1
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Li D, Zou B, Hu Q, Zhang X, Zeng W, Liu L, Yu M. Single-Cell RNA Sequencing of the Primary Visual Cortex in Mice With Optic Nerve Injury. Invest Ophthalmol Vis Sci 2025; 66:31. [PMID: 40408096 PMCID: PMC12118511 DOI: 10.1167/iovs.66.5.31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Accepted: 04/19/2025] [Indexed: 06/01/2025] Open
Abstract
Purpose Glial cells play a critical role in primary visual cortex (V1 region) damage caused by optic nerve injury, but the mechanisms driving progression of V1 region injury and glial cell heterogeneity remain poorly understood. This study aimed to investigate the damage changes in the V1 region of mice after optic nerve crush (ONC) by single-cell RNA sequencing (scRNA-seq). Methods Hematoxylin and eosin (H&E) and immunofluorescence staining were used to evaluate the changes of retinal thickness, astrocytes, and microglia in the V1 region after ONC in mice. Single cell suspensions in the V1 region of mice were prepared and analyzed by scRNA-seq with Seurat, cellchat, CytoTRACE in R software. The expression of PTGDS and CRYAB was measured by qPCR, Western blot, and immunofluorescence. Results After unilateral ONC, retinal thinning in both eyes and activation of astrocytes and microglia in contralateral V1 region were observed. Genes related to neuroinflammation and apoptosis in the bilateral V1 region were upregulated, and the related pathways included MAPK, TNF, and apoptosis signaling pathways. Notably, the V1 region contralateral to the ONC eye exhibited more pronounced differential gene expression, and the protein expression of neuroinflammation-related genes Ptgds and Cryab increased. We further investigated the heterogeneity and pseudotime trajectories of astrocytes and microglia, demonstrating the key branches that dominate neuroinflammation. Conclusions This study generates an atlas of the V1 region of the mouse brain, highlighting the role of astrocytes and microglia in the damage changes in the V1 region after ONC, and suggesting Ptgds and Cryab as potential targets to reduce neuroinflammation.
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Affiliation(s)
- Deling Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
| | - Bin Zou
- Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Qinyuan Hu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
| | - Xinyi Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
| | - Weiting Zeng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
| | - Liling Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
| | - Minbin Yu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong, China
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2
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von Bernhardi R, Eugenín J. Ageing-related changes in the regulation of microglia and their interaction with neurons. Neuropharmacology 2025; 265:110241. [PMID: 39617175 DOI: 10.1016/j.neuropharm.2024.110241] [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: 06/05/2024] [Revised: 09/24/2024] [Accepted: 11/26/2024] [Indexed: 12/12/2024]
Abstract
Ageing is one of the most important risk factors for chronic health conditions, including neurodegenerative diseases. Inflammation is a feature of ageing, as well as a key pathophysiological mechanism for degenerative diseases. Microglia play multiple roles in the central nervous system; their states entail a complex assemblage of responses reflecting the multiplicity of functions they fulfil both under homeostatic basal conditions and in response to stimuli. Whereas glial cells can promote neuronal homeostasis and limit neurodegeneration, age-related inflammation (i.e. inflammaging) leads to the functional impairment of microglia and astrocytes, exacerbating their response to stimuli. Thus, microglia are key mediators for age-dependent changes of the nervous system, participating in the generation of a less supportive or even hostile environment for neurons. Whereas multiple changes of ageing microglia have been described, here we will focus on the neuron-microglia regulatory crosstalk through fractalkine (CX3CL1) and CD200, and the regulatory cytokine Transforming Growth Factor β1 (TGFβ1), which is involved in immunomodulation and neuroprotection. Ageing results in a dysregulated activation of microglia, affecting neuronal survival, and function. The apparent unresponsiveness of aged microglia to regulatory signals could reflect a restriction in the mechanisms underlying their homeostatic and reactive states. The spectrum of functions, required to respond to life-long needs for brain maintenance and in response to disease, would progressively narrow, preventing microglia from maintaining their protective functions. This article is part of the Special Issue on "Microglia".
