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Wang H, Zhao Q, Zhang Y, Ma J, Lei M, Zhang Z, Xue H, Liu J, Sun Z, Xu J, Zhai Y, Wang Y, Cai M, Zhu W, Liu F. Shared genetic architecture of cortical thickness alterations in major depressive disorder and schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111121. [PMID: 39154931 DOI: 10.1016/j.pnpbp.2024.111121] [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: 05/28/2024] [Revised: 07/29/2024] [Accepted: 08/15/2024] [Indexed: 08/20/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) and schizophrenia (SCZ) are heritable brain disorders characterized by alterations in cortical thickness. However, the shared genetic basis for cortical thickness changes in these disorders remains unclear. METHODS We conducted a systematic literature search on cortical thickness in MDD and SCZ through PubMed and Web of Science. A coordinate-based meta-analysis was performed to identify cortical thickness changes. Additionally, utilizing summary statistics from the largest genome-wide association studies for depression (Ncase = 268,615, Ncontrol = 667,123) and SCZ (Ncase = 53,386, Ncontrol = 77,258), we explored shared genomic loci using conjunctional false discovery rate (conjFDR) analysis. Transcriptome-neuroimaging association analysis was then employed to identify shared genes associated with cortical thickness alterations, and enrichment analysis was finally carried out to elucidate the biological significance of these genes. RESULTS Our search yielded 34 MDD (Ncase = 1621, Ncontrol = 1507) and 19 SCZ (Ncase = 1170, Ncontrol = 1043) neuroimaging studies for cortical thickness meta-analysis. Specific alterations in the left supplementary motor area were observed in MDD, while SCZ exhibited widespread reductions in various brain regions, particularly in the frontal and temporal areas. The conjFDR approach identified 357 genomic loci jointly associated with MDD and SCZ. Within these loci, 55 genes were found to be associated with cortical thickness alterations in both disorders. Enrichment analysis revealed their involvement in nervous system development, apoptosis, and cell communication. CONCLUSION This study revealed the shared genetic architecture underlying cortical thickness alterations in MDD and SCZ, providing insights into common neurobiological pathways. The identified genes and pathways may serve as potential transdiagnostic markers, informing precision medicine approaches in psychiatric care.
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Affiliation(s)
- He Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Qiyu Zhao
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yijing Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Juanwei Ma
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Minghuan Lei
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhihui Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hui Xue
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiawei Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zuhao Sun
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jinglei Xu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ying Zhai
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ying Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Mengjing Cai
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China; Department of Medical Imaging, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou 450000, China.
| | - Wenshuang Zhu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China; Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
| | - Feng Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
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Peng Y, Chai C, Xue K, Tang J, Wang S, Su Q, Liao C, Zhao G, Wang S, Zhang N, Zhang Z, Lei M, Liu F, Liang M. Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study. CNS Neurosci Ther 2024; 30:e14906. [PMID: 39118226 PMCID: PMC11310100 DOI: 10.1111/cns.14906] [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: 01/06/2024] [Revised: 07/09/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024] Open
Abstract
AIMS Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia. METHODS A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia. RESULTS The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity. CONCLUSIONS This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.
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Affiliation(s)
- Yanmin Peng
- School of Medical Imaging and Tianjin Key Laboratory of Functional ImagingTianjin Medical UniversityTianjinChina
| | - Chao Chai
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
- Department of Radiology, School of Medicine, Tianjin First Central HospitalNankai UniversityTianjinChina
| | - Kaizhong Xue
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jie Tang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Sijia Wang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Qian Su
- Department of Molecular Imaging and Nuclear MedicineTianjin Medical University Cancer Institute and HospitalTianjinChina
| | - Chongjian Liao
- School of Medical Imaging and Tianjin Key Laboratory of Functional ImagingTianjin Medical UniversityTianjinChina
| | - Guoshu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Nannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Minghuan Lei
- 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
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional ImagingTianjin Medical UniversityTianjinChina
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Sun H, Bai T, Zhang X, Fan X, Zhang K, Zhang J, Hu Q, Xu J, Tian Y, Wang K. Molecular mechanisms underlying structural plasticity of electroconvulsive therapy in major depressive disorder. Brain Imaging Behav 2024; 18:930-941. [PMID: 38664360 DOI: 10.1007/s11682-024-00884-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/11/2024] [Indexed: 08/31/2024]
Abstract
Although previous studies reported structural changes associated with electroconvulsive therapy (ECT) in major depressive disorder (MDD), the underlying molecular basis of ECT remains largely unknown. Here, we combined two independent structural MRI datasets of MDD patients receiving ECT and transcriptomic gene expression data from Allen Human Brain Atlas to reveal the molecular basis of ECT for MDD. We performed partial least square regression to explore whether/how gray matter volume (GMV) alterations were associated with gene expression level. Functional enrichment analysis was conducted using Metascape to explore ontological pathways of the associated genes. Finally, these genes were further assigned to seven cell types to determine which cell types contribute most to the structural changes in MDD patients after ECT. We found significantly increased GMV in bilateral hippocampus in MDD patients after ECT. Transcriptome-neuroimaging association analyses showed that expression levels of 726 genes were positively correlated with the increased GMV in MDD after ECT. These genes were mainly involved in synaptic signaling, calcium ion binding and cell-cell signaling, and mostly belonged to excitatory and inhibitory neurons. Moreover, we found that the MDD risk genes of CNR1, HTR1A, MAOA, PDE1A, and SST as well as ECT related genes of BDNF, DRD2, APOE, P2RX7, and TBC1D14 showed significantly positive associations with increased GMV. Overall, our findings provide biological and molecular mechanisms underlying structural plasticity induced by ECT in MDD and the identified genes may facilitate future therapy for MDD.
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Affiliation(s)
- Hui Sun
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tongjian Bai
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei, 230022, China
| | - Xiaodong Zhang
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Xinxin Fan
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Kai Zhang
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Qingmao Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Yanghua Tian
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei, 230022, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230022, China.
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China.
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230022, China.
- Department of Neurology, the Second Hospital of Anhui Medical University, Hefei, 230022, China.
| | - Kai Wang
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei, 230022, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230022, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, 230022, China
- Anhui Province clinical research center for neurological disease, Hefei, 230022, China
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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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5
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Jiang Y, Zhou Y, Xie Y, Zhou J, Cai M, Tang J, Liu F, Ma J, Liu H. Functional magnetic resonance imaging alternations in suicide attempts individuals and their association with gene expression. Neuroimage Clin 2024; 43:103645. [PMID: 39059208 PMCID: PMC11326948 DOI: 10.1016/j.nicl.2024.103645] [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: 05/27/2024] [Revised: 06/29/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024]
Abstract
BACKGROUND Functional Magnetic Resonance Imaging (fMRI) has shown brain activity alterations in individuals with a history of attempted suicide (SA) who are diagnosed with depression disorder (DD) or bipolar disorder (BD). However, patterns of spontaneous brain activity and their genetic correlations need further investigation. METHODS A voxel-based meta-analysis of 19 studies including 26 datasets, involving 742 patients with a history of SA and 978 controls (both nonsuicidal patients and healthy controls) was conducted. We examined fMRI changes in SA patients and analyzed the association between these changes and gene expression profiles using data from the Allen Human Brain Atlas by partial least squares regression analysis. RESULTS SA patients demonstrated increased spontaneous brain activity in several brain regions including the bilateral inferior temporal gyrus, hippocampus, fusiform gyrus, and right insula, and decreased activity in areas like the bilateral paracentral lobule and inferior frontal gyrus. Additionally, 5,077 genes were identified, exhibiting expression patterns associated with SA-related fMRI alterations. Functional enrichment analyses demonstrated that these SA-related genes were enriched for biological functions including glutamatergic synapse and mitochondrial structure. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons cells, and during early developmental periods. CONCLUSION Our findings suggest a neurobiological basis for fMRI abnormalities in SA patients with DD or BD, potentially guiding future genetic and therapeutic research.
