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Hart XM, Gründer G, Ansermot N, Conca A, Corruble E, Crettol S, Cumming P, Hefner G, Frajerman A, Howes O, Jukic M, Kim E, Kim S, Manisalco I, Moriguchi S, Müller DJ, Nakajima S, Osugo M, Paulzen M, Ruhe HG, Scherf-Clavel M, Schoretsanitis G, Serretti A, Spina E, Spigset O, Steimer W, Süzen HS, Uchida H, Unterecker S, Vandenberghe F, Verstuyft C, Zernig G, Hiemke C, Eap CB. Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: focus on antipsychotics. World J Biol Psychiatry 2024:1-123. [PMID: 38913780 DOI: 10.1080/15622975.2024.2366235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 06/06/2024] [Indexed: 06/26/2024]
Abstract
BACKGROUND For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialized tools are used. Three tools have been proven useful to personalize drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging. METHODS In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 50 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)). RESULTS Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings. CONCLUSION All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimize treatment effects, minimize side effects and ultimately reduce the global burden of diseases, personalized drug treatment has not yet become the standard of care in psychiatry.
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Affiliation(s)
- X M Hart
- Central Institute of Mental Health, Department of Molecular Neuroimaging, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - G Gründer
- Central Institute of Mental Health, Department of Molecular Neuroimaging, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim - Heidelberg - Ulm
| | - N Ansermot
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Prilly, Switzerland
| | - A Conca
- Dipartimento di Psichiatria, Comprensorio Sanitario di Bolzano, Bolzano, Italy
| | - E Corruble
- Université Paris-Saclay, AP-HP, Service Hospitalo-Universitaire de Psychiatrie, Hôpital de Bicêtre
- Equipe MOODS, Inserm U1018, CESP (Centre de Recherche en Epidémiologie et Sante des Populations), Le Kremlin-Bicêtre, France
| | - S Crettol
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - P Cumming
- Department of Nuclear Medicine, Bern University Hospital, Bern, Switzerland
- School of Psychology and Counseling, Queensland University of Technology, Brisbane, Australia
| | - G Hefner
- Vitos Clinic for Forensic Psychiatry, Forensic Psychiatry, Eltville, Germany
| | - A Frajerman
- Université Paris-Saclay, AP-HP, Service Hospitalo-Universitaire de Psychiatrie, Hôpital de Bicêtre
- Equipe MOODS, Inserm U1018, CESP (Centre de Recherche en Epidémiologie et Sante des Populations), Le Kremlin-Bicêtre, France
| | - O Howes
- Department of Psychosis Studies, IoPPN, King's College London, De Crespigny Park, London, SE5 8AF, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - M Jukic
- Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia and Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden
| | - E Kim
- Department of Psychiatry, Seoul National University College of Medicine, Republic of Korea
| | - S Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Republic of Korea
| | - I Manisalco
- Dipartimento di Psichiatria, Comprensorio Sanitario di Bolzano, Bolzano, Italy
| | - S Moriguchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - D J Müller
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada, and Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - S Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - M Osugo
- Department of Psychosis Studies, IoPPN, King's College London, De Crespigny Park, London, SE5 8AF, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - M Paulzen
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University
- JARA - Translational Brain Medicine, Aachen, Germany; Alexianer Center for Mental Health, Aachen, Germany
| | - H G Ruhe
- Department of psychiatry, Radboudumc, Nijmegen, Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands
| | - M Scherf-Clavel
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - G Schoretsanitis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, 8032 Zurich, Switzerland
| | - A Serretti
- Department of Medicine and Surgery, Kore University of Enna, Italy
| | - E Spina
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - O Spigset
- Department of Clinical Pharmacology, St. Olav University Hospital, Trondheim, Norway, and Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - W Steimer
- Institute of Clinical Chemistry and Pathobiochemistry, Technical University Munich, Munich, Germany
| | - H S Süzen
- Department of Pharmaceutic Toxicology, Faculty of Pharmacy, Ankara University, Ankara, Turkey
| | - H Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - S Unterecker
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - F Vandenberghe
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Prilly, Switzerland
| | - C Verstuyft
- Department of Molecular Genetics, Pharmacogenetics and Hormonology Bicêtre University Hospital Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Le Kremlin Bicêtre, F-94275, France
- CESP, MOODS Team, INSERM UMR 1018, Medicine Faculty, Paris-Saclay University, Le Kremlin Bicêtre, France
| | - G Zernig
- Department of Pharmacology, Medical University Innsbruck; Private Practice for Psychotherapy and Court-Certified Witness, Hall in Tirol, Austria
| | - C Hiemke
- Department of Psychiatry and Psychotherapy and Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center of Mainz, Germany
| | - C B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Department of Psychiatry, Centre for Psychiatric Neuroscience, Lausanne University Hospital, University of Lausanne, 1008 Prilly, Switzerland
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, University of Lausanne, Lausanne, Switzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Lausanne, Switzerland
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Sun Y, Zhang Y, Lu Z, Liao Y, Feng Q, Yu M, Chen Y, Kang Z, Feng X, Zhao G, Sun J, Yang Y, Guo L, Zhang D, Bi W, Huang H, Yue W. Contribution of copy number variants on antipsychotic treatment response in Han Chinese patients with schizophrenia. EBioMedicine 2024; 105:105195. [PMID: 38870545 DOI: 10.1016/j.ebiom.2024.105195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 05/17/2024] [Accepted: 05/28/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia. METHODS A total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed. FINDINGS Higher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33-7.19) and risk CNVs was 8.47 (95% CI: 1.92-37.43). CNV interacted with genetic risk score on APD efficacy (Beta = -1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%-82.82%). INTERPRETATION Copy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted. FUNDING National Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.
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Affiliation(s)
- Yaoyao Sun
- 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 100191, China
| | - 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 100191, 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 100191, 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 100191, China
| | - Qidi Feng
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mingrui Yu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yu Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - 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 100191, China
| | - Xiaoyang Feng
- 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 100191, China
| | - Guorui Zhao
- 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 100191, China
| | - Junyuan Sun
- 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 100191, China
| | - 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 100191, China
| | - Liangkun Guo
- 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 100191, China
| | - Dai 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 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Wenjian Bi
- Department of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - 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 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China.
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Ma Y, Gao K, Sun X, Wang J, Yang Y, Wu J, Chai A, Yao L, Liu N, Yu H, Su Y, Lu T, Wang L, Yue W, Zhang X, Xu L, Zhang D, Li J. STON2 variations are involved in synaptic dysfunction and schizophrenia-like behaviors by regulating Syt1 trafficking. Sci Bull (Beijing) 2024; 69:1458-1471. [PMID: 38402028 DOI: 10.1016/j.scib.2024.02.013] [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: 07/04/2023] [Revised: 11/13/2023] [Accepted: 02/06/2024] [Indexed: 02/26/2024]
Abstract
Synaptic dysfunction is a core component of the pathophysiology of schizophrenia. However, the genetic risk factors and molecular mechanisms related to synaptic dysfunction are still not fully understood. The Stonin 2 (STON2) gene encodes a major adaptor for clathrin-mediated endocytosis (CME) of synaptic vesicles. In this study, we showed that the C-C (307Pro-851Ala) haplotype of STON2 increases the susceptibility to schizophrenia and examined whether STON2 variations cause schizophrenia-like behaviors through the regulation of CME. We found that schizophrenia-related STON2 variations led to protein dephosphorylation, which affected its interaction with synaptotagmin 1 (Syt1), a calcium sensor protein located in the presynaptic membrane that is critical for CME. STON2307Pro851Ala knockin mice exhibited deficits in synaptic transmission, short-term plasticity, and schizophrenia-like behaviors. Moreover, among seven antipsychotic drugs, patients with the C-C (307Pro-851Ala) haplotype responded better to haloperidol than did the T-A (307Ser-851Ser) carriers. The recovery of deficits in Syt1 sorting and synaptic transmission by acute administration of haloperidol effectively improved schizophrenia-like behaviors in STON2307Pro851Ala knockin mice. Our findings demonstrated the effect of schizophrenia-related STON2 variations on synaptic dysfunction through the regulation of CME, which might be attractive therapeutic targets for treating schizophrenia-like phenotypes.
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Affiliation(s)
- Yuanlin Ma
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; The First Affiliated Hospital, Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Kai Gao
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China
| | - Xiaoxuan Sun
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Jinxin Wang
- Chinese Institute for Brain Research, Beijing 102206, China
| | - 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Jianying Wu
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Anping Chai
- Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Shenzhen Key Laboratory of Translational Research for Brain Diseases, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Li Yao
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Nan Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Hao Yu
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Yi Su
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Lifang Wang
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lin Xu
- Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Dai 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China
| | - Jun Li
- 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), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China.
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Zhang L, Cheng Y, Xue Z, Wu S, Qiu Z, Jiang H. Comparative Molecular Taxonomics of Neuron in Cingulate Cortex of Rhesus Monkey and Mouse via Single-Nucleus RNA Sequencing. Neurosci Bull 2024:10.1007/s12264-024-01209-y. [PMID: 38780751 DOI: 10.1007/s12264-024-01209-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 11/25/2023] [Indexed: 05/25/2024] Open
Affiliation(s)
- Lei Zhang
- Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yanyong Cheng
- Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Zhenyu Xue
- Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Shihao Wu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
- Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Zilong Qiu
- Shanghai Jiao Tong University School of Medicine Songjiang Institute, Shanghai, 200025, China.
| | - Hong Jiang
- Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
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Chen S, Tang D, Deng L, Xu S. Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection. iScience 2024; 27:109560. [PMID: 38638564 PMCID: PMC11024917 DOI: 10.1016/j.isci.2024.109560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/29/2023] [Accepted: 03/22/2024] [Indexed: 04/20/2024] Open
Abstract
The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.
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Affiliation(s)
- Sihan Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Die Tang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
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Wang M, Gu Y, Li Q, Feng B, Lv X, Zhang H, Kong Q, Dong Z, Tian X, Zhang Y. The Traf2 and NcK interacting kinase inhibitor NCB-0846 suppresses seizure activity involving the decrease of GRIA1. Genes Dis 2024; 11:100997. [PMID: 38292191 PMCID: PMC10826163 DOI: 10.1016/j.gendis.2023.03.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/09/2023] [Accepted: 03/29/2023] [Indexed: 02/01/2024] Open
Abstract
Epilepsy, one of the most common neurological disorders, is characterized by spontaneous recurrent seizures. Temporal lobe epilepsy (TLE) is one of the most common medically intractable seizure disorders. Traf2-and NcK-interacting kinase (TNIK) has recently attracted attention as a critical modulation target of many neurological and psychiatric disorders, but its role in epilepsy remains unclear. In this study, we hypothesized the involvement of TNIK in epilepsy and investigated TNIK expression in patients with intractable TLE and in a pilocarpine-induced rat model of epilepsy by western blotting, immunofluorescence, and immunohistochemistry. A pentylenetetrazole (PTZ)-induced epilepsy rat model was used to determine the effect of the TNIK inhibitor NCB-0846 on behavioral manifestations of epilepsy. Coimmunoprecipitation (Co-IP)/mass spectrometry (MS) was used to identify the potential mechanism. Through Co-IP, we detected and confirmed the main potential TNIK interactors. Subcellular fractionation was used to establish the effect of NCB-0846 on the expression of the main interactors in postsynaptic density (PSD) fractions. We found that TNIK was primarily located in neurons and decreased significantly in epilepsy model rats and TLE patients compared with controls. NCB-0846 delayed kindling progression and decreased seizure severity. Co-IP/MS identified 63 candidate TNIK interactors in rat hippocampi, notably CaMKII. Co-IP showed that TNIK might correlate with endogenous GRIA1, SYN2, PSD-95, CaMKIV, GABRG1, and GABRG2. In addition, the significant decrease in GRIA1 in hippocampal total lysate and PSDs after NCB-0846 treatment might help modify the progression of PTZ kindling. Our results suggest that TNIK contributes to epileptic pathology and is a potential antiepileptic drug target.
