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Zhong Y, Tubbs JD, Leung PBM, Zhan N, Hui TCK, Ho KKY, Hung KSY, Cheung EFC, So HC, Lui SSY, Sham PC. Whole-exome sequencing in a Chinese sample provides preliminary evidence for the link between rare/low-frequency immune-related variants and early-onset schizophrenia. Asian J Psychiatr 2024; 96:104046. [PMID: 38663229 DOI: 10.1016/j.ajp.2024.104046] [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: 03/19/2024] [Accepted: 04/06/2024] [Indexed: 06/01/2024]
Abstract
Rare and low-frequency variants contribute to schizophrenia (SCZ), and may influence its age-at-onset (AAO). We examined the association of rare or low-frequency deleterious coding variants in Chinese patients with SCZ. We collected DNA samples in 197 patients with SCZ spectrum disorder and 82 healthy controls (HC), and performed exome sequencing. The AAO variable was ascertained in the majority of SCZ participants for identify the early-onset (EOS, AAO<=18) and adult-onset (AOS, AAO>18) subgroups. We examined the overall association of rare/low-frequency, damaging variants in SCZ versus HC, EOS versus HC, and AOS versus HC at the gene and gene-set levels using Sequence Kernel Association Test. The quantitative rare-variant association test of AAO was conducted. Resampling was used to obtain empirical p-values and to control for family-wise error rate (FWER). In binary-trait association tests, we identified 5 potential candidate risk genes and 10 gene ontology biological processes (GOBP) terms, among which PADI2 reached FWER-adjusted significance. In quantitative rare-variant association tests, we found marginally significant correlations of AAO with alterations in 4 candidate risk genes, and 5 GOBP pathways. Together, the biological and functional profiles of these genes and gene sets supported the involvement of perturbations of neural systems in SCZ, and altered immune functions in EOS.
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Affiliation(s)
- Yuanxin Zhong
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Justin D Tubbs
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Perry B M Leung
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Na Zhan
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Tomy C K Hui
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Karen K Y Ho
- Department of General Adult Psychiatry, Castle Peak Hospital, Hong Kong Special Administrative Region of China
| | - Karen S Y Hung
- Department of General Adult Psychiatry, Castle Peak Hospital, Hong Kong Special Administrative Region of China
| | - Eric F C Cheung
- Department of General Adult Psychiatry, Castle Peak Hospital, Hong Kong Special Administrative Region of China
| | - Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region of China; Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region of China.
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China.
| | - Pak C Sham
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region of China.
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Song P, Li X, Yuan X, Pang L, Song X, Wang Y. Identifying frequency-dependent imaging genetic associations via hypergraph-structured multi-task sparse canonical correlation analysis. Comput Biol Med 2024; 171:108051. [PMID: 38335819 DOI: 10.1016/j.compbiomed.2024.108051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/03/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024]
Abstract
Identifying complex associations between genetic variations and imaging phenotypes is a challenging task in the research of brain imaging genetics. The previous study has proved that neuronal oscillations within distinct frequency bands are derived from frequency-dependent genetic modulation. Thus it is meaningful to explore frequency-dependent imaging genetic associations, which may give important insights into the pathogenesis of brain disorders. In this work, the hypergraph-structured multi-task sparse canonical correlation analysis (HS-MTSCCA) was developed to explore the associations between multi-frequency imaging phenotypes and single-nucleotide polymorphisms (SNPs). Specifically, we first created a hypergraph for the imaging phenotypes of each frequency and the SNPs, respectively. Then, a new hypergraph-structured constraint was proposed to learn high-order relationships among features in each hypergraph, which can introduce biologically meaningful information into the model. The frequency-shared and frequency-specific imaging phenotypes and SNPs could be identified using the multi-task learning framework. We also proposed a useful strategy to tackle this algorithm and then demonstrated its convergence. The proposed method was evaluated on four simulation datasets and a real schizophrenia dataset. The experimental results on synthetic data showed that HS-MTSCCA outperforms the other competing methods according to canonical correlation coefficients, canonical weights, and cosine similarity. And the results on real data showed that HS-MTSCCA could obtain superior canonical coefficients and canonical weights. Furthermore, the identified frequency-shared and frequency-specific biomarkers could provide more interesting and meaningful information, demonstrating that HS-MTSCCA is a powerful method for brain imaging genetics.
