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Zhao Y, Zhong Y, Chen W, Chang S, Cao Q, Wang Y, Yang L. Ocular and neural genes jointly regulate the visuospatial working memory in ADHD children. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2023; 19:14. [PMID: 37658396 PMCID: PMC10472596 DOI: 10.1186/s12993-023-00216-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 08/16/2023] [Indexed: 09/03/2023]
Abstract
OBJECTIVE Working memory (WM) deficits have frequently been linked to attention deficit hyperactivity disorder (ADHD). Despite previous studies suggested its high heritability, its genetic basis, especially in ADHD, remains unclear. The current study aimed to comprehensively explore the genetic basis of visual-spatial working memory (VSWM) in ADHD using wide-ranging genetic analyses. METHODS The current study recruited a cohort consisted of 802 ADHD individuals, all met DSM-IV ADHD diagnostic criteria. VSWM was assessed by Rey-Osterrieth complex figure test (RCFT), which is a widely used psychological test include four memory indexes: detail delayed (DD), structure delayed (SD), structure immediate (SI), detail immediate (DI). Genetic analyses were conducted at the single nucleotide polymorphism (SNP), gene, pathway, polygenic and protein network levels. Polygenic Risk Scores (PRS) were based on summary statistics of various psychiatric disorders, including ADHD, autism spectrum disorder (ASD), major depressive disorder (MDD), schizophrenia (SCZ), obsessive compulsive disorders (OCD), and substance use disorder (SUD). RESULTS Analyses at the single-marker level did not yield significant results (5E-08). However, the potential signals with P values less than E-05 and their mapped genes suggested the regulation of VSWM involved both ocular and neural system related genes, moreover, ADHD-related genes were also involved. The gene-based analysis found RAB11FIP1, whose encoded protein modulates several neurodevelopment processes and visual system, as significantly associated with DD scores (P = 1.96E-06, Padj = 0.036). Candidate pathway enrichment analyses (N = 53) found that forebrain neuron fate commitment significantly enriched in DD (P = 4.78E-04, Padj = 0.025), and dopamine transport enriched in SD (P = 5.90E-04, Padj = 0.031). We also observed a significant negative relationship between DD scores and ADHD PRS scores (P = 0.0025, Empirical P = 0.048). CONCLUSIONS Our results emphasized the joint contribution of ocular and neural genes in regulating VSWM. The study reveals a shared genetic basis between ADHD and VSWM, with GWAS indicating the involvement of ADHD-related genes in VSWM. Additionally, the PRS analysis identifies a significant relationship between ADHD-PRS and DD scores. Overall, our findings shed light on the genetic basis of VSWM deficits in ADHD, and may have important implications for future research and clinical practice.
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Affiliation(s)
- Yilu Zhao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Yuanxin Zhong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
| | - Wei Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Qingjiu Cao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Yufeng Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Li Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), 51 Huayuan Bei Road, Beijing, 100191, China.