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Affiliation(s)
- Min Wang
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Yixue Gu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Qiubo Li
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Bangzhe Feng
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Xinke Lv
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Hao Zhang
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Qingxia Kong
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Zhifang Dong
- Pediatric Research Institute, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Xin Tian
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Yanke Zhang
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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El-Ashry AM, Abd Elhay ES, Taha SM, Khedr MA, Attalla Mansour FS, Alabdullah AAS, Farghaly Abdelaliem SM, El-Sayed MM. Effect of applying nursing-based cognitive defusion techniques on mindful awareness, cognitive fusion, and believability of delusions among clients with schizophrenia: a randomized control trial. Front Psychiatry 2024; 15:1369160. [PMID: 38736628 PMCID: PMC11082577 DOI: 10.3389/fpsyt.2024.1369160] [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: 01/11/2024] [Accepted: 03/25/2024] [Indexed: 05/14/2024] Open
Abstract
Background Applying cognitive defusion techniques to enduring psychotic symptoms, such as delusions, presents both a challenge and a promising opportunity for psychiatric nurses to manage delusions among schizophrenia clients. Objective This study aimed to examine the impact of cognitive defusion techniques on psychological flexibility, mindful awareness, cognitive fusion, and the believability of delusions in schizophrenia clients. Methodology This study used a single-blind, parallel-arm Randomized Controlled Trial design. Over five weeks, 70 clients with schizophrenia were randomized to either the cognitive defusion intervention group (n = 35) or the control group (n = 35). Findings The participants showed significant reductions in the believability of delusions, cognitive fusion, and psychological inflexibility immediately after the intervention and at follow-up. Notable enhancements were observed in cognitive defusion and mindfulness awareness abilities. Conclusion Cognitive defusion techniques positively affect schizophrenia clients who struggle with persistent delusional beliefs. This underscores the importance of further investigating this approach to decrease the intensity of delusions as part of a comprehensive therapeutic intervention. Psychiatric nurses must receive training in "cognitive defusion skills" to aid schizophrenia clients in becoming more aware of their emotions and modifying their coping strategies for delusional beliefs. On August 3, 2023, the research was retrospectively registered under the reference number NCT05759091 as a randomized clinical trial. Clinical trial registration https://classic.clinicaltrials.gov/ct2/show/NCT05759091, identifier NCT05759091.
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Affiliation(s)
- Ayman Mohamed El-Ashry
- Department of Psychiatric and Mental Health Nursing, Faculty of Nursing, Alexandria University, Alexandria, Egypt
| | | | | | - Mahmoud Abdelwahab Khedr
- Department of Nursing, College of Applied Medical Sciences, Hafr Albatin University, Hafr Albatin, Saudi Arabia
| | | | - Amany Anwar Saeed Alabdullah
- Department of Maternity and Child Health Nursing, College of Nursing, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
| | | | - Mona Metwally El-Sayed
- Department of Psychiatric and Mental Health Nursing, Faculty of Nursing, Alexandria University, Alexandria, Egypt
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8
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Qi X, Yu X, Wei L, Jiang H, Dong J, Li H, Wei Y, Zhao L, Deng W, Guo W, Hu X, Li T. Novel α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) potentiator LT-102: A promising therapeutic agent for treating cognitive impairment associated with schizophrenia. CNS Neurosci Ther 2024; 30:e14713. [PMID: 38615362 PMCID: PMC11016348 DOI: 10.1111/cns.14713] [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: 07/15/2023] [Revised: 03/07/2024] [Accepted: 03/23/2024] [Indexed: 04/16/2024] Open
Abstract
AIMS We aimed to evaluate the potential of a novel selective α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) potentiator, LT-102, in treating cognitive impairments associated with schizophrenia (CIAS) and elucidating its mechanism of action. METHODS The activity of LT-102 was examined by Ca2+ influx assays and patch-clamp in rat primary hippocampal neurons. The structure of the complex was determined by X-ray crystallography. The selectivity of LT-102 was evaluated by hERG tail current recording and kinase-inhibition assays. The electrophysiological characterization of LT-102 was characterized by patch-clamp recording in mouse hippocampal slices. The expression and phosphorylation levels of proteins were examined by Western blotting. Cognitive function was assessed using the Morris water maze and novel object recognition tests. RESULTS LT-102 is a novel and selective AMPAR potentiator with little agonistic effect, which binds to the allosteric site formed by the intradimer interface of AMPAR's GluA2 subunit. Treatment with LT-102 facilitated long-term potentiation in mouse hippocampal slices and reversed cognitive deficits in a phencyclidine-induced mouse model. Additionally, LT-102 treatment increased the protein level of brain-derived neurotrophic factor and the phosphorylation of GluA1 in primary neurons and hippocampal tissues. CONCLUSION We conclude that LT-102 ameliorates cognitive impairments in a phencyclidine-induced model of schizophrenia by enhancing synaptic function, which could make it a potential therapeutic candidate for CIAS.
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Affiliation(s)
- Xueyu Qi
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain‐Machine Integration, State Key Laboratory of Brain‐Machine IntelligenceZhejiang UniversityHangzhouChina
- NHC and CAMS Key Laboratory of Medical NeurobiologyZhejiang UniversityHangzhouChina
| | - Xueli Yu
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain‐Machine Integration, State Key Laboratory of Brain‐Machine IntelligenceZhejiang UniversityHangzhouChina
- NHC and CAMS Key Laboratory of Medical NeurobiologyZhejiang UniversityHangzhouChina
| | - Long Wei
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
| | - Han Jiang
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
| | - Jiangwen Dong
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
| | - Hongxing Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
| | - Yingying Wei
- The Psychiatric Laboratory, the State Key Laboratory of BiotherapyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Liansheng Zhao
- The Psychiatric Laboratory, the State Key Laboratory of BiotherapyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Wei Deng
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain‐Machine Integration, State Key Laboratory of Brain‐Machine IntelligenceZhejiang UniversityHangzhouChina
- NHC and CAMS Key Laboratory of Medical NeurobiologyZhejiang UniversityHangzhouChina
| | - Wanjun Guo
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain‐Machine Integration, State Key Laboratory of Brain‐Machine IntelligenceZhejiang UniversityHangzhouChina
- NHC and CAMS Key Laboratory of Medical NeurobiologyZhejiang UniversityHangzhouChina
| | - Xun Hu
- The Clinical Research Center and Department of Pathology, The Second Affiliated HospitalZhejiang University School of MedicineZhejiangHangzhouChina
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital and School of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhouChina
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain‐Machine Integration, State Key Laboratory of Brain‐Machine IntelligenceZhejiang UniversityHangzhouChina
- NHC and CAMS Key Laboratory of Medical NeurobiologyZhejiang UniversityHangzhouChina
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9
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Chakraborty S, Sarma J, Roy SS, Mitra S, Bagchi S, Das S, Saha S, Mahapatra S, Bhattacharjee S, Maulik M, Acharya M. Post-GWAS functional analyses of CNTNAP5 suggests its role in glaucomatous neurodegeneration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.583830. [PMID: 38903068 PMCID: PMC11188073 DOI: 10.1101/2024.03.14.583830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Primary angle closure glaucoma (PACG) affects more than 20 million people worldwide, with an increased prevalence in south-east Asia. In a prior haplotype-based GWAS, we identified a novel CNTNAP5 genic region, significantly associated with PACG. In the current study, we have extended our perception of CNTNAP5 involvement in glaucomatous neurodegeneration in a zebrafish model, through investigating phenotypic consequences pertinent to retinal degeneration upon knockdown of cntnap5 by translation-blocking morpholinos. While cntnap5 knockdown was successfully validated using an antibody, immunofluorescence followed by western blot analyses in cntnap5-morphant (MO) zebrafish revealed increased expression of acetylated tubulin indicative of perturbed cytoarchitecture of retinal layers. Moreover, significant loss of Nissl substance is observed in the neuro-retinal layers of cntnap5-MO zebrafish eye, indicating neurodegeneration. Additionally, in spontaneous movement behavioural analysis, cntnap5-MO zebrafish have a significantly lower average distance traversed in light phase compared to mismatch-controls, whereas no significant difference was observed in the dark phase, corroborating with vision loss in the cntnap5-MO zebrafish. This study provides the first direct functional evidence of a putative role of CNTNAP5 in visual neurodegeneration.
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Affiliation(s)
- Sudipta Chakraborty
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
- Regional Centre for Biotechnology, Fardiabad, India
| | - Jyotishman Sarma
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
- Regional Centre for Biotechnology, Fardiabad, India
| | - Shantanu Saha Roy
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Sukanya Mitra
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
- Regional Centre for Biotechnology, Fardiabad, India
| | - Sayani Bagchi
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Sankhadip Das
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Sreemoyee Saha
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Surajit Mahapatra
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Samsiddhi Bhattacharjee
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Mahua Maulik
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
| | - Moulinath Acharya
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, India
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10
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Gendosz de Carrillo D, Kocikowska O, Rak M, Krzan A, Student S, Jędrzejowska-Szypułka H, Pawletko K, Lasek-Bal A. The Relevance of Reperfusion Stroke Therapy for miR-9-3p and miR-9-5p Expression in Acute Stroke-A Preliminary Study. Int J Mol Sci 2024; 25:2766. [PMID: 38474013 DOI: 10.3390/ijms25052766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Reperfusion stroke therapy is a modern treatment that involves thrombolysis and the mechanical removal of thrombus from the extracranial and/or cerebral arteries, thereby increasing penumbra reperfusion. After reperfusion therapy, 46% of patients are able to live independently 3 months after stroke onset. MicroRNAs (miRNAs) are essential regulators in the development of cerebral ischemia/reperfusion injury and the efficacy of the applied treatment. The first aim of this study was to examine the change in serum miRNA levels via next-generation sequencing (NGS) 10 days after the onset of acute stroke and reperfusion treatment. Next, the predictive values of the bioinformatics analysis of miRNA gene targets for the assessment of brain ischemic response to reperfusion treatment were explored. Human serum samples were collected from patients on days 1 and 10 after stroke onset and reperfusion treatment. The samples were subjected to NGS and then validated using qRT-PCR. Differentially expressed miRNAs (DEmiRNAs) were used for enrichment analysis. Hsa-miR-9-3p and hsa-miR-9-5p expression were downregulated on day 10 compared to reperfusion treatment on day 1 after stroke. The functional analysis of miRNA target genes revealed a strong association between the identified miRNA and stroke-related biological processes related to neuroregeneration signaling pathways. Hsa-miR-9-3p and hsa-miR-9-5p are potential candidates for the further exploration of reperfusion treatment efficacy in stroke patients.
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Affiliation(s)
- Daria Gendosz de Carrillo
- Department of Physiology, Faculty of Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department of Histology and Cell Pathology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Olga Kocikowska
- Department of Physiology, Faculty of Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department of Engineering and Systems Biology, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
| | - Małgorzata Rak
- Department of Physiology, Faculty of Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Aleksandra Krzan
- Department of Neurology, School of Health Sciences, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department of Neurology, Upper-Silesian Medical Center of the Silesian Medical University, 40-752 Katowice, Poland
| | - Sebastian Student
- Department of Engineering and Systems Biology, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
- Biotechnology Centre, Silesian University of Technology, 44-100 Gliwice, Poland
| | - Halina Jędrzejowska-Szypułka
- Department of Physiology, Faculty of Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Katarzyna Pawletko
- Department of Physiology, Faculty of Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department for Experimental Medicine, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Anetta Lasek-Bal
- Department of Neurology, School of Health Sciences, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department of Neurology, Upper-Silesian Medical Center of the Silesian Medical University, 40-752 Katowice, Poland
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11
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Liao Y, Yu H, Zhang Y, Lu Z, Sun Y, Guo L, Guo J, Kang Z, Feng X, Sun Y, Wang G, Su Z, Lu T, Yang Y, Li W, Lv L, Yan H, Zhang D, Yue W. Genome-wide association study implicates lipid pathway dysfunction in antipsychotic-induced weight gain: multi-ancestry validation. Mol Psychiatry 2024:10.1038/s41380-024-02447-2. [PMID: 38336841 DOI: 10.1038/s41380-024-02447-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/21/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024]
Abstract
Antipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic medication and may contribute to diabetes and coronary heart disease. To expand the unclear genetic mechanism underlying AIWG, we conducted a two-stage genome-wide association study in Han Chinese patients with schizophrenia. The study included a discovery cohort of 1936 patients and a validation cohort of 534 patients, with an additional 630 multi-ancestry patients from the CATIE study for external validation. We applied Mendelian randomization (MR) analysis to investigate the relationship between AIWG and antipsychotic-induced lipid changes. Our results identified two novel genome-wide significant loci associated with AIWG: rs10422861 in PEPD (P = 1.373 × 10-9) and rs3824417 in PTPRD (P = 3.348 × 10-9) in Chinese Han samples. The association of rs10422861 was validated in the European samples. Fine-mapping and functional annotation revealed that PEPD and PTPRD are potentially causal genes for AIWG, with their proteins being prospective therapeutic targets. Colocalization analysis suggested that AIWG and type 2 diabetes (T2D) shared a causal variant in PEPD. Polygenic risk scores (PRSs) for AIWG and T2D significantly predicted AIWG in multi-ancestry samples. Furthermore, MR revealed a risky causal effect of genetically predicted changes in low-density lipoprotein cholesterol (P = 7.58 × 10-4) and triglycerides (P = 2.06 × 10-3) caused by acute-phase of antipsychotic treatment on AIWG, which had not been previously reported. Our model, incorporating antipsychotic-induced lipid changes, PRSs, and clinical predictors, significantly predicted BMI percentage change after 6-month antipsychotic treatment (AUC = 0.79, R2 = 0.332). Our results highlight that the mechanism of AIWG involves lipid pathway dysfunction and may share a genetic basis with T2D through PEPD. Overall, this study provides new insights into the pathogenesis of AIWG and contributes to personalized treatment of schizophrenia.
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Affiliation(s)
- Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, Shandong, 272067, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China.