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Affiliation(s)
- Peilun Song
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xue Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, China; Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiuxia Yuan
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, China; Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Lijuan Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, China; Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, China; Biological Psychiatry International Joint Laboratory of Henan/Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Yaping Wang
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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Barnett MM, Reay WR, Geaghan MP, Kiltschewskij DJ, Green MJ, Weidenhofer J, Glatt SJ, Cairns MJ. miRNA cargo in circulating vesicles from neurons is altered in individuals with schizophrenia and associated with severe disease. SCIENCE ADVANCES 2023; 9:eadi4386. [PMID: 38019909 PMCID: PMC10686555 DOI: 10.1126/sciadv.adi4386] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023]
Abstract
While RNA expression appears to be altered in several brain disorders, the constraints of postmortem analysis make it impractical for well-powered population studies and biomarker development. Given that the unique molecular composition of neurons are reflected in their extracellular vesicles (EVs), we hypothesized that the fractionation of neuron derived EVs provides an opportunity to specifically profile their encapsulated contents noninvasively from blood. To investigate this hypothesis, we determined miRNA expression in microtubule associated protein 1B (MAP1B)-enriched serum EVs derived from neurons from a large cohort of individuals with schizophrenia and nonpsychiatric comparison participants. We observed dysregulation of miRNA in schizophrenia subjects, in particular those with treatment-resistance and severe cognitive deficits. These data support the hypothesis that schizophrenia is associated with alterations in posttranscriptional regulation of synaptic gene expression and provides an example of the potential utility of tissue-specific EV analysis in brain disorders.
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Affiliation(s)
- Michelle M. Barnett
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - William R. Reay
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Michael P. Geaghan
- Kinghorn Centre for Clinical Genomics, Garvan Medical Research Institute, Darlinghurst, NSW 2010, Australia
| | - Dylan J. Kiltschewskij
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Melissa J. Green
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Judith Weidenhofer
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia
| | - Stephen J. Glatt
- Psychiatric Genetic Epidemiology and Neurobiology Laboratory (PsychGENe lab), Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
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Zhong Y, Tubbs JD, Leung PBM, Zhan N, Hui TCK, Ho KKY, Hung KSY, Cheung EFC, So HC, Lui SSY, Sham PC. Early-onset schizophrenia is associated with immune-related rare variants in a Chinese sample. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.21.23298115. [PMID: 38045317 PMCID: PMC10690336 DOI: 10.1101/2023.11.21.23298115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Background Rare variants are likely to contribute to schizophrenia (SCZ), given the large discrepancy between the heritability estimated from twin and GWAS studies. Furthermore, the nature of the rare-variant contribution to SCZ may vary with the "age-at-onset" (AAO), since early-onset has been suggested as being indicative of neurodevelopment deviance. Objective To examine the association of rare deleterious coding variants in early- and adult-onset SCZ in a Chinese sample. Method Exome sequencing was performed on DNA from 197 patients with SCZ spectrum disorder and 82 healthy controls (HC) of Chinese ancestry recruited in Hong Kong. We also gathered AAO information in the majority of SCZ samples. Patients were classified into early-onset (EOS, AAO<18) and adult-onset (AOS, AAO>18). We collapsed the rare variants to improve statistical power and examined the overall association of rare variants in SCZ versus HC, EOS versus HC, and AOS versus HC at the gene and gene-set levels by Sequence Kernel Association Test. The quantitative rare-variant association test of AAO was also conducted. We focused on variants which were predicted to have a medium or high impact on the protein-encoding process as defined by Ensembl. We applied a 100000-time permutation test to obtain empirical p-values, with significance threshold set at p < 1e -3 to control family-wise error rates. Moreover, we compared the burden of targeted rare variants in significant risk genes and gene sets in cases and controls. Results Based on several binary-trait association tests (i.e., SCZ vs HC, EOS vs HC and AOS vs HC), we identified 7 candidate risk genes and 20 gene ontology biological processes (GOBP) terms, which exhibited higher burdens in SCZ than in controls. Based on quantitative rare-variant association tests, we found that alterations in 5 candidate risk genes and 7 GOBP pathways were significantly correlated with AAO. Based on biological and functional profiles of the candidate risk genes and gene sets, our findings suggested that, in addition to the involvement of perturbations in neural systems in SCZ in general, altered immune responses may be specifically implicated in EOS. Conclusion Disrupted immune responses may exacerbate abnormal perturbations during neurodevelopment and trigger the early onset of SCZ. We provided evidence of rare variants increasing SCZ risk in the Chinese population.