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Li Z, Dang W, Hao T, Zhang H, Yao Z, Zhou W, Deng L, Yu H, Wen Y, Liu L. Shared genetics and causal relationships between major depressive disorder and COVID-19 related traits: a large-scale genome-wide cross-trait meta-analysis. Front Psychiatry 2023; 14:1144697. [PMID: 37426090 PMCID: PMC10328439 DOI: 10.3389/fpsyt.2023.1144697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 05/31/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction The comorbidity between major depressive disorder (MDD) and coronavirus disease of 2019 (COVID-19) related traits have long been identified in clinical settings, but their shared genetic foundation and causal relationships are unknown. Here, we investigated the genetic mechanisms behind COVID-19 related traits and MDD using the cross-trait meta-analysis, and evaluated the underlying causal relationships between MDD and 3 different COVID-19 outcomes (severe COVID-19, hospitalized COVID-19, and COVID-19 infection). Methods In this study, we conducted a comprehensive analysis using the most up-to-date and publicly available GWAS summary statistics to explore shared genetic etiology and the causality between MDD and COVID-19 outcomes. We first used genome-wide cross-trait meta-analysis to identify the pleiotropic genomic SNPs and the genes shared by MDD and COVID-19 outcomes, and then explore the potential bidirectional causal relationships between MDD and COVID-19 outcomes by implementing a bidirectional MR study design. We further conducted functional annotations analyses to obtain biological insight for shared genes from the results of cross-trait meta-analysis. Results We have identified 71 SNPs located on 25 different genes are shared between MDD and COVID-19 outcomes. We have also found that genetic liability to MDD is a causal factor for COVID-19 outcomes. In particular, we found that MDD has causal effect on severe COVID-19 (OR = 1.832, 95% CI = 1.037-3.236) and hospitalized COVID-19 (OR = 1.412, 95% CI = 1.021-1.953). Functional analysis suggested that the shared genes are enriched in Cushing syndrome, neuroactive ligand-receptor interaction. Discussion Our findings provide convincing evidence on shared genetic etiology and causal relationships between MDD and COVID-19 outcomes, which is crucial to prevention, and therapeutic treatment of MDD and COVID-19.
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Affiliation(s)
- Ziqi Li
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Weijia Dang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Tianqi Hao
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Hualin Zhang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ziwei Yao
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wenchao Zhou
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Liufei Deng
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Hongmei Yu
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yalu Wen
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Long Liu
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
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Bai L, Yang G, Qin Z, Lyu J, Wang Y, Feng J, Liu M, Gong T, Li X, Li Z, Li J, Qin J, Yang W, Ding C. Proteome-Wide Profiling of Readers for DNA Modification. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101426. [PMID: 34351703 PMCID: PMC8498917 DOI: 10.1002/advs.202101426] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/02/2021] [Indexed: 05/13/2023]
Abstract
DNA modifications, represented by 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC), play important roles in epigenetic regulation of biological processes. The specific recognition of DNA modifications by the transcriptional protein machinery is thought to be a potential mechanism for epigenetic-driven gene regulation, and many modified DNA-specific binding proteins have been uncovered. However, the panoramic view of the roles of DNA modification readers at the proteome level remains largely unclear. Here, a recently developed concatenated tandem array of consensus transcription factor (TF) response elements (catTFREs) approach is employed to profile the binding activity of TFs at DNA modifications. Modified DNA-binding activity is quantified for 1039 TFs, representing 70% of the TFs in the human genome. Additionally, the modified DNA-binding activity of 600 TFs is monitored during the mouse brain development from the embryo to the adult stages. Readers of these DNA modifications are predicted, and the hierarchical networks between the transcriptional protein machinery and modified DNA are described. It is further demonstrated that ZNF24 and ZSCAN21 are potential readers of 5fC-modified DNA. This study provides a landscape of TF-DNA modification interactions that can be used to elucidate the epigenetic-related transcriptional regulation mechanisms under physiological conditions.
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Affiliation(s)
- Lin Bai
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Guojian Yang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Zhaoyu Qin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Jiacheng Lyu
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Yunzhi Wang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Jinwen Feng
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Mingwei Liu
- State Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (The PHOENIX Center, Beijing)Institute of LifeomicsBeijing102206China
| | - Tongqing Gong
- State Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (The PHOENIX Center, Beijing)Institute of LifeomicsBeijing102206China
| | - Xianju Li
- State Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (The PHOENIX Center, Beijing)Institute of LifeomicsBeijing102206China
| | - Zhengyang Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Jixi Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
| | - Jun Qin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
- State Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (The PHOENIX Center, Beijing)Institute of LifeomicsBeijing102206China
| | - Wenjun Yang
- Department of Pediatric OrthopedicsXin Hua Hospital AffiliatedShanghai Jiao Tong University School of MedicineShanghai200092China
| | - Chen Ding
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesInstitute of Biomedical SciencesHuman Phenome InstituteZhongshan HospitalFudan UniversityShanghai200433China
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