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Liangkun Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Jing Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Xiaoyang Feng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yutao Sun
- No.5 Hospital, Tangshan, Hebei, 063000, China
| | - Guishan Wang
- The Second Affiliated Hospital of Jining Medical College, Jining, 272051, China
| | - Zhonghua Su
- The Second Affiliated Hospital of Jining Medical College, Jining, 272051, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Yongfeng Yang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China
| | - Wenqiang Li
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China
| | - Luxian Lv
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China
- Chinese Institute for Brain Research, Beijing, 102206, China
- Institute for Brain Research and Rehabilitation (IBRR), Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), Beijing, 100191, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
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12
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Abad-Santos F, Aliño SF, Borobia AM, García-Martín E, Gassó P, Maroñas O, Agúndez JAG. Developments in pharmacogenetics, pharmacogenomics, and personalized medicine. Pharmacol Res 2024; 200:107061. [PMID: 38199278 DOI: 10.1016/j.phrs.2024.107061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/13/2023] [Accepted: 01/04/2024] [Indexed: 01/12/2024]
Abstract
The development of Pharmacogenetics and Pharmacogenomics in Western Europe is highly relevant in the worldwide scenario. Despite the usually low institutional support, many research groups, composed of basic and clinical researchers, have been actively working for decades in this field. Their contributions made an international impact and paved the way for further studies and pharmacogenomics implementation in clinical practice. In this manuscript, that makes part of the Special Issue entitled Spanish Pharmacology, we present an analysis of the state of the art of Pharmacogenetics and Pharmacogenomics research in Europe, we compare it with the developments in Spain, and we summarize the most salient contributions since 1988 to the present, as well as recent developments in the clinical application of pharmacogenomics knowledge. Finally, we present some considerations on how we could improve translation to clinical practice in this specific scenario.
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Affiliation(s)
- Francisco Abad-Santos
- Clinical Pharmacology Department, Hospital Universitario de La Princesa, Universidad Autónoma de Madrid (UAM), CIBEREHD, Instituto de Investigación Sanitaria La Princesa (IP), Madrid, Spain.
| | - Salvador F Aliño
- Gene Therapy and Pharmacogenomics Group, Department of Pharmacology, Faculty of Medicine, Universitat de València, Av. Blasco Ibáñez 15, 46010 Valencia, Spain
| | - Alberto M Borobia
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, Universidad Autónoma de Madrid (UAM), IdiPAZ, Madrid, Spain
| | - Elena García-Martín
- Department of Pharmacology, Universidad de Extremadura, Avda de la Universidad s/n, 10071 Cáceres, Spain
| | - Patricia Gassó
- Basic Clinical Practice Department, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona Clínic Schizophrenia Unit (BCSU), IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Olalla Maroñas
- Public Foundation of Genomic Medicine, Santiago University Hospital, Genomic Medicine group, Pharmacogenetics and Drug Discovery (GenDeM), CIBERER, Santiago Health Research Institute (IDIS), Galicia, Spain
| | - José A G Agúndez
- Universidad de Extremadura. University Institute of Molecular Pathology Biomarkers, Avda de las Ciencias s/n, 10071 Cáceres, Spain.
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13
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Tandon R, Nasrallah H, Akbarian S, Carpenter WT, DeLisi LE, Gaebel W, Green MF, Gur RE, Heckers S, Kane JM, Malaspina D, Meyer-Lindenberg A, Murray R, Owen M, Smoller JW, Yassin W, Keshavan M. The schizophrenia syndrome, circa 2024: What we know and how that informs its nature. Schizophr Res 2024; 264:1-28. [PMID: 38086109 DOI: 10.1016/j.schres.2023.11.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.
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Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI 49008, United States of America.
| | - Henry Nasrallah
- Department of Psychiatry, University of Cincinnati College of Medicine Cincinnati, OH 45267, United States of America
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance and Harvard Medical School, Cambridge, MA 02139, United States of America
| | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Dusseldorf, Heinrich-Heine University, Dusseldorf, Germany
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute of Neuroscience and Human Behavior, UCLA, Los Angeles, CA 90024, United States of America; Greater Los Angeles Veterans' Administration Healthcare System, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States of America
| | - Stephan Heckers
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37232, United States of America
| | - John M Kane
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Glen Oaks, NY 11004, United States of America
| | - Dolores Malaspina
- Department of Psychiatry, Neuroscience, Genetics, and Genomics, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannhein/Heidelberg University, Mannheim, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology, and Neuroscience, Kings College, London, UK
| | - Michael Owen
- Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Psychiatric and Neurodevelopmental Unit, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States of America
| | - Walid Yassin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
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Wang Y, Wang G, Gong M, Yang Y, Ling Y, Fang X, Zhu T, Wang Z, Zhang X, Zhang C. Systemic inflammatory biomarkers in Schizophrenia are changed by ECT administration and related to the treatment efficacy. BMC Psychiatry 2024; 24:53. [PMID: 38233774 PMCID: PMC10792810 DOI: 10.1186/s12888-023-05469-2] [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] [Received: 06/25/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024] Open
Abstract
Immune inflammation has long been implicated in the pathogenesis of schizophrenia. Despite as a rapid and effective physical therapy, the role of immune inflammation in electroconvulsive therapy (ECT) for schizophrenia remains elusive. The neutrophils to lymphocytes (NLR), platelets to monocytes (PLR) and monocytes to lymphocytes (MLR) are inexpensive and accessible biomarkers of systemic inflammation. In this study, 70 schizophrenia patients and 70 age- and sex-matched healthy controls were recruited. The systemic inflammatory biomarkers were measured before and after ECT. Our results indicated schizophrenia had significantly higher peripheral NLR, PLR and MLR compared to health controls at baseline, while lymphocytes did not differ. After 6 ECT, the psychiatric symptoms were significantly improved, as demonstrated by the Positive and Negative Syndrome Scale (PANSS). However, there was a decline in cognitive function scores, as indicated by the Mini-Mental State Examination (MMSE). Notably, the neutrophils and NLR were significantly reduced following ECT. Although lymphocytes remained unchanged following ECT, responders had significantly higher lymphocytes compared to non-responders. Moreover, the linear regression analyses revealed that higher lymphocytes served as a predictor of larger improvement in positive symptom following ECT. Overall, our findings further highlighted the presence of systemic inflammation in schizophrenia patients, and that ECT may exert a therapeutic effect in part by attenuating systemic inflammation. Further research may therefore lead to new treatment strategies for schizophrenia targeting the immune system.
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Affiliation(s)
- Yu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China
| | - Guangfa Wang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, 221004, Xuzhou, Jiangsu, China
| | - Muxin Gong
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, 221004, Xuzhou, Jiangsu, China
| | - Yujing Yang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, 221004, Xuzhou, Jiangsu, China
| | - Yuru Ling
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China
| | - Tingting Zhu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China
| | - Zixu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 210029, Nanjing, Jiangsu, China.
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, 221004, Xuzhou, Jiangsu, China.
| | - Caiyi Zhang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, 221004, Xuzhou, Jiangsu, China.
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15
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Lv X, Hou YS, Zhang ZH, Yue WH. OXTR polymorphisms associated with severity and treatment responses of schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:7. [PMID: 38184684 PMCID: PMC10851696 DOI: 10.1038/s41537-023-00413-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 11/13/2023] [Indexed: 01/08/2024]
Abstract
The mechanisms generating specific symptoms of schizophrenia remain unclear and genetic research makes it possible to explore these issues at a fundamental level. Taking into account the associations between the oxytocin system and social functions, which are apparently impaired in schizophrenia patients, we hypothesized that the oxytocin receptor gene (OXTR) might be associated with schizophrenia symptoms in both severity and responses to antipsychotics and did this exploratory positional study. A total of 2363 patients with schizophrenia (1181 males and 1182 females) included in our study were randomly allocated to seven antipsychotic treatment groups and received antipsychotic monotherapy for 6 weeks. Their blood DNA was genotyped for OXTR polymorphisms. Their symptom severity was assessed by Positive and Negative Syndrome Scale (PANSS), and the scores were transformed into seven factors (positive, disorganized, negative symptoms apathy/avolition, negative symptoms deficit of expression, hostility, anxiety and depression). Percentage changes in PANSS scores from baseline to week 6 were calculated to quantify antipsychotic responses. We found that OXTR polymorphisms were nominally associated with the severity of overall symptoms (rs237899, β = 1.669, p = 0.019), hostility symptoms (rs237899, β = 0.427, p = 0.044) and anxiety symptoms (rs13316193, β = -0.197, p = 0.038). As for treatment responses, OXTR polymorphisms were nominally associated with the improvement in negative symptoms apathy/avolition (rs2268490, β = 2.235, p = 0.0499). No association between severity or response to treatment and OXTR polymorphisms was found with statistical correction for multiplicity. Overall, our results highlighted the possibility of nominally significant associations of the OXTR gene with the severity and improvement in schizophrenia symptoms. Given the exploratory nature of this study, these associations are indicative of the role of the OXTR gene in the pathology of schizophrenia and may contribute to further elucidate the mechanism of specific symptoms of schizophrenia and to exploit antipsychotics more effective to specific symptoms.
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Affiliation(s)
- Xue Lv
- The First Affiliated Hospital of Xinxiang Medical College, 453100, Xinxiang, Henan, China
| | - Yue-Sen Hou
- The First Affiliated Hospital of Xinxiang Medical College, 453100, Xinxiang, Henan, China
- Henan Key Laboratory of Neurorestoratology, 453199, Xinxiang, Henan, China
- Henan Engineering Research Center of Physical Diagnostics and Treatment Technology for the Mental and Neurological Diseases, 453005, Xinxiang, Henan, China
| | - Zhao-Hui Zhang
- The First Affiliated Hospital of Xinxiang Medical College, 453100, Xinxiang, Henan, China.
| | - Wei-Hua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, 100191, Beijing, China.
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16
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Alrefai AA, Ramadan AN, Omar MM, Elghobashy YA, Soliman SE. Association between genetic variants of GRM7 (rs1396409 and rs9883258) and treatment outcomes in Schizophrenic Egyptian patients. NUCLEOSIDES, NUCLEOTIDES & NUCLEIC ACIDS 2023; 43:540-556. [PMID: 38723257 DOI: 10.1080/15257770.2023.2283184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 11/07/2023] [Indexed: 06/06/2024]
Abstract
BACKGROUND AND AIM This study evaluated the association between rs1396409 and rs9883258 and the risk of schizophrenia (SCZ) and treatment outcomes in Egyptian patients. METHODS This study included 88 patients with SCZ and 88 healthy controls. Lipid profile was assayed. Genotyping of rs1396409 and rs9883258 polymorphisms was analyzed using real-time PCR. RESULTS The rs1396409 AG genotype frequency was significantly associated with SCZ risk (p = 0.002). Also, significant increased risk of SCZ was observed under allelic (p = 0.001), dominant (p = 0.001) and overdominant (p = 0.001) genetic model of rs1396409. However, rs9883258 AA genotype revealed nonsignificant association with SCZ. Cases with the rs1396409AG genotype exhibited hypertriglyceridemia (p < 0.001) and hypercholesterolemia (p = 0.001). In total, 72.3% and 74.5% of the cases presented with rs1396409 AG have negative symptoms (p = 0.022) and exhibited poor drug response (p = 0.023), respectively; all cases with rs1396409 GG genotype attempted suicide (p = 0.002) and are drug-free (p = 0.003). SCZ patients with negative symptoms had hypercholesterolemia (p = 0.008) mainly low-density lipoproteins (LDLc) (p = 0.016), and those with cognitive symptoms presented with low level of high-density lipoprotein (HDLc) (p = 0.023). Moreover, the multivariate regression analysis revealed that both rs1396409 G allele and HDLc were predictors of SCZ (p = 0.003 and 0.001, resp.). CONCLUSION The current study concluded that metabotropic glutamate receptor 7 (GRM7) rs1396409 AG could be a potential biomarker for SCZ diagnosis. It also revealed an independent association between the GRM7 rs1396409 G allele, HDLc and SCZ development.
