37606608 PMCID: PMC10619410 DOI: 10.1002/hbm.26463] [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: 03/28/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/23/2023] Open
Abstract
Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.
Collapse
Affiliation(s)
- Elmo P. Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Turku Institute for Advanced Studies, Department of Psychology and Speech‐Language PathologyUniversity of TurkuTurkuFinland
| | - Eeva Eskola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Elisabeth Nordenswan
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eeva Holmberg
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of RadiologyUniversity of TurkuTurkuFinland
| | - Jani Saunavaara
- Department of Medical PhysicsTurku University Hospital and University of TurkuTurkuFinland
| | - Riitta Parkkola
- Department of RadiologyUniversity of TurkuTurkuFinland
- Department of RadiologyTurku University HospitalTurkuFinland
| | - Tuire Lähdesmäki
- Pediatric Neurology, Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | | | - Eeva‐Leena Kataja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Turku Collegium for Science, Medicine and TechnologyUniversity of TurkuTurkuFinland
- Department of PsychiatryUniversity of OxfordOxfordUK
| |
Collapse
|
28
|
Kotikalapudi R, Kincses B, Zunhammer M, Schlitt F, Asan L, Schmidt-Wilcke T, Kincses ZT, Bingel U, Spisak T. Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach. Pain 2023; 164:2516-2527. [PMID: 37318027 PMCID: PMC10578427 DOI: 10.1097/j.pain.0000000000002958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 02/18/2023] [Accepted: 03/23/2023] [Indexed: 06/16/2023]
Abstract
ABSTRACT Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.
Collapse
Affiliation(s)
- Raviteja Kotikalapudi
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Medicine Essen, Essen, Germany
| | - Balint Kincses
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Medicine Essen, Essen, Germany
- Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Medicine Essen, Essen, Germany
| | - Matthias Zunhammer
- Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Medicine Essen, Essen, Germany
| | - Frederik Schlitt
- Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Medicine Essen, Essen, Germany
| | - Livia Asan
- Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Medicine Essen, Essen, Germany
| | - Tobias Schmidt-Wilcke
- Institute for Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
- Neurocenter, District Hospital Mainkofen, Deggendorf, Germany
| | - Zsigmond T. Kincses
- Departments of Neurology and
- Radiology, University of Szeged, Szeged, Hungary
| | - Ulrike Bingel
- Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Medicine Essen, Essen, Germany
| | - Tamas Spisak
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Medicine Essen, Essen, Germany
| |
Collapse
|
29
|
Vo A, Tremblay C, Rahayel S, Shafiei G, Hansen JY, Yau Y, Misic B, Dagher A. Network connectivity and local transcriptomic vulnerability underpin cortical atrophy progression in Parkinson's disease. Neuroimage Clin 2023; 40:103523. [PMID: 38016407 PMCID: PMC10687705 DOI: 10.1016/j.nicl.2023.103523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/30/2023] [Accepted: 10/05/2023] [Indexed: 11/30/2023]
Abstract
Parkinson's disease pathology is hypothesized to spread through the brain via axonal connections between regions and is further modulated by local vulnerabilities within those regions. The resulting changes to brain morphology have previously been demonstrated in both prodromal and de novo Parkinson's disease patients. However, it remains unclear whether the pattern of atrophy progression in Parkinson's disease over time is similarly explained by network-based spreading and local vulnerability. We address this gap by mapping the trajectory of cortical atrophy rates in a large, multi-centre cohort of Parkinson's disease patients and relate this atrophy progression pattern to network architecture and gene expression profiles. Across 4-year follow-up visits, increased atrophy rates were observed in posterior, temporal, and superior frontal cortices. We demonstrated that this progression pattern was shaped by network connectivity. Regional atrophy rates were strongly related to atrophy rates across structurally and functionally connected regions. We also found that atrophy progression was associated with specific gene expression profiles. The genes whose spatial distribution in the brain was most related to atrophy rate were those enriched for mitochondrial and metabolic function. Taken together, our findings demonstrate that both global and local brain features influence vulnerability to neurodegeneration in Parkinson's disease.
Collapse
Affiliation(s)
- Andrew Vo
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Christina Tremblay
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Shady Rahayel
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada; Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montréal, Canada
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Yvonne Yau
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
| |
Collapse
|
30
|
Schilling KG, Chad JA, Chamberland M, Nozais V, Rheault F, Archer D, Li M, Gao Y, Cai L, Del'Acqua F, Newton A, Moyer D, Gore JC, Lebel C, Landman BA. White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559330. [PMID: 37808645 PMCID: PMC10557619 DOI: 10.1101/2023.09.25.559330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.
