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Qu J, Qu Y, Zhu R, Wu Y, Xu G, Wang D. Transcriptional expression patterns of the cortical morphometric similarity network in progressive supranuclear palsy. CNS Neurosci Ther 2024; 30:e14901. [PMID: 39097922 PMCID: PMC11298202 DOI: 10.1111/cns.14901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/09/2024] [Accepted: 07/24/2024] [Indexed: 08/06/2024] Open
Abstract
BACKGROUND It has been demonstrated that progressive supranuclear palsy (PSP) correlates with structural abnormalities in several distinct regions of the brain. However, whether there are changes in the morphological similarity network (MSN) and the relationship between changes in brain structure and gene expression remain largely unknown. METHODS We used two independent cohorts (discovery dataset: PSP: 51, healthy controls (HC): 82; replication dataset: PSP: 53, HC: 55) for MSN analysis and comparing the longitudinal changes in the MSN of PSP. Then, we applied partial least squares regression to determine the relationships between changes in MSN and spatial transcriptional features and identified specific genes associated with MSN differences in PSP. We further investigated the biological processes enriched in PSP-associated genes and the cellular characteristics of these genes, and finally, we performed an exploratory analysis of the relationship between MSN changes and neurotransmitter receptors. RESULTS We found that the MSN in PSP patients was mainly decreased in the frontal and temporal cortex but increased in the occipital cortical region. This difference is replicable. In longitudinal studies, MSN differences are mainly manifested in the frontal and parietal regions. Furthermore, the expression pattern associated with MSN changes in PSP involves genes implicated in astrocytes and excitatory and inhibitory neurons and is functionally enriched in neuron-specific biological processes related to synaptic signaling. Finally, we found that the changes in MSN were mainly negatively correlated with the levels of serotonin, norepinephrine, and opioid receptors. CONCLUSIONS These results have enhanced our understanding of the microscale genetic and cellular mechanisms responsible for large-scale morphological abnormalities in PSP patients, suggesting potential targets for future therapeutic trials.
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Affiliation(s)
- Junyu Qu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Yancai Qu
- Department of NeurosurgeryTraditional Chinese Medicine Hospital of Muping DistrictYantaiChina
| | - Rui Zhu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Yongsheng Wu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Guihua Xu
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
| | - Dawei Wang
- Department of RadiologyQilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong UniversityJinanChina
- Magnetic Field‐free Medicine & Functional ImagingResearch Institute of Shandong UniversityJinanChina
- Magnetic Field‐free Medicine & Functional Imaging (MF)Shandong Key LaboratoryJinanChina
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2
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Vilela J, Rasga C, Santos JX, Martiniano H, Marques AR, Oliveira G, Vicente AM. Bridging Genetic Insights with Neuroimaging in Autism Spectrum Disorder-A Systematic Review. Int J Mol Sci 2024; 25:4938. [PMID: 38732157 PMCID: PMC11084239 DOI: 10.3390/ijms25094938] [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: 02/29/2024] [Revised: 04/22/2024] [Accepted: 04/25/2024] [Indexed: 05/13/2024] Open
Abstract
Autism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder characterized by impaired social interaction and communication, and repetitive patterns of behavior. Family studies show that ASD is highly heritable, and hundreds of genes have previously been implicated in the disorder; however, the etiology is still not fully clear. Brain imaging and electroencephalography (EEG) are key techniques that study alterations in brain structure and function. Combined with genetic analysis, these techniques have the potential to help in the clarification of the neurobiological mechanisms contributing to ASD and help in defining novel therapeutic targets. To further understand what is known today regarding the impact of genetic variants in the brain alterations observed in individuals with ASD, a systematic review was carried out using Pubmed and EBSCO databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This review shows that specific genetic variants and altered patterns of gene expression in individuals with ASD may have an effect on brain circuits associated with face processing and social cognition, and contribute to excitation-inhibition imbalances and to anomalies in brain volumes.