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Affiliation(s)
- Rommy von Bernhardi
- Universidad San Sebastian, Faculty for Odontology and Rehabilitation Sciences. Lota 2465, Providencia, Santiago, PO. 7510602, Chile.
| | - Jaime Eugenín
- Universidad de Santiago de Chile, Faculty of Chemistry and Biology, Av. Libertador Bernardo O'Higgins 3363, Santiago, PO. 7510602, Chile.
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3
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Knight SR, Abbasova L, Zeighami Y, Hansen JY, Martins D, Zelaya F, Dipasquale O, Liu T, Shin D, Bossong M, Azis M, Antoniades M, Howes OD, Bonoldi I, Egerton A, Allen P, O'Daly O, McGuire P, Modinos G. Transcriptional and Neurochemical Signatures of Cerebral Blood Flow Alterations in Individuals With Schizophrenia or at Clinical High Risk for Psychosis. Biol Psychiatry 2025:S0006-3223(25)00076-9. [PMID: 39923816 DOI: 10.1016/j.biopsych.2025.01.028] [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: 07/19/2024] [Revised: 01/24/2025] [Accepted: 01/31/2025] [Indexed: 02/11/2025]
Abstract
BACKGROUND The brain integrates multiple scales of description, from the level of cells and molecules to large-scale networks and behavior. Understanding relationships across these scales may be fundamental to advancing understanding of brain function in health and disease. Recent neuroimaging research has shown that functional brain alterations that are associated with schizophrenia spectrum disorders (SSDs) are already present in young adults at clinical high risk for psychosis (CHR-P), but the cellular and molecular determinants of these alterations remain unclear. METHODS Here, we used regional cerebral blood flow (rCBF) data from 425 individuals (122 with an SSD compared with 116 healthy control participants [HCs] and 129 individuals at CHR-P compared with 58 HCs) and applied a novel pipeline to integrate brainwide rCBF case-control maps with publicly available transcriptomic data (17,205 gene maps) and neurotransmitter atlases (19 maps) from 1074 healthy volunteers. RESULTS We identified significant correlations between astrocyte, oligodendrocyte, oligodendrocyte precursor cell, and vascular leptomeningeal cell gene modules for both SSD and CHR-P rCBF phenotypes. Additionally, endothelial cell genes were correlated in SSD, and microglia in CHR-P. Receptor distribution significantly predicted case-control rCBF differences, with dominance analysis highlighting dopamine (D1, D2, dopamine transporter), acetylcholine (VAChT, M1), gamma-aminobutyric acid A (GABAA), and glutamate (NMDA) receptors as key predictors for SSD (R2adjusted = 0.58, false discovery rate [FDR]-corrected p < .05) and CHR-P (R2adjusted = 0.6, pFDR < .05) rCBF phenotypes. These associations were primarily localized in subcortical regions and implicate cell types involved in stress response and inflammation, alongside specific neuroreceptor systems, in shared and distinct rCBF phenotypes in psychosis. CONCLUSIONS Our findings underscore the value of integrating multiscale data as a promising hypothesis-generating approach toward decoding biological pathways involved in neuroimaging-based psychosis phenotypes, potentially guiding novel interventions.
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Affiliation(s)
- Samuel R Knight
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Leyla Abbasova
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Medical Research Council Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Yashar Zeighami
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Olea Medical, La Ciotat, France
| | - Thomas Liu
- Centre for Functional MRI, University of California San Diego, San Diego, California
| | - David Shin
- Global MR Applications and Workflow, GE Healthcare, Menlo Park, California
| | - Matthijs Bossong
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Department of Psychiatry, Brain Center Rudoph Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Matilda Azis
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Mathilde Antoniades
- Center for AI and Data Science for Integrated Diagnostics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Ilaria Bonoldi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Paul Allen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Philip McGuire
- Department of Psychiatry, Oxford University, Oxford, United Kingdom
| | - Gemma Modinos
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Medical Research Council Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
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Ma J, Qi R, Wang J, Berto S, Wang GZ. Human-unique brain cell clusters are associated with learning disorders and human episodic memory activity. Mol Psychiatry 2025; 30:353-359. [PMID: 39227435 DOI: 10.1038/s41380-024-02722-2] [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: 01/30/2024] [Revised: 08/16/2024] [Accepted: 08/22/2024] [Indexed: 09/05/2024]
Abstract
The advanced evolution of the human cerebral cortex forms the basis for our high-level cognitive functions. Through a comparative analysis of single-nucleus transcriptome data from the human neocortex and that of chimpanzees, macaques, and marmosets, we discovered 20 subgroups of cell types unique to the human brain, which include 11 types of excitatory neurons. Many of these human-unique cell clusters exhibit significant overexpression of genes regulated by human-specific enhancers. Notably, these specific cell clusters also express genes associated with disease risk, particularly those related to brain dysfunctions like learning disorders. Furthermore, genes linked to cortical thickness and human episodic memory encoding activities show heightened expression within these cell subgroups. These findings underscore the critical role of human brain-unique cell clusters in the evolution of human brain functions.