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Sada-Fuente E, Aranda S, Papiol S, Heilbronner U, Moltó MD, Aguilar EJ, González-Peñas J, Andreu-Bernabeu Á, Arango C, Crespo-Facorro B, González-Pinto A, Fañanás L, Arias B, Bobes J, Costas J, Martorell L, Schulze TG, Kalman JL, Vilella E, Muntané G. Common genetic variants contribute to heritability of age at onset of schizophrenia. Transl Psychiatry 2023; 13:201. [PMID: 37308478 PMCID: PMC10261125 DOI: 10.1038/s41398-023-02508-0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/23/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Schizophrenia (SCZ) is a complex disorder that typically arises in late adolescence or early adulthood. Age at onset (AAO) of SCZ is associated with long-term outcomes of the disease. We explored the genetic architecture of AAO with a genome-wide association study (GWAS), heritability, polygenic risk score (PRS), and copy number variant (CNV) analyses in 4 740 subjects of European ancestry. Although no genome-wide significant locus was identified, SNP-based heritability of AAO was estimated to be between 17 and 21%, indicating a moderate contribution of common variants. We also performed cross-trait PRS analyses with a set of mental disorders and identified a negative association between AAO and common variants for SCZ, childhood maltreatment and attention-deficit/hyperactivity disorder. We also investigated the role of copy number variants (CNVs) in AAO and found an association with the length and number of deletions (P-value = 0.03), whereas the presence of CNVs previously reported in SCZ was not associated with earlier onset. To our knowledge, this is the largest GWAS of AAO of SCZ to date in individuals from European ancestry, and the first study to determine the involvement of common variants in the heritability of AAO. Finally, we evidenced the role played by higher SCZ load in determining AAO but discarded the role of pathogenic CNVs. Altogether, these results shed light on the genetic architecture of AAO, which needs to be confirmed with larger studies.
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Affiliation(s)
- Ester Sada-Fuente
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Department of Psychiatry, Universitat Rovira i Virgili (URV), Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Selena Aranda
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Department of Psychiatry, Universitat Rovira i Virgili (URV), Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
| | - María Dolores Moltó
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Genetics, Universitat de Valencia, 46100, Valencia, Spain
- Biomedical Research Institute INCLIVA, 46010, Valencia, Spain
| | - Eduardo J Aguilar
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Biomedical Research Institute INCLIVA, 46010, Valencia, Spain
- Department of Psychiatry, Hospital Clínico Universitario de Valencia, 46010, Valencia, Spain
- Faculty of Medicine, Universidad de Valencia, 46010, Valencia, Spain
| | - Javier González-Peñas
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Gregorio Marañón Health Research Institute (IiSGM), Hospital General Universitario Gregorio Marañón, 28007, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Gregorio Marañón Health Research Institute (IiSGM), Hospital General Universitario Gregorio Marañón, 28007, Madrid, Spain
- Faculty of Medicine, Universidad Complutense, 28007, Madrid, Spain
| | - Celso Arango
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Gregorio Marañón Health Research Institute (IiSGM), Hospital General Universitario Gregorio Marañón, 28007, Madrid, Spain
- Faculty of Medicine, Universidad Complutense, 28007, Madrid, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Universidad de Cantabria, 39005, Santander, Cantabria, Spain
- Hospital Universitario Marqués de Valdecilla-IDIVAL, 39008, Santander, Cantabria, Spain
- Department of Psychiatry, University Hospital Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBiS), Sevilla, Spain
| | - Ana González-Pinto
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Hospital Universitario Araba, Instituto de Investigación Sanitaria Bioaraba, Universidad del País Vasco, 01009, Vitoria, Spain
| | - Lourdes Fañanás
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, Universitat de Barcelona, Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028, Barcelona, Spain
| | - Barbara Arias
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, Universitat de Barcelona, Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028, Barcelona, Spain
| | - Julio Bobes
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Faculty of Medicine and Health Sciences - Psychiatry, Universidad de Oviedo, 33006, Oviedo, Spain
- Mental Health Services of Principado de Asturias (SESPA), Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), 33011, Oviedo, Spain
- Instituto de Neurociencias del Principado de Asturias (INEUROPA), 33003, Oviedo, Spain
| | - Javier Costas
- Psychiatric Genetics Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Servizo Galego de Saúde (SERGAS), Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), 15706, Santiago de Compostela, Spain
| | - Lourdes Martorell
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Department of Psychiatry, Universitat Rovira i Virgili (URV), Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, US
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, 80336, Munich, Germany
| | - Elisabet Vilella
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Department of Psychiatry, Universitat Rovira i Virgili (URV), Reus, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
| | - Gerard Muntané
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Department of Psychiatry, Universitat Rovira i Virgili (URV), Reus, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain.