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Affiliation(s)
- Yurong Jiang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yujing Zhou
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, 116000 Dalian, Liaoning, China
| | - Yingying Xie
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Junzi Zhou
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Mengjing Cai
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jie Tang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Feng Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Juanwei Ma
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Huaigui Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
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Almodóvar-Payá C, Guardiola-Ripoll M, Giralt-López M, Oscoz-Irurozqui M, Canales-Rodríguez EJ, Madre M, Soler-Vidal J, Ramiro N, Callado LF, Arias B, Gallego C, Pomarol-Clotet E, Fatjó-Vilas M. NRN1 epistasis with BDNF and CACNA1C: mediation effects on symptom severity through neuroanatomical changes in schizophrenia. Brain Struct Funct 2024; 229:1299-1315. [PMID: 38720004 PMCID: PMC11147852 DOI: 10.1007/s00429-024-02793-5] [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: 12/27/2023] [Accepted: 03/19/2024] [Indexed: 06/05/2024]
Abstract
The expression of Neuritin-1 (NRN1), a neurotrophic factor crucial for neurodevelopment and synaptic plasticity, is enhanced by the Brain Derived Neurotrophic Factor (BDNF). Although the receptor of NRN1 remains unclear, it is suggested that NRN1's activation of the insulin receptor (IR) pathway promotes the transcription of the calcium voltage-gated channel subunit alpha1 C (CACNA1C). These three genes have been independently associated with schizophrenia (SZ) risk, symptomatology, and brain differences. However, research on how they synergistically modulate these phenotypes is scarce. We aimed to study whether the genetic epistasis between these genes affects the risk and clinical presentation of the disorder via its effect on brain structure. First, we tested the epistatic effect of NRN1 and BDNF or CACNA1C on (i) the risk for SZ, (ii) clinical symptoms severity and functionality (onset, PANSS, CGI and GAF), and (iii) brain cortical structure (thickness, surface area and volume measures estimated using FreeSurfer) in a sample of 86 SZ patients and 89 healthy subjects. Second, we explored whether those brain clusters influenced by epistatic effects mediate the clinical profiles. Although we did not find a direct epistatic impact on the risk, our data unveiled significant effects on the disorder's clinical presentation. Specifically, the NRN1-rs10484320 x BDNF-rs6265 interplay influenced PANSS general psychopathology, and the NRN1-rs4960155 x CACNA1C-rs1006737 interaction affected GAF scores. Moreover, several interactions between NRN1 SNPs and BDNF-rs6265 significantly influenced the surface area and cortical volume of the frontal, parietal, and temporal brain regions within patients. The NRN1-rs10484320 x BDNF-rs6265 epistasis in the left lateral orbitofrontal cortex fully mediated the effect on PANSS general psychopathology. Our study not only adds clinical significance to the well-described molecular relationship between NRN1 and BDNF but also underscores the utility of deconstructing SZ into biologically validated brain-imaging markers to explore their mediation role in the path from genetics to complex clinical manifestation.
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Affiliation(s)
- Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERER (Biomedical Research Network in Rare Diseases), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria Giralt-López
- Department of Child and Adolescent Psychiatry, Germans Trias i Pujol University Hospital (HUGTP), Barcelona, Spain
- Department of Psychiatry and Legal Medicine, Faculty of Medicine, Autonomous University of Barcelona (UAB), Barcelona, Spain
| | - Maitane Oscoz-Irurozqui
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Red de Salud Mental de Gipuzkoa, Osakidetza-Basque Health Service, Gipuzkoa, Spain
| | - Erick Jorge Canales-Rodríguez
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mercè Madre
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Mental Health, IR SANT PAU, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma Barcelona, Barcelona, Spain
| | - Joan Soler-Vidal
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
- Hospital Benito Menni, Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain
| | - Núria Ramiro
- Hospital San Rafael, Germanes Hospitalàries, Barcelona, Spain
| | - Luis F Callado
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
- Department of Pharmacology, University of the Basque Country (UPV/EHU), Bizkaia, Spain
- BioBizkaia Health Research Institute, Bizkaia, Spain
| | - Bárbara Arias
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain
| | - Carme Gallego
- Department of Cells and Tissues, Molecular Biology Institute of Barcelona (IBMB-CSIC), Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain.
- CIBERSAM (Biomedical Research Network in Mental Health), Instituto de Salud Carlos III, Madrid, Spain.
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Cai M, Ji Y, Zhao Q, Xue H, Sun Z, Wang H, Zhang Y, Chen Y, Zhao Y, Zhang Y, Lei M, Wang C, Zhuo C, Liu N, Liu H, Liu F. Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression. Neuroimage 2024; 289:120551. [PMID: 38382862 DOI: 10.1016/j.neuroimage.2024.120551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/18/2024] [Accepted: 02/19/2024] [Indexed: 02/23/2024] Open
Abstract
It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.
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Affiliation(s)
- Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - He Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yijing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yao Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yujie Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Chunyang Wang
- Department of Scientific Research, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Chuanjun Zhuo
- Laboratory of Psychiatric-Neuroimaging-Genetic and Co-morbidity (PGNP_Lab), Tianjin Anding Hospital, Nankai University Affiliated Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, 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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8
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Wang M, Zhao SW, Wu D, Zhang YH, Han YK, Zhao K, Qi T, Liu Y, Cui LB, Wei Y. Transcriptomic and neuroimaging data integration enhances machine learning classification of schizophrenia. PSYCHORADIOLOGY 2024; 4:kkae005. [PMID: 38694267 PMCID: PMC11061866 DOI: 10.1093/psyrad/kkae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/26/2024] [Accepted: 03/25/2024] [Indexed: 05/04/2024]
Abstract
Background Schizophrenia is a polygenic disorder associated with changes in brain structure and function. Integrating macroscale brain features with microscale genetic data may provide a more complete overview of the disease etiology and may serve as potential diagnostic markers for schizophrenia. Objective We aim to systematically evaluate the impact of multi-scale neuroimaging and transcriptomic data fusion in schizophrenia classification models. Methods We collected brain imaging data and blood RNA sequencing data from 43 patients with schizophrenia and 60 age- and gender-matched healthy controls, and we extracted multi-omics features of macroscale brain morphology, brain structural and functional connectivity, and gene transcription of schizophrenia risk genes. Multi-scale data fusion was performed using a machine learning integration framework, together with several conventional machine learning methods and neural networks for patient classification. Results We found that multi-omics data fusion in conventional machine learning models achieved the highest accuracy (AUC ~0.76-0.92) in contrast to the single-modality models, with AUC improvements of 8.88 to 22.64%. Similar findings were observed for the neural network, showing an increase of 16.57% for the multimodal classification model (accuracy 71.43%) compared to the single-modal average. In addition, we identified several brain regions in the left posterior cingulate and right frontal pole that made a major contribution to disease classification. Conclusion We provide empirical evidence for the increased accuracy achieved by imaging genetic data integration in schizophrenia classification. Multi-scale data fusion holds promise for enhancing diagnostic precision, facilitating early detection and personalizing treatment regimens in schizophrenia.
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Affiliation(s)
- Mengya Wang
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
| | - Shu-Wan Zhao
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
- Schizophrenia Imaging Lab, Xijing 986 Hospital, Fourth Military Medical University, Xi'an, 710054, China
| | - Di Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xi'an Gaoxin Hospital, Xi'an, 710075, China
| | - Yan-Kun Han
- Schizophrenia Imaging Lab, Xijing 986 Hospital, Fourth Military Medical University, Xi'an, 710054, China
| | - Kun Zhao
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
| | - Ting Qi
- Department of Neurology, School of Medicine, University of California San Francisco, San Francisco, 94143, California
| | - Yong Liu
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
| | - Long-Biao Cui
- Schizophrenia Imaging Lab, Xijing 986 Hospital, Fourth Military Medical University, Xi'an, 710054, China
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, 710032, China
| | - Yongbin Wei
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
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9
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Ji Y, Cai M, Zhou Y, Ma J, Zhang Y, Zhang Z, Zhao J, Wang Y, Jiang Y, Zhai Y, Xu J, Lei M, Xu Q, Liu H, Liu F. Exploring functional dysconnectivity in schizophrenia: alterations in eigenvector centrality mapping and insights into related genes from transcriptional profiles. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:37. [PMID: 38491019 PMCID: PMC10943118 DOI: 10.1038/s41537-024-00457-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/05/2024] [Indexed: 03/18/2024]
Abstract
Schizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data. A cohort of 91 patients with schizophrenia and 91 matched healthy controls were included during the discovery stage. Additionally, in the replication stage, 153 individuals with schizophrenia and 182 healthy individuals participated. Subsequently, a comprehensive analysis was performed using an independent transcriptional database derived from six postmortem healthy adult brains to explore potential genetic factors influencing the observed functional dysconnectivity, and to investigate the roles of identified genes in neural processes and pathways. The results revealed significant and reliable alterations in the ECM across multiple brain regions in schizophrenia. Specifically, there was a significant decrease in ECM in the bilateral superior and middle temporal gyrus, and an increase in the bilateral thalamus in both the discovery and replication stages. Furthermore, transcriptional analysis revealed 420 genes whose expression patterns were related to changes in ECM, and these genes were enriched mainly in biological processes associated with synaptic signaling and transmission. Together, this study enhances our knowledge of the neural processes and pathways involved in schizophrenia, shedding light on the genetic factors that may be linked to functional dysconnectivity in this disorder.
