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Zhang Z, Xiao Y, Zhao S, Liu J, Zeng J, Xiao F, Liao B, Shan X, Zhu H, Guo H. FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs). J Transl Med 2024; 22:833. [PMID: 39256832 PMCID: PMC11389277 DOI: 10.1186/s12967-024-05641-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 08/29/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Family with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed. METHODS A comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan-Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments. RESULTS FAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times. CONCLUSIONS FAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.
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Affiliation(s)
- Zhe Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Yao Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Siyi Zhao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jun Liu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jie Zeng
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Feng Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Bin Liao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Xuesong Shan
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Hong Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
- Institute of Neuroscience, Nanchang University, Jiangxi, China.
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China.
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China.
| | - Hua Guo
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
- Institute of Neuroscience, Nanchang University, Jiangxi, China.
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China.
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China.
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Yang XZ, Huang MY, Han F, Ni J, Zhou LX, Yao M, Zhang DD, Zhu YC. Genome-Wide Mendelian Randomization Study Reveals Druggable Genes for Cerebral Small Vessel Disease. Stroke 2024; 55:2264-2273. [PMID: 39114924 DOI: 10.1161/strokeaha.124.046544] [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: 01/17/2024] [Revised: 07/10/2024] [Accepted: 07/18/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is a group of neurological disorders that affect the small blood vessels within the brain, for which no effective treatments are currently available. We conducted a Mendelian randomization (MR) study to identify candidate therapeutic genes for CSVD. METHODS We retrieved genome-wide association study data from 6 recently conducted, extensive investigations focusing on CSVD magnetic resonance imaging markers and performed a 2-sample MR analysis to assess the potential causal effects of gene expression and protein level within druggable genes on CSVD in blood and brain tissues. Colocalization analyses and repeat studies were undertaken to verify the relationship. Additionally, mediation analysis was conducted to explore the potential mechanisms involving druggable genes and known risk factors for CSVD. Finally, phenome-wide MR analyses were applied to evaluate the potential adverse effects related to the identified druggable genes for CSVD treatment. RESULTS Overall, 5 druggable genes consistently showed associations with CSVD in MR analyses across both the discovery and validation cohorts. Notably, the ALDH2 and KLHL24 genes were identified as associated with CSVD in both blood and brain tissues, whereas the genes ADRB1, BTN3A2, and EFEMP1 were exclusively detected in brain tissue. Moreover, mediation analysis elucidated the proportion of the total effects mediated by CSVD risk factors through candidate druggable genes, which ranged from 5.5% to 18.5%, and offered potential explanations for the observed results. A comprehensive phenome-wide MR analysis further emphasized both the therapeutic benefits and potential side effects of targeting these candidate druggable genes. CONCLUSIONS This study provides genetic evidence supporting the potential therapeutic benefits of targeting druggable genes for treating CSVD, which will be useful for prioritizing CSVD drug development.
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Affiliation(s)
- Xin-Zhuang Yang
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
- Center for Bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine & Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y.)
| | - Mei-Ying Huang
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
| | - Fei Han
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
| | - Jun Ni
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
| | - Li-Xin Zhou
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
| | - Ming Yao
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
| | - Ding-Ding Zhang
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
- Center for Prevention and Early Intervention, National Infrastructures for Translational Medicine, Institute of Clinical Medicine & Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.-D.Z.)
| | - Yi-Cheng Zhu
- Department of Neurology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China (X.-Z.Y., M.-Y.H., F.H., J.-N., L.-X.Z., M.Y., D.-D.Z., Y.-C.Z.)