Collapse
Affiliation(s)
- Kurt G Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Maxime Chamberland
- Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
| | | | - Francois Rheault
- Medical Imaging and Neuroinformatic (MINi) Lab, Department of Computer Science, University of Sherbrooke, Canada
| | - Derek Archer
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, 37212, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Muwei Li
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Flavio Del'Acqua
- NatbrainLab, Department of Forensics and Neurodevelopmental Sciences, King's College London, London UK
| | - Allen Newton
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel Moyer
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - John C Gore
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute (ACHRI), Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Bennett A Landman
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
31
|
Moodie JE, Harris SE, Harris MA, Buchanan CR, Davies G, Taylor A, Redmond P, Liewald D, del C Valdés Hernández M, Shenkin S, Russ TC, Muñoz Maniega S, Luciano M, Corley J, Stolicyn A, Shen X, Steele D, Waiter G, Sandu-Giuraniuc A, Bastin ME, Wardlaw JM, McIntosh A, Whalley H, Tucker-Drob EM, Deary IJ, Cox SR. General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532915. [PMID: 36993650 PMCID: PMC10055068 DOI: 10.1101/2023.03.16.532915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
Collapse
Affiliation(s)
- Joanna E. Moodie
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Mathew A. Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Colin R. Buchanan
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - David Liewald
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Maria del C Valdés Hernández
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Susan Shenkin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Ageing and Health Research Group, Usher Institute, University of Edinburgh, UK
| | - Tom C. Russ
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Michelle Luciano
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Douglas Steele
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Gordon Waiter
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Anca Sandu-Giuraniuc
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Mark E. Bastin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Joanna M. Wardlaw
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Heather Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| |
Collapse
|
32
|
Rakesh D, Whittle S, Sheridan MA, McLaughlin KA. Childhood socioeconomic status and the pace of structural neurodevelopment: accelerated, delayed, or simply different? Trends Cogn Sci 2023; 27:833-851. [PMID: 37179140 PMCID: PMC10524122 DOI: 10.1016/j.tics.2023.03.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 05/15/2023]
Abstract
Socioeconomic status (SES) is associated with children's brain and behavioral development. Several theories propose that early experiences of adversity or low SES can alter the pace of neurodevelopment during childhood and adolescence. These theories make contrasting predictions about whether adverse experiences and low SES are associated with accelerated or delayed neurodevelopment. We contextualize these predictions within the context of normative development of cortical and subcortical structure and review existing evidence on SES and structural brain development to adjudicate between competing hypotheses. Although none of these theories are fully consistent with observed SES-related differences in brain development, existing evidence suggests that low SES is associated with brain structure trajectories more consistent with a delayed or simply different developmental pattern than an acceleration in neurodevelopment.
Collapse
Affiliation(s)
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Victoria, Australia
| | - Margaret A Sheridan
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | |
Collapse
|
33
|
Kerrebijn I, Wainberg M, Zhukovsky P, Chen Y, Davie M, Felsky D, Tripathy SJ. Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease. Neuroimage 2023; 276:120177. [PMID: 37211192 DOI: 10.1016/j.neuroimage.2023.120177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 05/08/2023] [Accepted: 05/16/2023] [Indexed: 05/23/2023] Open
Abstract
Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.
Collapse
Affiliation(s)
- Isabel Kerrebijn
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Michael Wainberg
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter Zhukovsky
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Yuxiao Chen
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Melanie Davie
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Daniel Felsky
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto ON, Canada
| | - Shreejoy J Tripathy
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
34
|
Abé C, Liberg B, Klahn AL, Petrovic P, Landén M. Mania-related effects on structural brain changes in bipolar disorder - a narrative review of the evidence. Mol Psychiatry 2023; 28:2674-2682. [PMID: 37147390 PMCID: PMC10615759 DOI: 10.1038/s41380-023-02073-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 05/07/2023]
Abstract
Cross-sectional neuroimaging studies show that bipolar disorder is associated with structural brain abnormalities, predominantly observed in prefrontal and temporal cortex, cingulate gyrus, and subcortical regions. However, longitudinal studies are needed to elucidate whether these abnormalities presage disease onset or are consequences of disease processes, and to identify potential contributing factors. Here, we narratively review and summarize longitudinal structural magnetic resonance imaging studies that relate imaging outcomes to manic episodes. First, we conclude that longitudinal brain imaging studies suggest an association of bipolar disorder with aberrant brain changes, including both deviant decreases and increases in morphometric measures. Second, we conclude that manic episodes have been related to accelerated cortical volume and thickness decreases, with the most consistent findings occurring in prefrontal brain areas. Importantly, evidence also suggests that in contrast to healthy controls, who in general show age-related cortical decline, brain metrics remain stable or increase during euthymic periods in bipolar disorder patients, potentially reflecting structural recovering mechanisms. The findings stress the importance of preventing manic episodes. We further propose a model of prefrontal cortical trajectories in relation to the occurrence of manic episodes. Finally, we discuss potential mechanisms at play, remaining limitations, and future directions.