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Affiliation(s)
- Joana Vilela
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
| | - Célia Rasga
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
| | - João Xavier Santos
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
| | - Hugo Martiniano
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
| | - Ana Rita Marques
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
| | - Guiomar Oliveira
- Unidade de Neurodesenvolvimento e Autismo, Serviço do Centro de Desenvolvimento da Criança, Centro de Investigação e Formação Clínica, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-602 Coimbra, Portugal;
- Coimbra Institute for Biomedical Imaging and Translational Research, University Clinic of Pediatrics, Faculty of Medicine, University of Coimbra, 3000-602 Coimbra, Portugal
| | - Astrid Moura Vicente
- Departamento de Promoção da Saúde e Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal; (J.V.); (C.R.); (J.X.S.); (H.M.); (A.R.M.)
- BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisboa, Campo Grande, C8, 1749-016 Lisboa, Portugal
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Zhu W, Liu F, Fu J, Qin W, Xue K, Tang J, Zhang Y, Yu C. Genes associated with spontaneous brain activity changes in clinically different patients with major depressive disorder: A transcription-neuroimaging association study. CNS Neurosci Ther 2023; 29:3913-3924. [PMID: 37311691 PMCID: PMC10651976 DOI: 10.1111/cns.14311] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 05/19/2023] [Accepted: 06/02/2023] [Indexed: 06/15/2023] Open
Abstract
AIMS The amplitude of low-frequency fluctuations (ALFF) of resting-state functional MRI signals is a reliable neuroimaging measure of spontaneous brain activity. Inconsistent ALFF alterations have been reported in major depressive disorder (MDD) possibly due to clinical heterogeneity. This study was designed to investigate clinically sensitive and insensitive genes associated with ALFF alterations in MDD and the potential mechanisms. METHODS Transcription-neuroimaging association analyses of case-control ALFF differences from two independent neuroimaging datasets with gene expression data from Allen Human Brain Atlas were performed to identify the two gene sets. Various enrichment analyses were conducted to characterize their preference in biological functions, cell types, temporal stages, and shared effects with other psychiatric disorders. RESULTS Compared with controls, first-episode and drug-naïve patients showed more extensive ALFF alterations than patients with varied clinical features. We identified 903 clinically sensitive genes and 633 clinically insensitive genes, and the former was enriched for genes with down-regulated expression in the cerebral cortex of MDD patients. Despite shared functions of cell communication, signaling, and transport, clinically sensitive genes were enriched for cell differentiation and development whereas clinically insensitive genes were for ion transport and synaptic signaling. Clinically sensitive genes showed enrichment for microglia and macrophage from childhood to young adulthood in contrast to clinically insensitive genes for neurons before early infancy. Clinically sensitive genes (15.2%) were less likely correlated with ALFF alterations in schizophrenia than clinically insensitive genes (66.8%), and both were not relevant to bipolar disorder and adult attention deficit and hyperactivity disorder based on a third independent neuroimaging dataset. CONCLUSIONS Present results provide novel insights into the molecular mechanisms of spontaneous brain activity changes in clinically different patients with MDD.
