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Zhang C, Yang Z, Li X, Zhao L, Guo W, Deng W, Wang Q, Hu X, Li M, Sham PC, Xiao X, Li T. Unraveling NEK4 as a Potential Drug Target in Schizophrenia and Bipolar I Disorder: A Proteomic and Genomic Approach. Schizophr Bull 2024; 50:1185-1196. [PMID: 38869147 PMCID: PMC11349004 DOI: 10.1093/schbul/sbae094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
BACKGROUND AND HYPOTHESIS Investigating the shared brain protein and genetic components of schizophrenia (SCZ) and bipolar I disorder (BD-I) presents a unique opportunity to understand the underlying pathophysiological processes and pinpoint potential drug targets. STUDY DESIGN To identify overlapping susceptibility brain proteins in SCZ and BD-I, we carried out proteome-wide association studies (PWAS) and Mendelian Randomization (MR) by integrating human brain protein quantitative trait loci with large-scale genome-wide association studies for both disorders. We utilized transcriptome-wide association studies (TWAS) to determine the consistency of mRNA-protein dysregulation in both disorders. We applied pleiotropy-informed conditional false discovery rate (pleioFDR) analysis to identify common risk genetic loci for SCZ and BD-I. Additionally, we performed a cell-type-specific analysis in the human brain to detect risk genes notably enriched in distinct brain cell types. The impact of risk gene overexpression on dendritic arborization and axon length in neurons was also examined. STUDY RESULTS Our PWAS identified 42 proteins associated with SCZ and 14 with BD-I, among which NEK4, HARS2, SUGP1, and DUS2 were common to both conditions. TWAS and MR analysis verified the significant risk gene NEK4 for both SCZ and BD-I. PleioFDR analysis further supported genetic risk loci associated with NEK4 for both conditions. The cell-type specificity analysis revealed that NEK4 is expressed on the surface of glutamatergic neurons, and its overexpression enhances dendritic arborization and axon length in cultured primary neurons. CONCLUSIONS These findings underscore a shared genetic origin for SCZ and BD-I, offering novel insights for potential therapeutic target identification.
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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
- Nanhu Brain-Computer Interface Institute, Hangzhou, China
| | - ZhiHui Yang
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiaojing Li
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 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
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wanjun Guo
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 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
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 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
| | - 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 Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ming Li
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 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
| | - Xiao Xiao
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Tao Li
- Nanhu Brain-Computer Interface Institute, Hangzhou, China
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 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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Huang D, Ovcharenko I. The contribution of silencer variants to human diseases. Genome Biol 2024; 25:184. [PMID: 38978133 PMCID: PMC11232194 DOI: 10.1186/s13059-024-03328-1] [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: 12/18/2023] [Accepted: 06/28/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Although disease-causal genetic variants have been found within silencer sequences, we still lack a comprehensive analysis of the association of silencers with diseases. Here, we profiled GWAS variants in 2.8 million candidate silencers across 97 human samples derived from a diverse panel of tissues and developmental time points, using deep learning models. RESULTS We show that candidate silencers exhibit strong enrichment in disease-associated variants, and several diseases display a much stronger association with silencer variants than enhancer variants. Close to 52% of candidate silencers cluster, forming silencer-rich loci, and, in the loci of Parkinson's-disease-hallmark genes TRIM31 and MAL, the associated SNPs densely populate clustered candidate silencers rather than enhancers displaying an overall twofold enrichment in silencers versus enhancers. The disruption of apoptosis in neuronal cells is associated with both schizophrenia and bipolar disorder and can largely be attributed to variants within candidate silencers. Our model permits a mechanistic explanation of causative SNP effects by identifying altered binding of tissue-specific repressors and activators, validated with a 70% of directional concordance using SNP-SELEX. Narrowing the focus of the analysis to individual silencer variants, experimental data confirms the role of the rs62055708 SNP in Parkinson's disease, rs2535629 in schizophrenia, and rs6207121 in type 1 diabetes. CONCLUSIONS In summary, our results indicate that advances in deep learning models for the discovery of disease-causal variants within candidate silencers effectively "double" the number of functionally characterized GWAS variants. This provides a basis for explaining mechanisms of action and designing novel diagnostics and therapeutics.
