|
1
|
Yang H, Sun W, Li J, Zhang X. Epigenetics factors in schizophrenia: future directions for etiologic and therapeutic study approaches. Ann Gen Psychiatry 2025; 24:21. [PMID: 40186258 PMCID: PMC11969811 DOI: 10.1186/s12991-025-00557-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 03/14/2025] [Indexed: 04/07/2025] Open
Abstract
Schizophrenia is a complex, heterogeneous, and highly disabling severe mental disorder whose pathogenesis has not yet been fully elucidated. Epigenetics, as a bridge between genetic and environmental factors, plays an important role in the pathophysiology of schizophrenia. Over the past decade, epigenetic-wide association studies have rapidly become an important branch of psychiatric research, especially in deciphering the molecular mechanisms of schizophrenia. This review systematically analyzes recent advances in epigenome-wide association studies (EWAS) of schizophrenia, focusing on technological developments. We synthesize findings from large-scale EWAS alongside emerging evidence on DNA methylation patterns, histone modifications, and regulatory networks, emphasizing their roles in disease mechanisms and treatment responses. In addition, this review provides a prospective outlook, evaluating the impact that technological developments may have on future studies of schizophrenia. With the continuous advancement of high-throughput sequencing technology and the increasing maturity of big data analysis methods, epigenetics is expected to have a significant impact on the early diagnosis, prognosis assessment and even personalized treatment of schizophrenia.
Collapse
Affiliation(s)
- Haidong Yang
- Department of Psychiatry, The Fourth People's Hospital of Lianyungang, The Affiliated KangDa College of Nanjing Medical University, Lianyungang, 222003, People's Republic of China
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, People's Republic of China
| | - Wenxi Sun
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, People's Republic of China
| | - Jin Li
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, People's Republic of China
| | - Xiaobin Zhang
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, People's Republic of China.
| |
Collapse
|
|
2
|
Weekley BH, Ahmed NI, Maze I. Elucidating neuroepigenetic mechanisms to inform targeted therapeutics for brain disorders. iScience 2025; 28:112092. [PMID: 40160416 PMCID: PMC11951040 DOI: 10.1016/j.isci.2025.112092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2025] Open
Abstract
The evolving field of neuroepigenetics provides important insights into the molecular foundations of brain function. Novel sequencing technologies have identified patient-specific mutations and gene expression profiles involved in shaping the epigenetic landscape during neurodevelopment and in disease. Traditional methods to investigate the consequences of chromatin-related mutations provide valuable phenotypic insights but often lack information on the biochemical mechanisms underlying these processes. Recent studies, however, are beginning to elucidate how structural and/or functional aspects of histone, DNA, and RNA post-translational modifications affect transcriptional landscapes and neurological phenotypes. Here, we review the identification of epigenetic regulators from genomic studies of brain disease, as well as mechanistic findings that reveal the intricacies of neuronal chromatin regulation. We then discuss how these mechanistic studies serve as a guideline for future neuroepigenetics investigations. We end by proposing a roadmap to future therapies that exploit these findings by coupling them to recent advances in targeted therapeutics.
Collapse
Affiliation(s)
- Benjamin H. Weekley
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Newaz I. Ahmed
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ian Maze
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| |
Collapse
|
|
3
|
Nani JV, Muotri AR, Hayashi MAF. Peering into the mind: unraveling schizophrenia's secrets using models. Mol Psychiatry 2025; 30:659-678. [PMID: 39245692 DOI: 10.1038/s41380-024-02728-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 08/21/2024] [Accepted: 08/27/2024] [Indexed: 09/10/2024]
Abstract
Schizophrenia (SCZ) is a complex mental disorder characterized by a range of symptoms, including positive and negative symptoms, as well as cognitive impairments. Despite the extensive research, the underlying neurobiology of SCZ remain elusive. To overcome this challenge, the use of diverse laboratory modeling techniques, encompassing cellular and animal models, and innovative approaches like induced pluripotent stem cell (iPSC)-derived neuronal cultures or brain organoids and genetically engineered animal models, has been crucial. Immortalized cellular models provide controlled environments for investigating the molecular and neurochemical pathways involved in neuronal function, while iPSCs and brain organoids, derived from patient-specific sources, offer significant advantage in translational research by facilitating direct comparisons of cellular phenotypes between patient-derived neurons and healthy-control neurons. Animal models can recapitulate the different psychopathological aspects that should be modeled, offering valuable insights into the neurobiology of SCZ. In addition, invertebrates' models are genetically tractable and offer a powerful approach to dissect the core genetic underpinnings of SCZ, while vertebrate models, especially mammals, with their more complex nervous systems and behavioral repertoire, provide a closer approximation of the human condition to study SCZ-related traits. This narrative review provides a comprehensive overview of the diverse modeling approaches, critically evaluating their strengths and limitations. By synthesizing knowledge from these models, this review offers a valuable source for researchers, clinicians, and stakeholders alike. Integrating findings across these different models may allow us to build a more holistic picture of SCZ pathophysiology, facilitating the exploration of new research avenues and informed decision-making for interventions.