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Affiliation(s)
- Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ruicheng Qi
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jing Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Stefano Berto
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
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5
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Zhao K, Wang D, Wang D, Chen P, Wei Y, Tu L, Chen Y, Tang Y, Yao H, Zhou B, Lu J, Wang P, Liao Z, Chen Y, Han Y, Zhang X, Liu Y. Macroscale connectome topographical structure reveals the biomechanisms of brain dysfunction in Alzheimer's disease. SCIENCE ADVANCES 2024; 10:eado8837. [PMID: 39392880 PMCID: PMC11809497 DOI: 10.1126/sciadv.ado8837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 09/11/2024] [Indexed: 10/13/2024]
Abstract
The intricate spatial configurations of brain networks offer essential insights into understanding the specific patterns of brain abnormalities and the underlying biological mechanisms associated with Alzheimer's disease (AD), normal aging, and other neurodegenerative disorders. This study investigated alterations in the topographical structure of the brain related to aging and neurodegenerative diseases by analyzing brain gradients derived from structural MRI data across multiple cohorts (n = 7323). The analysis identified distinct gradient patterns in AD, aging, and other neurodegenerative conditions. Gene enrichment analysis indicated that inorganic ion transmembrane transport was the most significant term in normal aging, while chemical synaptic transmission is a common enrichment term across various neurodegenerative diseases. Moreover, the findings show that each disorder exhibits unique dysfunctional neurophysiological characteristics. These insights are pivotal for elucidating the distinct biological mechanisms underlying AD, thereby enhancing our understanding of its unique clinical phenotypes in contrast to normal aging and other neurodegenerative disorders.
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Affiliation(s)
- Kun Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
- Research Institute of Shandong University: Magnetic Field-free Medicine & Functional Imaging, Jinan, China
- Shandong Key Laboratory: Magnetic Field-free Medicine & Functional Imaging (MF), Jinan, China
| | - Dong Wang
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Pindong Chen
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Center, Chinese Academy of Sciences, Beijing, China
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Liyun Tu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Yuqi Chen
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Yi Tang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Hongxiang Yao
- Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Bo Zhou
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China
| | - Zhengluan Liao
- Department of Psychiatry, People’s Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Yan Chen
- Department of Psychiatry, People’s Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
- Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Center, Chinese Academy of Sciences, Beijing, China
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6
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Khan AF, Iturria-Medina Y. Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms. Transl Psychiatry 2024; 14:386. [PMID: 39313512 PMCID: PMC11420368 DOI: 10.1038/s41398-024-03073-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 08/20/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024] Open
Abstract
From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.
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Affiliation(s)
- Ahmed Faraz Khan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada.
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7
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Krug A, Stein F, David FS, Schmitt S, Brosch K, Pfarr JK, Ringwald KG, Meller T, Thomas-Odenthal F, Meinert S, Thiel K, Winter A, Waltemate L, Lemke H, Grotegerd D, Opel N, Repple J, Hahn T, Streit F, Witt SH, Rietschel M, Andlauer TFM, Nöthen MM, Philipsen A, Nenadić I, Dannlowski U, Kircher T, Forstner AJ. Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample. Transl Psychiatry 2024; 14:235. [PMID: 38830892 PMCID: PMC11148082 DOI: 10.1038/s41398-024-02936-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 06/05/2024] Open
Abstract
There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.