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Yang J, Tao H, Sun F, Fan Z, Yang J, Liu Z, Xue Z, Chen X. The anatomical networks based on probabilistic structurally connectivity in bipolar disorder across mania, depression, and euthymic states. J Affect Disord 2023; 329:42-49. [PMID: 36842653 DOI: 10.1016/j.jad.2023.02.109] [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: 04/10/2022] [Revised: 02/17/2023] [Accepted: 02/21/2023] [Indexed: 02/27/2023]
Abstract
BACKGROUNDS There have pieces of evidence of the distinct aberrant functional network topology profile in bipolar disorder (BD) across mania, depression, and euthymic episodes. However, the underlying anatomical network topology pattern in BD across different episodes is unclear. METHODS We calculated the whole-brain probabilistic structurally connectivity across 143 subjects (72 with BD [34 depression; 13 mania; 25 euthymic] and 53 healthy controls), and used graph theory to examine the trait- and state-related topology alterations of the structural connectome in BD. The correlation analysis was further conducted to explore the relationship between detected network measures and clinical symptoms. RESULTS There no omnibus alteration of any global network metrics were observed across all diagnostic groups. In the regional network metrics level, bipolar depression showed increased clustering coefficient in the right lingual gyrus compared with all other groups, and the increased clustering coefficient in the right lingual gyrus positively correlated with depression, anxiety, and illness burden symptoms but negatively correlated with mania symptoms; manic and euthymic patients showed decreased clustering coefficient in the left inferior occipital gyrus compared with HCs. LIMITATIONS The moderate sample size of all patient groups (especially for subjects with mania) might have contributed to the negative findings of the trait feature in this study. CONCLUSIONS We demonstrated the altered regional connectivity pattern in the occipital lobe of the bipolar depression and mania episode, especially the lingual gyrus. The association of the clustering coefficient in the lingual gyrus with clinical symptoms helps monitor the state of BD.
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Affiliation(s)
- Jie Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Haojuan Tao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Fuping Sun
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Zebin Fan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jun Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Zhening Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Zhimin Xue
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xudong Chen
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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Ben-Azu B, del Re EC, VanderZwaag J, Carrier M, Keshavan M, Khakpour M, Tremblay MÈ. Emerging epigenetic dynamics in gut-microglia brain axis: experimental and clinical implications for accelerated brain aging in schizophrenia. Front Cell Neurosci 2023; 17:1139357. [PMID: 37256150 PMCID: PMC10225712 DOI: 10.3389/fncel.2023.1139357] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 04/27/2023] [Indexed: 06/01/2023] Open
Abstract
Brain aging, which involves a progressive loss of neuronal functions, has been reported to be premature in probands affected by schizophrenia (SCZ). Evidence shows that SCZ and accelerated aging are linked to changes in epigenetic clocks. Recent cross-sectional magnetic resonance imaging analyses have uncovered reduced brain reserves and connectivity in patients with SCZ compared to typically aging individuals. These data may indicate early abnormalities of neuronal function following cyto-architectural alterations in SCZ. The current mechanistic knowledge on brain aging, epigenetic changes, and their neuropsychiatric disease association remains incomplete. With this review, we explore and summarize evidence that the dynamics of gut-resident bacteria can modulate molecular brain function and contribute to age-related neurodegenerative disorders. It is known that environmental factors such as mode of birth, dietary habits, stress, pollution, and infections can modulate the microbiota system to regulate intrinsic neuronal activity and brain reserves through the vagus nerve and enteric nervous system. Microbiota-derived molecules can trigger continuous activation of the microglial sensome, groups of receptors and proteins that permit microglia to remodel the brain neurochemistry based on complex environmental activities. This remodeling causes aberrant brain plasticity as early as fetal developmental stages, and after the onset of first-episode psychosis. In the central nervous system, microglia, the resident immune surveillance cells, are involved in neurogenesis, phagocytosis of synapses and neurological dysfunction. Here, we review recent emerging experimental and clinical evidence regarding the gut-brain microglia axis involvement in SCZ pathology and etiology, the hypothesis of brain reserve and accelerated aging induced by dietary habits, stress, pollution, infections, and other factors. We also include in our review the possibilities and consequences of gut dysbiosis activities on microglial function and dysfunction, together with the effects of antipsychotics on the gut microbiome: therapeutic and adverse effects, role of fecal microbiota transplant and psychobiotics on microglial sensomes, brain reserves and SCZ-derived accelerated aging. We end the review with suggestions that may be applicable to the clinical setting. For example, we propose that psychobiotics might contribute to antipsychotic-induced therapeutic benefits or adverse effects, as well as reduce the aging process through the gut-brain microglia axis. Overall, we hope that this review will help increase the understanding of SCZ pathogenesis as related to chronobiology and the gut microbiome, as well as reveal new concepts that will serve as novel treatment targets for SCZ.