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Affiliation(s)
- Abeer A Alrefai
- Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt
- Biochemistry Department, Faculty of Medicine, UQU, Mecca, KSA
| | - Ahmed N Ramadan
- Neuropsychiatry Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt
| | - Marwa M Omar
- Clinical Pathology Departments, Faculty of Medicine, Menoufia University, Menoufia, Egypt
| | | | - Shimaa E Soliman
- Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt
- Medical Biochemistry Unit, Department of Pathology, College of Medicine, Qassim University, Buraydah, KSA
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17
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Boberg J, Kaldo V, Mataix-Cols D, Crowley JJ, Roelstraete B, Halvorsen M, Forsell E, Isacsson NH, Sullivan PF, Svanborg C, Andersson EH, Lindefors N, Kravchenko O, Mattheisen M, Danielsdottir HB, Ivanova E, Boman M, Fernández de la Cruz L, Wallert J, Rück C. Swedish multimodal cohort of patients with anxiety or depression treated with internet-delivered psychotherapy (MULTI-PSYCH). BMJ Open 2023; 13:e069427. [PMID: 37793927 PMCID: PMC10551950 DOI: 10.1136/bmjopen-2022-069427] [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] [Received: 12/07/2022] [Accepted: 08/15/2023] [Indexed: 10/06/2023] Open
Abstract
PURPOSE Depression and anxiety afflict millions worldwide causing considerable disability. MULTI-PSYCH is a longitudinal cohort of genotyped and phenotyped individuals with depression or anxiety disorders who have undergone highly structured internet-based cognitive-behaviour therapy (ICBT). The overarching purpose of MULTI-PSYCH is to improve risk stratification, outcome prediction and secondary preventive interventions. MULTI-PSYCH is a precision medicine initiative that combines clinical, genetic and nationwide register data. PARTICIPANTS MULTI-PSYCH includes 2668 clinically well-characterised adults with major depressive disorder (MDD) (n=1300), social anxiety disorder (n=640) or panic disorder (n=728) assessed before, during and after 12 weeks of ICBT at the internet psychiatry clinic in Stockholm, Sweden. All patients have been blood sampled and genotyped. Clinical and genetic data have been linked to several Swedish registers containing a wide range of variables from patient birth up to 10 years after the end of ICBT. These variable types include perinatal complications, school grades, psychiatric and somatic comorbidity, dispensed medications, medical interventions and diagnoses, healthcare and social benefits, demographics, income and more. Long-term follow-up data will be collected through 2029. FINDINGS TO DATE Initial uses of MULTI-PSYCH include the discovery of an association between PRS for autism spectrum disorder and response to ICBT, the development of a machine learning model for baseline prediction of remission status after ICBT in MDD and data contributions to genome wide association studies for ICBT outcome. Other projects have been launched or are in the planning phase. FUTURE PLANS The MULTI-PSYCH cohort provides a unique infrastructure to study not only predictors or short-term treatment outcomes, but also longer term medical and socioeconomic outcomes in patients treated with ICBT for depression or anxiety. MULTI-PSYCH is well positioned for research collaboration.
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Affiliation(s)
- Julia Boberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Viktor Kaldo
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Psychology, Faculty of Health and Life Sciences, Linnaeus University, Växjö, Sweden
| | - David Mataix-Cols
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - James J Crowley
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Bjorn Roelstraete
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Matthew Halvorsen
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Erik Forsell
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Nils H Isacsson
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Patrick F Sullivan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Cecilia Svanborg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Evelyn H Andersson
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Nils Lindefors
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Olly Kravchenko
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Manuel Mattheisen
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Hilda B Danielsdottir
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Ekaterina Ivanova
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Magnus Boman
- Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Stockholm, Sweden
- Department of Computer and Software Systems, School of EECS, KTH Royal Institute of Technology, Stockholm, Stockholm, Sweden
| | - Lorena Fernández de la Cruz
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - John Wallert
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
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18
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Wang Y, Fang X, Wang G, Tang W, Liu S, Yang Y, Chen J, Ling Y, Zhou C, Zhang X, Zhang C, Su KP. The association between inflammation and kynurenine pathway metabolites in electroconvulsive therapy for schizophrenia: Implications for clinical efficacy. Brain Behav Immun 2023; 113:1-11. [PMID: 37353059 DOI: 10.1016/j.bbi.2023.06.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/30/2023] [Accepted: 06/15/2023] [Indexed: 06/25/2023] Open
Abstract
The kynurenine pathway (KP) of tryptophan has been implicated in the pathogenesis of schizophrenia and its interaction with the immune system has been suggested to play a role. In this study, 28 schizophrenia patients and 25 healthy controls were recruited and divided into different inflammatory subgroups using a two-step recursive clustering analysis. Cytokine gene expression and plasma KP metabolites were measured before, during and after treatment. Our findings indicated that schizophrenia patients had lower levels of Tryptophan (TRP), N-formylkynurenine (NFK), xanthinic acid (XA), quinolinic acid (QA), kynurenic acid (KYNA), KYNA/KYN and QA/KYNA, but higher levels of IL-18 mRNA, KYN/TRP compared to healthy controls (all p < 0.05). After electroconvulsive therapy (ECT), patients with low inflammation achieved better clinical improvement (PANSS scores) compared to those with high inflammation (F = 5.672, P = 0.025), especially in negative symptoms (F = 6.382, P = 0.018, η2 = 0.197). While IL-18 mRNA (F = 32.910, P < 0.0001) was significantly decreased following ECT, the KYN/TRP (F = 3.455, p = 0.047) and KYNA/TRP (F = 4.264, P = 0.026) only significantly decreased in patients with low inflammation. Correlation analyses revealed that baseline IL-18 gene expression significantly correlated with pre- (r = 0.537, p = 0.008) and post-KYNA/TRP (r = 0.443, p = 0.034), post-KYN/TRP (r = 0.510, p = 0.013), and post-negative symptoms (r = 0.525, p = 0.010). Moreover, baseline TRP (r = -0.438, p = 0.037) and XA (r = -0.516, p = 0.012) were negatively correlated with baseline PANSS, while post-KYN (r = -0.475, p = 0.022), 2-AA (r = -0.447, p = 0.032) and KYN/TRP (r = -0.566, p = 0.005) were negatively correlated with Montreal Cognitive Assessment (MoCA) following ECT. Overall, these findings suggested that the association between inflammation and kynurenine pathway plays an essential role in mechanism of ECT for schizophrenia and that the regulation of ECT on KP is influenced by inflammatory characteristics, which may relate to clinical efficacy in schizophrenia.
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Affiliation(s)
- Yu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Guangfa Wang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Wei Tang
- The Affiliated Wenzhou Kangning Hospital, Wenzhou Medical University, China
| | - Shasha Liu
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yujing Yang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Jin Chen
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yuru Ling
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
| | - Caiyi Zhang
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
| | - Kuan-Pin Su
- College of Medicine, China Medical University, Taichung, Taiwan; An-Nan Hospital, China Medical University, Tainan, Taiwan.
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19
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Lu Z, Zhang Y, Sun Y, Liao Y, Kang Z, Feng X, Yan H, Wang L, Lu T, Zhang D, Yue W. Therapeutic outcomes wide association scan of different antipsychotics in patients with schizophrenia: Randomized clinical trials and multi-ancestry validation. Psychiatry Clin Neurosci 2023; 77:486-496. [PMID: 37210704 DOI: 10.1111/pcn.13567] [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] [Received: 03/25/2023] [Revised: 05/05/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
AIM This study identified discrepant therapeutic outcomes of antipsychotics. METHODS A total of 5191 patients with schizophrenia were enrolled, 3030 as discovery cohort, 1395 as validation cohort, and 766 as multi-ancestry validation cohort. Therapeutic Outcomes Wide Association Scan was conducted. Types of antipsychotics (one antipsychotic vs other antipsychotics) were dependent variables, therapeutic outcomes including efficacy and safety were independent variables. RESULTS In discovery cohort, olanzapine related to higher risk of weight gain (AIWG, OR: 2.21-2.86), liver dysfunction (OR: 1.75-2.33), sedation (OR: 1.76-2.86), increased lipid level (OR: 2.04-2.12), and lower risk of extrapyramidal syndrome (EPS, OR: 0.14-0.46); risperidone related to higher risk of hyperprolactinemia (OR: 12.45-20.53); quetiapine related to higher risk of sedation (OR = 1.73), palpitation (OR = 2.87), increased lipid level (OR = 1.69), lower risk of hyperprolactinemia (OR: 0.09-0.11), and EPS (OR: 0.15-0.44); aripiprazole related to lower risk of hyperprolactinemia (OR: 0.09-0.14), AIWG (OR = 0.44), sedation (OR: 0.33-0.47), and QTc prolongation (β = -2.17); ziprasidone related to higher risk of increased QT interval (β range: 3.11-3.22), nausea (OR: 3.22-3.91), lower risk of AIWG (OR: 0.27-0.46), liver dysfunction (OR: 0.41-0.38), and increased lipid level (OR: 0.41-0.55); haloperidol related to higher risk of EPS (OR: 2.64-6.29), hyperprolactinemia (OR: 5.45-9.44), and increased salivation (OR: 3.50-3.68). Perphenazine related to higher risk of EPS (OR: 1.89-2.54). Higher risk of liver dysfunction in olanzapine and lower risk of hyperprolactinemia in aripiprazole were confirmed in validation cohort, and higher risk of AIWG in olanzapine and hyperprolactinemia in risperidone were confirmed in multi-ancestry validation cohort. CONCLUSION Future precision medicine should focus on personalized side-effects.
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Affiliation(s)
- Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Xiaoyang Feng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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20
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Wang X, Mei D, Lu Z, Zhang Y, Sun Y, Lu T, Yan H, Yue W. Genome-wide association study identified six loci associated with adverse drug reactions to aripiprazole in schizophrenia patients. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:44. [PMID: 37491364 PMCID: PMC10368716 DOI: 10.1038/s41537-023-00369-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 06/19/2023] [Indexed: 07/27/2023]
Abstract
Aripiprazole is recommended for routine use in schizophrenia patients. However, the biological mechanism for the adverse drug reactions (ADRs) among schizophrenia patients with the antipsychotic drug aripiprazole is far from clear. To explore the potential genetic factors that may cause movement-related adverse antipsychotic effects in patients, we conducted an association analysis between movement-related ADRs and SNPs in schizophrenia patients receiving aripiprazole monotherapy. In this study, multiple ADRs of 384 patients were quantified within 6-week treatment, and the scores of movement-related ADRs at baseline and follow-up time points during treatment were obtained. The highest score record was used as the quantitative index in analysis, and genetic analysis at the genome-wide level was conducted. The SNP rs4149181 in SLC22A8 [P = 2.28 × 10-8] showed genome-wide significance, and rs2284223 in ADCYAP1R1 [P = 9.76 × 10-8], rs73258503 in KCNIP4 [P = 1.39 × 10-7], rs678428 in SMAD9 [P = 4.70 × 10-7], rs6421034 in NAP1L4 [P = 6.80 × 10-7], and rs1394796 in ERBB4 [P = 8.60 × 10-7] were found to be significantly associated with movement-related ADRs. The combined prediction model of these six loci showed acceptable performance in predicting adverse events [area under the curve (AUC): 0.84]. Combined with the function and network of the above genes and other candidate loci (KCNA1, CACNG1, etc.), we hypothesize that SLC22A8 and KCNIP4-Kv channel perform their respective functions as transporter or channel and participate in the in vivo metabolism or effects of aripiprazole. The above results imply the important function of ion transporters and channels in movement-related adverse antipsychotic effects in aripiprazole monotherapy schizophrenia patients.
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Affiliation(s)
- Xueping Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China
| | - Dongli Mei
- School of Nursing, Peking University, 10019, Beijing, China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China.
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China.
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China.
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China.
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), 100191, Beijing, China.
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
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21
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Cui LB, Wang XY, Fu YF, Liu XF, Wei Y, Zhao SW, Gu YW, Fan JW, Wu WJ, Gong H, Lin BD, Yin H, Guan F, Chang X. Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia. BMC Med 2023; 21:250. [PMID: 37424013 DOI: 10.1186/s12916-023-02963-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023] Open
Abstract
BACKGROUND Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.
| | - Xian-Yang Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hengfen Gong
- School of Medicine, Shanghai Pudong New Area Mental Health Center, Tongji University, Shanghai, China
| | - Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, China.
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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22
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Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, Yang YF, Xiao X, Yan H, Lu TL, Li J, Liao YD, Kang ZW, Wang LF, Li Y, Li M, Liu B, Huang HL, Lv LX, Yao Y, Tan YL, Breen G, Everall I, Wang HX, Huang Z, Zhang D, Yue WH. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res 2023; 10:24. [PMID: 37269009 DOI: 10.1186/s40779-023-00459-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/05/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment. METHODS Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial (n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial (n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls (n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R2 for regression, and decision curve analysis. RESULTS Six risk genes for SCZ (LINC01795, DDHD2, SBNO1, KCNG2, SEMA7A, and RUFY1) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867-0.881), R2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R2 = 0.507]. CONCLUSIONS This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC-ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).