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Affiliation(s)
- Axel Krug
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany.
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Kai G Ringwald
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- German Centre for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Jena, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Till F M Andlauer
- Department of Neurology, Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
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8
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Kim J, Vanrobaeys Y, Davatolhagh MF, Kelvington B, Chatterjee S, Ferri SL, Angelakos C, Mills AA, Fuccillo MV, Nickl-Jockschat T, Abel T. A chromosome region linked to neurodevelopmental disorders acts in distinct neuronal circuits in males and females to control locomotor behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594746. [PMID: 38952795 PMCID: PMC11216371 DOI: 10.1101/2024.05.17.594746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Biological sex shapes the manifestation and progression of neurodevelopmental disorders (NDDs). These disorders often demonstrate male-specific vulnerabilities; however, the identification of underlying mechanisms remains a significant challenge in the field. Hemideletion of the 16p11.2 region (16p11.2 del/+) is associated with NDDs, and mice modeling 16p11.2 del/+ exhibit sex-specific striatum-related phenotypes relevant to NDDs. Striatal circuits, crucial for locomotor control, consist of two distinct pathways: the direct and indirect pathways originating from D1 dopamine receptor (D1R) and D2 dopamine receptor (D2R) expressing spiny projection neurons (SPNs), respectively. In this study, we define the impact of 16p11.2 del/+ on striatal circuits in male and female mice. Using snRNA-seq, we identify sex- and cell type-specific transcriptomic changes in the D1- and D2-SPNs of 16p11.2 del/+ mice, indicating distinct transcriptomic signatures in D1-SPNs and D2-SPNs in males and females, with a ∼5-fold greater impact in males. Further pathway analysis reveals differential gene expression changes in 16p11.2 del/+ male mice linked to synaptic plasticity in D1- and D2-SPNs and GABA signaling pathway changes in D1-SPNs. Consistent with our snRNA-seq study revealing changes in GABA signaling pathways, we observe distinct changes in miniature inhibitory postsynaptic currents (mIPSCs) in D1- and D2-SPNs from 16p11.2 del/+ male mice. Behaviorally, we utilize conditional genetic approaches to introduce the hemideletion selectively in either D1- or D2-SPNs and find that conditional hemideletion of genes in the 16p11.2 region in D2-SPNs causes hyperactivity in male mice, but hemideletion in D1-SPNs does not. Within the striatum, hemideletion of genes in D2-SPNs in the dorsal lateral striatum leads to hyperactivity in males, demonstrating the importance of this striatal region. Interestingly, conditional 16p11.2 del/+ within the cortex drives hyperactivity in both sexes. Our work reveals that a locus linked to NDDs acts in different striatal circuits, selectively impacting behavior in a sex- and cell type-specific manner, providing new insight into male vulnerability for NDDs. Highlights - 16p11.2 hemideletion (16p11.2 del/+) induces sex- and cell type-specific transcriptomic signatures in spiny projection neurons (SPNs). - Transcriptomic changes in GABA signaling in D1-SPNs align with changes in inhibitory synapse function. - 16p11.2 del/+ in D2-SPNs causes hyperactivity in males but not females. - 16p11.2 del/+ in D2-SPNs in the dorsal lateral striatum drives hyperactivity in males. - 16p11.2 del/+ in cortex drives hyperactivity in both sexes. Graphic abstract
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9
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Phalnikar K, Srividya M, Mythri SV, Vasavi NS, Ganguly A, Kumar A, S P, Kalia K, Mishra SS, Dhanya SK, Paul P, Holla B, Ganesh S, Reddy PC, Sud R, Viswanath B, Muralidharan B. Altered neuroepithelial morphogenesis and migration defects in iPSC-derived cerebral organoids and 2D neural stem cells in familial bipolar disorder. OXFORD OPEN NEUROSCIENCE 2024; 3:kvae007. [PMID: 38638145 PMCID: PMC11024480 DOI: 10.1093/oons/kvae007] [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: 09/08/2023] [Revised: 01/26/2024] [Accepted: 02/26/2024] [Indexed: 04/20/2024]
Abstract