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Affiliation(s)
- Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yujing Zhou
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Juanwei Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yijing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiaxuan Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Ying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yurong Jiang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Ying Zhai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jinglei Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
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10
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Wang Y, Xiao Y, Xing Y, Yu M, Wang X, Ren J, Liu W, Zhong Y. Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures. CNS Neurosci Ther 2024; 30:e14680. [PMID: 38529533 PMCID: PMC10964038 DOI: 10.1111/cns.14680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear. OBJECTIVE This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates. METHODS The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes. RESULTS Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development. CONCLUSIONS These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.
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Affiliation(s)
- Yajie Wang
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
- Department of NeurologyThe First People's Hospital of YanchengYanchengChina
| | - Yiwen Xiao
- School of PsychologyNanjing Normal UniversityNanjingChina
| | - Yi Xing
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Miao Yu
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiao Wang
- Department of RadiologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Jingru Ren
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Weiguo Liu
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yuan Zhong
- School of PsychologyNanjing Normal UniversityNanjingChina
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11
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Zhou C, Tang X, Yu M, Zhang H, Zhang X, Gao J, Zhang X, Chen J. Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia. Transl Psychiatry 2024; 14:124. [PMID: 38413564 PMCID: PMC10899251 DOI: 10.1038/s41398-024-02827-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: 07/19/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.
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Affiliation(s)
- Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaowei Tang
- Department of Psychiatry, Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou, Jiangsu, China
| | - Miao Yu
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongying Zhang
- Department of Radiology, Subei People's Hospital of Jiangsu Province, Yangzhou University, Yangzhou, Jiangsu, China
| | - Xiaobin Zhang
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Ju Gao
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China.
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
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12
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Gui W, Lu F, Fu L, Deng Z, Zhao X, Cheng W, Yang Y, Wang Y. Genetic mechanisms underlying local spontaneous brain activity in episodic migraine. Front Neurosci 2024; 18:1348591. [PMID: 38379763 PMCID: PMC10876778 DOI: 10.3389/fnins.2024.1348591] [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: 12/03/2023] [Accepted: 01/17/2024] [Indexed: 02/22/2024] Open
Abstract
Advances in neuroimaging techniques during the past few decades have captured impaired functional brain activity in migraine disorders, yet the molecular mechanisms accounting for its alterations in migraine remain largely unknown. A total of 27 patients with episodic migraine (EM) and 30 matched healthy controls (HCs) underwent resting-state functional and structural magnetic resonance imaging (MRI) scans. Regional homogeneity (ReHo), low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) of fMRI were compared between the two groups. Based on the Allen Human Brain Atlas and risk genes in migraine, we identified gene expression profiles associated with ReHo alterations in EM. Compared with HCs, patients with EM showed increased ReHo in the left orbital part of the superior frontal gyrus (P < 0.05, cluster-level FWE-corrected). The expression profiles of 16 genes were significantly correlated with ReHo alterations in EM (P < 0.05/5,013, Bonferroni corrected). These genes were mainly enriched for transcription regulation, synaptic transmission, energy metabolism, and migraine disorders. Furthermore, the neural activation was positively correlated with Hamilton Rating Scale for Anxiety (HAMA) scores. To test the stability of our results, we repeated our procedure by using ALFF and fALFF and found these results had a high degree of consistency. Overall, these findings not only demonstrated that regional brain activity was increased in patients with EM, which was associated with emotional regulation but also provided new insights into the genetic mechanisms underlying these changes in migraine.
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Affiliation(s)
- Wei Gui
- Department of Neurology, Epilepsy and Headache Group, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Fengqing Lu
- Department of Neurology, Epilepsy and Headache Group, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lulan Fu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Ziru Deng
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiuxiu Zhao
- Anhui Provincial Stereotactic Neurosurgical Institute, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China, Hefei, China
| | - Wenwen Cheng
- Anhui Provincial Stereotactic Neurosurgical Institute, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China, Hefei, China
| | - Ying Yang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China, Hefei, China
| | - Yu Wang
- Department of Neurology, Epilepsy and Headache Group, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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13
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Zheng J, Womer FY, Tang L, Guo H, Zhang X, Tang Y, Wang F. Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorder. Transl Psychiatry 2024; 14:17. [PMID: 38195555 PMCID: PMC10776753 DOI: 10.1038/s41398-023-02724-8] [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: 10/09/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024] Open
Abstract
Several lines of evidence support the involvement of transcriptomic and epigenetic mechanisms in the brain structural deficits of major depressive disorder (MDD) separately. However, research in these two areas has remained isolated. In this study, we proposed an integrative strategy that combined neuroimaging, brain-wide gene expression, and peripheral DNA methylation data to investigate the genetic basis of gray matter abnormalities in MDD. The MRI T1-weighted images and Illumina 850 K DNA methylation microarrays were obtained from 269 patients and 416 healthy controls, and brain-wide transcriptomic data were collected from Allen Human Brain Atlas. The between-group differences in gray matter volume (GMV) and differentially methylated CpG positions (DMPs) were examined. The genes with their expression patterns spatially related to GMV changes and genes with DMPs were overlapped and selected. Using principal component regression, the associations between DMPs in overlapped genes and GMV across individual patients were investigated, and the region-specific correlations between methylation status and gene expression were examined. We found significant associations between the decreased GMV and DMPs methylation status in the anterior cingulate cortex, inferior frontal cortex, and fusiform face cortex regions. These DMPs genes were primarily enriched in the neurodevelopmental and synaptic transmission process. There was a significant negative correlation between DNA methylation and gene expression in genes associated with GMV changes of the frontal cortex in MDD. Our findings suggest that GMV abnormalities in MDD may have a transcriptomic and epigenetic basis. This imaging-transcriptomic-epigenetic integrative analysis provides spatial and biological links between cortical morphological deficits and peripheral epigenetic signatures in MDD.
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Affiliation(s)
- Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China.
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China.
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, China.
- Shengjing Hospital of China Medical University, Shenyang, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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14
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Li B, Lin Y, Ren C, Cheng J, Zhang Y, Han S. Gray matter volume abnormalities in obsessive-compulsive disorder correlate with molecular and transcriptional profiles. J Affect Disord 2024; 344:182-190. [PMID: 37838261 DOI: 10.1016/j.jad.2023.10.076] [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: 07/07/2023] [Revised: 09/17/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023]
Abstract
Neuroimaging studies have consistently established altered brain structure in obsessive-compulsive disorder (OCD). However, the molecular and genetic mechanisms underlying structural brain abnormalities remain unclear. In this study, we aimed to investigate altered gray matter volume and its underlying molecular and genetic mechanisms in patients with OCD. Gray matter morphological abnormalities measured with voxel based morphometry analysis were identified in patients with OCD in comparison to sex- and age-matched healthy controls (HCs). Spatial correlations between gray matter morphological abnormalities and neurotransmitter maps were calculated to identify neurotransmitters relating to structural abnormalities. Structural abnormalities related genes were identified by conducting transcriptome-neuroimaging spatial correlations. Compared with HCs, patients with OCD demonstrated significant morphological abnormalities in distributed brain areas, including gray matter atrophy in the anterior cingulate and increased gray matter volume in the thalamus, caudate and precentral and postcentral gyrus. The morphological abnormalities were significantly associated with dopamine synthesis capacity and expression profiles of 1110 genes enriched for trans-synaptic signaling, regulation of membrane potential, modulation of chemical synaptic transmission, brain development, synapse organization and regulation of neurotransmitter levels. These results elucidate the molecular and transcriptional basis of altered gray matter morphology and build linking between molecular, transcriptional and neuroimaging information facilitating an integrative understanding of OCD.