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Affiliation(s)
- Di Huang
- Intramural Research Program, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ivan Ovcharenko
- Intramural Research Program, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20892, USA.
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Zhang Y, Shi C, Wu H, Yan H, Xia M, Jiao H, Zhou D, Wu W, Zhong M, Lou W, Gao X, Bian H, Chang X. Characteristics of changes in plasma proteome profiling after sleeve gastrectomy. Front Endocrinol (Lausanne) 2024; 15:1330139. [PMID: 38375199 PMCID: PMC10875463 DOI: 10.3389/fendo.2024.1330139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/17/2024] [Indexed: 02/21/2024] Open
Abstract
Bariatric surgery (BS), recognized as the most effective intervention for morbid obesity and associated metabolic comorbidities, encompasses both weight loss-dependent and weight loss-independent mechanisms to exert its metabolic benefits. In this study, we employed plasma proteomics technology, a recently developed mass spectrometric approach, to quantitatively assess 632 circulating proteins in a longitudinal cohort of 9 individuals who underwent sleeve gastrectomy (SG). Through time series clustering and Gene Ontology (GO) enrichment analysis, we observed that complement activation, proteolysis, and negative regulation of triglyceride catabolic process were the primary biological processes enriched in down-regulated proteins. Conversely, up-regulated differentially expressed proteins (DEPs) were significantly associated with negative regulation of peptidase activity, fibrinolysis, keratinocyte migration, and acute-phase response. Notably, we identified seven proteins (ApoD, BCHE, CNDP1, AFM, ITIH3, SERPINF1, FCN3) that demonstrated significant alterations at 1-, 3-, and 6-month intervals post SG, compared to baseline. These proteins play essential roles in metabolism, immune and inflammatory responses, as well as oxidative stress. Consequently, they hold promising potential as therapeutic targets for combating obesity and its associated comorbidities.
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Affiliation(s)
- Yuying Zhang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chenye Shi
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Haifu Wu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hongmei Yan
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Heng Jiao
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Di Zhou
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wei Wu
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ming Zhong
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wenhui Lou
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hua Bian
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xinxia Chang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China
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Li W, Chen R, Feng L, Dang X, Liu J, Chen T, Yang J, Su X, Lv L, Li T, Zhang Z, Luo XJ. Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders. Nat Hum Behav 2024; 8:361-379. [PMID: 37945807 DOI: 10.1038/s41562-023-01746-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 10/04/2023] [Indexed: 11/12/2023]
Abstract
Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.
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Affiliation(s)
- Wenqiang Li
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Rui Chen
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Laipeng Feng
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Xinglun Dang
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Tengfei Chen
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Jinfeng Yang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xi Su
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Luxian Lv
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhijun Zhang
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China
- Department of Neurology, Affiliated Zhongda Hospital, Southeast University, Nanjing, China
- Department of Mental Health and Public Health, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xiong-Jian Luo
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China.
- Department of Neurology, Affiliated Zhongda Hospital, Southeast University, Nanjing, China.
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Wahbeh MH, Boyd RJ, Yovo C, Rike B, McCallion AS, Avramopoulos D. A Functional Schizophrenia-associated genetic variant near the TSNARE1 and ADGRB1 genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.570831. [PMID: 38187620 PMCID: PMC10769312 DOI: 10.1101/2023.12.18.570831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Recent collaborative genome wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes; yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated 4 isogenic clones homozygous for the risk allele and 5 clones homozygous for the non-risk allele into neural precursor cells. Employing RNA-seq, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at FDR <0.05 and 259 genes at FDR <0.1. We demonstrate that these genes are highly interconnected in pathways enriched for synaptic proteins, axon guidance, and regulation of synapse assembly. Exploration of genes near rs4129585 suggests that this variant does not regulate TSNARE1 transcripts, as previously thought, but may regulate the neighboring ADGRB1, a regulator of synaptogenesis. Our results suggest that rs4129585 is a functional common variant that functions in specific pathways likely involved in SCZ risk.