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Affiliation(s)
- Benneth Ben-Azu
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Department of Pharmacology, Faculty of Basic Medical Sciences, College of Health Sciences, Delta State University, Abraka, Nigeria
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- VA Boston Healthcare System, Brockton, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Jared VanderZwaag
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Micaël Carrier
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | | | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Axe Neurosciences, Centre de Recherche du CHU de Québec, Université Laval, Québec City, QC, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
- Department of Molecular Medicine, Université Laval, Québec City, QC, Canada
- Centre for Advanced Materials and Related Technology (CAMTEC), Institute on Aging and Lifelong Health (IALH), University of Victoria, Victoria, BC, Canada
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Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia. Sci Rep 2023; 13:2139. [PMID: 36747015 PMCID: PMC9901842 DOI: 10.1038/s41598-023-29117-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 01/31/2023] [Indexed: 02/08/2023] Open
Abstract
Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. We identified 20 differently expressed proteins that were validated on an independent cohort of patients with schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. and almost half of them are new for schizophrenia. The metabolomic survey revealed 18 group-specific compounds, most of which were the part of transformation of tyrosine and steroids with the prevalence to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.). The GWAS assay mostly failed to reveal significantly associated loci therefore 52 loci with the smoothened p < 10-5 were fractionally integrated into proteome-metabolome data. We integrated three omics layers and powered them by the quantitative analysis to propose a map of molecular events associated with schizophrenia psychopathology. The resulting interplay between different molecular layers emphasizes a strict implication of lipids transport, oxidative stress, imbalance in steroidogenesis and associated impartments of thyroid hormones as key interconnected nodes essential for understanding of how the regulation of distinct metabolic axis is achieved and what happens in the conditioned proteome and metabolome to produce a schizophrenia-specific pattern.
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9
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Alkelai A, Greenbaum L, Shohat S, Povysil G, Malakar A, Ren Z, Motelow JE, Schechter T, Draiman B, Chitrit-Raveh E, Hughes D, Jobanputra V, Shifman S, Goldstein DB, Kohn Y. Genetic insights into childhood-onset schizophrenia: The yield of clinical exome sequencing. Schizophr Res 2023; 252:138-145. [PMID: 36645932 DOI: 10.1016/j.schres.2022.12.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 12/19/2022] [Accepted: 12/26/2022] [Indexed: 01/15/2023]
Abstract
Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset prior to 13 years of age. Although genetic factors play a role in COS etiology, only a few causal variants have been reported to date. This study presents a diagnostic exome sequencing (ES) in 37 Israeli Jewish families with a proband diagnosed with COS. By implementing a trio/duo ES approach and applying a well-established diagnostic pipeline, we detected clinically significant variants in 7 probands (19 %). These single nucleotide variants and indels were mostly inherited. The implicated genes were ANKRD11, GRIA2, CHD2, CLCN3, CLTC, IGF1R and MICU1. In a secondary analysis that compared COS patients to 4721 healthy controls, we observed that patients had a significant enrichment of rare loss of function (LoF) variants in LoF intolerant genes associated with developmental diseases. Taken together, ES could be considered as a valuable tool in the genetic workup for COS patients.
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Affiliation(s)
- Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA; Regeneron Genetics Center, Tarrytown, NY, USA.
| | - Lior Greenbaum
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel; The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tal Aviv University, Tel Aviv, Israel
| | - Shahar Shohat
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Ayan Malakar
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Joshua E Motelow
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA; Department of Pediatrics, Division of Critical Care and Hospital Medicine, Columbia University Irving Medical Center, New York-Presbyterian Morgan Stanley Children's Hospital of New York, New York, NY, USA
| | - Tanya Schechter
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Benjamin Draiman
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Eti Chitrit-Raveh
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Daniel Hughes
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Vaidehi Jobanputra
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA; New York Genome Center, New York, NY, USA
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Yoav Kohn
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel; Hadassah-Hebrew University School of Medicine, Jerusalem, Israel
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10
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Fišar Z. Biological hypotheses, risk factors, and biomarkers of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2023; 120:110626. [PMID: 36055561 DOI: 10.1016/j.pnpbp.2022.110626] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 12/19/2022]
Abstract
Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.
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Affiliation(s)
- Zdeněk Fišar
- Charles University and General University Hospital in Prague, First Faculty of Medicine, Department of Psychiatry, Czech Republic.