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Affiliation(s)
- Wenshuang Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Jie Tang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | | | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of SciencesShanghaiChina
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4
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Xie Y, Sun J, Man W, Zhang Z, Zhang N. Personalized estimates of brain cortical structural variability in individuals with Autism spectrum disorder: the predictor of brain age and neurobiology relevance. Mol Autism 2023; 14:27. [PMID: 37507798 PMCID: PMC10375633 DOI: 10.1186/s13229-023-00558-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a heritable condition related to brain development that affects a person's perception and socialization with others. Here, we examined variability in the brain morphology in ASD children and adolescent individuals at the level of brain cortical structural profiles and the level of each brain regional measure. METHODS We selected brain structural MRI data in 600 ASDs and 729 normal controls (NCs) from Autism Brain Imaging Data Exchange (ABIDE). The personalized estimate of similarity between gray matter volume (GMV) profiles of an individual to that of others in the same group was assessed by using the person-based similarity index (PBSI). Regional contributions to PBSI score were utilized for brain age gap estimation (BrainAGE) prediction model establishment, including support vector regression (SVR), relevance vector regression (RVR), and Gaussian process regression (GPR). The association between BrainAGE prediction in ASD and clinical performance was investigated. We further explored the related inter-regional profiles of gene expression from the Allen Human Brain Atlas with variability differences in the brain morphology between groups. RESULTS The PBSI score of GMV was negatively related to age regardless of the sample group, and the PBSI score was significantly lower in ASDs than in NCs. The regional contributions to the PBSI score of 126 brain regions in ASDs showed significant differences compared to NCs. RVR model achieved the best performance for predicting brain age. Higher inter-individual brain morphology variability was related to increased brain age, specific to communication symptoms. A total of 430 genes belonging to various pathways were identified as associated with brain cortical morphometric variation. The pathways, including short-term memory, regulation of system process, and regulation of nervous system process, were dominated mainly by gene sets for manno midbrain neurotypes. LIMITATIONS There is a sample mismatch between the gene expression data and brain imaging data from ABIDE. A larger sample size can contribute to the model training of BrainAGE and the validation of the results. CONCLUSIONS ASD has personalized heterogeneity brain morphology. The brain age gap estimation and transcription-neuroimaging associations derived from this trait are replenished in an additional direction to boost the understanding of the ASD brain.
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Affiliation(s)
- Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Weiqi Man
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
- Department of Radiology, Tianjin First Central Hospital, Tianjin, 300192, China
| | - Zhang Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
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Bruce MR, Couch ACM, Grant S, McLellan J, Ku K, Chang C, Bachman A, Matson M, Berman RF, Maddock RJ, Rowland D, Kim E, Ponzini MD, Harvey D, Taylor SL, Vernon AC, Bauman MD, Van de Water J. Altered behavior, brain structure, and neurometabolites in a rat model of autism-specific maternal autoantibody exposure. Mol Psychiatry 2023; 28:2136-2147. [PMID: 36973347 PMCID: PMC10575787 DOI: 10.1038/s41380-023-02020-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 02/23/2023] [Accepted: 02/27/2023] [Indexed: 03/29/2023]
Abstract
Maternal immune dysregulation is a prenatal risk factor for autism spectrum disorder (ASD). Importantly, a clinically relevant connection exists between inflammation and metabolic stress that can result in aberrant cytokine signaling and autoimmunity. In this study we examined the potential for maternal autoantibodies (aAbs) to disrupt metabolic signaling and induce neuroanatomical changes in the brains of exposed offspring. To accomplish this, we developed a model of maternal aAb exposure in rats based on the clinical phenomenon of maternal autoantibody-related ASD (MAR-ASD). Following confirmation of aAb production in rat dams and antigen-specific immunoglobulin G (IgG) transfer to offspring, we assessed offspring behavior and brain structure longitudinally. MAR-ASD rat offspring displayed a reduction in pup ultrasonic vocalizations and a pronounced deficit in social play behavior when allowed to freely interact with a novel partner. Additionally, longitudinal in vivo structural magnetic resonance imaging (sMRI) at postnatal day 30 (PND30) and PND70, conducted in a separate cohort of animals, revealed sex-specific differences in total and regional brain volume. Treatment-specific effects by region appeared to converge on midbrain and cerebellar structures in MAR-ASD offspring. Simultaneously, in vivo 1H magnetic resonance spectroscopy (1H-MRS) data were collected to examine brain metabolite levels in the medial prefrontal cortex. Results showed that MAR-ASD offspring displayed decreased levels of choline-containing compounds and glutathione, accompanied by increased taurine compared to control animals. Overall, we found that rats exposed to MAR-ASD aAbs present with alterations in behavior, brain structure, and neurometabolites; reminiscent of findings observed in clinical ASD.