Collapse
Affiliation(s)
- Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Quantify Research, Stockholm, Sweden
| | - Benny Liberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Luisa Klahn
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Cognitive and Computational Neuropsychiatry, Karolinska Institutet, Stockholm, Sweden
- Center for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| |
Collapse
|
35
|
Pretzsch CM, Ecker C. Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review. Front Neurosci 2023; 17:1172779. [PMID: 37457001 PMCID: PMC10347684 DOI: 10.3389/fnins.2023.1172779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.
Collapse
Affiliation(s)
- Charlotte M. Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| |
Collapse
|
36
|
Roe JM, Vidal-Pineiro D, Amlien IK, Pan M, Sneve MH, Thiebaut de Schotten M, Friedrich P, Sha Z, Francks C, Eilertsen EM, Wang Y, Walhovd KB, Fjell AM, Westerhausen R. Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex. eLife 2023; 12:e84685. [PMID: 37335613 PMCID: PMC10368427 DOI: 10.7554/elife.84685] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 06/16/2023] [Indexed: 06/21/2023] Open
Abstract
Cortical asymmetry is a ubiquitous feature of brain organization that is subtly altered in some neurodevelopmental disorders, yet we lack knowledge of how its development proceeds across life in health. Achieving consensus on the precise cortical asymmetries in humans is necessary to uncover the developmental timing of asymmetry and the extent to which it arises through genetic and later influences in childhood. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in seven datasets and chart asymmetry trajectories longitudinally across life (4-89 years; observations = 3937; 70% longitudinal). We find replicable asymmetry interrelationships, heritability maps, and test asymmetry associations in large-scale data. Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in childhood and peaks in early adulthood. Areal asymmetry is low-moderately heritable (max h2SNP ~19%) and correlates phenotypically and genetically in specific regions, indicating coordinated development of asymmetries partly through genes. In contrast, thickness asymmetry is globally interrelated across the cortex in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in population-level right-asymmetric regions (and vice versa), and exhibits low or absent heritability. We find less areal asymmetry in the most consistently lateralized region in humans associates with subtly lower cognitive ability, and confirm small handedness and sex effects. Results suggest areal asymmetry is developmentally stable and arises early in life through genetic but mainly subject-specific stochastic effects, whereas childhood developmental growth shapes thickness asymmetry and may lead to directional variability of global thickness lateralization in the population.
Collapse
Affiliation(s)
- James M Roe
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Didac Vidal-Pineiro
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Mengyu Pan
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Markus H Sneve
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Michel Thiebaut de Schotten
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of BordeauxBordeauxFrance
- Brian Connectivity and Behaviour Laboratory, Sorbonne UniversityParisFrance
| | - Patrick Friedrich
- Institute of Neuroscience and Medicine, Research Centre JülichJülichGermany
| | - Zhiqiang Sha
- Language and Genetics Department, Max Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for PsycholinguisticsNijmegenNetherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenNetherlands
- Department of Human Genetics, Radboud University Medical CenterNijmegenNetherlands
| | - Espen M Eilertsen
- PROMENTA Research Center, Department of Psychology, University of OsloOsloNorway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
- Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of OsloOsloNorway
- Department of Radiology and Nuclear Medicine, Oslo University HospitalOsloNorway
| | - René Westerhausen
- Section for Cognitive and Clinical Neuroscience, Department of Psychology, University of OsloOsloNorway
| |
Collapse
|
37
|
Xu H, Xu C, Yang Z, Bai G, Yin B. Two sides of the same coin: distinct neuroanatomical patterns predict crystallized and fluid intelligence in adults. Front Neurosci 2023; 17:1199106. [PMID: 37304014 PMCID: PMC10249781 DOI: 10.3389/fnins.2023.1199106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
Background Crystallized intelligence (Gc) and fluid intelligence (Gf) are regarded as distinct intelligence components that statistically correlate with each other. However, the distinct neuroanatomical signatures of Gc and Gf in adults remain contentious. Methods Machine learning cross-validated elastic net regression models were performed on the Human Connectome Project Young Adult dataset (N = 1089) to characterize the neuroanatomical patterns of structural magnetic resonance imaging variables that are associated with Gc and Gf. The observed relationships were further examined by linear mixed-effects models. Finally, intraclass correlations were computed to examine the similarity of the neuroanatomical correlates between Gc and Gf. Results The results revealed distinct multi-region neuroanatomical patterns predicted Gc and Gf, respectively, which were robust in a held-out test set (R2 = 2.40, 1.97%, respectively). The relationship of these regions with Gc and Gf was further supported by the univariate linear mixed effects models. Besides that, Gc and Gf displayed poor neuroanatomical similarity. Conclusion These findings provided evidence that distinct machine learning-derived neuroanatomical patterns could predict Gc and Gf in healthy adults, highlighting differential neuroanatomical signatures of different aspects of intelligence.