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Affiliation(s)
- Liang-Kun Guo
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yi Su
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Yu-Ya-Nan Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, 272067, Shandong, China
| | - Zhe Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Wen-Qiang Li
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yong-Feng Yang
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hao Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Tian-Lan Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Jun Li
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yun-Dan Liao
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Zhe-Wei Kang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Li-Fang Wang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yue Li
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hai-Liang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Lu-Xian Lv
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yin Yao
- Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Yun-Long Tan
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ian Everall
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Hong-Xing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Zhuo Huang
- State Key Laboratory of Natural and Biomimetic Drugs, Key Laboratory for Neuroscience for Ministry of Education, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, 100191, China.
| | - Dai Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Wei-Hua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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23
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Alemany-Navarro M, Tubío-Fungueiriño M, Diz-de Almeida S, Cruz R, Lombroso A, Real E, Soria V, Bertolín S, Fernández-Prieto M, Alonso P, Menchón JM, Carracedo A, Segalàs C. The genomics of visuospatial neurocognition in obsessive-compulsive disorder: A preliminary GWAS. J Affect Disord 2023; 333:365-376. [PMID: 37094658 DOI: 10.1016/j.jad.2023.04.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/04/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND The study of Obsessive-Compulsive Disorder (OCD) genomics has primarily been tackled by Genome-wide association studies (GWAS), which have encountered troubles in identifying replicable single nucleotide polymorphisms (SNPs). Endophenotypes have emerged as a promising avenue of study in trying to elucidate the genomic bases of complex traits such as OCD. METHODS We analyzed the association of SNPs across the whole genome with the construction of visuospatial information and executive performance through four neurocognitive variables assessed by the Rey-Osterrieth Complex Figure Test (ROCFT) in a sample of 133 OCD probands. Analyses were performed at SNP- and gene-level. RESULTS No SNP reached genome-wide significance, although there was one SNP almost reaching significant association with copy organization (rs60360940; P = 9.98E-08). Suggestive signals were found for the four variables at both SNP- (P < 1E-05) and gene-levels (P < 1E-04). Most of the suggestive signals pointed to genes and genomic regions previously associated with neurological function and neuropsychological traits. LIMITATIONS Our main limitations were the sample size, which was limited to identify associated signals at a genome-wide level, and the composition of the sample, more representative of rather severe OCD cases than a population-based OCD sample with a broad severity spectrum. CONCLUSIONS Our results suggest that studying neurocognitive variables in GWAS would be more informative on the genetic basis of OCD than the classical case/control GWAS, facilitating the genetic characterization of OCD and its different clinical profiles, the development of individualized treatment approaches, and the improvement of prognosis and treatment response.
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Affiliation(s)
- M Alemany-Navarro
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; IBIS (Universidad de Sevilla, HUVR, Junta de Andalucia, CSIC) Sevilla, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain.
| | - M Tubío-Fungueiriño
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - S Diz-de Almeida
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - R Cruz
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - A Lombroso
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - E Real
- Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - V Soria
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - S Bertolín
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - M Fernández-Prieto
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - P Alonso
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - J M Menchón
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Servicio Galego de Saúde (SERGAS), Santiago de Compostela, Spain
| | - C Segalàs
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
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24
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De Simone G, Mazza B, Vellucci L, Barone A, Ciccarelli M, de Bartolomeis A. Schizophrenia Synaptic Pathology and Antipsychotic Treatment in the Framework of Oxidative and Mitochondrial Dysfunction: Translational Highlights for the Clinics and Treatment. Antioxidants (Basel) 2023; 12:antiox12040975. [PMID: 37107350 PMCID: PMC10135787 DOI: 10.3390/antiox12040975] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/05/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
Schizophrenia is a worldwide mental illness characterized by alterations at dopaminergic and glutamatergic synapses resulting in global dysconnectivity within and between brain networks. Impairments in inflammatory processes, mitochondrial functions, energy expenditure, and oxidative stress have been extensively associated with schizophrenia pathophysiology. Antipsychotics, the mainstay of schizophrenia pharmacological treatment and all sharing the common feature of dopamine D2 receptor occupancy, may affect antioxidant pathways as well as mitochondrial protein levels and gene expression. Here, we systematically reviewed the available evidence on antioxidants' mechanisms in antipsychotic action and the impact of first- and second-generation compounds on mitochondrial functions and oxidative stress. We further focused on clinical trials addressing the efficacy and tolerability of antioxidants as an augmentation strategy of antipsychotic treatment. EMBASE, Scopus, and Medline/PubMed databases were interrogated. The selection process was conducted in respect of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Several mitochondrial proteins involved in cell viability, energy metabolism, and regulation of oxidative systems were reported to be significantly modified by antipsychotic treatment with differences between first- and second-generation drugs. Finally, antioxidants may affect cognitive and psychotic symptoms in patients with schizophrenia, and although the evidence is only preliminary, the results indicate that further studies are warranted.
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Affiliation(s)
- Giuseppe De Simone
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
| | - Benedetta Mazza
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
| | - Licia Vellucci
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
| | - Annarita Barone
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences, and Dentistry, University Medical School of Naples "Federico II", Via Pansini 5, 80131 Naples, Italy
- UNESCO Chair on Health Education and Sustainable Development, University of Naples "Federico II", 80131 Naples, Italy
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25
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Scala JJ, Ganz AB, Snyder MP. Precision Medicine Approaches to Mental Health Care. Physiology (Bethesda) 2023; 38:0. [PMID: 36099270 PMCID: PMC9870582 DOI: 10.1152/physiol.00013.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/08/2022] [Accepted: 09/12/2022] [Indexed: 02/04/2023] Open
Abstract
Developing a more comprehensive understanding of the physiological underpinnings of mental illness, precision medicine has the potential to revolutionize psychiatric care. With recent breakthroughs in next-generation multi-omics technologies and data analytics, it is becoming more feasible to leverage multimodal biomarkers, from genetic variants to neuroimaging biomarkers, to objectify diagnostics and treatment decisions in psychiatry and improve patient outcomes. Ongoing work in precision psychiatry will parallel progress in precision oncology and cardiology to develop an expanded suite of blood- and neuroimaging-based diagnostic tests, empower monitoring of treatment efficacy over time, and reduce patient exposure to ineffective treatments. The emerging model of precision psychiatry has the potential to mitigate some of psychiatry's most pressing issues, including improving disease classification, lengthy treatment duration, and suboptimal treatment outcomes. This narrative-style review summarizes some of the emerging breakthroughs and recurring challenges in the application of precision medicine approaches to mental health care.
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Affiliation(s)
- Jack J Scala
- Department of Genetics, Stanford University, Stanford, California
| | - Ariel B Ganz
- Department of Genetics, Stanford University, Stanford, California
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford, California
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26
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Sun Y, Zhang Y, Lu Z, Yan H, Guo L, Liao Y, Lu T, Wang L, Li J, Li W, Yang Y, Yu H, Lv L, Zhang D, Bi W, Yue W. Longitudinal Network Analysis Reveals Interactive Change of Schizophrenia Symptoms During Acute Antipsychotic Treatment. Schizophr Bull 2023; 49:208-217. [PMID: 36179110 PMCID: PMC9810008 DOI: 10.1093/schbul/sbac131] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS Complex schizophrenia symptoms were recently conceptualized as interactive symptoms within a network system. However, it remains unknown how a schizophrenia network changed during acute antipsychotic treatment. The present study aimed to evaluate the interactive change of schizophrenia symptoms under seven antipsychotics from individual time series. STUDY DESIGN Data on 3030 schizophrenia patients were taken from a multicenter randomized clinical trial and used to estimate the partial correlation cross-sectional networks and longitudinal random slope networks based on multivariate multilevel model. Thirty symptoms assessed by The Positive and Negative Syndrome Scale clustered the networks. STUDY RESULTS Five stable communities were detected in cross-sectional networks and random slope networks that describe symptoms change over time. Delusions, emotional withdrawal, and lack of spontaneity and flow of conversation featured as central symptoms, and conceptual disorganization, hostility, uncooperativeness, and difficulty in abstract thinking featured as bridge symptoms, all showing high centrality in the random slope network. Acute antipsychotic treatment changed the network structure (M-test = 0.116, P < .001) compared to baseline, and responsive subjects showed lower global strength after treatment (11.68 vs 14.18, S-test = 2.503, P < .001) compared to resistant subjects. Central symptoms and bridge symptoms kept higher centrality across random slope networks of different antipsychotics. Quetiapine treatment network showed improvement in excitement symptoms, the one featured as both central and bridge symptom. CONCLUSION Our findings revealed the central symptoms, bridge symptoms, cochanging features, and individualized features under different antipsychotics of schizophrenia. This brings implications for future targeted drug development and search for pathophysiological mechanisms.
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Affiliation(s)
- Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Liangkun Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Jun Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Wenqiang Li
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Yongfeng Yang
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, Shandong, P. R. China
| | - Luxian Lv
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, P. R. China
| | - Wenjian Bi
- Department of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, P. R. China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, P. R. China
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27
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Du H, Ma J, Zhou W, Li M, Huai C, Shen L, Wu H, Zhao X, Zhang N, Gao S, Wang Q, He L, Wu X, Qin S, Zhao M. Methylome-wide association study of different responses to risperidone in schizophrenia. Front Pharmacol 2022; 13:1078464. [PMID: 36618913 PMCID: PMC9815458 DOI: 10.3389/fphar.2022.1078464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Accumulating evidence shows that DNA methylation plays a role in antipsychotic response. However, the mechanisms by which DNA methylation changes are associated with antipsychotic responses remain largely unknown. Methods: We performed a methylome-wide association study (MWAS) to evaluate the association between DNA methylation and the response to risperidone in schizophrenia. Genomic DNA methylation patterns were assessed using the Agilent Human DNA Methylation Microarray. Results: We identified numerous differentially methylated positions (DMPs) and regions (DMRs) associated with antipsychotic response. CYP46A1, SPATS2, and ATP6V1E1 had the most significant DMPs, with p values of 2.50 × 10-6, 3.53 × 10-6, and 5.71 × 10-6, respectively. The top-ranked DMR was located on chromosome 7, corresponding to the PTPRN2 gene with a Šidák-corrected p-value of 9.04 × 10-13. Additionally, a significant enrichment of synaptic function and neurotransmitters was found in the differentially methylated genes after gene ontology and pathway analysis. Conclusion: The identified DMP- and DMR-overlapping genes associated with antipsychotic response are related to synaptic function and neurotransmitters. These findings may improve understanding of the mechanisms underlying antipsychotic response and guide the choice of antipsychotic in schizophrenia.
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Affiliation(s)
- Huihui Du
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jingsong Ma
- School o f Engineering, Westlake University, Hangzhou, Zhejiang, China,Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Wei Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Mo Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Cong Huai
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Lu Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Wu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xianglong Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Na Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Songyin Gao
- Zhumadian Psychiatric Hospital, Zhumadian, China
| | - Qi Wang
- Hebei Mental Health Center, Hebei Sixth People’s Hospital, Baoding, China
| | - Lin He
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuming Wu
- Nantong Fourth People’s Hospital, Nantong, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
| | - Shengying Qin
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
| | - Mingzhe Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China,Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
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28
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Guo L, Ni Z, Wei G, Cheng W, Huang X, Yue W. Epigenome-wide DNA methylation analysis of whole blood cells derived from patients with GAD and OCD in the Chinese Han population. Transl Psychiatry 2022; 12:465. [PMID: 36344488 PMCID: PMC9640561 DOI: 10.1038/s41398-022-02236-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 10/14/2022] [Accepted: 10/26/2022] [Indexed: 11/09/2022] Open
Abstract
Generalized anxiety disorder (GAD) and obsessive-compulsive disorder (OCD) had high comorbidity and affected more than 44 million people around the world leading to a huge burden on health and economy. Here, we conducted an epigenome-wide DNA methylation study employing 93 patients with GAD, 65 patients with OCD, and 302 health controls, to explore epigenetic alterations associated with the onset and differences of GAD and OCD. We identified multiple differentially methylated positions (DMPs) and regions (DMRs): three DMP genes included RIOK3 (cg21515243, p = 8.00 × 10-10), DNASE2 (cg09379601, p = 1.10 × 10-9), and PSMB4 (cg01334186, p = 3.70 × 10-7) and two DMR genes USP6NL (p = 4.50 × 10-4) and CPLX1 (p = 6.95 × 10-4) were associated with the onset of GAD and OCD; three DMPs genes included LDLRAP1 (cg21400344, p = 4.40 × 10-12), ACIN1 (cg23712970, p = 2.98×10-11), and SCRT1 (cg25472897, p = 5.60 × 10-11) and three DMR genes WDR19 (p = 3.39 × 10-3), SYCP1 (p = 6.41 × 10-3), and FAM172A (p = 5.74 × 10-3) were associated with the differences between GAD and OCD. Investigation of epigenetic age and chronological age revealed a different epigenetic development trajectory of GAD and OCD. Conclusively, our findings which yielded robust models may aid in distinguishing patients from healthy controls (AUC = 0.90-0.99) or classifying patients with GAD and OCD (AUC = 0.89-0.99), and may power the precision medicine for them.
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Affiliation(s)
- Liangkun Guo
- grid.459847.30000 0004 1798 0615Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191 China ,grid.459847.30000 0004 1798 0615National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China ,grid.506261.60000 0001 0706 7839NHC Key Laboratory of Mental Health, & Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Beijing, 100191 China
| | - Zhaojun Ni
- grid.459847.30000 0004 1798 0615Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191 China ,grid.459847.30000 0004 1798 0615National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China ,grid.506261.60000 0001 0706 7839NHC Key Laboratory of Mental Health, & Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Beijing, 100191 China
| | - Guiming Wei
- Department of Neurology, Shandong Daizhuang Hospital, 272051 Jining, Shandong China
| | - Weiqiu Cheng
- grid.5510.10000 0004 1936 8921NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Xuebing Huang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China. .,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China. .,NHC Key Laboratory of Mental Health, & Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Beijing, 100191, China.
| | - Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China. .,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China. .,NHC Key Laboratory of Mental Health, & Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Beijing, 100191, China. .,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China. .,Chinese Institute for Brain Research, Beijing, 102206, China.