Collapse
Affiliation(s)
- João V Nani
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil.
- National Institute for Translational Medicine (INCT-TM, CNPq/FAPESP/CAPES), Ribeirão Preto, Brazil.
| | - Alysson R Muotri
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mirian A F Hayashi
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil.
- National Institute for Translational Medicine (INCT-TM, CNPq/FAPESP/CAPES), Ribeirão Preto, Brazil.
| |
Collapse
|
|
4
|
Rawani NS, Chan AW, Todd KG, Baker GB, Dursun SM. The Role of Neuroglia in the Development and Progression of Schizophrenia. Biomolecules 2024; 15:10. [PMID: 39858403 PMCID: PMC11761573 DOI: 10.3390/biom15010010] [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: 09/25/2024] [Revised: 12/04/2024] [Accepted: 12/20/2024] [Indexed: 01/27/2025] Open
Abstract
Schizophrenia is a complex heterogenous disorder thought to be caused by interactions between genetic and environmental factors. The theories developed to explain the etiology of schizophrenia have focused largely on the dysfunction of neurotransmitters such as dopamine, serotonin and glutamate with their receptors, although research in the past several decades has indicated strongly that other factors are also involved and that the role of neuroglial cells in psychotic disorders including schizophrenia should be given more attention. Although glia were originally thought to be present in the brain only to support neurons in a physical, metabolic and nutritional capacity, it has become apparent that these cells have a variety of important physiological roles and that abnormalities in their function may make significant contributions to the symptoms of schizophrenia. In the present paper, we review the interactions of brain microglia, astrocytes and oligodendroglia with aspects such as transmitter dysregulation, neuro-inflammation, oxidative stress, synaptic function, the gut microbiome, myelination and the blood-brain barrier that appear to affect the cause, development and treatment of schizophrenia. We also review crosstalk between microglia, astrocytes and oligodendrocytes and the effects of antipsychotics on neuroglia. Problems associated with studies on specific biomarkers for glia in schizophrenia are discussed.
Collapse
Affiliation(s)
| | | | | | - Glen B. Baker
- Neurochemical Research Unit and Bebensee Schizophrenia Research Unit, Department of Psychiatry and Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB T6G 2G3, Canada; (N.S.R.); (A.W.C.); (K.G.T.); (S.M.D.)
| | | |
Collapse
|
|
5
|
Zhu L, Wu H, Peng L, Huang X, Yang R, Ma W, Zhong L, Li B, Song J, Luo S, Gao L, Wu X, Ma W, Bao F, Liu A. CD4 + Effective Memory T Cell Markers GBP2 and LAG3 Are Risk Factors for PTB and COVID-19 Infection: A Study Integrating Single-Cell Expression Quantitative Trait Locus and Mendelian Randomization Analyses. Int J Mol Sci 2024; 25:9971. [PMID: 39337460 PMCID: PMC11432203 DOI: 10.3390/ijms25189971] [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: 08/28/2024] [Revised: 09/13/2024] [Accepted: 09/14/2024] [Indexed: 09/30/2024] Open
Abstract
Observational studies indicate that variations in peripheral blood mononuclear cell (PBMC) subsets are associated with an increased risk of pulmonary tuberculosis (PTB) and coronavirus disease 2019 (COVID-19), but causal validation is lacking. Here, we combined single-cell expression quantitative trait locus (sc-eQTL) and two-sample mendelian randomization (MR) analyses to elucidate the causal relationship between PBMC subsets and the occurrence of PTB and COVID-19 and verified by RT-qPCR. We observed an increase in the CD4+ Effective Memory T Cell (CD4+ TEM) cluster in both PTB and COVID-19 patients according to the single-cell transcriptional landscape of PBMC. Through MR analysis using an inverse variance weighted (IVW) method, we found strong evidence of positive correlations between CD4+ TEM cell markers (GBP2, TRAV1-2, and ODF2L) and PTB, and between markers (LAG3 and SLFN5) and COVID-19, especially highlighted by lead eQTL-SNPs of GBP2 (rs2256752, p = 4.76321 × 10-15) and LAG3 (rs67706382, p = 6.16× 10-16). Similar results were observed in validation sets, and no pleiotropy was detected in sensitivity analyses including weighted median (WM), MR-Egger, MR-pleiotropy residual sum and outlier, and leave-one-out analyses (all p > 0.05). We visualized the colocalization of marker-eQTLs and markers of PTB and COVID-19 genome-wide association study (GWAS) associations. Based on CellChat analyses, monocytes communicated predominantly with CD4+ TEM cells positively expressing PTB markers (GBP2, TRAV1-2, and ODF2L) and COVID-19 markers (LAG3 and SLFN5) in both PTB and COVID-19. Our data suggest a causal effect between two key CD4+ TEM cell markers (GBP2 and LAG3) and the risk for PTB and COVID-19 infection. Our findings provide novel insights into the biological mechanism for PTB and COVID-19 infection, but future single-cell studies are necessary to further enhance understanding of this find.