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Affiliation(s)
- Marah H Wahbeh
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Rachel J Boyd
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Christian Yovo
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Bailey Rike
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Andrew S McCallion
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Dimitrios Avramopoulos
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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Price E, Fedida LM, Pugacheva EM, Ji YJ, Loukinov D, Lobanenkov VV. An updated catalog of CTCF variants associated with neurodevelopmental disorder phenotypes. Front Mol Neurosci 2023; 16:1185796. [PMID: 37324587 PMCID: PMC10264798 DOI: 10.3389/fnmol.2023.1185796] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 05/02/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction CTCF-related disorder (CRD) is a neurodevelopmental disorder (NDD) caused by monoallelic pathogenic variants in CTCF. The first CTCF variants in CRD cases were documented in 2013. To date, 76 CTCF variants have been further described in the literature. In recent years, due to the increased application of next-generation sequencing (NGS), growing numbers of CTCF variants are being identified, and multiple genotype-phenotype databases cataloging such variants are emerging. Methods In this study, we aimed to expand the genotypic spectrum of CRD, by cataloging NDD phenotypes associated with reported CTCF variants. Here, we systematically reviewed all known CTCF variants reported in case studies and large-scale exome sequencing cohorts. We also conducted a meta-analysis using public variant data from genotype-phenotype databases to identify additional CTCF variants, which we then curated and annotated. Results From this combined approach, we report an additional 86 CTCF variants associated with NDD phenotypes that have not yet been described in the literature. Furthermore, we describe and explain inconsistencies in the quality of reported variants, which impairs the reuse of data for research of NDDs and other pathologies. Discussion From this integrated analysis, we provide a comprehensive and annotated catalog of all currently known CTCF mutations associated with NDD phenotypes, to aid diagnostic applications, as well as translational and basic research.
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Tiukacheva EA, Ulianov SV, Karpukhina A, Razin SV, Vassetzky Y. 3D genome alterations and editing in pathology. Mol Ther 2023; 31:924-933. [PMID: 36755493 PMCID: PMC10124079 DOI: 10.1016/j.ymthe.2023.02.005] [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] [Received: 07/25/2022] [Revised: 12/07/2022] [Accepted: 02/03/2023] [Indexed: 02/10/2023] Open
Abstract
The human genome is folded into a multi-level 3D structure that controls many nuclear functions including gene expression. Recently, alterations in 3D genome organization were associated with several genetic diseases and cancer. As a consequence, experimental approaches are now being developed to modify the global 3D genome organization and that of specific loci. Here, we discuss emerging experimental approaches of 3D genome editing that may prove useful in biomedicine.
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Affiliation(s)
- Eugenia A Tiukacheva
- CNRS UMR9018, Institut Gustave Roussy, 94805 Villejuif, France; Institute of Gene Biology, Moscow 119334, Russia; Moscow Institute of Physics and Technology, Moscow 141700, Russia; Faculty of Biology, Lomonosov Moscow State University, Moscow 119991, Russia; Koltzov Institute of Developmental Biology, Moscow 119334, Russia
| | - Sergey V Ulianov
- Institute of Gene Biology, Moscow 119334, Russia; Faculty of Biology, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Anna Karpukhina
- CNRS UMR9018, Institut Gustave Roussy, 94805 Villejuif, France; Koltzov Institute of Developmental Biology, Moscow 119334, Russia
| | - Sergey V Razin
- Institute of Gene Biology, Moscow 119334, Russia; Faculty of Biology, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Yegor Vassetzky
- CNRS UMR9018, Institut Gustave Roussy, 94805 Villejuif, France; Koltzov Institute of Developmental Biology, Moscow 119334, Russia.
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Karpov D, Golimbet V. Cellular and supracellular models in the study of molecular mechanisms associated with schizophrenia. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:46-50. [DOI: 10.17116/jnevro202212211146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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