Bipolar disorder (BD) is a severe mental illness that can result from neurodevelopmental aberrations, particularly in familial BD, which may include causative genetic variants. In the present study, we derived cortical organoids from BD patients and healthy (control) individuals from a clinically dense family in the Indian population. Our data reveal that the patient organoids show neurodevelopmental anomalies, including organisational, proliferation and migration defects. The BD organoids show a reduction in both the number of neuroepithelial buds/cortical rosettes and the ventricular zone size. Additionally, patient organoids show a lower number of SOX2-positive and EdU-positive cycling progenitors, suggesting a progenitor proliferation defect. Further, the patient neurons show abnormal positioning in the ventricular/intermediate zone of the neuroepithelial bud. Transcriptomic analysis of control and patient organoids supports our cellular topology data and reveals dysregulation of genes crucial for progenitor proliferation and neuronal migration. Lastly, time-lapse imaging of neural stem cells in 2D in vitro cultures reveals abnormal cellular migration in BD samples. Overall, our study pinpoints a cellular and molecular deficit in BD patient-derived organoids and neural stem cell cultures.
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Affiliation(s)
- Kruttika Phalnikar
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - M Srividya
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - S V Mythri
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - N S Vasavi
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Archisha Ganguly
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Aparajita Kumar
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Padmaja S
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Kishan Kalia
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Srishti S Mishra
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Sreeja Kumari Dhanya
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
| | - Pradip Paul
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Bharath Holla
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Suhas Ganesh
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Puli Chandramouli Reddy
- Centre of Excellence in Epigenetics, Department of Life Sciences, Shiv Nadar Institution of Eminence, Delhi-NCR, India-201314
| | - Reeteka Sud
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Biju Viswanath
- National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road Bengaluru, Karnataka, India-560029
| | - Bhavana Muralidharan
- Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK - Post, Bellary Road, Bengaluru, Karnataka, India-560065
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10
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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.
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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
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Jimenez-Marin A, Diez I, Erramuzpe A, Stramaglia S, Bonifazi P, Cortes JM. Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain. Sci Data 2024; 11:256. [PMID: 38424112 PMCID: PMC10904384 DOI: 10.1038/s41597-024-03060-2] [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: 08/10/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
The human brain is an extremely complex network of structural and functional connections that operate at multiple spatial and temporal scales. Investigating the relationship between these multi-scale connections is critical to advancing our comprehension of brain function and disorders. However, accurately predicting structural connectivity from its functional counterpart remains a challenging pursuit. One of the major impediments is the lack of public repositories that integrate structural and functional networks at diverse resolutions, in conjunction with modular transcriptomic profiles, which are essential for comprehensive biological interpretation. To mitigate this limitation, our contribution encompasses the provision of an open-access dataset consisting of derivative matrices of functional and structural connectivity across multiple scales, accompanied by code that facilitates the investigation of their interrelations. We also provide additional resources focused on neuro-genetic associations of module-level network metrics, which present promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.
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Affiliation(s)
- Antonio Jimenez-Marin
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- Biomedical Research Doctorate Program, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Ibai Diez
- Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, United States of America
| | - Asier Erramuzpe
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| | - Sebastiano Stramaglia
- Dipartamento Interateneo di Fisica, Universita Degli Studi di Bari Aldo Moro, INFN, Bari, Italy
| | - Paolo Bonifazi
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| | - Jesus M Cortes
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain.
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain.
- Department of Cell Biology and Histology, University of the Basque Country (UPV/EHU), Leioa, Spain.