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Affiliation(s)
- Matthew R Bruce
- Department of Internal Medicine, Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, CA, USA
| | - Amalie C M Couch
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simone Grant
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Janna McLellan
- Department of Internal Medicine, Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, CA, USA
| | - Katherine Ku
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Christina Chang
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Angelica Bachman
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Matthew Matson
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Robert F Berman
- Department of Neurological Surgery, University of California, Davis, CA, USA
- MIND Institute, University of California, Davis, CA, USA
| | - Richard J Maddock
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - Douglas Rowland
- Center for Molecular and Genomic Imaging, University of California, Davis, CA, USA
| | - Eugene Kim
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Matthew D Ponzini
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Danielle Harvey
- Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Sandra L Taylor
- Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Anthony C Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Melissa D Bauman
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
- MIND Institute, University of California, Davis, CA, USA
| | - Judy Van de Water
- Department of Internal Medicine, Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, CA, USA.
- MIND Institute, University of California, Davis, CA, USA.
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6
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Fang Q, Cai H, Jiang P, Zhao H, Song Y, Zhao W, Yu Y, Zhu J. Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder. J Affect Disord 2023; 325:522-533. [PMID: 36657492 DOI: 10.1016/j.jad.2023.01.051] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 12/30/2022] [Accepted: 01/11/2023] [Indexed: 01/18/2023]
Abstract
BACKGROUND Despite remarkable success in identifying genetic risk factors for depression, there are still open questions about the exact genetic mechanisms underlying certain disease phenotypes, such as brain structural and functional impairments. METHODS Comprehensive multi-modal neuroimaging meta-analyses were conducted to examine changes in brain structure and function in drug-naive first-episode patients with major depressive disorder (DF-MDD). Combined with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were performed to identify genes whose expression related to these brain structural and functional changes, followed by a range of gene functional signature analyses. RESULTS Meta-analyses revealed gray matter atrophy in the insula, temporal pole, cerebellum and postcentral gyrus, and a complex pattern of hyper-function in the temporal pole and hypo-function in the cuneus/precuneus, angular gyrus and lingual gyrus in DF-MDD. Moreover, these brain structural and functional changes were spatially associated with the expression of 1194 and 1733 genes, respectively. Importantly, there were commonalities and differences in the two gene sets and their functional signatures including functional enrichment, specific expression, behavioral relevance, and constructed protein-protein interaction networks. LIMITATIONS The results merit further verification using a large sample of DF-MDD. CONCLUSIONS Our findings not only corroborate the polygenic nature of depression, but also suggest common and distinct genetic modulations of brain structural and functional impairments in this disorder.
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Affiliation(s)
- Qian Fang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Ping Jiang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Han Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yu Song
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.
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7
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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: 20] [Impact Index Per Article: 20.0] [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.
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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
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8
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Li Q, Xu X, Qian Y, Cai H, Zhao W, Zhu J, Yu Y. Resting-state brain functional alterations and their genetic mechanisms in drug-naive first-episode psychosis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:13. [PMID: 36841861 PMCID: PMC9968350 DOI: 10.1038/s41537-023-00338-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 02/07/2023] [Indexed: 02/27/2023]
Abstract
Extensive research has established the presence of resting-state brain functional damage in psychosis. However, the genetic mechanisms of such disease phenotype are yet to be unveiled. We investigated resting-state brain functional alterations in patients with drug-naive first-episode psychosis (DFP) by performing a neuroimaging meta-analysis of 8 original studies comprising 500 patients and 469 controls. Combined with the Allen Human Brain Atlas, we further conducted transcriptome-neuroimaging spatial correlations to identify genes whose expression levels were linked to brain functional alterations in DFP, followed by a range of gene functional characteristic analyses. Meta-analysis revealed a mixture of increased and decreased brain function in widespread areas including the default-mode, visual, motor, striatal, and cerebellar systems in DFP. Moreover, these brain functional alterations were spatially associated with the expression of 1662 genes, which were enriched for molecular functions, cellular components, and biological processes of the cerebral cortex, as well as psychiatric disorders including schizophrenia. Specific expression analyses demonstrated that these genes were specifically expressed in the brain tissue, in cortical neurons and immune cells, and during nearly all developmental periods. Concurrently, the genes could construct a protein-protein interaction network supported by hub genes and were linked to multiple behavioral domains including emotion, attention, perception, and motor. Our findings provide empirical evidence for the notion that brain functional damage in DFP involves a complex interaction of polygenes with various functional characteristics.