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11
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Almodóvar-Payá C, Guardiola-Ripoll M, Giralt-López M, Gallego C, Salgado-Pineda P, Miret S, Salvador R, Muñoz MJ, Lázaro L, Guerrero-Pedraza A, Parellada M, Carrión MI, Cuesta MJ, Maristany T, Sarró S, Fañanás L, Callado LF, Arias B, Pomarol-Clotet E, Fatjó-Vilas M. NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches. Int J Mol Sci 2022; 23:ijms23137456. [PMID: 35806464 PMCID: PMC9267632 DOI: 10.3390/ijms23137456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022] Open
Abstract
Included in the neurotrophins family, the Neuritin 1 gene (NRN1) has emerged as an attractive candidate gene for schizophrenia (SZ) since it has been associated with the risk for the disorder and general cognitive performance. In this work, we aimed to further investigate the association of NRN1 with SZ by exploring its role on age at onset and its brain activity correlates. First, we developed two genetic association analyses using a family-based sample (80 early-onset (EO) trios (offspring onset ≤ 18 years) and 71 adult-onset (AO) trios) and an independent case–control sample (120 healthy subjects (HS), 87 EO and 138 AO patients). Second, we explored the effect of NRN1 on brain activity during a working memory task (N-back task; 39 HS, 39 EO and 39 AO; matched by age, sex and estimated IQ). Different haplotypes encompassing the same three Single Nucleotide Polymorphisms(SNPs, rs3763180–rs10484320–rs4960155) were associated with EO in the two samples (GCT, TCC and GTT). Besides, the GTT haplotype was associated with worse N-back task performance in EO and was linked to an inefficient dorsolateral prefrontal cortex activity in subjects with EO compared to HS. Our results show convergent evidence on the NRN1 association with EO both from genetic and neuroimaging approaches, highlighting the role of neurotrophins in the pathophysiology of SZ.
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Affiliation(s)
- Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Giralt-López
- Departament de Psiquiatria, Hospital Universitari Germans Trias i Pujol (HUGTP), 08916 Badalona, Barcelona, Spain;
- Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain
| | - Carme Gallego
- Department of Cell Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), 08028 Barcelona, Barcelona, Spain;
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Salvador Miret
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Centre de Salut Mental d’Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida, 25198 Lleida, Lleida, Spain
- Institut de Recerca Biomèdica (IRB), 25198 Lleida, Lleida, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - María J. Muñoz
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Luisa Lázaro
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, 08036 Barcelona, Barcelona, Spain
- Departament de Medicina, Universitat de Barcelona (UB), 08036 Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Barcelona, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Mara Parellada
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Servicio de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM), 28007 Madrid, Madrid, Spain
- Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense, 28040 Madrid, Madrid, Spain
| | | | - Manuel J. Cuesta
- Servicio de Psiquiatría, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain;
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), 31008 Pamplona, Navarra, Spain
| | - Teresa Maristany
- Departament de Diagnòstic per la Imatge, Hospital Sant Joan de Déu Fundació de Recerca, 08950 Esplugues de Llobregat, Barcelona, Spain;
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Lourdes Fañanás
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Luis F. Callado
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Pharmacology, University of the Basque Country, UPV/EHU, 48940 Leioa, Bizkaia, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain
| | - Bárbara Arias
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Correspondence: (E.P.-C.); (M.F.-V.)
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Correspondence: (E.P.-C.); (M.F.-V.)
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12
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Yang Y, Su Y, Wei G, Kang Z, Lu Z, Liao Y, Lu T, Yan H, Yue W, Qin Y, Zhang Y. Association of NKAPL rs1635 With Cognitive Function in Early-Onset Schizophrenia. Front Genet 2022; 13:941171. [PMID: 35801084 PMCID: PMC9253766 DOI: 10.3389/fgene.2022.941171] [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: 05/11/2022] [Accepted: 06/01/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND: Schizophrenia is a severe mental disorder with high heritability, and cognitive dysfunction is one of the core features. Growing evidence suggests the genetic risk of schizophrenia may contribute to cognitive impairments. The variant rs1635 (nucleotide sequence: c.455C>A; amino acid sequence: T152N) located on the (NFKB activating protein like) NKAPL gene confers risk for schizophrenia and might play a role in the neurodevelopmental process, which is particularly relevant to cognitive function. However, the relationship between rs1635 and cognitive function remains unclear. METHODS: A total of 130 patients with early-onset schizophrenia (EOS) and 300 patients with adult-onset schizophrenia (AOS) of Han Chinese were recruited and underwent neurocognitive tests by using the MATRICS Consensus Cognitive Battery (MCCB). The NKAPL rs1635 was genotyped by using DNA sequencing. The peripheral blood NKAPL mRNA expression level was examined in 152T or 152N carriers (n = 20) in EOS patients, by using the qRT-PCR. The phosphorylation level of NAKPL T152N polymorphism was detected by cell experiments. In utero electroporation of mouse embryos was examined to explore the effect of Nkapl on neuronal migration. RESULTS: Compared with rs1635 AA and AC carriers, CC (the CC genotype encodes the protein NKAPL-152T) carriers of EOS patients performed better in cognitive domain of speed of processing (t = 2.644, p = 0.009), trail making test (t = 2.221, p = 0.028) and category fluency (t = 2.578, p = 0.011). However, patients with AOS exhibited no significant differences in seven domains among the three genotype groups. There were no significant differences in cognitive performance between EOS and AOS. In EOS patients, NKAPL mRNA level in NKAPL-152N carriers is significantly lower than that of NKAPL-152T carriers. The phosphorylation level of NKAPL-152N is significantly decreased compared to NKAPL-152T. In utero electroporation showed that Nkapl deletion impairs the embryonic radial migration process. CONCLUSION: The present study found that NKAPL rs1635 was associated with cognitive impairments and peripheral blood mRNA expression level in EOS patients. The NKAPL full-length protein is required for embryonic cortical neuronal migration. The phosphorylation level of NKAPL-152N is significantly decreased. The NKAPL T152N may affect the NAKPL mRNA expression level and embryonic cortical neuronal migration by regulating the NAKPL protein phosphorylation. These data suggest that NKAPL rs1635 affects cognitive function by regulating early brain development in early-onset schizophrenia.