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Affiliation(s)
- Beibei Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Yanan Lin
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Cuiping Ren
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
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15
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Guo L, Ma J, Cai M, Zhang M, Xu Q, Wang H, Zhang Y, Yao J, Sun Z, Chen Y, Xue H, Zhang Y, Wang S, Xue K, Zhu D, Liu F. Transcriptional signatures of the whole-brain voxel-wise resting-state functional network centrality alterations in schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:87. [PMID: 38104130 PMCID: PMC10725456 DOI: 10.1038/s41537-023-00422-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023]
Abstract
Neuroimaging studies have revealed that patients with schizophrenia exhibit disrupted resting-state functional connectivity. However, the inconsistent findings across these studies have hindered our comprehensive understanding of the functional connectivity changes associated with schizophrenia, and the molecular mechanisms associated with these alterations remain largely unclear. A quantitative meta-analysis was first conducted on 21 datasets, involving 1057 patients and 1186 healthy controls, to examine disrupted resting-state functional connectivity in schizophrenia, as measured by whole-brain voxel-wise functional network centrality (FNC). Subsequently, partial least squares regression analysis was employed to investigate the relationship between FNC changes and gene expression profiles obtained from the Allen Human Brain Atlas database. Finally, gene enrichment analysis was performed to unveil the biological significance of the altered FNC-related genes. Compared with healthy controls, patients with schizophrenia show consistently increased FNC in the right inferior parietal cortex extending to the supramarginal gyrus, angular gyrus, bilateral medial prefrontal cortex, and right dorsolateral prefrontal cortex, while decreased FNC in the bilateral insula, bilateral postcentral gyrus, and right inferior temporal gyrus. Meta-regression analysis revealed that increased FNC in the right inferior parietal cortex was positively correlated with clinical score. In addition, these observed functional connectivity changes were found to be spatially associated with the brain-wide expression of specific genes, which were enriched in diverse biological pathways and cell types. These findings highlight the aberrant functional connectivity observed in schizophrenia and its potential molecular underpinnings, providing valuable insights into the neuropathology of dysconnectivity associated with this disorder.
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Affiliation(s)
- Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Juanwei Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Minghui Zhang
- Department of Ultrasound, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - He Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yijing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jia Yao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yujie Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
| | - Dan Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
- Department of Radiology, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
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16
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Guo X, Li J, Su Q, Song J, Cheng C, Chu X, Zhao R. Transcriptional correlates of frequency-dependent brain functional activity associated with symptom severity in degenerative cervical myelopathy. Neuroimage 2023; 284:120451. [PMID: 37949259 DOI: 10.1016/j.neuroimage.2023.120451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Neuroimaging techniques provide insights into the brain abnormalities secondary to degenerative cervical myelopathy (DCM) and their association with neurological deficits. However, the neural correlates underlying the discrepancy between symptom severity and the degree of spinal cord compression, as well as the transcriptional correlates of these cortical abnormalities, remain unknown in DCM patients. METHODS In this cross-sectional study, which collected resting-state functional MRI (rs-fMRI) images and the Japanese Orthopedic Association (JOA) score, enrolled 104 participants (54 patients and 50 healthy controls). The frequency-dependent amplitude of low-frequency fluctuation (ALFF) was obtained for all participants. We investigated the ALFF differences between mild-symptom DCM patients and severe-symptom DCM patients while carefully matching the degree of compression between these two groups via both univariate comparison and searchlight classification for three frequency bands (e.g., Slow-4, Slow-5, and Full-band). Additionally, we identified genes associated with symptom severity in DCM patients by linking the spatial patterns of gene expression of Allen Human Brain Atlas and brain functional differences between mild symptom and severe symptom groups. RESULTS (1) We found that the frequency-specific brain activities within the sensorimotor network (SMN), visual network (VN), and default mode network (DMN) were associated with the varying degrees of functional impairment in DCM patients; (2) the frequency-specific brain activity within the SMN correlated with the functional recovery in patients with DCM; (3) a spatial correlation between the brain-wide expression of genes involved in neuronal migration and the brain functional activities associated with symptom severity was identified in DCM patients. CONCLUSION In conclusion, our study bridges gaps between genes, cell classes, biological processes, and brain functional correlates of DCM. While our findings are correlational in nature, they suggest that the neural activities of sensorimotor cortices in DCM are associated with the severity of symptoms and might be associated with neuronal migration within the brain.
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Affiliation(s)
- Xing Guo
- Department of Orthopedic, Cangzhou Central Hospital, Cangzhou, Hebei 061017, China
| | - Jie Li
- Department of Orthopedic, Cangzhou Central Hospital, Cangzhou, Hebei 061017, China; Department of Minimally Invasive Spine Surgery, Tianjin Hospital, Tianjin 300211, China
| | - Qian Su
- Department of Orthopedic, Cangzhou Central Hospital, Cangzhou, Hebei 061017, China; Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for China, Tianjin 300060, China
| | - Jiajun Song
- Department of Orthopedics Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Cai Cheng
- Department of Orthopedic, Cangzhou Central Hospital, Cangzhou, Hebei 061017, China.
| | - Xu Chu
- Department of Shoulder and Elbow of Sports Medicine, Honghui Hospital, Xi'an Jiaotong University, Xi'an 710054, China.
| | - Rui Zhao
- Department of Orthopedics Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China.
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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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18
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Chai C, Ding H, Du X, Xie Y, Man W, Zhang Y, Ji Y, Liang M, Zhang B, Ning Y, Zhuo C, Yu C, Qin W. Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia. Eur Psychiatry 2023; 66:e78. [PMID: 37702075 PMCID: PMC10594537 DOI: 10.1192/j.eurpsy.2023.2446] [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: 10/31/2022] [Revised: 05/20/2023] [Accepted: 08/01/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated. METHODS A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively. RESULTS Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western). CONCLUSIONS These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.
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Affiliation(s)
- Chao Chai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Xiaotong Du
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Weiqi Man
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Yu Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yi Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Bin Zhang
- Department of Psychiatry, Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chuanjun Zhuo
- Department of Psychiatry, Tianjin Fourth Center Hospital, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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19
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Liu XF, Zhao SW, Cui JJ, Gu YW, Fan JW, Fu YF, Zhang YH, Yin H, Chen K, Cui LB. Differential expression of diacylglycerol kinase ζ is involved in inferior parietal lobule-related dysfunction in schizophrenia with cognitive impairments. BMC Psychiatry 2023; 23:526. [PMID: 37479996 PMCID: PMC10362743 DOI: 10.1186/s12888-023-04955-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 06/13/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Cognitive impairment is the main factor in the poor prognosis of schizophrenia, but its mechanism remains unclear. The inferior parietal lobule (IPL) is related to various clinical symptoms and cognitive impairment in schizophrenia. We aimed to explore the relationship between IPL-related functions and cognitive impairment in schizophrenia. METHODS 136 schizophrenia patients and 146 demographically matched healthy controls were enrolled for a cross-sectional study. High-spatial-resolution structural and resting-state functional images were acquired to demonstrate the alternations of brain structure and function. At the same time, the digit span and digit symbol coding tasks of the Chinese Wechsler Adult Intelligence Test Revised (WAIS-RC) were utilized in assessing the subjects' cognitive function. Patients were divided into cognitive impairment and normal cognitive groups according to their cognitive score and then compared whether there were differences between the three groups in fractional amplitude of low-frequency fluctuation (fALFF). In addition, we did a correlation analysis between cognitive function and the fALFF for the left IPL of patients and healthy controls. Based on the Allen Human Brain Atlas, we obtained genes expressed in the left IPL, which were then intersected with the transcriptome-wide association study results and differentially expressed genes in schizophrenia. RESULTS Grouping of patients by the backward digit span task and the digit symbol coding task showed differences in fALFF values between healthy controls and cognitive impairment patients (P < 0.05). We found a negative correlation between the backward digit span task score and fALFF of the left IPL in healthy controls (r = - 0.388, P = 0.003), which was not seen in patients (r = 0.203, P = 0.020). In addition, none of the other analyses were statistically significant (P > 0.017). In addition, we found that diacylglycerol kinase ζ (DGKζ) is differentially expressed in the left IPL and associated with schizophrenia. CONCLUSION Our study demonstrates that the left IPL plays a vital role in cognitive impairment in schizophrenia. DGKζ may act as an essential regulator in the left IPL of schizophrenia patients with cognitive impairment.