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Nair PC, Mangoni AA, Rodionov RN. Redefining the biological and pathophysiological role of dimethylarginine dimethylaminohydrolase 2. Trends Mol Med 2024; 30:552-561. [PMID: 38553332 DOI: 10.1016/j.molmed.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/01/2024] [Accepted: 03/07/2024] [Indexed: 06/15/2024]
Abstract
The enzyme dimethylarginine dimethylaminohydrolase (DDAH) 1 metabolizes asymmetric dimethylarginine (ADMA), a critical endogenous cardiovascular risk factor. In the past two decades, there has been significant controversy about whether DDAH2, the other DDAH isoform, is also able to directly metabolize ADMA. There has been evidence that DDAH2 regulates several critical processes involved in cardiovascular and immune homeostasis. However, the molecular mechanisms underpinning these effects are unclear. In this opinion, we discuss the previous and current knowledge of ADMA metabolism by DDAH in light of a recent consortium study, which convincingly demonstrated that DDAH2 is not capable of metabolizing ADMA, unlike DDAH1. Thus, further research in this field is needed to uncover the molecular mechanisms of DDAH2 and its role in various disorders.
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Affiliation(s)
- Pramod C Nair
- Discipline of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia; Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia; South Australian Health and Medical Research Institute, University of Adelaide, Adelaide, SA, Australia; Discipline of Medicine, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia.
| | - Arduino A Mangoni
- Discipline of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia; Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Bedford Park, SA, Australia
| | - Roman N Rodionov
- Department of Internal Medicine III, Technische Universität Dresden, Dresden, Germany
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De Ridder D, Siddiqi MA, Dauwels J, Serdijn WA, Strydis C. NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed? Neuromodulation 2024; 27:711-729. [PMID: 38639704 DOI: 10.1016/j.neurom.2024.01.003] [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: 08/07/2023] [Revised: 11/05/2023] [Accepted: 01/10/2024] [Indexed: 04/20/2024]
Abstract
OBJECTIVES Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement. The goal of this manuscript is to 1) develop a general theoretical framework of brain functioning that is amenable to surgical neuromodulation, and 2) describe the engineering requirements of the next generation of implantable brain stimulators that follow from this theoretic model. MATERIALS AND METHODS A neuroscience and engineering literature review was performed to develop a universal theoretical model of brain functioning and dysfunctioning amenable to surgical neuromodulation. RESULTS Even though a single target can modulate an entire network, research in network science reveals that many brain disorders are the consequence of maladaptive interactions among multiple networks rather than a single network. Consequently, targeting the main connector hubs of those multiple interacting networks involved in a brain disorder is theoretically more beneficial. We, thus, envision next-generation network implants that will rely on distributed, multisite neuromodulation targeting correlated and anticorrelated interacting brain networks, juxtaposing alternative implant configurations, and finally providing solid recommendations for the realization of such implants. In doing so, this study pinpoints the potential shortcomings of other similar efforts in the field, which somehow fall short of the requirements. CONCLUSION The concept of network stimulation holds great promise as a universal approach for treating neurologic and psychiatric disorders.
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Affiliation(s)
- Dirk De Ridder
- Section of Neurosurgery, Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
| | - Muhammad Ali Siddiqi
- Department of Electrical Engineering, Lahore University of Management Sciences, Lahore, Pakistan; Neuroscience Department, Erasmus Medical Center, Rotterdam, The Netherlands; Quantum and Computer Engineering Department, Delft University of Technology, Delft, The Netherlands
| | - Justin Dauwels
- Microelectronics Department, Delft University of Technology, Delft, The Netherlands
| | - Wouter A Serdijn
- Neuroscience Department, Erasmus Medical Center, Rotterdam, The Netherlands; Section Bioelectronics, Delft University of Technology, Delft, The Netherlands
| | - Christos Strydis
- Neuroscience Department, Erasmus Medical Center, Rotterdam, The Netherlands; Quantum and Computer Engineering Department, Delft University of Technology, Delft, The Netherlands
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5
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Moodie JE, Harris SE, Harris MA, Buchanan CR, Davies G, Taylor A, Redmond P, Liewald D, del C Valdés Hernández M, Shenkin S, Russ TC, Muñoz Maniega S, Luciano M, Corley J, Stolicyn A, Shen X, Steele D, Waiter G, Sandu-Giuraniuc A, Bastin ME, Wardlaw JM, McIntosh A, Whalley H, Tucker-Drob EM, Deary IJ, Cox SR. General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532915. [PMID: 36993650 PMCID: PMC10055068 DOI: 10.1101/2023.03.16.532915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
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Affiliation(s)
- Joanna E. Moodie
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Mathew A. Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Colin R. Buchanan
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - David Liewald
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Maria del C Valdés Hernández
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Susan Shenkin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Ageing and Health Research Group, Usher Institute, University of Edinburgh, UK
| | - Tom C. Russ
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Michelle Luciano
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Douglas Steele
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Gordon Waiter
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Anca Sandu-Giuraniuc
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Mark E. Bastin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Joanna M. Wardlaw
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Heather Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
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Mou T, Liang J, Vu TN, Tian M, Gao Y. A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue. SENSORS (BASEL, SWITZERLAND) 2023; 23:1432. [PMID: 36772473 PMCID: PMC9921444 DOI: 10.3390/s23031432] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/15/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.