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29
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Sun J, Zhang X, Cong Q, Chen D, Yi Z, Huang H, Wang C, Li M, Zeng R, Liu Y, Huai C, Chen L, Liu C, Zhang Y, Xu Y, Fan L, Wang G, Song C, Wei M, Du H, Zhu J, He L, Qin S. miR143-3p-Mediated NRG-1-Dependent Mitochondrial Dysfunction Contributes to Olanzapine Resistance in Refractory Schizophrenia. Biol Psychiatry 2022; 92:419-433. [PMID: 35662508 DOI: 10.1016/j.biopsych.2022.03.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 11/10/2021] [Accepted: 03/11/2022] [Indexed: 11/02/2022]
Abstract
BACKGROUND Olanzapine is an effective antipsychotic medication for treatment-resistant schizophrenia (TRS); however, the therapeutic effectiveness of olanzapine has been found to vary in individual patients. It is imperative to unravel its resistance mechanisms and find reliable targets to develop novel precise therapeutic strategies. METHODS Unbiased RNA sequencing analysis was performed using homogeneous populations of neural stem cells derived from induced pluripotent stem cells in 3 olanzapine responder (reduction of Positive and Negative Syndrome Scale score ≥25%) and 4 nonresponder (reduction of Positive and Negative Syndrome Scale score <25%) inpatients with TRS. We also used a genotyping study from patients with TRS to assess the candidate genes associated with the olanzapine response. CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9-mediated genome editing, neurologic behavioral tests, RNA silencing, and microRNA sequencing were used to investigate the phenotypic mechanisms of an olanzapine resistance gene in patients with TRS. RESULTS Neuregulin-1 (NRG-1) deficiency-induced mitochondrial dysfunction is associated with olanzapine treatment outcomes in TRS. NRG-1 knockout mice showed schizophrenia-relevant behavioral deficits and yielded olanzapine resistance. Notably, miR143-3p is a critical NRG-1 target related to mitochondrial dysfunction, and miR143-3p levels in neural stem cells associate with severity to olanzapine resistance in TRS. Meanwhile, olanzapine resistance in NRG-1 knockout mice could be rescued by treatment with miR143-3p agomir via intracerebral injection. CONCLUSIONS Our findings provide direct evidence of olanzapine resistance resulting from NRG-1 deficiency-induced mitochondrial dysfunction, and they link olanzapine resistance and NRG-1 deficiency-induced mitochondrial dysfunction to an NRG-1/miR143-3p axis, which constitutes a novel biomarker and target for TRS.
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Affiliation(s)
- Jing Sun
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China; Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Xiaoya Zhang
- Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Qijie Cong
- Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Dong Chen
- Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Zhenghui Yi
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Cong Wang
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Mo Li
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Rongsen Zeng
- Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Yunxi Liu
- Neurobiology & Mitochondrial Key Laboratory, School of Pharmacy, Jiangsu University, Zhenjiang, China
| | - Cong Huai
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Luan Chen
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Chuanxin Liu
- School of Mental Health, Jining Medical University, Jining, China
| | - Yan Zhang
- The Second People's Hospital of Lishui, Lishui, China
| | - Yong Xu
- Department of Psychiatry, First Hospital, First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Lingzi Fan
- Zhumadian Psychiatric Hospital, Zhumadian, China
| | - Guoqiang Wang
- Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Chuanfu Song
- The Fourth People's Hospital of Wuhu, Wuhu, China
| | - Muyun Wei
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Huihui Du
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Jinhang Zhu
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Lin He
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Shengying Qin
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China.
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30
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Xie Y, Ding H, Du X, Chai C, Wei X, Sun J, Zhuo C, Wang L, Li J, Tian H, Liang M, Zhang S, Yu C, Qin W. Morphometric Integrated Classification Index: A Multisite Model-Based, Interpretable, Shareable and Evolvable Biomarker for Schizophrenia. Schizophr Bull 2022; 48:1217-1227. [PMID: 35925032 PMCID: PMC9673259 DOI: 10.1093/schbul/sbac096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Multisite massive schizophrenia neuroimaging data sharing is becoming critical in understanding the pathophysiological mechanism and making an objective diagnosis of schizophrenia; it remains challenging to obtain a generalizable and interpretable, shareable, and evolvable neuroimaging biomarker for schizophrenia diagnosis. STUDY DESIGN A Morphometric Integrated Classification Index (MICI) was proposed as a potential biomarker for schizophrenia diagnosis based on structural magnetic resonance imaging data of 1270 subjects from 10 sites (588 schizophrenia patients and 682 normal controls). An optimal XGBoost classifier plus sample-weighted SHapley Additive explanation algorithms were used to construct the MICI measure. STUDY RESULTS The MICI measure achieved comparable performance with the sample-weighted ensembling model and merged model based on raw data (Delong test, P > 0.82) while outperformed the single-site models (Delong test, P < 0.05) in either the independent-sample testing datasets from the 9 sites or the independent-site dataset (generalizable). Besides, when new sites were embedded in, the performance of this measure was gradually increasing (evolvable). Finally, MICI was strongly associated with the severity of schizophrenia brain structural abnormality, with the patients' positive and negative symptoms, and with the brain expression profiles of schizophrenia risk genes (interpretable). CONCLUSIONS In summary, the proposed MICI biomarker may provide a simple and explainable way to support clinicians for objectively diagnosing schizophrenia. Finally, we developed an online model share platform to promote biomarker generalization and provide free individual prediction services (http://micc.tmu.edu.cn/mici/index.html).
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Affiliation(s)
- Yingying Xie
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Xiaotong Du
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chao Chai
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaotong Wei
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jie Sun
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chuanjun Zhuo
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Lina Wang
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Jie Li
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | | | - Meng Liang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | | | | | - Wen Qin
- To whom correspondence should be addressed; Department of Radiology, and Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital. Anshan Road No 154, Heping District, Tianjin 300052, China.
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Dagilis AJ, Sardell JM, Josephson MP, Su Y, Kirkpatrick M, Peichel CL. Searching for signatures of sexually antagonistic selection on stickleback sex chromosomes. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210205. [PMID: 35694749 PMCID: PMC9189504 DOI: 10.1098/rstb.2021.0205] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Intralocus sexually antagonistic selection occurs when an allele is beneficial to one sex but detrimental to the other. This form of selection is thought to be key to the evolution of sex chromosomes but is hard to detect. Here we perform an analysis of phased young sex chromosomes to look for signals of sexually antagonistic selection in the Japan Sea stickleback (Gasterosteus nipponicus). Phasing allows us to date the suppression of recombination on the sex chromosome and provides unprecedented resolution to identify sexually antagonistic selection in the recombining region of the chromosome. We identify four windows with elevated divergence between the X and Y in the recombining region, all in or very near genes associated with phenotypes potentially under sexually antagonistic selection in humans. We are unable, however, to rule out the alternative hypothesis that the peaks of divergence result from demographic effects. Thus, although sexually antagonistic selection is a key hypothesis for the formation of supergenes on sex chromosomes, it remains challenging to detect. This article is part of the theme issue ‘Genomic architecture of supergenes: causes and evolutionary consequences’.
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Affiliation(s)
- Andrius J Dagilis
- Department of Integrative Biology, University of Texas, Austin TX 78712, USA.,Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jason M Sardell
- Department of Integrative Biology, University of Texas, Austin TX 78712, USA
| | - Matthew P Josephson
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland
| | - Yiheng Su
- Department of Computer Science, University of Texas, Austin TX 78712, USA
| | - Mark Kirkpatrick
- Department of Integrative Biology, University of Texas, Austin TX 78712, USA
| | - Catherine L Peichel
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland
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32
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Zhao M, Ma J, Li M, Zhu W, Zhou W, Shen L, Wu H, Zhang N, Wu S, Fu C, Li X, Yang K, Tang T, Shen R, He L, Huai C, Qin S. Different responses to risperidone treatment in Schizophrenia: a multicenter genome-wide association and whole exome sequencing joint study. Transl Psychiatry 2022; 12:173. [PMID: 35484098 PMCID: PMC9050705 DOI: 10.1038/s41398-022-01942-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 04/15/2022] [Accepted: 04/20/2022] [Indexed: 12/11/2022] Open
Abstract
Risperidone is routinely used in the clinical management of schizophrenia, but the treatment response is highly variable among different patients. The genetic underpinnings of the treatment response are not well understood. We performed a pharmacogenomic study of the treatment response to risperidone in patients with schizophrenia by using a SNP microarray -based genome-wide association study (GWAS) and whole exome sequencing (WES)-based GWAS. DNA samples were collected from 189 patients for the GWAS and from 222 patients for the WES after quality control in multiple centers of China. Antipsychotic response phenotypes of patients who received eight weeks of risperidone treatment were quantified with percentage change on the Positive and Negative Syndrome Scale (PANSS). The GWAS revealed a significant association between several SNPs and treatment response, such as three GRM7 SNPs (rs141134664, rs57521140, and rs73809055). Gene-based analysis in WES revealed 13 genes that were associated with antipsychotic response, such as GPR12 and MAP2K3. We did not identify shared loci or genes between GWAS and WES, but association signals tended to cluster into the GPCR gene family and GPCR signaling pathway, which may play an important role in the treatment response etiology. This study may provide a research paradigm for pharmacogenomic research, and these data provide a promising illustration of our potential to identify genetic variants underlying antipsychotic responses and may ultimately facilitate precision medicine in schizophrenia.
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Affiliation(s)
- Mingzhe Zhao
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Jingsong Ma
- grid.494629.40000 0004 8008 9315School of Engineering, Westlake University, 18 Shilongshan Road, Hangzhou, 310024 Zhejiang Province China ,grid.494629.40000 0004 8008 9315Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou, 310024 Zhejiang Province China
| | - Mo Li
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Wenli Zhu
- The Fourth People’s Hospital of Wuhu, No.1 East Wuxiashan Road, Wuhu, 241003 China
| | - Wei Zhou
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Lu Shen
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Hao Wu
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Na Zhang
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Shaochang Wu
- The Second People’s Hospital of Lishui, No.69 Beihua Road, Lishui, 323020 China
| | - Chunpeng Fu
- The Third People’s Hospital of Shangrao, No.1 Fenghuang East Avenue, Taokan Road, Shangrao, 334000 China
| | - Xianxi Li
- Shanghai Yangpu district mental health center, No.585 Jungong Road, Yangpu District, Shanghai, 900093 China
| | - Ke Yang
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Tiancheng Tang
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Ruoxi Shen
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Lin He
- grid.16821.3c0000 0004 0368 8293Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030 China ,grid.16821.3c0000 0004 0368 8293School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Cong Huai
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030, China. .,School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Shengying Qin
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200030, China. .,School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
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McCutcheon RA, McGuire P. Reinventing schizophrenia: The rules of the game. Schizophr Res 2022; 242:94-95. [PMID: 34998652 DOI: 10.1016/j.schres.2021.12.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/09/2021] [Indexed: 12/24/2022]
Affiliation(s)
- Robert A McCutcheon
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, De Crespigny Park, London SE5 8AF, UK.
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, De Crespigny Park, London SE5 8AF, UK
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Swathy B, Banerjee M. Understanding Pharmaco-Epigenomic Response of Antipsychotic Drugs Using Genome-Wide MicroRNA Expression Profile in Liver Cell Line. Front Mol Neurosci 2022; 15:786632. [PMID: 35392270 PMCID: PMC8980709 DOI: 10.3389/fnmol.2022.786632] [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: 09/30/2021] [Accepted: 02/18/2022] [Indexed: 12/01/2022] Open
Abstract
Interindividual variability in drug response is a major concern among patients undergoing antipsychotic drug treatment. Apart from genetic and physiological factors, this variability in drug response could also be attributed to epigenetic mechanisms. The microRNAs (miRNAs) are key epigenetic markers that play an important role in pathogenesis and drug response. Several studies have shown that miRNAs are implicated in regulating the expression of various genes involved in drug metabolism and transport. In a conventional clinical setup, it is extremely difficult to distinguish the role of miRNA in pathogenesis and drug response as it is difficult to obtain drug naïve patients. To resolve this issue, we aimed to identify the role of antipsychotic drug treatment in inducing miRNA expression under an in vitro condition using a hepatic cell line. A liver cell line was treated with a maximum tolerable drug dosage model for haloperidol, clozapine in monotherapy, and their combination in polytherapy. Genome-wide miRNA profiling was performed using 60,000 miRNA probes in the microarray format in different treatment groups. Several miRNAs were observed to be differentially expressed impacting the pharmacokinetic, pharmacodynamics, and epigenomics properties of antipsychotic drug treatment. Interestingly, some of these miRNA expression patterns were similar to reported miRNA observations on schizophrenia pathogenesis. This study unravels the potential role of miRNAs in the mechanism of action of the antipsychotic drug and could also reflect in drug-induced side effects. This study also signifies the importance of pharmacoepigenomics approach while evaluating the role of miRNAs in pathogenesis.