Collapse
Affiliation(s)
- Liangyu Zhu
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Hanxin Wu
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Li Peng
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Xun Huang
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Rui Yang
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Weijie Ma
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Lei Zhong
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Bingxue Li
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
- Yunnan Provincial Key Laboratory of Public Health and Biosafety, School of Public Health, Kunming Medical University, Kunming 650500, China
| | - Jieqin Song
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Suyi Luo
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Li Gao
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Xinya Wu
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Weijiang Ma
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
| | - Fukai Bao
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
- Yunnan Provincial Key Laboratory of Public Health and Biosafety, School of Public Health, Kunming Medical University, Kunming 650500, China
| | - Aihua Liu
- Yunnan Province Key Laboratory of Children’s Major Diseases Research, Department of Pathogen Biology and Immunology, School of Basic Medicine, Kunming Medical University, Kunming 650500, China; (L.Z.); (H.W.); (L.P.); (X.H.); (R.Y.); (W.M.); (L.Z.); (B.L.); (J.S.); (S.L.); (L.G.); (X.W.); (W.M.)
- Yunnan Provincial Key Laboratory of Public Health and Biosafety, School of Public Health, Kunming Medical University, Kunming 650500, China
| |
Collapse
|
|
6
|
Sun G, Zhou Y, Han X, Che X, Yu S, Song D, Ma F, Huang L. Potential marker genes for chronic obstructive pulmonary disease revealed based on single-cell sequencing and Mendelian randomization analysis. Aging (Albany NY) 2024; 16:8922-8943. [PMID: 38787375 PMCID: PMC11164476 DOI: 10.18632/aging.205849] [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: 12/05/2023] [Accepted: 04/15/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Progress is being made in the prevention and treatment of chronic obstructive pulmonary disease (COPD), but it is still unsatisfactory. With the development of genetic technology, validated genetic information can better explain COPD. OBJECTIVE The study utilized scRNA-seq and Mendelian randomization analysis of eQTLs to identify crucial genes and potential mechanistic pathways underlying COPD pathogenesis. MEHODS Single-cell sequencing data were used to identify marker genes for immune cells in the COPD process. Data on eQTLs for immune cell marker genes were obtained from the eQTLGen consortium. To estimate the causal effect of marker genes on COPD, we selected an independent cohort (ukb-b-16751) derived from the UK Biobank database for two-sample Mendelian randomization analysis. Subsequently, we performed immune infiltration analysis, gene set enrichment analysis (GSEA), and co-expression network analysis on the key genes. RESULTS The 154 immune cell-associated marker genes identified were mainly involved in pathways such as vacuolar cleavage, positive regulation of immune response and regulation of cell activation. Mendelian randomization analysis screened four pairs of marker genes (GZMH, COTL1, CSTA and CD14) were causally associated with COPD. These four key genes were significantly associated with immune cells. In addition, we have identified potential transcription factors associated with these key genes using the Cistrome database, thus contributing to a deeper understanding of the regulatory network of these gene expressions. CONCLUSIONS This eQTLs Mendelian randomization study identified four key genes (GZMH, COTL1, CSTA, and CD14) causally associated with COPD, providing new insights for prevention and treatment of COPD.
Collapse
Affiliation(s)
- Gang Sun
- General Hospital of Northern Theater Command, Shenyang 110000, Liaoning, China
| | - Yun Zhou
- East China Normal University Wuhu Affiliated Hospital (The Second People’s Hospital of Wuhu City), Wuhu 241000, Anhui, China
| | - Xiaoxiao Han
- The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei 230022, Anhui China
| | - Xiangqian Che
- General Hospital of Northern Theater Command, Shenyang 110000, Liaoning, China
| | - Shuo Yu
- The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei 230022, Anhui China
| | - Di Song
- General Hospital of Northern Theater Command, Shenyang 110000, Liaoning, China
| | - Feifei Ma
- General Hospital of Northern Theater Command, Shenyang 110000, Liaoning, China
| | - Lewei Huang
- General Hospital of Northern Theater Command, Shenyang 110000, Liaoning, China
| |
Collapse
|
|
7
|
Luo L, Pang T, Zheng H, Liufu C, Chang S. xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data. J Transl Med 2024; 22:387. [PMID: 38664746 PMCID: PMC11044291 DOI: 10.1186/s12967-024-05065-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/05/2024] [Indexed: 04/29/2024] Open
Abstract
BACKGROUND Integrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes. METHODS In this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored. RESULTS Our findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes. CONCLUSIONS The analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.
Collapse
Affiliation(s)
- Lingxue Luo
- 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), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Tao Pang
- 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), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Haohao Zheng
- 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), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Chao Liufu
- 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), 51 Huayuan Bei Road, Beijing, 100191, China
| | - Suhua Chang
- 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), 51 Huayuan Bei Road, Beijing, 100191, China.
- Research Units of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Beijing, 100191, China.
| |
Collapse
|