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12
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Scher MS. The science of uncertainty guides fetal-neonatal neurology principles and practice: diagnostic-prognostic opportunities and challenges. Front Neurol 2024; 15:1335933. [PMID: 38352135 PMCID: PMC10861710 DOI: 10.3389/fneur.2024.1335933] [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: 11/09/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024] Open
Abstract
Fetal-neonatal neurologists (FNNs) consider diagnostic, therapeutic, and prognostic decisions strengthened by interdisciplinary collaborations. Bio-social perspectives of the woman's health influence evaluations of maternal-placental-fetal (MPF) triad, neonate, and child. A dual cognitive process integrates "fast thinking-slow thinking" to reach shared decisions that minimize bias and maintain trust. Assessing the science of uncertainty with uncertainties in science improves diagnostic choices across the developmental-aging continuum. Three case vignettes highlight challenges that illustrate this approach. The first maternal-fetal dyad involved a woman who had been recommended to terminate her pregnancy based on an incorrect diagnosis of an encephalocele. A meningocele was subsequently identified when she sought a second opinion with normal outcome for her child. The second vignette involved two pregnancies during which fetal cardiac rhabdomyoma was identified, suggesting tuberous sclerosis complex (TSC). One woman sought an out-of-state termination without confirmation using fetal brain MRI or postmortem examination. The second woman requested pregnancy care with postnatal evaluations. Her adult child experiences challenges associated with TSC sequelae. The third vignette involved a prenatal diagnosis of an open neural tube defect with arthrogryposis multiplex congenita. The family requested prenatal surgical closure of the defect at another institution at their personal expense despite receiving a grave prognosis. The subsequent Management of Myelomeningocele Study (MOMS) would not have recommended this procedure. Their adult child requires medical care for global developmental delay, intractable epilepsy, and autism. These three evaluations involved uncertainties requiring shared clinical decisions among all stakeholders. Falsely negative or misleading positive interpretation of results reduced chances for optimal outcomes. FNN diagnostic skills require an understanding of dynamic gene-environment interactions affecting reproductive followed by pregnancy exposomes that influence the MPF triad health with fetal neuroplasticity consequences. Toxic stressor interplay can impair the neural exposome, expressed as anomalous and/or destructive fetal brain lesions. Functional improvements or permanent sequelae may be expressed across the lifespan. Equitable and compassionate healthcare for women and families require shared decisions that preserve pregnancy health, guided by person-specific racial-ethnic, religious, and bio-social perspectives. Applying developmental origins theory to neurologic principles and practice supports a brain health capital strategy for all persons across each generation.
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Affiliation(s)
- Mark Steven Scher
- Fetal/Neonatal Neurology Program, Division of Pediatric Neurology, Department of Pediatrics, Case Western Reserve University, Cleveland, OH, United States
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13
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Huang S, Wu SJ, Sansone G, Ibrahim LA, Fishell G. Layer 1 neocortex: Gating and integrating multidimensional signals. Neuron 2024; 112:184-200. [PMID: 37913772 PMCID: PMC11180419 DOI: 10.1016/j.neuron.2023.09.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/23/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.
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Affiliation(s)
- Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulia Sansone
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Leena Ali Ibrahim
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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14
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Scher MS. Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice. Front Neurol 2024; 14:1321674. [PMID: 38288328 PMCID: PMC10824035 DOI: 10.3389/fneur.2023.1321674] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 12/07/2023] [Indexed: 01/31/2024] Open
Abstract
An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype-genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene-environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.
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Affiliation(s)
- Mark S. Scher
- Division of Pediatric Neurology, Department of Pediatrics, Case Western Reserve University School of Medicine, Cleveland, OH, United States
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15
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Suresh H, Crow M, Jorstad N, Hodge R, Lein E, Dobin A, Bakken T, Gillis J. Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution. Nat Ecol Evol 2023; 7:1930-1943. [PMID: 37667001 PMCID: PMC10627823 DOI: 10.1038/s41559-023-02186-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 08/02/2023] [Indexed: 09/06/2023]
Abstract
Enhanced cognitive function in humans is hypothesized to result from cortical expansion and increased cellular diversity. However, the mechanisms that drive these phenotypic innovations remain poorly understood, in part because of the lack of high-quality cellular resolution data in human and non-human primates. Here, we take advantage of single-cell expression data from the middle temporal gyrus of five primates (human, chimp, gorilla, macaque and marmoset) to identify 57 homologous cell types and generate cell type-specific gene co-expression networks for comparative analysis. Although orthologue expression patterns are generally well conserved, we find 24% of genes with extensive differences between human and non-human primates (3,383 out of 14,131), which are also associated with multiple brain disorders. To assess the functional significance of gene expression differences in an evolutionary context, we evaluate changes in network connectivity across meta-analytic co-expression networks from 19 animals. We find that a subset of these genes has deeply conserved co-expression across all non-human animals, and strongly divergent co-expression relationships in humans (139 out of 3,383, <1% of primate orthologues). Genes with human-specific cellular expression and co-expression profiles (such as NHEJ1, GTF2H2, C2 and BBS5) typically evolve under relaxed selective constraints and may drive rapid evolutionary change in brain function.