Collapse
Affiliation(s)
- Hui Xu
- Department of Neurosurgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- Peter Boris Centre for Addictions Research, St. Joseph’s Healthcare Hamilton, McMaster University, Hamilton, ON, Canada
| | - Cheng Xu
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Zhenliang Yang
- Faculty of Psychology, Tianjin Normal University, Tianjin, China
| | - Guanghui Bai
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Bo Yin
- Department of Neurosurgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| |
Collapse
|
38
|
Gutteridge DS, Segal A, McNeil JJ, Beilin L, Brodtmann A, Chowdhury EK, Egan GF, Ernst ME, Hussain SM, Reid CM, Robb CE, Ryan J, Woods RL, Keage HA, Jamadar S. The relationship between long-term blood pressure variability and cortical thickness in older adults. Neurobiol Aging 2023; 129:157-167. [PMID: 37331246 DOI: 10.1016/j.neurobiolaging.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/02/2023] [Accepted: 05/17/2023] [Indexed: 06/20/2023]
Abstract
High blood pressure variability (BPV) is a risk factor for cognitive decline and dementia, but its association with cortical thickness is not well understood. Here we use a topographical approach, to assess links between long-term BPV and cortical thickness in 478 (54% men at baseline) community dwelling older adults (70-88 years) from the ASPirin in Reducing Events in the Elderly NEURO sub-study. BPV was measured as average real variability, based on annual visits across three years. Higher diastolic BPV was significantly associated with reduced cortical thickness in multiple areas, including temporal (banks of the superior temporal sulcus), parietal (supramarginal gyrus, post-central gyrus), and posterior frontal areas (pre-central gyrus, caudal middle frontal gyrus), while controlling for mean BP. Higher diastolic BPV was associated with faster progression of cortical thinning across the three years. Diastolic BPV is an important predictor of cortical thickness, and trajectory of cortical thickness, independent of mean blood pressure. This finding suggests an important biological link in the relationship between BPV and cognitive decline in older age.
Collapse
Affiliation(s)
- D S Gutteridge
- Cognitive Ageing and Impairment Neuroscience Laboratory (CAIN), University of South Australia, Adelaide, South Australia, Australia.
| | - A Segal
- Turner Institute for Brain & Mental Health, Monash University, Melbourne, Victoria, Australia
| | - J J McNeil
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia
| | - L Beilin
- School of Medicine, Royal Perth Hospital Unit, University of Western Australia, Perth, Western Australia, Australia
| | - A Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - E K Chowdhury
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - G F Egan
- Turner Institute for Brain & Mental Health, Monash University, Melbourne, Victoria, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - M E Ernst
- Department of Family Medicine, Carver College of Medicine. The University of Iowa, Iowa City, IA, USA; Department of Pharmacy Practice and Science, College of Pharmacy, Carver College of Medicine. The University of Iowa, Iowa City, IA, USA
| | - S M Hussain
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia; Department of Medical Education, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
| | - C M Reid
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia; School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - C E Robb
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia
| | - J Ryan
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia
| | - R L Woods
- School of Public Health & Preventative Medicine, Monash University, Melbourne, Victoria, Australia
| | - H A Keage
- Cognitive Ageing and Impairment Neuroscience Laboratory (CAIN), University of South Australia, Adelaide, South Australia, Australia
| | - S Jamadar
- Turner Institute for Brain & Mental Health, Monash University, Melbourne, Victoria, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| |
Collapse
|
39
|
Li Y, Chang J, Chen X, Liu J, Zhao L. Advances in the Study of APOE and Innate Immunity in Alzheimer's Disease. J Alzheimers Dis 2023:JAD230179. [PMID: 37182889 DOI: 10.3233/jad-230179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Alzheimer's disease (AD) is a progressive degenerative disease of the nervous system (CNS) with an insidious onset. Clinically, it is characterized by a full range of dementia manifestations including memory impairment, aphasia, loss of speech, loss of use, loss of recognition, impairment of visuospatial skills, and impairment of executive function, as well as changes in personality and behavior. The exact cause of AD has not yet been identified. Nevertheless, modern research indicates that genetic factors contribute to 70% of human's risk of AD. Apolipoprotein (APOE) accounts for up to 90% of the genetic predisposition. APOE is a crucial gene that cannot be overstated. In addition, innate immunity plays a significant role in the etiology and treatment of AD. Understanding the different subtypes of APOE and their interconnections is of paramount importance. APOE and innate immunity, along with their relationship to AD, are primary research motivators for in-depth research and clinical trials. The exploration of novel technologies has led to an increasing trend in the study of AD at the cellular and molecular levels and continues to make more breakthroughs and progress. As of today, there is no effective treatment available for AD around the world. This paper aims to summarize and analyze the role of APOE and innate immunity, as well as development trends in recent years. It is anticipated that APOE and innate immunity will provide a breakthrough for humans to hinder AD progression in the near future.