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Affiliation(s)
- Yang Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yi Su
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Guiming Wei
- Department of Neurology, Shandong Daizhuang Hospital, Jining, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Ying Qin
- The Second People’s Hospital of Guizhou Province, Guiyang, China
- *Correspondence: Ying Qin, ; Yuyanan Zhang,
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- *Correspondence: Ying Qin, ; Yuyanan Zhang,
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13
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Sun Y, Lv Y, Ren HW, Wang GY, Xuan LN, Luo YY, Luan ZL. Association between MAP3K4 gene polymorphisms and the risk of schizophrenia susceptibility in a Northeast Chinese Han population. Metab Brain Dis 2022; 37:1365-1371. [PMID: 35445959 DOI: 10.1007/s11011-022-00957-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/09/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia stands out as one of the most devastating psychiatric disorders. Previous findings have shown that schizophrenia is a polygenic genetic disorder. Thus, abnormal neurodevelopment and neurogenesis may be associated with the etiology of schizophrenia, so genes which affect these processes may be potential candidate genes of schizophrenia. Mitogen-activated protein kinase kinase kinase 4 (MAP3K4) gene is a member of the mitogen-activated protein kinase family. Taking into account previous findings, MAP3K4 plays a crucial role in the fundamental pathology of various nervous system diseases. In the present study, we aim to explore the association of MAP3K4 and schizophrenia in an independent case-control sample including 627 schizophrenic patients and 1175 healthy controls from a Northeast Chinese Han population. Both the allelic and genotypic association analyses showed that 6 SNPs in MAP3K4 were significantly associated with schizophrenia (rs590988, rs625977, rs9295134, rs12110787, rs1001808 and rs9355870). After rigorous Bonferroni correction, 4 SNPs (rs9295134, rs12110787, rs1001808 and rs9355870) were still significantly associated with the disease. The haplotype composed of these four SNPs also showed significantly global and individual association with schizophrenia. These results suggest that MAP3K4 is a susceptibility gene for schizophrenia in the Northeast Chinese Han population.
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Affiliation(s)
- Yang Sun
- Department of Psychiatry, Dalian Seventh People's Hospital, 116023, Dalian, China
| | - Ye Lv
- Advanced Institute for Medical Sciences, Dalian Medical University, 9 W., S. Lvshun Blvd, 116044, Dalian, China
| | - Hui-Wen Ren
- Advanced Institute for Medical Sciences, Dalian Medical University, 9 W., S. Lvshun Blvd, 116044, Dalian, China
| | - Guan-Yu Wang
- Department of Neurosurgery, Epileptic Center of Liaoning, the Second Affiliated Hospital of Dalian Medical University, 116023, Dalian, China
| | - Li-Na Xuan
- Department of Neurosurgery, Epileptic Center of Liaoning, the Second Affiliated Hospital of Dalian Medical University, 116023, Dalian, China
| | - Yi-Yang Luo
- Advanced Institute for Medical Sciences, Dalian Medical University, 9 W., S. Lvshun Blvd, 116044, Dalian, China
| | - Zhi-Lin Luan
- Advanced Institute for Medical Sciences, Dalian Medical University, 9 W., S. Lvshun Blvd, 116044, Dalian, China.