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Epistatic interactions of NRG1 and ERBB4 on antipsychotic treatment response in first-episode schizophrenia patients. Schizophr Res 2022; 241:197-200. [PMID: 35144058 DOI: 10.1016/j.schres.2022.01.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 12/20/2021] [Accepted: 01/21/2022] [Indexed: 11/21/2022]
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36
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Sheng L, Luo Q, Chen L. Amino Acid Solute Carrier Transporters in Inflammation and Autoimmunity. Drug Metab Dispos 2022; 50:DMD-AR-2021-000705. [PMID: 35152203 DOI: 10.1124/dmd.121.000705] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/14/2022] [Accepted: 01/27/2022] [Indexed: 02/21/2024] Open
Abstract
The past decade exposed the importance of many homeostasis and metabolism related proteins in autoimmunity disease and inflammation. Solute carriers (SLCs) are a group of membrane channels that can transport amino acids, the building blocks of proteins, nutrients, and neurotransmitters. This review summarizes the role of SLCs amino acid transporters in inflammation and autoimmunity disease. In detail, the importance of Glutamate transporters SLC1A1, SLC1A2, and SLC1A3, mainly expressed in the brain where they help prevent glutamate excitotoxicity, is discussed in the context of central nervous system disorders such as multiple sclerosis. Similarly, the cationic amino acid transporter SLC7A1 (CAT1), which is an important arginine transporter for T cells, and SLC7A2 (CAT2), essential for innate immunity. SLC3 family proteins, which bind with light chains from the SLC7 family (SLC7A5, SLC7A7 and SLC7A11) to form heteromeric amino acid transporters, are also explored to describe their roles in T cells, NK cells, macrophages and tumor immunotherapies. Altogether, the link between SLC amino acid transporters with inflammation and autoimmunity may contribute to a better understanding of underlying mechanism of disease and provide novel potential therapeutic avenues. Significance Statement SIGNIFICANCE STATEMENT In this review, we summarize the link between SLC amino acid transporters and inflammation and immune responses, specially SLC1 family members and SLC7 members. Studying the link may contribute to a better understanding of related diseases and provide potential therapeutic targets and useful to the researchers who have interest in the involvement of amino acids in immunity.
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Affiliation(s)
| | - Qi Luo
- Tsinghua University, China
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37
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ATAD3B and SKIL polymorphisms associated with antipsychotic-induced QTc interval change in patients with schizophrenia: a genome-wide association study. Transl Psychiatry 2022; 12:56. [PMID: 35136033 PMCID: PMC8825824 DOI: 10.1038/s41398-022-01825-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 11/26/2022] Open
Abstract
QTc interval prolongation is one of the most common antipsychotic-induced side effects which could lead to ventricular tachycardia or Torsade de Pointes, even cardiac arrest. There is very limited understanding on the genetic factors that associated with antipsychotic-induced QTc interval change. We conducted a genome-wide association study (GWAS) of antipsychotic-induced QTc interval change among patients with schizophrenia. A total of 2040 patients with schizophrenia were randomly assigned to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and first-generation antipsychotics; first-generation antipsychotics including haloperidol or perphenazine were also assigned randomly) and received 6-week antipsychotic treatment. We identified two novel loci (rs200050752 in ATAD3B and rs186507741 in SKIL) that were associated with antipsychotic-induced QTc interval change at a genome-wide significance level. The combination of polygenic risk score (PRS), based the GWAS of myocardial infarction from BioBank Japan project, and clinical data (sex, heart rate and QTc interval at baseline) could be applied to predict whether patients with schizophrenia have QTc interval prolongation (10 ms was applied as threshold, P < 0.001, area under the curve [AUC] was 0.797), especially for the first episode patients (P < 0.001, AUC was 0.872). We identified two loci located within genes related to mitochondrial function and cell growth and differentiation, which were both associated with schizophrenia and heart function. The combination of PRS and clinical data could predict whether patients with schizophrenia have the side effect of QTc interval prolongation, which could fundamentally guide the choice of antipsychotic in patients with schizophrenia, especially for the first-episode patients.
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Guan F, Ni T, Zhu W, Williams LK, Cui LB, Li M, Tubbs J, Sham PC, Gui H. Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction. Mol Psychiatry 2022; 27:113-126. [PMID: 34193973 PMCID: PMC11018294 DOI: 10.1038/s41380-021-01201-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/15/2021] [Accepted: 06/17/2021] [Indexed: 02/06/2023]
Abstract
Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.
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Affiliation(s)
- Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Tong Ni
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Weili Zhu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Air Force Medical University, Xi'an, Shaanxi, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Justin Tubbs
- 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
| | - 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.
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA.
- Behavioral Health Services, Henry Ford Health System, Detroit, MI, USA.
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Elsheikh SSM, Müller DJ, Pouget JG. Pharmacogenetics of Antipsychotic Treatment in Schizophrenia. Methods Mol Biol 2022; 2547:389-425. [PMID: 36068471 DOI: 10.1007/978-1-0716-2573-6_14] [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] [Indexed: 06/15/2023]
Abstract
Antipsychotics are the mainstay treatment for schizophrenia. There is large variability between individuals in their response to antipsychotics, both in efficacy and adverse effects of treatment. While the source of interindividual variability in antipsychotic response is not completely understood, genetics is a major contributing factor. The identification of pharmacogenetic markers that predict antipsychotic efficacy and adverse reactions is a growing area of research and holds the potential to replace the current trial-and-error approach to treatment selection in schizophrenia with a personalized medicine approach.In this chapter, we provide an overview of the current state of pharmacogenetics in schizophrenia treatment. The most promising pharmacogenetic findings are presented for both antipsychotic response and commonly studied adverse reactions. The application of pharmacogenetics to schizophrenia treatment is discussed, with an emphasis on the clinical utility of pharmacogenetic testing and directions for future research.
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Affiliation(s)
| | - Daniel J Müller
- The Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| | - Jennie G Pouget
- The Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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40
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Yuan R, Li Y, Fu Y, Ning A, Wang D, Zhang R, Yu S, Xu Q. TNIK influence the effects of antipsychotics on Wnt/β-catenin signaling pathway. Psychopharmacology (Berl) 2021; 238:3283-3292. [PMID: 34350475 DOI: 10.1007/s00213-021-05943-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 07/19/2021] [Indexed: 10/20/2022]
Abstract
RationaleTraf2- and Nck-interacting kinase (TNIK), a member of germinal center kinase (GCK) family, has been implicated as a risk factor in schizophrenia and bipolar disorder as well as the action of antipsychotics. TNIK is an essential activator of Wnt/β-catenin signaling pathway which has been identified involved in the mechanism underlying the effects of antipsychotics. Thus, the effects of TNIK on antipsychotics may be achieved by influencing Wnt/β-catenin signaling pathway proteins.Objectives and methodsIn the current study, the effects of up- or downregulated TNIK on β-catenin, T-cell factor 4 (TCF-4), glycogen synthase kinase-3β (GSK3β), and phosphorylated GSK3β (p-GSK3β) were examined in the human glioma U251 cells. Then, we observed the effects of antipsychotics (clozapine and risperidone) on the above proteins and evaluated the role of differentially expressed TNIK on antipsychotic-treated cell groups.ResultsThe result showed that clozapine treatment decreased β-catenin and TCF-4 levels in U251 cells, and risperidone had the similar effects on β-catenin and p-GSK3β. The downregulated TNIK using siRNA impeded the regulation of antipsychotics on Wnt pathway proteins via increasing the expression levels of TCF-4, β-catenin, or p-GSK3β, whereas the upregulated TNIK made no significant change.ConclusionsThe influence of TNIK on the effects of antipsychotics may be partly through Wnt/β-catenin signaling pathway.
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Affiliation(s)
- Ruixue Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yaojing Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingmei Fu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ailing Ning
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dongxiang Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ran Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shunying Yu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Qingqing Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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41
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Spiros A, Geerts H. Toward Predicting Impact of Common Genetic Variants on Schizophrenia Clinical Responses With Antipsychotics: A Quantitative System Pharmacology Study. Front Neurosci 2021; 15:738903. [PMID: 34658776 PMCID: PMC8511786 DOI: 10.3389/fnins.2021.738903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
CNS disorders are lagging behind other indications in implementing genotype-dependent treatment algorithms for personalized medicine. This report uses a biophysically realistic computer model of an associative and dorsal motor cortico-striatal-thalamo-cortical loop and a working memory cortical model to investigate the pharmacodynamic effects of COMTVal158Met rs4680, 5-HTTLPR rs 25531 s/L and D2DRTaq1A1 genotypes on the clinical response of 7 antipsychotics. The effect of the genotypes on dopamine and serotonin dynamics and the level of target exposure for the drugs was calibrated from PET displacement studies. The simulations suggest strong gene-gene pharmacodynamic interactions unique to each antipsychotic. For PANSS Total, the D2DRTaq1 allele has the biggest impact, followed by the 5-HTTLPR rs25531. The A2A2 genotype improved efficacy for all drugs, with a more complex outcome for the 5-HTTLPR rs25531 genotype. Maximal range in PANSS Total for all 27 individual combinations is 3 (aripiprazole) to 5 points (clozapine). The 5-HTTLPR L/L with aripiprazole and risperidone and the D2DRTaq1A2A2 allele with haloperidol, clozapine and quetiapine reduce the motor side-effects with opposite effects for the s/s genotype. The COMT genotype has a limited effect on antipsychotic effect and EPS. For cognition, the COMT MM 5-HTTLPR L/L genotype combination has the best performance for all antipsychotics, except clozapine. Maximal difference is 25% of the total dynamic range in a 2-back working memory task. Aripiprazole is the medication that is best suited for the largest number of genotype combinations (10) followed by Clozapine and risperidone (6), haloperidol and olanzapine (3) and quetiapine and paliperidone for one genotype. In principle, the platform could identify the best antipsychotic treatment balancing efficacy and side-effects for a specific individual genotype. Once the predictions of this platform are validated in a clinical setting the platform has potential to support rational personalized treatment guidance in clinical practice.
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Affiliation(s)
- Athan Spiros
- In Silico Biosciences, Berwyn, PA, United States
| | - Hugo Geerts
- In Silico Biosciences, Berwyn, PA, United States.,Certara QSP, Canterbury, United Kingdom
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42
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An K, Guo P, Zhang H, Zhu W, Cao W, Shi J, Wang S. Decreased Plasma Level of Lipoprotein Lipase Predicted Verbal Disfluency in Chinese Type 2 Diabetes Mellitus Patients with Early Cognitive Deficits. Curr Alzheimer Res 2021; 18:656-666. [PMID: 34551696 DOI: 10.2174/1567205018666210922105850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/06/2021] [Accepted: 08/18/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Lipoprotein Lipase (LPL) is the rate-limiting enzyme catalyzing the hydrolysis of triglycerides and contributes to the amyloid-β formation, which shows promise as a pathological factor of cognitive decline in Type 2 Diabetes Mellitus (T2DM). This study aimed to investigate the pathogenetic roles of LPL and rs328 polymorphism in Mild Cognitive Impairment (MCI) in patients with T2DM. METHODS Chinese patients with T2DM were recruited and divided into two groups based on the Montreal Cognitive Assessment score. Demographic data were collected, LPL was measured and neuropsychological test results were examined. RESULTS Seventy-nine patients with diabetes and MCI had significantly decreased plasma LPL levels (p = 0.007) when compared with health-cognition controls (n = 91). Correlation analysis revealed that LPL was positively correlated with clock drawing test (r = 0.158, p = 0.043) and logical memory test (r = 0.162, p = 0.037), while lipoprotein a (r = -0.214, p = 0.006) was inversely associated with LPL. Logistic regression analysis further demonstrated that LPL concentration was an independent factor for diabetic MCI (p = 0.036). No significant differences were observed in the distributions of rs328 variants between patients with MCI and the controls. Moreover, no remarkable association was found among plasma LPL levels, cognitive performances, and lipid levels between the genotypic subgroups. The trail making test A was increased in the GC group when compared with the CC genotype in the control group. CONCLUSION Decreased plasma level of LPL could probably predict early cognitive deficits, especially verbal disfluency.