Collapse
Affiliation(s)
- Yujiao Li
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Jun Chang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Xi Chen
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Jianwei Liu
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lan Zhao
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| |
Collapse
|
40
|
Großmann W. Listening with an Ageing Brain - a Cognitive Challenge. Laryngorhinootologie 2023; 102:S12-S34. [PMID: 37130528 PMCID: PMC10184676 DOI: 10.1055/a-1973-3038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Hearing impairment has been recently identified as a major modifiable risk factor for cognitive decline in later life and has been becoming of increasing scientific interest. Sensory and cognitive decline are connected by complex bottom-up and top-down processes, a sharp distinction between sensation, perception, and cognition is impossible. This review provides a comprehensive overview on the effects of healthy and pathological aging on auditory as well as cognitive functioning on speech perception and comprehension, as well as specific auditory deficits in the 2 most common neurodegenerative diseases in old age: Alzheimer disease and Parkinson syndrome. Hypotheses linking hearing loss to cognitive decline are discussed, and current knowledge on the effect of hearing rehabilitation on cognitive functioning is presented. This article provides an overview of the complex relationship between hearing and cognition in old age.
Collapse
Affiliation(s)
- Wilma Großmann
- Universitätsmedizin Rostock, Klinik und Poliklinik für Hals-Nasen-Ohrenheilkunde,Kopf- und Halschirurgie "Otto Körner"
| |
Collapse
|
41
|
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, Milà-Alomà M, Lorenzini L, Ingala S, Meije Wink A, Mutsaerts HJMM, Minguillón C, Fauria K, Molinuevo JL, Haller S, Chetelat G, Waldman A, Schwarz AJ, Barkhof F, Suridjan I, Kollmorgen G, Bayfield A, Zetterberg H, Blennow K, Suárez-Calvet M, Vilaplana V, Gispert JD. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex. eLife 2023; 12:e81067. [PMID: 37067031 PMCID: PMC10181824 DOI: 10.7554/elife.81067] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 04/10/2023] [Indexed: 04/18/2023] Open
Abstract
Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.
Collapse
Affiliation(s)
- Irene Cumplido-Mayoral
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | - Marina García-Prat
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN)MadridSpain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - Karine Fauria
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
| | - Sven Haller
- CIRD Centre d'Imagerie Rive DroiteGenevaSwitzerland
| | - Gael Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and BrainCyceronFrance
| | - Adam Waldman
- Centre for Dementia Prevention, Edinburgh Imaging, and UK Dementia Research Institute at The University of EdinburghEdinburghUnited Kingdom
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Institutes of Neurology and Healthcare Engineering, University College LondonLondonUnited Kingdom
| | | | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of NeurologyLondonUnited Kingdom
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- UK Dementia Research Institute at UCLLondonUnited Kingdom
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridFrance
- Servei de Neurologia, Hospital del MarBarcelonaSpain
| | - Verónica Vilaplana
- Department of Signal Theory and Communications, Universitat Politècnica de CatalunyaBarcelonaSpain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN)MadridSpain
| | | | | | | | | |
Collapse
|
42
|
Navarri X, Vosberg DE, Shin J, Richer L, Leonard G, Pike GB, Banaschewski T, 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, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Pausova Z, Paus T. A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents. Dev Cogn Neurosci 2023; 60:101232. [PMID: 36963244 PMCID: PMC10064237 DOI: 10.1016/j.dcn.2023.101232] [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: 11/14/2022] [Revised: 03/14/2023] [Accepted: 03/15/2023] [Indexed: 03/17/2023] Open
Abstract
Although many studies of the adolescent brain identified positive associations between cognitive abilities and cortical thickness, little is known about mechanisms underlying such brain-behavior relationships. With experience-induced plasticity playing an important role in shaping the cerebral cortex throughout life, it is likely that some of the inter-individual variations in cortical thickness could be explained by genetic variations in relevant molecular processes, as indexed by a polygenic score of neuronal plasticity (PGS-NP). Here, we studied associations between PGS-NP, cognitive abilities, and thickness of the cerebral cortex, estimated from magnetic resonance images, in the Saguenay Youth Study (SYS, 533 females, 496 males: age=15.0 ± 1.8 years of age; cross-sectional), and the IMAGEN Study (566 females, 556 males; between 14 and 19 years; longitudinal). Using Gene Ontology, we first identified 199 genes implicated in neuronal plasticity, which mapped to 155,600 single nucleotide polymorphisms (SNPs). Second, we estimated their effect sizes from an educational attainment meta-GWAS to build a PGS-NP. Third, we examined a possible moderating role of PGS-NP in the relationship between performance intelligence quotient (PIQ), and its subtests, and the thickness of 34 cortical regions. In SYS, we observed a significant interaction between PGS-NP and object assembly