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Affiliation(s)
- Tian Mou
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518000, China
| | - Jianwen Liang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518000, China
| | - Trung Nghia Vu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SE 17177 Stockholm, Sweden
| | - Mu Tian
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518000, China
| | - Yi Gao
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518000, China
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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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Wang Y, Wang X, Yang C, Hua W, Wang H. m6A Regulator-Mediated RNA Methylation Modification Patterns are Involved in the Pathogenesis and Immune Microenvironment of Depression. Front Genet 2022; 13:865695. [PMID: 35480327 PMCID: PMC9035487 DOI: 10.3389/fgene.2022.865695] [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: 01/30/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022] Open
Abstract
Depression is a genetical disease characterized by neuroinflammatory symptoms and is difficult to diagnose and treat effectively. Recently, modification of N6-methyladenosine (m6A) at the gene level was shown to be closely related to immune regulation. This study was conducted to explore the effect of m6A modifications on the occurrence of depression and composition of the immune microenvironment. We downloaded gene expression profile data of healthy and depressed rats from the Gene Expression Omnibus. We described the overall expression of m6A regulators in animal models of depression and constructed risk and clinical prediction models using training and validation sets. Bioinformatics analysis was performed using gene ontology functions, gene set enrichment analysis, gene set variation analysis, weighted gene co-expression network analysis, and protein-protein interaction networks. We used CIBERSORT to identify immune-infiltrating cells in depression and perform correlation analysis. We then constructed two molecular subtypes of depression and assessed the correlation between the key genes and molecular subtypes. Through differential gene analysis of m6A regulators in depressed rats, we identified seven m6A regulators that were significantly upregulated in depressed rats and successfully constructed a clinical prediction model. Gene Ontology functional annotation showed that the m6A regulators enriched differentially expressed genes in biological processes, such as the regulation of mRNA metabolic processes. Further, 12 hub genes were selected from the protein-protein interaction network. Immune cell infiltration analysis showed that levels of inflammatory cells, such as CD4 T cells, were significantly increased in depressed rats and were significantly correlated with the depression hub genes. Depression was divided into two subtypes, and the correlation between hub genes and these two subtypes was clarified. We described the effect of m6A modification on the pathogenesis of depression, focusing on the role of inflammatory infiltration.
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Affiliation(s)
- Ye Wang
- The Third Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Xinyi Wang
- The Third Central Clinical College of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, China
- Nankai University Affinity the Third Central Hospital, Tianjin, China
| | - Chenyi Yang
- The Third Central Clinical College of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, China
- Nankai University Affinity the Third Central Hospital, Tianjin, China
| | - Wei Hua
- The Third Central Clinical College of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, China
- Nankai University Affinity the Third Central Hospital, Tianjin, China
| | - Haiyun Wang
- The Third Central Clinical College of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, China
- Nankai University Affinity the Third Central Hospital, Tianjin, China
- *Correspondence: Haiyun Wang,
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