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Affiliation(s)
- Xiao-Fan Liu
- Department of Radiology, Xi'an People's Hospital, Xi'an, China
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jin-Jin Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yue-Wen Gu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital, Xi'an, China.
| | - Kun Chen
- Department of Human Anatomy and K. K. Leung Brain Research Centre, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
| | - Long-Biao Cui
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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20
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Han Y, Yang Y, Zhou Z, Jin X, Shi H, Shao M, Song M, Su X, Wang Q, Liu Q, Li W, Lv L. Cortical anatomical variations, gene expression profiles, and clinical phenotypes in patients with schizophrenia. Neuroimage Clin 2023; 39:103451. [PMID: 37315484 PMCID: PMC10509526 DOI: 10.1016/j.nicl.2023.103451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) patients display significant structural brain abnormalities; nevertheless, the genetic mechanisms regulating cortical anatomical variations and their correlation with the disease phenotype are still ambiguous. STUDY DESIGN We characterized anatomical variation using a surface-based method derived from structural magnetic resonance imaging of patients with SZ and age- and sex-matched healthy controls (HCs). Partial least-squares regression was performed across cortex regions between anatomical variation and average transcriptional profiles of SZ risk genes and all qualified genes from the Allen Human Brain Atlas. The morphological features of each brain region were correlated to symptomology variables in patients with SZ using partial correlation analysis. STUDY RESULTS A total of 203 SZ and 201 HCs were included in the final analysis. We observed significant variation of 55 regions of cortical thickness, 23 regions of volume, 7 regions of area, and 55 regions of local gyrification index (LGI) between SZ and HC groups. Expression profiles of 4 SZ risk genes and 96 genes from all qualified genes showed a correlation to anatomical variability, however, after multiple comparisons, the correlations were no longer significant. LGI variability in multiple frontal subregions was associated with specific symptoms of SZ, whereas cognitive function involving attention/vigilance was linked to LGI variability across nine brain regions. CONCLUSIONS Cortical anatomical variation of patients with schizophrenia is associated with gene transcriptome profiles as well as clinical phenotypes.
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Affiliation(s)
- Yong Han
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Zhilu Zhou
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xueyan Jin
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Minglong Shao
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Meng Song
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xi Su
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Qi Wang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Qing Liu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China.
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China.
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21
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Cao H, Wei X, Zhang W, Xiao Y, Zeng J, Sweeney JA, Gong Q, Lui S. Cerebellar Functional Dysconnectivity in Drug-Naïve Patients With First-Episode Schizophrenia. Schizophr Bull 2023; 49:417-427. [PMID: 36200880 PMCID: PMC10016395 DOI: 10.1093/schbul/sbac121] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Cerebellar functional dysconnectivity has long been implicated in schizophrenia. However, the detailed dysconnectivity pattern and its underlying biological mechanisms have not been well-charted. This study aimed to conduct an in-depth characterization of cerebellar dysconnectivity maps in early schizophrenia. STUDY DESIGN Resting-state fMRI data were processed from 196 drug-naïve patients with first-episode schizophrenia and 167 demographically matched healthy controls. The cerebellum was parcellated into nine functional systems based on a state-of-the-art atlas, and seed-based connectivity for each cerebellar system was examined. The observed connectivity alterations were further associated with schizophrenia risk gene expressions using data from the Allen Human Brain Atlas. STUDY RESULTS Overall, we observed significantly increased cerebellar connectivity with the sensorimotor cortex, default-mode regions, ventral part of visual cortex, insula, and striatum. In contrast, decreased connectivity was shown chiefly within the cerebellum, and between the cerebellum and the lateral prefrontal cortex, temporal lobe, and dorsal visual areas. Such dysconnectivity pattern was statistically similar across seeds, with no significant group by seed interactions identified. Moreover, connectivity strengths of hypoconnected but not hyperconnected regions were significantly correlated with schizophrenia risk gene expressions, suggesting potential genetic underpinnings for the observed hypoconnectivity. CONCLUSIONS These findings suggest a common bidirectional dysconnectivity pattern across different cerebellar subsystems, and imply that such bidirectional alterations may relate to different biological mechanisms.
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Affiliation(s)
- Hengyi Cao
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Xia Wei
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Qiyong Gong
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
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22
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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: 11] [Impact Index Per Article: 11.0] [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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23
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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: 6] [Impact Index Per Article: 6.0] [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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24
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Xu X, Li Q, Qian Y, Cai H, Zhang C, Zhao W, Zhu J, Yu Y. Genetic mechanisms underlying gray matter volume changes in patients with drug-naive first-episode schizophrenia. Cereb Cortex 2023; 33:2328-2341. [PMID: 35640648 DOI: 10.1093/cercor/bhac211] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Brain structural damage is a typical feature of schizophrenia. Investigating such disease phenotype in patients with drug-naive first-episode schizophrenia (DFSZ) may exclude the confounds of antipsychotics and illness chronicity. However, small sample sizes and marked clinical heterogeneity have precluded definitive identification of gray matter volume (GMV) changes in DFSZ as well as their underlying genetic mechanisms. Here, GMV changes in DFSZ were assessed using a neuroimaging meta-analysis of 19 original studies, including 605 patients and 637 controls. Gene expression data were derived from the Allen Human Brain Atlas and processed with a newly proposed standardized pipeline. Then, we used transcriptome-neuroimaging spatial correlations to identify genes associated with GMV changes in DFSZ, followed by a set of gene functional feature analyses. Meta-analysis revealed consistent GMV reduction in the right superior temporal gyrus, right insula and left inferior temporal gyrus in DFSZ. Moreover, we found that these GMV changes were spatially correlated with expression levels of 1,201 genes, which exhibited a wide range of functional features. Our findings may provide important insights into the genetic mechanisms underlying brain morphological abnormality in schizophrenia.
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Affiliation(s)
- Xiaotao Xu
- Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China.,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
| | - Qian Li
- Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,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
| | - 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
| | - Cun 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
| | - 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
| | - 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
| | - 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.,Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China
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25
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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: 25] [Impact Index Per Article: 25.0] [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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26
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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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27
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Ardesch DJ, Libedinsky I, Scholtens LH, Wei Y, van den Heuvel MP. Convergence of brain transcriptomic and neuroimaging patterns in schizophrenia, bipolar disorder, autism spectrum disorder and major depression disorder. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023. [DOI: 10.1016/j.bpsc.2022.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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28
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Zhu F, Xiao Y, Tao B, Gao Z, Gao X, Zhao Q, Zhang Q, Tang B, Zhang X, Zhao Y, Bishop JR, Sweeney JA, Lui S. Radiomic features of gray matter in never-treated first-episode schizophrenia. Cereb Cortex 2022; 33:5957-5967. [PMID: 36513368 DOI: 10.1093/cercor/bhac474] [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: 08/12/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 12/15/2022] Open
Abstract
Alterations of radiomic features (RFs) in gray matter are observed in schizophrenia, of which the results may be limited by small study samples and confounding effects of drug therapies. We tested for RFs alterations of gray matter in never-treated first-episode schizophrenia (NT-FES) patients and examined their associations with known gene expression profiles. RFs were examined in the first sample with 197 NT-FES and 178 healthy controls (HCs) and validated in the second independent sample (90 NT-FES and 74 HCs). One-year follow-up data were available from 87 patients to determine whether RFs were associated with treatment outcomes. Associations between identified RFs in NT-FES and gene expression profiles were evaluated. NT-FES exhibited alterations of 30 RFs, with the greatest involvement of microstructural heterogeneity followed by measures of brain region shape. The identified RFs were mainly located in the central executive network, frontal-temporal network, and limbic system. Two baseline RFs with the involvement of microstructural heterogeneity predicted treatment response with moderate accuracy (78% for the first sample, 70% for the second sample). Exploratory analyses indicated that RF alterations were spatially related to the expression of schizophrenia risk genes. In summary, the present findings link brain abnormalities in schizophrenia with molecular features and treatment response.
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Affiliation(s)
- Fei Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ziyang Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xin Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qi Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Biqiu Tang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | | | - Yu Zhao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH 45219, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
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29
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Tian T, Li Y, Li J, Zhang G, Wang J, Wan C, Fang J, Wu D, Zhou Y, Qin Y, Zhu H, Liu D, Zhu W. Genetic influence on brain volume alterations related to self-reported childhood abuse. Front Neurosci 2022; 16:1019718. [PMID: 36203798 PMCID: PMC9530554 DOI: 10.3389/fnins.2022.1019718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 08/30/2022] [Indexed: 11/13/2022] Open
Abstract
As an important predictor of adulthood psychopathology, self-reported childhood abuse appears heritable and is associated with brain abnormalities. However, the specific genetic mechanisms behind these brain alterations remain largely unknown. This study recruited young adults who reported different degrees of childhood abuse from the community. In order to fully understand the influence of genes on brain changes related to self-reported childhood abuse, various experiments were conducted in this study. Firstly, volume changes of gray matter and white matter related to childhood abuse were investigated by using advanced magnetic resonance imaging techniques. After sequencing the whole exons, we further investigated the relationship between polygenic risk score, brain volume alterations, and childhood abuse score. Furthermore, transcription-neuroimaging association analysis was used to identify risk genes whose expressions were associated with brain volume alterations. The gray matter volumes of left caudate and superior parietal lobule, and white matter volumes of left cerebellum and right temporal lobe-basal ganglia region were significantly correlated with the childhood abuse score. More importantly, brain volume changes mediated the influence of polygenic risk on self-reported childhood abuse. Additionally, transcription-neuroimaging association analysis reported 63 risk genes whose expression levels were significantly associated with childhood abuse-related brain volume changes. These genes are involved in multiple biological processes, such as nerve development, synaptic transmission, and cell construction. Combining data from multiple perspectives, our work provides evidence of brain abnormalities associated with childhood abuse, and further indicates that polygene genetic risk and risk gene expression may affect the occurrence of childhood abuse by brain regulation, which provides insights into the molecularpathology and neuromechanism of childhood adversity. Paying attention to the physical and mental health of high-risk children may be a fundamental way to prevent childhood abuse and promote lifelong mental health.