vis-à-vis thickness in male adolescents (p = 0.026). A median-split analysis showed that, in males with a 'high' PGS-NP, stronger associations between object assembly and thickness were found in regions with larger age-related changes in thickness (r = 0.55, p = 0.00075). Although the interaction between PIQ and PGS-NP was non-significant (p = 0.064), we performed a similar median-split analysis. Again, in the high PGS-NP males, positive associations between PIQ and thickness were observed in regions with larger age-related changes in thickness (r = 0.40, p = 0.018). In the IMAGEN cohort, we did not replicate the first set of results (interaction between PGS-NP and cognitive abilities via-a-vis cortical thickness) while we did observe the same relationship between the brain-behaviour relationship and (longitudinal) changes in cortical thickness (Matrix reasoning: r = 0.63, p = 6.5e-05). No statistically significant results were observed in female adolescents in either cohort. Overall, these cross-sectional and longitudinal results suggest that molecular mechanisms involved in neuronal plasticity may contribute to inter-individual variations of cortical thickness related to cognitive abilities during adolescence in a sex-specific manner.
Collapse
Affiliation(s)
- Xavier Navarri
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada
| | - Daniel E Vosberg
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada
| | - Jean Shin
- Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Louis Richer
- Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
| | - Gabriel Leonard
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - 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
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, 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, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, 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 & psychiatrie", University Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS; Centre Borelli, Gif-sur-Yvette, France; and 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; and 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
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, 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 Neuroscience, 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
| | - Zdenka Pausova
- Departments of Physiology and Nutritional Sciences, Hospital for Sick Children, University of Toronto, Peter Gilgan Centre for Research and Learning, Toronto, ON M5G 0A4, Canada
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada; Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON M5S3G3, Canada.
| |
Collapse
|
43
|
Crews FT, Coleman LG, Macht VA, Vetreno RP. Targeting Persistent Changes in Neuroimmune and Epigenetic Signaling in Adolescent Drinking to Treat Alcohol Use Disorder in Adulthood. Pharmacol Rev 2023; 75:380-396. [PMID: 36781218 PMCID: PMC9969522 DOI: 10.1124/pharmrev.122.000710] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 12/15/2022] Open
Abstract
Studies universally find early age of drinking onset is linked to lifelong risks of alcohol problems and alcohol use disorder (AUD). Assessment of the lasting effect of drinking during adolescent development in humans is confounded by the diversity of environmental and genetic factors that affect adolescent development, including emerging personality disorders and progressive increases in drinking trajectories into adulthood. Preclinical studies using an adolescent intermittent ethanol (AIE) exposure rat model of underage binge drinking avoid the human confounds and support lifelong changes that increase risks. AIE increases adult alcohol drinking, risky decision-making, reward-seeking, and anxiety as well as reductions in executive function that all increase risks for the development of an AUD. AIE causes persistent increases in brain neuroimmune signaling high-mobility group box 1 (HMGB1), Toll-like receptor, receptor for advanced glycation end products, and innate immune genes that are also found to be increased in human AUD brain. HMGB1 is released from cells by ethanol, both free and within extracellular vesicles, that act on neurons and glia, shifting transcription and cellular phenotype. AIE-induced decreases in adult hippocampal neurogenesis and loss of basal forebrain cholinergic neurons are reviewed as examples of persistent AIE-induced pathology. Both are prevented and reversed by anti-inflammatory and epigenetic drugs. Findings suggest AIE-increased HMGB1 signaling induces the RE-1 silencing transcript blunting cholinergic gene expression, shifting neuronal phenotype. Inhibition of HMGB1 neuroimmune signaling, histone methylation enzymes, and galantamine, the cholinesterase inhibitor, both prevent and reverse AIE pathology. These findings provide new targets that may reverse AUD neuropathology as well as other brain diseases linked to neuroimmune signaling. SIGNIFICANCE STATEMENT: Adolescent underage binge drinking studies find that earlier adolescent drinking is associated with lifelong alcohol problems including high levels of lifetime alcohol use disorder (AUD). Preclinical studies find the underage binge drinking adolescent intermittent ethanol (AIE) model causes lasting changes in adults that increase risks of developing adult alcohol problems. Loss of hippocampal neurogenesis and loss of basal forebrain cholinergic neurons provide examples of how AIE-induced epigenetic and neuroimmune signaling provide novel therapeutic targets for adult AUD.