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Affiliation(s)
- Qian Li
- grid.459419.4Department of Radiology, Chaohu Hospital of Anhui Medical University, 238000 Hefei, China ,grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, China ,Research Center of Clinical Medical Imaging, Anhui Province, 230032 Hefei, China ,Anhui Provincial Institute of Translational Medicine, 230032 Hefei, China
| | - Xiaotao Xu
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, China ,Research Center of Clinical Medical Imaging, Anhui Province, 230032 Hefei, China ,Anhui Provincial Institute of Translational Medicine, 230032 Hefei, China
| | - Yinfeng Qian
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, China ,Research Center of Clinical Medical Imaging, Anhui Province, 230032 Hefei, China ,Anhui Provincial Institute of Translational Medicine, 230032 Hefei, China
| | - Huanhuan Cai
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, China ,Research Center of Clinical Medical Imaging, Anhui Province, 230032 Hefei, China ,Anhui Provincial Institute of Translational Medicine, 230032 Hefei, China
| | - Wenming Zhao
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, China ,Research Center of Clinical Medical Imaging, Anhui Province, 230032 Hefei, China ,Anhui Provincial Institute of Translational Medicine, 230032 Hefei, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China. .,Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China. .,Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China. .,Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China. .,Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
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9
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Xue K, Guo L, Zhu W, Liang S, Xu Q, Ma L, Liu M, Zhang Y, Liu F. Transcriptional signatures of the cortical morphometric similarity network gradient in first-episode, treatment-naive major depressive disorder. Neuropsychopharmacology 2023; 48:518-528. [PMID: 36253546 PMCID: PMC9852427 DOI: 10.1038/s41386-022-01474-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/15/2022] [Accepted: 10/05/2022] [Indexed: 02/02/2023]
Abstract
Recent studies have shown that major depressive disorder (MDD) is accompanied by alterations in functional and structural network gradients. However, whether changes are present in the cortical morphometric similarity (MS) network gradient, and the relationship between alterations of the gradient and gene expression remains largely unknown. In this study, the MS network was constructed, and its gradient was calculated in 71 patients with first-episode, treatment-naive MDD, and 69 demographically matched healthy controls. Between-group comparisons were performed to investigate abnormalities in the MS network gradient, and partial least squares regression analysis was conducted to explore the association between gene expression profiles and MS network gradient-based alternations in MDD. We found that the gradient was primarily significantly decreased in sensorimotor regions in patients with MDD compared with healthy controls, and increased in visual-related regions. In addition, the altered principal MS network gradient in the left postcentral cortex and right lingual cortex exhibited significant correlations with symptom severity. The abnormal gradient pattern was spatially correlated with the brain-wide expression of genes enriched for neurobiologically relevant pathways, downregulated in the MDD postmortem brain, and preferentially expressed in different cell types and cortical layers. These results demonstrated alterations of the principal MS network gradient in MDD and suggested the molecular mechanisms for structural alternations underlying MDD.
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Affiliation(s)
- Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenshuang Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Sixiang Liang
- Tianjin Anding Hospital, Tianjin, 300222, China
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100088, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yong Zhang
- Tianjin Anding Hospital, Tianjin, 300222, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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10
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Sun X, Huang W, Wang J, Xu R, Zhang X, Zhou J, Zhu J, Qian Y. Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study. Psychol Med 2023; 53:1-13. [PMID: 36601814 DOI: 10.1017/s0033291722003750] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD. METHODS To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses. RESULTS We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance. CONCLUSIONS Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.