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30
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Cattarinussi G, Kubera KM, Hirjak D, Wolf RC, Sambataro F. Neural Correlates of the Risk for Schizophrenia and Bipolar Disorder: A Meta-analysis of Structural and Functional Neuroimaging Studies. Biol Psychiatry 2022; 92:375-384. [PMID: 35523593 DOI: 10.1016/j.biopsych.2022.02.960] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/28/2022] [Accepted: 02/23/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (RELs), and early recognition biomarkers in ultrahigh risk populations. However, a comprehensive meta-analysis of structural and functional magnetic resonance imaging (MRI) studies examining relatives of patients with SCZ and BD has not been performed yet. METHODS We systematically searched PubMed, Scopus, and Web of Science for structural and functional MRI studies investigating relatives and healthy control subjects. A total of 230 eligible neuroimaging studies (6274 SCZ-RELs, 1900 BD-RELs, 10,789 healthy control subjects) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 structural MRI and 81 functional MRI investigations, including stratification by task type. We also meta-analyzed regional and global volumetric changes. Finally, we performed a meta-analysis of all MRI studies combined. RESULTS Reduced thalamic volume was present in both SCZ and BD RELs. Moreover, SCZ-RELs showed alterations in corticostriatal-thalamic networks, spanning the dorsolateral prefrontal cortex and temporal regions, while BD-RELs showed altered thalamocortical and limbic regions, including the ventrolateral prefrontal, superior parietal, and medial temporal cortices, with frontoparietal alterations in RELs of BD type I. CONCLUSIONS Familiarity for SCZ and BD is associated with alterations in the thalamocortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Fabio Sambataro
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy.
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31
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Shi W, Fan L, Wang H, Liu B, Li W, Li J, Cheng L, Chu C, Song M, Sui J, Luo N, Cui Y, Dong Z, Lu Y, Ma Y, Ma L, Li K, Chen J, Chen Y, Guo H, Li P, Lu L, Lv L, Wan P, Wang H, Wang H, Yan H, Yan J, Yang Y, Zhang H, Zhang D, Jiang T. Two subtypes of schizophrenia identified by an individual-level atypical pattern of tensor-based morphometric measurement. Cereb Cortex 2022; 33:3683-3700. [PMID: 36005854 DOI: 10.1093/cercor/bhac301] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 11/12/2022] Open
Abstract
Difficulties in parsing the multiaspect heterogeneity of schizophrenia (SCZ) based on current nosology highlight the need to subtype SCZ using objective biomarkers. Here, utilizing a large-scale multisite SCZ dataset, we identified and validated 2 neuroanatomical subtypes with individual-level abnormal patterns of the tensor-based morphometric measurement. Remarkably, compared with subtype 1, which showed moderate deficits of some subcortical nuclei and an enlarged striatum and cerebellum, subtype 2, which showed cerebellar atrophy and more severe subcortical nuclei atrophy, had a higher subscale score of negative symptoms, which is considered to be a core aspect of SCZ and is associated with functional outcome. Moreover, with the neuroimaging-clinic association analysis, we explored the detailed relationship between the heterogeneity of clinical symptoms and the heterogeneous abnormal neuroanatomical patterns with respect to the 2 subtypes. And the neuroimaging-transcription association analysis highlighted several potential heterogeneous biological factors that may underlie the subtypes. Our work provided an effective framework for investigating the heterogeneity of SCZ from multilevel aspects and may provide new insights for precision psychiatry.
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Affiliation(s)
- Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Chinese Institute for Brain Research, Beijing 102206, China
| | - Wen Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Luqi Cheng
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Ming Song
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Na Luo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhenwei Dong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kaixin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian 463000, China
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China.,Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China.,Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China.,Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, Zhumadian 463000, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, China
| | - Huiling Wang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China.,Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China.,Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China
| | - Jun Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China.,Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China.,Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China.,Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China.,Department of Psychology, Xinxiang Medical University, Xinxiang 453002, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China.,Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China.,Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China.,Innovation Academy for Artificial Intelligence, Chinese Academy of Sciences, Beijing 100190, China
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32
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Xie Y, Ding H, Du X, Chai C, Wei X, Sun J, Zhuo C, Wang L, Li J, Tian H, Liang M, Zhang S, Yu C, Qin W. Morphometric Integrated Classification Index: A Multisite Model-Based, Interpretable, Shareable and Evolvable Biomarker for Schizophrenia. Schizophr Bull 2022; 48:1217-1227. [PMID: 35925032 PMCID: PMC9673259 DOI: 10.1093/schbul/sbac096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Multisite massive schizophrenia neuroimaging data sharing is becoming critical in understanding the pathophysiological mechanism and making an objective diagnosis of schizophrenia; it remains challenging to obtain a generalizable and interpretable, shareable, and evolvable neuroimaging biomarker for schizophrenia diagnosis. STUDY DESIGN A Morphometric Integrated Classification Index (MICI) was proposed as a potential biomarker for schizophrenia diagnosis based on structural magnetic resonance imaging data of 1270 subjects from 10 sites (588 schizophrenia patients and 682 normal controls). An optimal XGBoost classifier plus sample-weighted SHapley Additive explanation algorithms were used to construct the MICI measure. STUDY RESULTS The MICI measure achieved comparable performance with the sample-weighted ensembling model and merged model based on raw data (Delong test, P > 0.82) while outperformed the single-site models (Delong test, P < 0.05) in either the independent-sample testing datasets from the 9 sites or the independent-site dataset (generalizable). Besides, when new sites were embedded in, the performance of this measure was gradually increasing (evolvable). Finally, MICI was strongly associated with the severity of schizophrenia brain structural abnormality, with the patients' positive and negative symptoms, and with the brain expression profiles of schizophrenia risk genes (interpretable). CONCLUSIONS In summary, the proposed MICI biomarker may provide a simple and explainable way to support clinicians for objectively diagnosing schizophrenia. Finally, we developed an online model share platform to promote biomarker generalization and provide free individual prediction services (http://micc.tmu.edu.cn/mici/index.html).
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Affiliation(s)
- Yingying Xie
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Xiaotong Du
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chao Chai
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaotong Wei
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jie Sun
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chuanjun Zhuo
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Lina Wang
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Jie Li
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | | | - Meng Liang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | | | | | - Wen Qin
- To whom correspondence should be addressed; Department of Radiology, and Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital. Anshan Road No 154, Heping District, Tianjin 300052, China.
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33
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Zhao H, Cai H, Mo F, Lu Y, Yao S, Yu Y, Zhu J. Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study. Cereb Cortex 2022; 33:3387-3400. [PMID: 35851912 DOI: 10.1093/cercor/bhac279] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/22/2022] [Accepted: 06/23/2022] [Indexed: 11/15/2022] Open
Abstract
Abstract
Functional homotopy, the high degree of spontaneous activity synchrony and functional coactivation between geometrically corresponding interhemispheric regions, is a fundamental characteristic of the intrinsic functional architecture of the brain. However, little is known about the genetic mechanisms underlying functional homotopy. Resting-state functional magnetic resonance imaging data from a discovery dataset (656 healthy subjects) and 2 independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects) were used to calculate voxel-mirrored homotopic connectivity (VMHC) indexing brain functional homotopy. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analysis was conducted to identify genes linked to VMHC. We found 1,001 genes whose expression measures were spatially associated with VMHC. Functional enrichment analyses demonstrated that these VMHC-related genes were enriched for biological functions including protein kinase activity, ion channel regulation, and synaptic function as well as many neuropsychiatric disorders. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons and immune cells, and during nearly all developmental periods. In addition, the VMHC-associated genes were linked to multiple behavioral domains, including vision, execution, and attention. Our findings suggest that interhemispheric communication and coordination involve a complex interaction of polygenes with a rich range of functional features.