Collapse
Affiliation(s)
- Fulton T Crews
- Bowles Center for Alcohol Studies and Departments of Pharmacology and Psychiatry, School of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Leon G Coleman
- Bowles Center for Alcohol Studies and Departments of Pharmacology and Psychiatry, School of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Victoria A Macht
- Bowles Center for Alcohol Studies and Departments of Pharmacology and Psychiatry, School of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Ryan P Vetreno
- Bowles Center for Alcohol Studies and Departments of Pharmacology and Psychiatry, School of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| |
Collapse
|
44
|
Paus T. Tracking Development of Connectivity in the Human Brain: Axons and Dendrites. Biol Psychiatry 2023; 93:455-463. [PMID: 36344316 DOI: 10.1016/j.biopsych.2022.08.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/15/2022] [Accepted: 08/02/2022] [Indexed: 02/04/2023]
Abstract
The neuron doctrine laid the foundation for our current thinking about the structural and functional organization of the human brain. With the basic units of the nervous system-neurons-being physically separate, their connectivity relies on the conduction of action potentials in axons and their transmission across the synaptic cleft to the dendrites of other neurons. This study reviews available ex vivo data about the cellular composition of the human cerebral cortex, focusing on axons and dendrites, to conceptualize biological sources of signals detected in vivo with magnetic resonance imaging. To bridge the gap between ex vivo and in vivo observations, I then explain the basic principles of virtual histology, an approach that integrates spatially cell- or process-specific transcriptomic data with magnetic resonance signals to facilitate their neurobiological interpretation. Finally, I provide an overview of the initial insights gained in this manner in studies of brain development and maturation, in both health and disease.
Collapse
Affiliation(s)
- Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montréal, Montreal, Quebec, Canada.
| |
Collapse
|
45
|
Arnatkeviciute A, Markello RD, Fulcher BD, Misic B, Fornito A. Toward Best Practices for Imaging Transcriptomics of the Human Brain. Biol Psychiatry 2023; 93:391-404. [PMID: 36725139 DOI: 10.1016/j.biopsych.2022.10.016] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/03/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022]
Abstract
Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.
Collapse
Affiliation(s)
- Aurina Arnatkeviciute
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia.
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Ben D Fulcher
- School of Physics, The University of Sydney, Sydney, New South Wales, Australia
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| |
Collapse
|
46
|
Luo Q, Chen J, Li Y, Lin X, Yu H, Lin X, Wu H, Peng H. Cortical thickness and curvature abnormalities in patients with major depressive disorder with childhood maltreatment: Neural markers of vulnerability? Asian J Psychiatr 2023; 80:103396. [PMID: 36508912 DOI: 10.1016/j.ajp.2022.103396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/07/2022] [Accepted: 11/12/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Childhood maltreatment has been related to various disadvantageous lifetime outcomes. However, the brain structural alterations that occur in major depressive disorder (MDD) patients with childhood maltreatment are incompletely investigated. METHODS We extensively explored the cortical abnormalities including cortical volume, surface area, thickness, sulcal depth, and curvature in maltreated MDD patients. Twoway ANOVA was performed to distinguish the effects of childhood maltreatment and depression on structural abnormalities. Partial correlation analysis was performed to explore the relationship between childhood maltreatment and cortical abnormalities. Moreover, we plotted the receiver operating characteristic curve to examine whether the observed cortical abnormalities could be used as neuro biomarkers to identify maltreated MDD patients. RESULTS We reach the following findings: (i) relative to MDD without childhood maltreatment, MDD patients with childhood maltreatment existed increased cortical curvature in inferior frontal gyrus; (ii) compared to HC without childhood maltreatment, decreased cortical thickness was observed in anterior cingulate cortex and medial prefrontal cortex in MDD patients with childhood maltreatment; (iii) we confirmed the inseparable relationship between cortical curvature alterations in inferior frontal gyrus as well as childhood maltreatment; (iv) cortical curvature abnormality in inferior frontal gyrus could be applied as neural biomarker for clinical identification of MDD patients with childhood maltreatment. CONCLUSIONS Childhood maltreatment have a significant effects on cortical thickness and curvature abnormalities involved in inferior frontal gyrus, anterior cingulate cortex and medial prefrontal cortex, constituting the vulnerability to depression.