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Affiliation(s)
- Xuetian Sun
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Weisheng Huang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jie Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Ruoxuan Xu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Xiaohan Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jianhui Zhou
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
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11
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Li Z, Li D, He Y, Wang K, Ma X, Chen X. Cross-Disorder Analysis of Shared Genetic Components Between Cortical Structures and Major Psychiatric Disorders. Schizophr Bull 2022; 48:1145-1154. [PMID: 35265999 PMCID: PMC9434450 DOI: 10.1093/schbul/sbac019] [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] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Although large-scale neuroimaging studies have demonstrated similar patterns of structural brain abnormalities across major psychiatric disorders, the underlying genetic etiology behind these similar cross-disorder patterns is not well understood. STUDY DESIGN We quantified the extent of shared genetic components between cortical structures and major psychiatric disorders (CS-MPD) by using genome-wide association study (GWAS) summary statistics of 70 cortical structures (surface area and thickness of the whole cortex and 34 cortical regions) and five major psychiatric disorders, consisting of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-disorder analyses were then conducted to estimate the degree of similarity in CS-MPD shared genetic components among these disorders. STUDY RESULTS The CS-MPD shared genetic components have medium-to-strong positive correlations in ADHD, BD, MDD, and SCZ (r = 0.415 to r = 0.806) while ASD was significantly correlated with ADHD, BD, and SCZ (r = 0.388 to r = 0.403). These pairwise correlations of CS-MPD shared genetic components among disorders were significantly associated with corresponding cross-disorder similarities in cortical structural abnormalities (r = 0.668), accounting for 44% variance. In addition, one latent shared factor consisted primarily of BD, MDD, and SCZ, explaining 62.47% of the total variance in CS-MPD shared genetic components of all disorders. CONCLUSIONS The current results bridge the gap between shared cross-disorder heritability and shared structural brain abnormalities in major psychiatric disorders, providing important implications for a shared genetic basis of cortical structures in these disorders.
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Affiliation(s)
- Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - David Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, PR China
| | - Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
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12
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Berto S, Treacher AH, Caglayan E, Luo D, Haney JR, Gandal MJ, Geschwind DH, Montillo AA, Konopka G. Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder. Nat Commun 2022; 13:3328. [PMID: 35680911 PMCID: PMC9184501 DOI: 10.1038/s41467-022-31053-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/13/2022] [Indexed: 12/13/2022] Open
Abstract
Gene expression covaries with brain activity as measured by resting state functional magnetic resonance imaging (MRI). However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate from the ABIDE I and II imaging cohorts with datasets of gene expression in brains of neurotypical individuals and individuals with autism spectrum disorder (ASD) with regionally matched brain activity measurements from fMRI datasets. We identify genes linked with brain activity whose association is disrupted in ASD. We identified a subset of genes that showed a differential developmental trajectory in individuals with ASD compared with controls. These genes are enriched in voltage-gated ion channels and inhibitory neurons, pointing to excitation-inhibition imbalance in ASD. We further assessed differences at the regional level showing that the primary visual cortex is the most affected region in ASD. Our results link disrupted brain expression patterns of individuals with ASD to brain activity and show developmental, cell type, and regional enrichment of activity linked genes. Gene expression patterns have been associated with functional activity patterns in the brain. Here the authors determine how gene expression patterns in the human brain supports brain phenotypes obtained from resting state fMRI imaging, identifying brain regions and genes relevant to autism.