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Affiliation(s)
- 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
| | - 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
| | - Fan Mo
- 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
| | - Yun Lu
- 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
| | - Shanwen Yao
- 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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34
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Zhao W, Voon V, Xue K, Xie C, Kang J, Lin CP, Wang J, Cheng J, Feng J. Common abnormal connectivity in first-episode and chronic schizophrenia in pre- and post-central regions: Implications for neuromodulation targeting. Prog Neuropsychopharmacol Biol Psychiatry 2022; 117:110556. [PMID: 35367293 DOI: 10.1016/j.pnpbp.2022.110556] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 03/23/2022] [Accepted: 03/27/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia is a neurodevelopmental disorder manifesting differing impairments at early onset and chronic disease stages. Brain imaging research suggests a core pathological region in patients with first-episode schizophrenia is Broca's area. With disease progression, alterations in thalamic connectivity becomes more prevalent. Understanding the common circuitry underlying pathology in these two groups might highlight a critical common network and novel targets for treatment. In this study, 937 subject samples were collected including patients with first-episode schizophrenia and those with chronic schizophrenia. We used hypothesis-based voxel-level functional connectivity analyses to calculate functional connectivity using the left Broca's area and thalamus as regions of interest in those with first-episode and chronic schizophrenia, respectively. We show for the first time that in both patients with first-episode and chronic schizophrenia the greatest functional connectivity disruption ended in the pre- and postcentral regions. At the early-onset stage, the core brain region is abnormally connected to pre- and postcentral areas responsible for mouth movement, while in the chronic stage, it expanded to a wider range of sensorimotor areas. Our findings suggest that expanding the focus on the low-order sensory-motor systems beyond high-order cognitive impairments in schizophrenia may show potential for neuromodulation treatment, given the relative accessibility of these cortical regions and their functional and structural connections to the core region at different stages of illness.
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Affiliation(s)
- Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kangkang Xue
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders (No. 13dz2260500), Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China; Shanghai Center for Mathematical Sciences, Shanghai, China.
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35
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Zhang C, Li X, Zhao L, Liang R, Deng W, Guo W, Wang Q, Hu X, Du X, Sham PC, Luo X, Li T. Comprehensive and integrative analyses identify TYW5 as a schizophrenia risk gene. BMC Med 2022; 20:169. [PMID: 35527273 PMCID: PMC9082878 DOI: 10.1186/s12916-022-02363-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 04/04/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Identifying the causal genes at the risk loci and elucidating their roles in schizophrenia (SCZ) pathogenesis remain significant challenges. To explore risk variants associated with gene expression in the human brain and to identify genes whose expression change may contribute to the susceptibility of SCZ, here we report a comprehensive integrative study on SCZ. METHODS We systematically integrated the genetic associations from a large-scale SCZ GWAS (N = 56,418) and brain expression quantitative trait loci (eQTL) data (N = 175) using a Bayesian statistical framework (Sherlock) and Summary data-based Mendelian Randomization (SMR). We also measured brain structure of 86 first-episode antipsychotic-naive schizophrenia patients and 152 healthy controls with the structural MRI. RESULTS Both Sherlock (P = 3. 38 × 10-6) and SMR (P = 1. 90 × 10-8) analyses showed that TYW5 mRNA expression was significantly associated with risk of SCZ. Brain-based studies also identified a significant association between TYW5 protein abundance and SCZ. The single-nucleotide polymorphism rs203772 showed significant association with SCZ and the risk allele is associated with higher transcriptional level of TYW5 in the prefrontal cortex. We further found that TYW5 was significantly upregulated in the brain tissues of SCZ cases compared with controls. In addition, TYW5 expression was also significantly higher in neurons induced from pluripotent stem cells of schizophrenia cases compared with controls. Finally, combining analysis of genotyping and MRI data showed that rs203772 was significantly associated with gray matter volume of the right middle frontal gyrus and left precuneus. CONCLUSIONS We confirmed that TYW5 is a risk gene for SCZ. Our results provide useful information toward a better understanding of the genetic mechanism of TYW5 in risk of SCZ.
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Affiliation(s)
- Chengcheng Zhang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaojing Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Rong Liang
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
| | - Wanjun Guo
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xun Hu
- The Clinical Research Center and Department of Pathology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiangdong Du
- Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China.,Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong, SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, SAR, China
| | - Xiongjian Luo
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China. .,NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
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36
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Transcriptomic and cellular decoding of functional brain connectivity changes reveal regional brain vulnerability to pro- and anti-inflammatory therapies. Brain Behav Immun 2022; 102:312-323. [PMID: 35259429 DOI: 10.1016/j.bbi.2022.03.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/16/2022] [Accepted: 03/03/2022] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Systemic inflammation induces acute changes in mood, motivation and cognition that closely resemble those observed in depressed individuals. However, the mechanistic pathways linking peripheral inflammation to depression-like psychopathology via intermediate effects on brain function remain incompletely understood. METHODS We combined data from 30 patients initiating interferon-α treatment for Hepatitis-C and 20 anti-tumour necrosis factor (TNF) therapy for inflammatory arthritis and used resting-state functional magnetic resonance imaging to investigate acute effects of each treatment on regional global brain connectivity (GBC). We leveraged transcriptomic data from the Allen Human Brain Atlas to uncover potential biological and cellular pathways underpinning regional vulnerability to GBC changes induced by each treatment. RESULTS Interferon-α and anti-TNF therapies both produced differential small-to-medium sized decreases in regional GBC. However, these were observed within distinct brain regions and the regional patterns of GBC changes induced by each treatment did not correlate suggesting independent underlying processes. Further, the spatial distribution of these differential GBC decreases could be captured by multivariate patterns of constitutive regional expression of genes respectively related to: i) neuroinflammation and glial cells; and ii) glutamatergic neurotransmission and neurons. The extent to which each participant expressed patterns of GBC changes aligning with these patterns of transcriptomic vulnerability also correlated with both acute treatment-induced changes in interleukin-6 (IL-6) and, for Interferon-α, longer-term treatment-associated changes in depressive symptoms. CONCLUSIONS Together, we present two transcriptomic models separately linking regional vulnerability to the acute effects of interferon-α and anti-TNF treatments on brain function to glial neuroinflammation and glutamatergic neurotransmission. These findings generate hypotheses about two potential brain mechanisms through which bidirectional changes in peripheral inflammation may contribute to the development/resolution of psychopathology.
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37
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Nawaz MS, Einarsson G, Bustamante M, Gisladottir RS, Walters GB, Jonsdottir GA, Skuladottir AT, Bjornsdottir G, Magnusson SH, Asbjornsdottir B, Unnsteinsdottir U, Sigurdsson E, Jonsson PV, Palmadottir VK, Gudjonsson SA, Halldorsson GH, Ferkingstad E, Jonsdottir I, Thorleifsson G, Holm H, Thorsteinsdottir U, Sulem P, Gudbjartsson DF, Stefansson H, Thorgeirsson TE, Ulfarsson MO, Stefansson K. Thirty novel sequence variants impacting human intracranial volume. Brain Commun 2022; 4:fcac271. [PMID: 36415660 PMCID: PMC9677475 DOI: 10.1093/braincomms/fcac271] [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: 04/13/2022] [Revised: 06/16/2022] [Accepted: 10/20/2022] [Indexed: 11/14/2022] Open
Abstract
Intracranial volume, measured through magnetic resonance imaging and/or estimated from head circumference, is heritable and correlates with cognitive traits and several neurological disorders. We performed a genome-wide association study meta-analysis of intracranial volume (n = 79 174) and found 64 associating sequence variants explaining 5.0% of its variance. We used coding variation, transcript and protein levels, to uncover 12 genes likely mediating the effect of these variants, including GLI3 and CDK6 that affect cranial synostosis and microcephaly, respectively. Intracranial volume correlates genetically with volumes of cortical and sub-cortical regions, cognition, learning, neonatal and neurological traits. Parkinson's disease cases have greater and attention deficit hyperactivity disorder cases smaller intracranial volume than controls. Our Mendelian randomization studies indicate that intracranial volume associated variants either increase the risk of Parkinson's disease and decrease the risk of attention deficit hyperactivity disorder and neuroticism or correlate closely with a confounder.