Collapse
Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Xiaohui Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
| |
Collapse
|
47
|
Cortical profiles of numerous psychiatric disorders and normal development share a common pattern. Mol Psychiatry 2023; 28:698-709. [PMID: 36380235 DOI: 10.1038/s41380-022-01855-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/19/2022] [Accepted: 10/24/2022] [Indexed: 11/16/2022]
Abstract
The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.
Collapse
|
48
|
Associations between cortical thickness and anxious/depressive symptoms differ by the quality of early care. Dev Psychopathol 2023; 35:73-84. [PMID: 35045914 PMCID: PMC9023591 DOI: 10.1017/s0954579421000845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
A variety of childhood experiences can lead to anxious/depressed (A/D) symptoms. The aim of the present study was to explore the brain morphological (cortical thickness and surface area) correlates of A/D symptoms and the extent to which these phenotypes vary depending on the quality of the parenting context in which children develop. Structural magnetic resonance imaging (MRI) scans were acquired on 45 children with Child Protective Services (CPS) involvement due to risk of not receiving adequate care (high-risk group) and 25 children without CPS involvement (low-risk group) (rangeage = 8.08-12.14; Mage = 10.05) to assess cortical thickness (CT) and cortical surface area (SA). A/D symptoms were measured using the Child Behavioral Checklist. The association between A/D symptoms and CT, but not SA, differed by risk status such that high-risk children showed decreasing CT as A/D scores increased, whereas low-risk children showed increasing CT as A/D scores increased. This interaction was specific to CT in prefrontal, frontal, temporal, and parietal cortical regions. The groups had marginally different A/D scores, in the direction of higher risk being associated with lower A/D scores. Results suggest that CT correlates of A/D symptoms are differentially shaped by the quality of early caregiving experiences and should be distinguished between high- and low-risk children.
Collapse
|
49
|
Zhang J, Treyer V, Sun J, Zhang C, Gietl A, Hock C, Razansky D, Nitsch RM, Ni R. Automatic analysis of skull thickness, scalp-to-cortex distance and association with age and sex in cognitively normal elderly. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.19.524484. [PMID: 36711717 PMCID: PMC9882276 DOI: 10.1101/2023.01.19.524484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Personalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T 1 -weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9±8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.
Collapse
Affiliation(s)
- Junhao Zhang
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
- Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Junfeng Sun
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chencheng Zhang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
- Neurimmune, Schlieren, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
- Neurimmune, Schlieren, Switzerland
| | - Ruiqing Ni
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
- Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland
- Zentrum für Neurowissenschaften Zurich, Zurich, Switzerland
| |
Collapse
|
50
|
Hollestein V, Poelmans G, Forde NJ, Beckmann CF, Ecker C, Mann C, Schäfer T, Moessnang C, Baumeister S, Banaschewski T, Bourgeron T, Loth E, Dell'Acqua F, Murphy DGM, Puts NA, Tillmann J, Charman T, Jones EJH, Mason L, Ambrosino S, Holt R, Bölte S, Buitelaar JK, Naaijen J. Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure. Transl Psychiatry 2023; 13:18. [PMID: 36681677 PMCID: PMC9867712 DOI: 10.1038/s41398-023-02317-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/22/2023] Open
Abstract
The excitatory/inhibitory (E/I) imbalance hypothesis posits that imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism. However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. We used innovative analysis methods-combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT) to investigate relationships between genetic variance, brain structure and autism symptomatology of participants from the AIMS-2-TRIALS LEAP cohort (autism = 359, male/female = 258/101; neurotypical control participants = 279, male/female = 178/101) aged 6-30 years. Using competitive gene-set analyses, we investigated whether aggregated genetic variation in glutamate and GABA gene-sets could be associated with behavioral measures of autism symptoms and brain structural variation. Further, using the same gene-sets, we corelated expression profiles throughout the cortex with differences in CT between autistic and neurotypical control participants, as well as in separate sensory subgroups. The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group. In adolescents and adults, brain regions with greater gene-expression of glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants although in opposing directions. Additionally, the gene expression profiles were associated with CT profiles in separate sensory subgroups. Our results suggest complex relationships between E/I related genetics and autism symptom profiles as well as brain structure alterations, where there may be differential roles for glutamate and GABA.
Collapse
Affiliation(s)
- Viola Hollestein
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Geert Poelmans
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Natalie J Forde
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christine Ecker
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Caroline Mann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Tim Schäfer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Sarah Baumeister
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tobias Banaschewski
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Thomas Bourgeron
- Institut Pasteur, Human Genetics and Cognitive Functions Unit, Paris, France
| | - Eva Loth
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Flavio Dell'Acqua
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council (MRC) Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Nicolaas A Puts
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council (MRC) Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Julian Tillmann
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, London, UK
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, London, UK
| | - Sara Ambrosino
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Rosemary Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, Western Australia
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| |
Collapse
|