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Affiliation(s)
- Stefano Berto
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Alex H Treacher
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Emre Caglayan
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Danni Luo
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jillian R Haney
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Michael J Gandal
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Daniel H Geschwind
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Albert A Montillo
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA. .,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA. .,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
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13
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Xie Y, Xu Z, Xia M, Liu J, Shou X, Cui Z, Liao X, He Y. Alterations in Connectome Dynamics in Autism Spectrum Disorder: A Harmonized Mega- and Meta-analysis Study Using the Autism Brain Imaging Data Exchange Dataset. Biol Psychiatry 2022; 91:945-955. [PMID: 35144804 DOI: 10.1016/j.biopsych.2021.12.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/22/2021] [Accepted: 12/07/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Neuroimaging studies have reported functional connectome aberrancies in autism spectrum disorder (ASD). However, the time-varying patterns of connectome topology in individuals with ASD and the connection between these patterns and gene expression profiles remain unknown. METHODS To investigate case-control differences in dynamic connectome topology, we conducted mega- and meta-analyses of resting-state functional magnetic resonance imaging data of 939 participants (440 patients with ASD and 499 healthy control subjects, all males) from 18 independent sites, selected from the Autism Brain Imaging Data Exchange (ABIDE) dataset. Functional data were preprocessed and analyzed using harmonized protocols, and brain module dynamics was assessed using a multilayer network model. We further leveraged postmortem brain-wide gene expression data to identify transcriptomic signatures associated with ASD-related alterations in brain dynamics. RESULTS Compared with healthy control participants, individuals with ASD exhibited a higher global mean and lower standard deviation of whole-brain module dynamics, indicating an unstable and less regionally differentiated pattern. More specifically, individuals with ASD showed higher module switching, primarily in the medial prefrontal cortex, posterior cingulate gyrus, and angular gyrus, and lower switching in the visual regions. These alterations in brain dynamics were predictive of social impairments in individuals with ASD and were linked with expression profiles of genes primarily involved in the regulation of neurotransmitter transport and secretion as well as with previously identified autism-related genes. CONCLUSIONS This study is the first to identify consistent alterations in brain network dynamics in ASD and the transcriptomic signatures related to those alterations, furthering insights into the biological basis behind this disorder.
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Affiliation(s)
- Yapei Xie
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jin Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaojing Shou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Xuhong Liao
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; School of Systems Science, Beijing Normal University, Beijing, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
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14
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Wang Z, Ji Y, Fu Y, Liu F, Du X, Liu H, Zhu W, Xue K, Qin W, Zhang Q. Gene expression associated with human brain activations in facial expression recognition. Brain Imaging Behav 2022; 16:1657-1670. [PMID: 35212890 DOI: 10.1007/s11682-022-00633-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2022] [Indexed: 11/30/2022]
Abstract
Previous studies identified some genetic loci of emotion, but few focused on human emotion-related gene expression. In this study, the facial expression recognition (FER) task-based high-resolution fMRI data of 203 subjects in the Human Connectome Project (HCP) and expression data of the six healthy human postmortem brain tissues in the Allen Human Brain Atlas (AHBA) were used to conduct a transcriptome-neuroimaging spatial association analysis. Finally, 371 genes were identified to be significantly associated with FER-related brain activations. Enrichment analyses revealed that FER-related genes were mainly expressed in the brain, especially neurons, and might be related to cell junction organization, synaptic functions, and nervous system development regulation, indicating that FER was a complex polygenetic biological process involving multiple pathways. Moreover, these genes exhibited higher enrichment for psychiatric diseases with heavy emotion impairments. This study provided new insight into understanding the FER-related biological mechanisms and might be helpful to explore treatment methods for emotion-related psychiatric disorders.
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Affiliation(s)
- Zirui Wang
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yuan Ji
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yumeng Fu
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Feng Liu
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Xin Du
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Huaigui Liu
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Wenshuang Zhu
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Kaizhong Xue
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Wen Qin
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Quan Zhang
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
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15
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Arnatkeviciute A, Fulcher BD, Bellgrove MA, Fornito A. Imaging Transcriptomics of Brain Disorders. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:319-331. [PMID: 36324650 PMCID: PMC9616271 DOI: 10.1016/j.bpsgos.2021.10.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/06/2021] [Accepted: 10/11/2021] [Indexed: 01/05/2023] Open
Abstract
Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.
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Affiliation(s)
- Aurina Arnatkeviciute
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
- Address correspondence to Aurina Arnatkeviciute, Ph.D
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Camperdown, New South Wales, Australia
| | - Mark A. Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
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16
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Abstract
PURPOSE OF REVIEW The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data. RECENT FINDINGS Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks. SUMMARY New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.
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Affiliation(s)
- Ibai Diez
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
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