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Li W, Zhang CY, Liu J, Guan F, Shao M, Zhang L, Liu Q, Yang Y, Su X, Zhang Y, Xiao X, Luo XJ, Li M, Lv L. Identification of a Risk Locus at 7p22.3 for Schizophrenia and Bipolar Disorder in East Asian Populations. Front Genet 2021; 12:789512. [PMID: 34976021 PMCID: PMC8719163 DOI: 10.3389/fgene.2021.789512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 11/23/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Shared psychopathological features and mechanisms have been observed between schizophrenia (SZ) and bipolar disorder (BD), but their common risk genes and full genetic architectures remain to be fully characterized. The genome-wide association study (GWAS) datasets offer the opportunity to explore this scientific question using combined genetic data from enormous samples, ultimately allowing a better understanding of the onset and development of these illnesses. Methods: We have herein performed a genome-wide meta-analysis in two GWAS datasets of SZ and BD respectively (24,600 cases and 40,012 controls in total, discovery sample), followed by replication analyses in an independent sample of 4,918 SZ cases and 5,506 controls of Han Chinese origin (replication sample). The risk SNPs were then explored for their correlations with mRNA expression of nearby genes in multiple expression quantitative trait loci (eQTL) datasets. Results: The single nucleotide polymorphisms (SNPs) rs1637749 and rs3800908 at 7p22.3 region were significant in both discovery and replication samples, and exhibited genome-wide significant associations when combining all East Asian SZ and BD samples (29,518 cases and 45,518 controls). The risk SNPs were also significant in GWAS of SZ and BD among Europeans. Both risk SNPs significantly predicted lower expression of MRM2 in the whole blood and brain samples in multiple datasets, which was consistent with its reduced mRNA level in the brains of SZ patients compared with normal controls. The risk SNPs were also associated with MAD1L1 expression in the whole blood sample. Discussion: We have identified a novel genome-wide risk locus associated with SZ and BD in East Asians, adding further support for the putative common genetic risk of the two illnesses. Our study also highlights the necessity and importance of mining public datasets to explore risk genes for complex psychiatric diseases.
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Affiliation(s)
- Wenqiang Li
- 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
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine and Forensics, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Minglong Shao
- 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
| | - Luwen Zhang
- 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
- 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
- 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
- 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
| | - Yan Zhang
- 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
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- *Correspondence: Ming Li, ; Luxian Lv,
| | - Luxian Lv
- 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
- Henan Province People’s Hospital, Zhengzhou, China
- *Correspondence: Ming Li, ; Luxian Lv,
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15
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Zhang L, Li Z, Liu Q, Shao M, Sun F, Su X, Song M, Zhang Y, Ding M, Lu Y, Liu J, Yang Y, Li M, Li W, Lv L. Weak Association Between the Glutamate Decarboxylase 1 Gene (GAD1) and Schizophrenia in Han Chinese Population. Front Neurosci 2021; 15:677153. [PMID: 34234640 PMCID: PMC8255988 DOI: 10.3389/fnins.2021.677153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 05/26/2021] [Indexed: 11/15/2022] Open
Abstract
Objectives Schizophrenia (SZ) is a complex psychiatric disorder with high heritability, and genetic components are thought to be pivotal risk factors for this illness. The glutamate decarboxylase 1 gene (GAD1) was hypothesized to be a candidate risk locus for SZ given its crucial role in the GABAergic neurotransmission system, and previous studies have examined the associations of single nucleotide polymorphisms (SNPs) spanning the GAD1 gene with SZ. However, inconsistent results were obtained. We hence examined the associations between GAD1 SNPs and SZ in two independent case-control samples of Han Chinese ancestry. Materials and Methods Two Han Chinese SZ case-control samples, referred as the discovery sample and the replication sample, respectively, were recruited for the current study. The discovery sample comprised of 528 paranoid SZ cases (with age of first onset ≥ 18) and 528 healthy controls; the independent replication sample contained 1,256 early onset SZ cases (with age of first onset < 18) and 2,661 healthy controls. Logistic regression analysis was performed to examine the associations between GAD1 SNPs and SZ. Results Ten SNPs covering GAD1 gene were analyzed in the discovery sample, and two SNPs showed nominal associations with SZ (rs2241165, P = 0.0181, OR = 1.261; rs2241164, P = 0.0225, OR = 1.219). SNP rs2241164 was also nominally significant in the independent replication sample (P = 0.0462, OR = 1.110), and the significance became stronger in a subsequent meta-analysis combining both discovery and replication samples (P = 0.00398, OR = 1.138). Nevertheless, such association could not survive multiple corrections, although the effect size of rs2241164 was comparable with other SZ risk loci identified in genome-wide association studies (GWAS) in Han Chinese population. We also examined the associations between GAD1 SNPs and SZ in published datasets of SZ GWAS in East Asians and Europeans, and no significant associations were observed. Conclusion We observed weak associations between GAD1 SNPs and risk of SZ in Han Chinese populations. Further analyses in larger Han Chinese samples with more detailed phenotyping are necessary to elucidate the genetic correlation between GAD1 SNPs and SZ.
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Affiliation(s)
- Luwen Zhang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Zhen Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Qing Liu
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Minglong Shao
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Fuping Sun
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xi Su
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Meng Song
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yan Zhang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Minli Ding
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Yanli Lu
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yongfeng Yang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Ming Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Wenqiang Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luxian Lv
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China.,Henan Province People's Hospital, Zhengzhou, China
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