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Affiliation(s)
- Ke An
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
| | - Peng Guo
- Changlu Street Community Health Service Center, No. 68 Bai Yu Road, Nanjing, 211512, China
| | - Haoqiang Zhang
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
| | - Wenwen Zhu
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
| | - Wuyou Cao
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
| | - Jijing Shi
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
| | - Shaohua Wang
- Department of Endocrinology, Affiliated Zhongda Hospital of Southeast University, No. 87 Ding Jia Qiao Road, Nanjing, 210009, China
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43
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Zhao R, Zhu T, Liu Q, Tian Q, Wang M, Chen J, Tong D, Yu B, Guo H, Xia K, Qiu Z, Hu Z. The autism risk gene CNTN4 modulates dendritic spine formation. Hum Mol Genet 2021; 31:207-218. [PMID: 34415325 DOI: 10.1093/hmg/ddab233] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 08/05/2021] [Accepted: 08/06/2021] [Indexed: 01/03/2023] Open
Abstract
Contactin 4 (CNTN4) is a crucial synaptic adhesion protein that belongs to the contactin superfamily. Evidence from both human genetics and mouse models suggests that synapse formation and structural deficits strongly correlate with neurodevelopmental disorders, including autism. In addition, several lines of evidence suggest that CNTN4 is associated with the risk of autism. However, the biological functions of CNTN4 in neural development and disease pathogenesis are poorly understood. In this study, we investigated whether and how CNTN4 is autonomously involved in the development of dendrites and dendritic spines in cortical neurons. Disruption of Cntn4 decreased the number of excitatory synapses, which led to a reduction in neural activity. Truncated proteins lacking the signal peptide, FnIII domains, or GPI domain lacked the ability to regulate dendritic spine formation, indicating that CNTN4 regulates dendritic spine density through a mechanism dependent on FnIII domains. Importantly, we revealed that autism-related variants lacked the ability to regulate spine density and neural activity. In conclusion, our study suggests that CNTN4 is essential for promoting dendrite growth and dendritic spine formation and that disruptive variants of CNTN4 interfere with abnormal synapse formation and may increase the risk of autism.
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Affiliation(s)
- Rongjuan Zhao
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Tengfei Zhu
- Department of Critical Care Medicine, The Third people's hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China.,Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qiong Liu
- Department of Neurology & Key Laboratory of Hunan Province in Neurodegenerative Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Qi Tian
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Meng Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Jingjing Chen
- Reproductive Medicine Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dali Tong
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Bin Yu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hui Guo
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Animal Models for Human Diseases, Central South University, Changsha, Hunan, China
| | - Kun Xia
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Animal Models for Human Diseases, Central South University, Changsha, Hunan, China.,Center for Excellence in Brain Science and Intelligences Technology (CEBSIT), CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Zilong Qiu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.,Center for Excellence in Brain Science and Intelligences Technology (CEBSIT), CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Zhengmao Hu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Animal Models for Human Diseases, Central South University, Changsha, Hunan, China
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Abstract
China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.
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Abstract
Ethnic differences may significantly influence the outcome of psychopharmacological treatment, in terms of prescription, adherence, clinical response, emergence of side effects, as well as pharmacokinetics and pharmacodynamics. The purpose of this review was to explore the available literature in order to provide general suggestions to help clinicians in choosing the best therapeutic option for patients, taking into account ethnicity. Although findings are sometimes controversial, the overall published studies suggest that ethnicities other than Caucasians tend to show a lower response to antidepressants and a reduced compliance. Africans tend to be more prescribed with antipsychotics, probably due to cultural stereotypes, except with clozapine, probably for their chronic benign neutropenia. Asians usually require less antipsychotic dosages than Caucasians. The differential response and side effect profile of antidepressants and antipsychotics have been related to individual intrinsic factors, to genetic make-up, but also to cultural and contextual variables. Interestingly, albeit limited data suggest ethnic-related genetic heterogeneity at the level of the serotonin transporters, the cytochromes and some neuroreceptors. Taken together, no conclusive findings are available about the role and impact of ethnicity in psychopharmacology. One of the main problems is that the majority of the studies in psychopharmacology have been conducted on Caucasians, so that there is an urgent need to have data in other populations. Furthermore, in the era of precision medicine, the role of ethnicity may be also supported by genetic analysis.
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Lisoway AJ, Chen CC, Zai CC, Tiwari AK, Kennedy JL. Toward personalized medicine in schizophrenia: Genetics and epigenetics of antipsychotic treatment. Schizophr Res 2021; 232:112-124. [PMID: 34049235 DOI: 10.1016/j.schres.2021.05.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 04/30/2021] [Accepted: 05/02/2021] [Indexed: 12/21/2022]
Abstract
Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.
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Affiliation(s)
- Amanda J Lisoway
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Cheng C Chen
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Clement C Zai
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Arun K Tiwari
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Canada
| | - James L Kennedy
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada.
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47
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Genetic underpinnings of affective temperaments: a pilot GWAS investigation identifies a new genome-wide significant SNP for anxious temperament in ADGRB3 gene. Transl Psychiatry 2021; 11:337. [PMID: 34075027 PMCID: PMC8169753 DOI: 10.1038/s41398-021-01436-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 04/29/2021] [Accepted: 05/05/2021] [Indexed: 12/22/2022] Open
Abstract
Although recently a large-sample GWASs identified significant loci in the background of depression, the heterogeneity of the depressive phenotype and the lack of accurate phenotyping hinders applicability of findings. We carried out a pilot GWAS with in-depth phenotyping of affective temperaments, considered as subclinical manifestations and high-risk states for affective disorders, in a general population sample of European origin. Affective temperaments were measured by TEMPS-A. SNP-level association was assessed by linear regression models, assuming an additive genetic effect, using PLINK1.9. Gender, age, the first ten principal components (PCs) and the other four temperaments were included in the regression models as covariates. SNP-level relevances (p-values) were aggregated to gene level using the PEGASUS method1. In SNP-based tests, a Bonferroni-corrected significance threshold of p ≤ 5.0 × 10-8 and a suggestive significance threshold of p ≤ 1.0 × 10-5, whereas in gene-based tests a Bonferroni-corrected significance of 2.0 × 10-6 and a suggestive significance of p ≤ 4.0 × 10-4 was established. To explore known functional effects of the most significant SNPs, FUMA v1.3.5 was used. We identified 1 significant and 21 suggestively significant SNPs in ADGRB3, expressed in the brain, for anxious temperament. Several other brain-relevant SNPs and genes emerged at suggestive significance for the other temperaments. Functional analyses reflecting effect on gene expression and participation in chromatin interactions also pointed to several genes expressed in the brain with potentially relevant phenotypes regulated by our top SNPs. Our findings need to be tested in larger GWA studies and candidate gene analyses in well-phenotyped samples in relation to affective disorders and related phenotypes.
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Zhou J, Li M, Wang X, He Y, Xia Y, Sweeney JA, Kopp RF, Liu C, Chen C. Drug Response-Related DNA Methylation Changes in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder. Front Neurosci 2021; 15:674273. [PMID: 34054421 PMCID: PMC8155631 DOI: 10.3389/fnins.2021.674273] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/14/2021] [Indexed: 12/12/2022] Open
Abstract
Pharmacotherapy is the most common treatment for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Pharmacogenetic studies have achieved results with limited clinical utility. DNA methylation (DNAm), an epigenetic modification, has been proposed to be involved in both the pathology and drug treatment of these disorders. Emerging data indicates that DNAm could be used as a predictor of drug response for psychiatric disorders. In this study, we performed a systematic review to evaluate the reproducibility of published changes of drug response-related DNAm in SCZ, BD and MDD. A total of 37 publications were included. Since the studies involved patients of different treatment stages, we partitioned them into three groups based on their primary focuses: (1) medication-induced DNAm changes (n = 8); (2) the relationship between DNAm and clinical improvement (n = 24); and (3) comparison of DNAm status across different medications (n = 14). We found that only BDNF was consistent with the DNAm changes detected in four independent studies for MDD. It was positively correlated with clinical improvement in MDD. To develop better predictive DNAm factors for drug response, we also discussed future research strategies, including experimental, analytical procedures and statistical criteria. Our review shows promising possibilities for using BDNF DNAm as a predictor of antidepressant treatment response for MDD, while more pharmacoepigenetic studies are needed for treatments of various diseases. Future research should take advantage of a system-wide analysis with a strict and standard analytical procedure.
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Affiliation(s)
- Jiaqi Zhou
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Miao Li
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xueying Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yuwen He
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yan Xia
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, United States
| | - John A. Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, United States
| | - Richard F. Kopp
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, United States
| | - Chunyu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, United States
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Animal Models for Human Diseases, Central South University, Changsha, Hunan, China
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de Filippis R, De Fazio P, Gaetano R, Steardo L, Cedro C, Bruno A, Zoccali RA, Muscatello MRA. Current and emerging long-acting antipsychotics for the treatment of schizophrenia. Expert Opin Drug Saf 2021; 20:771-790. [PMID: 33775184 DOI: 10.1080/14740338.2021.1910674] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction: In this review, the authors discuss the role of long-acting injectable antipsychotics (LAIs) for schizophrenia, focusing on the effectiveness and new perspectives introduced by such treatment strategy. Despite their promising pharmacokinetic features and their potential advantages in medication adherence, clinical outcomes, and medical costs, LAIs are not habitually presented as an option for patients, especially in the early phase of schizophrenia.Areas covered: This review explores the panorama of available LAIs for the treatment of schizophrenia, first-episode of psychosis, approved indications, medical costs, medication adherence, side effects, effectiveness and differences between first-generation (FGA)-LAIs and second-generation (SGA)-LAIs.Expert Opinion: LAIs differ in terms of specific indications, approved injection sites, needle size, injection volume, injection interval as well as potential drug-drug interactions, and commonly reported adverse reactions. The approved indications have expanded beyond schizophrenia to include bipolar and schizoaffective disorder. SGA-LAIs are often preferred to FGA-LAIs. FGA-LAIs although are less chosen in new patients due to the induction of cognitive and extrapyramidal side effects, even if, on the other hand, many SGA-LAIs are burden by hyperprolactinemia and weight gain. After a review of the available evidence, insight is provided into the potential and current therapeutic opportunities offered by LAI antipsychotic formulations.
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Affiliation(s)
- Renato de Filippis
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Pasquale De Fazio
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Raffaele Gaetano
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Luca Steardo
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Clemente Cedro
- Psychiatry Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Antonio Bruno
- Psychiatry Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Rocco Antonio Zoccali
- Psychiatry Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Maria Rosaria Anna Muscatello
- Psychiatry Unit, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
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Li J, Wu H, Gao H, Kou R, Xie Y, Zhang Z, Zhang X. TLR4 promoter rs1927914 variant contributes to the susceptibility of esophageal squamous cell carcinoma in the Chinese population. PeerJ 2021; 9:e10754. [PMID: 33585082 PMCID: PMC7860108 DOI: 10.7717/peerj.10754] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 12/21/2020] [Indexed: 12/13/2022] Open
Abstract
Background Toll-like receptor 4 (TLR4), as a key regulator of both innate and acquired immunity, has been linked with the development of various cancers, including esophageal cancer. This study aims to analyze the association of potential functional genetic polymorphisms in TLR4 with the risk of esophageal cancer. Methods This case-control study involved in 480 ESCC patients and 480 health controls. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to genotype TLR4 rs1927914 polymorphism. Taqman probe method was used to determine the genotypes of TLR4 rs11536891 and rs7873784 variants. The relationship between TLR4 genetic variation and ESCC risk was analyzed by Logistic regression model by calculating the odds ratio (OR) and 95% confidence interval (95% CI). Results Compared with TLR4 rs1927914 AA genotype carriers, GG carriers had a lower ESCC risk (OR = 0.59, 95% CI [0.38–0.93], P = 0.023). Stratification analysis by age showed that TLR4 rs1927914 GG could affect the risk of ESCC in elderly people (OR = 0.59, 95% CI [0.36–0.97]). Smoking stratification analysis indicated that rs1927914 GG carriers were related to ESCC susceptibility among non-smokers (OR = 0.36, 95% CI [0.18–0.73]). Dual luciferase reporter assay suggested that rs1927914 G-containing TLR4 promoter displayed a 1.76-fold higher luciferase activity than rs1927914 A-containing counterpart in KYSE30 cells. Electrophoretic mobility shift assay (EMSA) showed the KYSE30 cell nuclear extract was able to bind the probe with rs1927914 G allele and this DNA-protein interaction could be eliminated by competition assays with unlabeled rs1927914 G probe, which indicating that the binding is sequence-specific. Our results also showed that TLR4 rs7873784 (G>C) and rs11536891 (T>C) conformed to complete genetic linkage. The genotype distributions of TLR4 rs11536891 variant among ESCC patients and normal controls have no statistical significance. Conclusion The TLR4 rs1927914 variant contributes to the ESCC risk by effecting the promoter activity.
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Affiliation(s)
- Jiaying Li
- School of Public Health, North China University of Science and Technology, Tangshan, China.,College of Life Science, North China University of Science and Technology, Tangshan, China
| | - Hongjiao Wu
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Hui Gao
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Ruihuan Kou
- Affliated Tangshan Gongren Hospital, North China University of Science and Technology, Tangshan, China
| | - Yuning Xie
- School of Public Health, North China University of Science and Technology, Tangshan, China.,College of Life Science, North China University of Science and Technology, Tangshan, China
| | - Zhi Zhang
- Affliated Tangshan Gongren Hospital, North China University of Science and Technology, Tangshan, China
| | - Xuemei Zhang
- School of Public Health, North China University of Science and Technology, Tangshan, China.,College of Life Science, North China University of Science and Technology, Tangshan, China
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