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Affiliation(s)
- Hamsini Suresh
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | | | | | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Alexander Dobin
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
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16
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Smeland OB, Kutrolli G, Bahrami S, Fominykh V, Parker N, Hindley GFL, Rødevand L, Jaholkowski P, Tesfaye M, Parekh P, Elvsåshagen T, Grotzinger AD, The International Multiple Sclerosis Genetics Consortium (IMSGC), The International Headache Genetics Consortium (IHGC), Steen NE, van der Meer D, O’Connell KS, Djurovic S, Dale AM, Shadrin AA, Frei O, Andreassen OA. The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.21.23292993. [PMID: 37503175 PMCID: PMC10371109 DOI: 10.1101/2023.07.21.23292993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.
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Affiliation(s)
- Olav B. Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gleda Kutrolli
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Vera Fominykh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadine Parker
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F. L. Hindley
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King’s College London, London, United Kingdom
| | - Linn Rødevand
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Piotr Jaholkowski
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Markos Tesfaye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torbjørn Elvsåshagen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Andrew D. Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | | | | | - Nils Eiel Steen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands
| | - Kevin S. O’Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M. Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, USA
- Department of Neurosciences, University of California San Diego, La Jolla, USA
- Department of Radiology, University of California, San Diego, La Jolla, USA
| | - Alexey A. Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
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17
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Suliman M, Al-Hawary SIS, Al-Dolaimy F, Hjazi A, Almalki SG, Alkhafaji AT, Alawadi AH, Alsaalamy A, Bijlwan S, Mustafa YF. Inflammatory diseases: Function of LncRNAs in their emergence and the role of mesenchymal stem cell secretome in their treatment. Pathol Res Pract 2023; 249:154758. [PMID: 37660657 DOI: 10.1016/j.prp.2023.154758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 09/05/2023]
Abstract
One of the best treatments for inflammatory diseases such as COVID-19, respiratory diseases and brain diseases is treatment with stem cells. Here we investigate the effect of stem cell therapy in the treatment of brain diseases.Preclinical studies have shown promising results, including improved functional recovery and tissue repair in animal models of neurodegenerative diseases, strokes,and traumatic brain injuries. However,ethical implications, safety concerns, and regulatory frameworks necessitate thorough evaluation before transitioning to clinical applications. Additionally, the complex nature of the brain and its intricate cellular environment present unique obstacles that must be overcome to ensure the successful integration and functionality of genetically engineered MSCs. The careful navigation of this path will determine whether the application of genetically engineered MSCs in brain tissue regeneration ultimately lives up to the hype surrounding it.
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Affiliation(s)
- Muath Suliman
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
| | | | | | - Ahmed Hjazi
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia.
| | - Sami G Almalki
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Majmaah, Saudi Arabia
| | | | - Ahmed Hussien Alawadi
- College of technical engineering, the Islamic University, Najaf, Iraq; College of technical engineering, the Islamic University of Al Diwaniyah, Iraq; College of technical engineering, the Islamic University of Babylon, Iraq
| | - Ali Alsaalamy
- College of technical engineering, Imam Ja'afar Al-Sadiq University, Al-Muthanna, Iraq
| | - Sheela Bijlwan
- Uttaranchal School of Computing Sciences, Uttaranchal University, Dehradun, India
| | - Yasser Fakri Mustafa
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Mosul, Mosul, Iraq
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