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Affiliation(s)
- Muhammad Sulaman Nawaz
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | | | | | - Rosa S Gisladottir
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,School of Humanities, University of Iceland, Saemundargata 2, 102 Reykjavik, Iceland
| | - G Bragi Walters
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | | | | | | | | | | | | | - Engilbert Sigurdsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland.,Department of Psychiatry, Landspitali-National University Hospital, Hringbraut 101, 101 Reykjavik, Iceland
| | - Palmi V Jonsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland.,Department of Geriatric Medicine, Landspitali University Hospital, Hringbraut 101, 101 Reykjavik, Iceland
| | - Vala Kolbrun Palmadottir
- Department of Internal Medicine, Landspitali University Hospital, Hringbraut 101, 101 Reykjavik, Iceland
| | | | - Gisli H Halldorsson
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Taeknigardur, Dunhagi 5, 107 Reykjavik, Iceland
| | - Egil Ferkingstad
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland
| | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland
| | | | - Patrick Sulem
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland
| | | | | | | | - Magnus O Ulfarsson
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,Faculty of Electrical and Computer Engineering, University of Iceland, Taeknigardur, Dunhagi 5, 107 Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Sturlugata 8, 102 Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
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38
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Martins D, Giacomel A, Williams SCR, Turkheimer F, Dipasquale O, Veronese M. Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain. Cell Rep 2021; 37:110173. [PMID: 34965413 DOI: 10.1016/j.celrep.2021.110173] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/30/2021] [Accepted: 12/03/2021] [Indexed: 12/12/2022] Open
Abstract
The integration of transcriptomic and neuroimaging data, "imaging transcriptomics," has recently emerged to generate hypotheses about potential biological pathways underlying regional variability in neuroimaging features. However, the validity of this approach is yet to be examined in depth. Here, we sought to bridge this gap by performing transcriptomic decoding of the regional distribution of well-known molecular markers spanning different elements of the biology of the healthy human brain. Imaging transcriptomics identifies biological and cell pathways that are consistent with the known biology of a wide range of molecular neuroimaging markers. The extent to which it can capture patterns of gene expression that align well with elements of the biology of the neuroinflammatory axis, at least in healthy controls without a proinflammatory challenge, is inconclusive. Imaging transcriptomics might constitute an interesting approach to improve our understanding of the biological pathways underlying regional variability in a wide range of neuroimaging phenotypes.
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Affiliation(s)
- Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK.
| | - Alessio Giacomel
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - Steven C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK; Department of Information Engineering, University of Padua, Via Gradenigo, 6/b, 35131 Padova, Italy.
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39
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Nojima K, Miyazaki H, Hori T, Vargova L, Oohashi T. Assessment of Possible Contributions of Hyaluronan and Proteoglycan Binding Link Protein 4 to Differential Perineuronal Net Formation at the Calyx of Held. Front Cell Dev Biol 2021; 9:730550. [PMID: 34604231 PMCID: PMC8485899 DOI: 10.3389/fcell.2021.730550] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 08/23/2021] [Indexed: 12/02/2022] Open
Abstract
The calyx of Held is a giant nerve terminal mediating high-frequency excitatory input to principal cells of the medial nucleus of the trapezoid body (MNTB). MNTB principal neurons are enwrapped by densely organized extracellular matrix structures, known as perineuronal nets (PNNs). Emerging evidence indicates the importance of PNNs in synaptic transmission at the calyx of Held. Previously, a unique differential expression of aggrecan and brevican has been reported at this calyceal synapse. However, the role of hyaluronan and proteoglycan binding link proteins (HAPLNs) in PNN formation and synaptic transmission at this synapse remains elusive. This study aimed to assess immunohistochemical evidence for the effect of HAPLN4 on differential PNN formation at the calyx of Held. Genetic deletion of Hapln4 exhibited a clear ectopic shift of brevican localization from the perisynaptic space between the calyx of Held terminals and principal neurons to the neuropil surrounding the whole calyx of Held terminals. In contrast, aggrecan expression showed a consistent localization at the surrounding neuropil, together with HAPLN1 and tenascin-R, in both gene knockout (KO) and wild-type (WT) mice. An in situ proximity ligation assay demonstrated the molecular association of brevican with HAPLN4 in WT and HAPLN1 in gene KO mice. Further elucidation of the roles of HAPLN4 may highlight the developmental and physiological importance of PNN formation in the calyx of Held.
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Affiliation(s)
- Kojiro Nojima
- Department of Molecular Biology and Biochemistry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Haruko Miyazaki
- Department of Molecular Biology and Biochemistry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Tetsuya Hori
- Cellular and Molecular Synaptic Function Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Lydia Vargova
- Department of Neuroscience, Charles University, Second Faculty of Medicine, Prague, Czechia.,Department of Cellular Physiology, Institute of Experimental Medicine AS CR, Prague, Czechia
| | - Toshitaka Oohashi
- Department of Molecular Biology and Biochemistry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
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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: 20] [Impact Index Per Article: 6.7] [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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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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42
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The gut microbiome is associated with brain structure and function in schizophrenia. Sci Rep 2021; 11:9743. [PMID: 33963227 PMCID: PMC8105323 DOI: 10.1038/s41598-021-89166-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/20/2021] [Indexed: 12/11/2022] Open
Abstract
The effect of the gut microbiome on the central nervous system and its possible role in mental disorders have received increasing attention. However, knowledge about the relationship between the gut microbiome and brain structure and function is still very limited. Here, we used 16S rRNA sequencing with structural magnetic resonance imaging (sMRI) and resting-state functional (rs-fMRI) to investigate differences in fecal microbiota between 38 patients with schizophrenia (SZ) and 38 demographically matched normal controls (NCs) and explored whether such differences were associated with brain structure and function. At the genus level, we found that the relative abundance of Ruminococcus and Roseburia was significantly lower, whereas the abundance of Veillonella was significantly higher in SZ patients than in NCs. Additionally, the analysis of MRI data revealed that several brain regions showed significantly lower gray matter volume (GMV) and regional homogeneity (ReHo) but significantly higher amplitude of low-frequency fluctuation in SZ patients than in NCs. Moreover, the alpha diversity of the gut microbiota showed a strong linear relationship with the values of both GMV and ReHo. In SZ patients, the ReHo indexes in the right STC (r = − 0.35, p = 0.031, FDR corrected p = 0.039), the left cuneus (r = − 0.33, p = 0.044, FDR corrected p = 0.053) and the right MTC (r = − 0.34, p = 0.03, FDR corrected p = 0.052) were negatively correlated with the abundance of the genus Roseburia. Our results suggest that the potential role of the gut microbiome in SZ is related to alterations in brain structure and function. This study provides insights into the underlying neuropathology of SZ.
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Tian T, Li J, Zhang G, Wang J, Liu D, Wan C, Fang J, Wu D, Zhou Y, Qin Y, Zhu W. Default Mode Network Alterations Induced by Childhood Trauma Correlate With Emotional Function and SLC6A4 Expression. Front Psychiatry 2021; 12:760411. [PMID: 35153849 PMCID: PMC8828908 DOI: 10.3389/fpsyt.2021.760411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
As one of the most studied resting-state functional networks, default mode network (DMN) is related to pathogenesis in neuropsychiatry. However, it is unclear whether changed DMN connectivity is transformed into vulnerability to psychopathology in adults who experienced childhood trauma, and what is the underlying genetic basis. Exploring the effect of DMN on environment-behavior pathway and the related genetic modulation mechanisms could further a better understanding of psychiatric pathogenesis and early prevention strategy. Two hundred and sixteen young adults with varying levels of early trauma indexed by the Childhood Trauma Questionnaire (CTQ) were recruited from the community. Static and dynamic functional connectivity based on DMN seeds and independent component analysis based on whole-brain voxels were combined to explore DMN alterations related to the CTQ score. Relationships between CTQ score, DMN connectivity, and behavioral scores were confirmed by mediation effect analysis. Imaging-genomic correlations were further used to identify risk genes whose expression was associated with the DMN changes. Dysregulated DMN connectivity was found both in seed-level and voxel-level analyses. Moreover, the functional disruption in the left temporal pole, right parahippocampal gyrus, and frontoparietal connectivity mediated the effects of childhood trauma on emotional behavior. The serotonin transporter gene was identified and might suggest the biological underpinning of the relationship between childhood trauma, DMN, and emotion regulation. Changed DMN may be useful as biomarkers to provide a powerful supplement to psychological evaluation related to childhood trauma. Combined with gene expression profiles, our findings advance a more integrative understanding of DMN alterations induced by childhood trauma, and clarify its implications for psychiatric pathogenesis and early prevention strategies.
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Affiliation(s)
- Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guiling Zhang
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dong Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Changhua Wan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jicheng Fang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Di Wu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yiran Zhou
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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